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cd133 expression  (Miltenyi Biotec)


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    Structured Review

    Miltenyi Biotec cd133 expression
    Cd133 Expression, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 96/100, based on 23 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/cd133+expression/Prominin-1+Antibody%2C+anti-mouse/pm40543657-214-5-28
    Average 96 stars, based on 23 article reviews
    cd133 expression - by Bioz Stars, 2026-09
    96/100 stars

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    Related Articles

    Incubation:

    Article Title: Alteration in stemness causes exclusivity between Epstein-Barr virus-positivity and microsatellite instability status in gastric cancer.
    Article Snippet: Each GC cell was incubated with TrypLE Express (Gibco, Carlsbad, CA, USA) for 10 min for detachment, with minimal loss of surface protein expression [16] . .. After washing with cold incubation buffer (comprised of PBS, 0.5% bovine serum albumin, and 0.05% sodium azide), cells were incubated on ice with antibodies anti-CD44 (1:50, ab81424, Abcam) or anti-CD133 (1:10, 130-098-826, Miltenyi Biotec, Germany) for 30 min. FACSCanto II System (BD Biosciences, San José, CA, USA) was used to detect CD44 and CD133 expression via allophycocyanin and phycoerythrin absorbance, respectively. ..

    Expressing:

    Article Title: Alteration in stemness causes exclusivity between Epstein-Barr virus-positivity and microsatellite instability status in gastric cancer.
    Article Snippet: Each GC cell was incubated with TrypLE Express (Gibco, Carlsbad, CA, USA) for 10 min for detachment, with minimal loss of surface protein expression [16] . .. After washing with cold incubation buffer (comprised of PBS, 0.5% bovine serum albumin, and 0.05% sodium azide), cells were incubated on ice with antibodies anti-CD44 (1:50, ab81424, Abcam) or anti-CD133 (1:10, 130-098-826, Miltenyi Biotec, Germany) for 30 min. FACSCanto II System (BD Biosciences, San José, CA, USA) was used to detect CD44 and CD133 expression via allophycocyanin and phycoerythrin absorbance, respectively. ..

    Article Title: Glutamine deprivation in glioblastoma stem cells triggers autophagic SIRT3 degradation to epigenetically restrict CD133 expression and stemness.
    Article Snippet: 1 Department of Biochemistry & Molecular Cell Biology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, China 2 College of Life Sciences, Shaanxi Normal University, Xi’an, Shaanxi, China 3 School of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China 4 Department of Neurology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China 5 Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Department of Biochemistry & Molecular Cell Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, China Abstract Glioblastoma multiforme (GBM) is a highly malignant brain tumor, and glioblastoma stem cells (GSCs) are the primary cause of GBM heterogeneity, invasiveness, and resistance to therapy.. Sirtuin 3 (SIRT3) is mainly localized in the mitochondrial matrix and plays an important role in maintaining GSC stemness through cooperative interaction with the chaperone protein tumor necrosis factor receptor-associated protein 1 (TRAP1) to modulate mitochondrial respiration and oxidative stress.. The present study aimed to further elucidate the specific mechanisms by which SIRT3 influences GSC stemness, including whether SIRT3 serves as an autophagy substrate and the mechanism of SIRT3 degradation.

    Article Title: Cilium induction triggers differentiation of glioma stem cells.
    Article Snippet: Typically, GSCs are characterized by forming spheres expressing stem-cell markers, such as CD133, sex-determining region Y-box 2 (Sox2), Musashi, and Nestin. .. CD133 expression was detected by anti-CD133–phycoerythrin (AC133-PE) antibody or PE-conjugated mouse immunoglobulin (Ig)G1 isotype control antibody (Miltenyi Biotec). .. The expression of Sox2 was analyzed by PerCP-Cy 5.5 mouse anti-Sox2 or PerCP-Cy 5.5 mouse IgG1 isotype e4 Cell Reports 36, 109656, September 7, 2021 control (Becton Dickinson [BD]).

    Article Title: The Long Non-coding RNA HOTAIR Controls the Self-renewal, Cell Senescence, and Secretion of Anti-aging Protein α-Klotho in Human Adult Renal Progenitor Cells.
    Article Snippet: The long non-coding RNAs (lncRNA) play an important role in several biological processes, including some renal diseases.. Nevertheless, little is known about lncRNA that are expressed in the healthy kidneys and involved in renal cell homeostasis and development, and even less is known about lncRNA involved in the maintenance of human adult renal stem/progenitor cells (ARPCs) that have been shown to be very important for renal homeostasis and repair processes.. Through a whole-genome transcriptome screening, we found that the HOTAIR lncRNA is highly expressed in renal progenitors and potentially involved in cell cycle and senescence biological processes.

    Article Title: Expansion of circulating stem-like CD8 + T cells by adding CD122-directed IL-2 complexes to radiation and anti-PD1 therapies in mice
    Article Snippet: The B16F10 cell line was provided by Prof. Hanspeter Pircher, (Medical Center – University of Freiburg, Germany) and transduced with lentiviral particles encoding the human stem cell marker CD133, and sorted for CD133 expression using the CD133 MicroBead Kit (Miltenyi Biotec). .. The B16F10 cell line was provided by Prof. Hanspeter Pircher, (Medical Center – University of Freiburg, Germany) and transduced with lentiviral particles encoding the human stem cell marker CD133, and sorted for CD133 expression using the CD133 MicroBead Kit (Miltenyi Biotec). ..

    Article Title: Glutamine deprivation in glioblastoma stem cells triggers autophagic SIRT3 degradation to epigenetically restrict CD133 expression and stemness
    Article Snippet: .. CD133+ GSCs were sorted by magnetic bead separation based on CD133 expression (Miltenyi Biotec). ..

    Article Title: PDPN marks a subset of aggressive and radiation-resistant glioblastoma cells
    Article Snippet: .. FACSAria (BD Biosciences) was used to analyze and sort GSCs based on PDPN and CD133 expression using a PE-conjugated mAb to PDPN (clone NZ-1, AngioBio) alone or in combination with an APC-conjugated mAb to CD133 (clone 293C3, Miltenyi Biotech). ..

    Article Title: An old spice with new tricks: Curcumin targets adenoma and colorectal cancer stem-like cells associated with poor survival outcomes.
    Article Snippet: Cell culture, in vitro methods and biophysical assays Full details on ex vivo spheroid and 2D-cell culture and incubation with curcumin are provided in Supplementary materials, along with descriptions of the protein pull-down methodology and biophysical assays. .. To assess ALDH activity and CD133+ expression, Aldefluor assay kits (Stem Cell Technologies, UK) and APC-conjugated mouse anti-human CD133 antibodies were used, with PE-conjugated mouse anti-human ESA antibody (Miltenyi Biotech, UK). .. For analysis of NANOG+ and NANOG+Ki67+ expression, cells were fixed and permeabilised using Cell Cignalling buffer set A (Miltenyi Biotech, UK).

    Control:

    Article Title: Cilium induction triggers differentiation of glioma stem cells.
    Article Snippet: Typically, GSCs are characterized by forming spheres expressing stem-cell markers, such as CD133, sex-determining region Y-box 2 (Sox2), Musashi, and Nestin. .. CD133 expression was detected by anti-CD133–phycoerythrin (AC133-PE) antibody or PE-conjugated mouse immunoglobulin (Ig)G1 isotype control antibody (Miltenyi Biotec). .. The expression of Sox2 was analyzed by PerCP-Cy 5.5 mouse anti-Sox2 or PerCP-Cy 5.5 mouse IgG1 isotype e4 Cell Reports 36, 109656, September 7, 2021 control (Becton Dickinson [BD]).

    FACS:

    Article Title: The Long Non-coding RNA HOTAIR Controls the Self-renewal, Cell Senescence, and Secretion of Anti-aging Protein α-Klotho in Human Adult Renal Progenitor Cells.
    Article Snippet: The long non-coding RNAs (lncRNA) play an important role in several biological processes, including some renal diseases.. Nevertheless, little is known about lncRNA that are expressed in the healthy kidneys and involved in renal cell homeostasis and development, and even less is known about lncRNA involved in the maintenance of human adult renal stem/progenitor cells (ARPCs) that have been shown to be very important for renal homeostasis and repair processes.. Through a whole-genome transcriptome screening, we found that the HOTAIR lncRNA is highly expressed in renal progenitors and potentially involved in cell cycle and senescence biological processes.

    Transduction:

    Article Title: Expansion of circulating stem-like CD8 + T cells by adding CD122-directed IL-2 complexes to radiation and anti-PD1 therapies in mice
    Article Snippet: The B16F10 cell line was provided by Prof. Hanspeter Pircher, (Medical Center – University of Freiburg, Germany) and transduced with lentiviral particles encoding the human stem cell marker CD133, and sorted for CD133 expression using the CD133 MicroBead Kit (Miltenyi Biotec). .. The B16F10 cell line was provided by Prof. Hanspeter Pircher, (Medical Center – University of Freiburg, Germany) and transduced with lentiviral particles encoding the human stem cell marker CD133, and sorted for CD133 expression using the CD133 MicroBead Kit (Miltenyi Biotec). ..

    Marker:

    Article Title: Expansion of circulating stem-like CD8 + T cells by adding CD122-directed IL-2 complexes to radiation and anti-PD1 therapies in mice
    Article Snippet: The B16F10 cell line was provided by Prof. Hanspeter Pircher, (Medical Center – University of Freiburg, Germany) and transduced with lentiviral particles encoding the human stem cell marker CD133, and sorted for CD133 expression using the CD133 MicroBead Kit (Miltenyi Biotec). .. The B16F10 cell line was provided by Prof. Hanspeter Pircher, (Medical Center – University of Freiburg, Germany) and transduced with lentiviral particles encoding the human stem cell marker CD133, and sorted for CD133 expression using the CD133 MicroBead Kit (Miltenyi Biotec). ..

    Activity Assay:

    Article Title: An old spice with new tricks: Curcumin targets adenoma and colorectal cancer stem-like cells associated with poor survival outcomes.
    Article Snippet: Cell culture, in vitro methods and biophysical assays Full details on ex vivo spheroid and 2D-cell culture and incubation with curcumin are provided in Supplementary materials, along with descriptions of the protein pull-down methodology and biophysical assays. .. To assess ALDH activity and CD133+ expression, Aldefluor assay kits (Stem Cell Technologies, UK) and APC-conjugated mouse anti-human CD133 antibodies were used, with PE-conjugated mouse anti-human ESA antibody (Miltenyi Biotech, UK). .. For analysis of NANOG+ and NANOG+Ki67+ expression, cells were fixed and permeabilised using Cell Cignalling buffer set A (Miltenyi Biotech, UK).



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    ( A ) General morphology of livers 2 days after PHx. ( B ) H&E staining of liver sections 2 days after PHx. ( C and D ) Ki67 + percentages in HNF4α + hepatocytes ( C ) and HNF4α− NPCs ( D ) 2 days after PHx. Means ± SEM are shown, n=3 per group, **p<0.01 (two-tailed unpaired t-test). n.s., not significant. ( E ) EpCAM was highly expressed in biliary epithelial cells (arrow), but not in the colony (dashed line). Stellate cells (GFAP) were not altered around the colony. ( F ) CK19 was highly expressed in biliary epithelial cells (arrow), but not in the colony (dashed line). <t>CD133</t> was highly expressed in the colony. ( G ) Sox9 and CD44 were highly expressed in biliary epithelial cells (arrowhead), but was not upregulated in the colony (dashed line) compared to surrounding hepatocytes. ( H ) α-fetoprotein (AFP) showed no difference between the colony (dashed line) and the surrounding tissue. ( I ) Liver/body weight ratios after PHx. Means ± SEM from three or more mice analyzed for each time point and group are shown. ( J and K ) Immunofluorescent staining of SKO liver sections 3 weeks after PHx. Colonies were of various sizes and locations as shown by arrows in ( J ). Macroscopic colonies were found as shown by arrows and dashed lines in ( K ). Immunofluorescent image in ( K ) corresponds to the magenta arrow in the liver image. PV, portal vein; CV, central vein. ( L ) Vasculature shown by PECAM did not distinguish the colony (arrow). ( M ) HGF expressed by non-parenchymal cells (NPCs) was not concentrated in the colony (dashed line). Scale bars, 1 cm ( A ) 100 μm ( B, E–G, I–L ).
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    Generation and characterization of siPD-L1-loaded <t>CD133-tEx.</t> A, Schematic representation of the engineering process for creating siPD-L1-loaded CD133-tEx. The DNA sequence encoding the CD133-targeting peptide was inserted into the pDisplay vector, which contains a portion of the PDGFR transmembrane domain, using restriction enzymes. This recombinant vector was then used to transfect ASCs. The transfected ASCs expressed the CD133-targeting peptide on their cell membranes, resulting in exosomes (tEx) displaying the CD133-targeting peptide on their surface. Finally, siPD-L1 was encapsulated within these exosomes using a transfection kit, creating siPD-L1-loaded CD133-tEx, referred to as tEx(s). B, NTA using Zetaview, demonstrating the size distribution of Ex and CD133-tEx. Both types of exosomes exhibited similar size and distribution profiles, indicating that the genetic engineering did not significantly alter their physical properties. C, Western blot analysis showing CD133 expression across various pancreatic cancer cell lines, including AsPC-1, MIA PaCa-2, PANC-1, and Capan-2 cells. Elevated CD133 expression was observed in AsPC-1, PANC-1, and Capan-2 cells, while MIA PaCa-2 cells exhibited lower CD133 expression levels. D, Flow cytometry analysis of exosomes derived from ASCs (Ex) and transfected ASCs (tEx) using CD63 and Myc markers (top panel), and CD81 and Myc markers (bottom panel). The flow cytometry histograms display the expression levels of these markers. CD63 and CD81 demonstrated comparable expression levels in ASCs and tASCs, with no significant difference. However, Myc expression, indicating the presence of the CD133-targeting peptide, was significantly higher in tEx compared to Ex, confirming the successful generation of tEx. Values are presented as mean ± standard deviation of three independent experiments. * P < 0.05. E, Immunohistochemical analysis of CD133 expression in normal pancreatic tissue and pancreatic cancer tissues. The expression of CD133 in pancreatic cancer was significantly elevated compared to normal pancreatic tissue (P < 0.05).
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    Generation and characterization of siPD-L1-loaded <t>CD133-tEx.</t> A, Schematic representation of the engineering process for creating siPD-L1-loaded CD133-tEx. The DNA sequence encoding the CD133-targeting peptide was inserted into the pDisplay vector, which contains a portion of the PDGFR transmembrane domain, using restriction enzymes. This recombinant vector was then used to transfect ASCs. The transfected ASCs expressed the CD133-targeting peptide on their cell membranes, resulting in exosomes (tEx) displaying the CD133-targeting peptide on their surface. Finally, siPD-L1 was encapsulated within these exosomes using a transfection kit, creating siPD-L1-loaded CD133-tEx, referred to as tEx(s). B, NTA using Zetaview, demonstrating the size distribution of Ex and CD133-tEx. Both types of exosomes exhibited similar size and distribution profiles, indicating that the genetic engineering did not significantly alter their physical properties. C, Western blot analysis showing CD133 expression across various pancreatic cancer cell lines, including AsPC-1, MIA PaCa-2, PANC-1, and Capan-2 cells. Elevated CD133 expression was observed in AsPC-1, PANC-1, and Capan-2 cells, while MIA PaCa-2 cells exhibited lower CD133 expression levels. D, Flow cytometry analysis of exosomes derived from ASCs (Ex) and transfected ASCs (tEx) using CD63 and Myc markers (top panel), and CD81 and Myc markers (bottom panel). The flow cytometry histograms display the expression levels of these markers. CD63 and CD81 demonstrated comparable expression levels in ASCs and tASCs, with no significant difference. However, Myc expression, indicating the presence of the CD133-targeting peptide, was significantly higher in tEx compared to Ex, confirming the successful generation of tEx. Values are presented as mean ± standard deviation of three independent experiments. * P < 0.05. E, Immunohistochemical analysis of CD133 expression in normal pancreatic tissue and pancreatic cancer tissues. The expression of CD133 in pancreatic cancer was significantly elevated compared to normal pancreatic tissue (P < 0.05).
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    A Flow diagram detailing the methodology used to identify HCC driver gene signatures. B Venn diagram illustrating the overlap of significantly differentially expressed genes across the three datasets. C Serial pattern analysis of each dataset. The upper panels show line plots of gene expression patterns in different sample groups (NL, CH, LC, DN, eHCC, and aHCC) on the X-axis. The bottom panels display heat maps of the gene expression levels. NL, normal liver; CH, chronic hepatitis; LC, liver cirrhosis; DN, dysplastic nodules; eHCC, early HCC; aHCC, advanced HCC. D Venn diagram showing the overlap of common genes across the five RNA-seq datasets (TCGA, ICGC, GSE77314, GSE114564, and GSE124535). E Heatmap of the GSE114564 dataset showing gene expression patterns. Different genes are listed on the right side of the heatmap. F Box plots showing <t>SORT1</t> expression at various stages of liver disease and cancer progression across the four datasets. The Y-axis represents SORT1 expression, whereas the X-axis represents different sample groups. G Paired plots showing the expression of SORT1 in HCC tumor (T) vs. non-tumoral (NT) tissues across four datasets: The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC), ICGC LIRI, GSE37991, and GSE77314. Each line connects the paired NT and T samples with a significant SORT1 upregulation in the tumor samples. H Kaplan–Meier survival analysis curve displaying survival probability over time for two groups: low and high SORT1 expression. The high SORT1 group showcases a reduced survival probability compared to the low SORT1 group, indicating the potential role of SORT1 as a prognostic marker. The hazard ratio (HR) of 1.44 (95% confidence interval (CI): 1.02–2.03) with a log-rank p -value of 0.039 suggests a significant association between high SORT1 expression and poor prognosis. I Bar graph showing fold-changes in SORT1 expression across a cohort of patients with HCC (n = 86), highlighting its differential expression in HCC. J Western blot analysis and quantitative optical density of SORT1 in paired HCC and adjacent normal tissues obtained from various patients. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as the loading control. Statistical significance is indicated as * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. The analysis was performed using one-way ANOVA.
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    ( A ) qRT-PCR analysis of triplicate RNA samples from Dox-induced vs. uninduced BAKP cells were subjected to RNA-seq analysis. ( B ) Volcano plot of RNA-seq analysis shows top upregulated genes (top panel), while differential expression table shows fold increase in <t>PROM1</t> and AREG expression (bottom panel). An adjusted p value (q-value < 0.05) and fold change (log2 fold change ≥ ±2) were used to identify significantly up- or downregulated genes. The top significantly upregulated genes (FDR < 0.01) are shown in the volcano plot.
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    ( A ) qRT-PCR analysis of triplicate RNA samples from Dox-induced vs. uninduced BAKP cells were subjected to RNA-seq analysis. ( B ) Volcano plot of RNA-seq analysis shows top upregulated genes (top panel), while differential expression table shows fold increase in <t>PROM1</t> and AREG expression (bottom panel). An adjusted p value (q-value < 0.05) and fold change (log2 fold change ≥ ±2) were used to identify significantly up- or downregulated genes. The top significantly upregulated genes (FDR < 0.01) are shown in the volcano plot.
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    Image Search Results


    ( A ) General morphology of livers 2 days after PHx. ( B ) H&E staining of liver sections 2 days after PHx. ( C and D ) Ki67 + percentages in HNF4α + hepatocytes ( C ) and HNF4α− NPCs ( D ) 2 days after PHx. Means ± SEM are shown, n=3 per group, **p<0.01 (two-tailed unpaired t-test). n.s., not significant. ( E ) EpCAM was highly expressed in biliary epithelial cells (arrow), but not in the colony (dashed line). Stellate cells (GFAP) were not altered around the colony. ( F ) CK19 was highly expressed in biliary epithelial cells (arrow), but not in the colony (dashed line). CD133 was highly expressed in the colony. ( G ) Sox9 and CD44 were highly expressed in biliary epithelial cells (arrowhead), but was not upregulated in the colony (dashed line) compared to surrounding hepatocytes. ( H ) α-fetoprotein (AFP) showed no difference between the colony (dashed line) and the surrounding tissue. ( I ) Liver/body weight ratios after PHx. Means ± SEM from three or more mice analyzed for each time point and group are shown. ( J and K ) Immunofluorescent staining of SKO liver sections 3 weeks after PHx. Colonies were of various sizes and locations as shown by arrows in ( J ). Macroscopic colonies were found as shown by arrows and dashed lines in ( K ). Immunofluorescent image in ( K ) corresponds to the magenta arrow in the liver image. PV, portal vein; CV, central vein. ( L ) Vasculature shown by PECAM did not distinguish the colony (arrow). ( M ) HGF expressed by non-parenchymal cells (NPCs) was not concentrated in the colony (dashed line). Scale bars, 1 cm ( A ) 100 μm ( B, E–G, I–L ).

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: ( A ) General morphology of livers 2 days after PHx. ( B ) H&E staining of liver sections 2 days after PHx. ( C and D ) Ki67 + percentages in HNF4α + hepatocytes ( C ) and HNF4α− NPCs ( D ) 2 days after PHx. Means ± SEM are shown, n=3 per group, **p<0.01 (two-tailed unpaired t-test). n.s., not significant. ( E ) EpCAM was highly expressed in biliary epithelial cells (arrow), but not in the colony (dashed line). Stellate cells (GFAP) were not altered around the colony. ( F ) CK19 was highly expressed in biliary epithelial cells (arrow), but not in the colony (dashed line). CD133 was highly expressed in the colony. ( G ) Sox9 and CD44 were highly expressed in biliary epithelial cells (arrowhead), but was not upregulated in the colony (dashed line) compared to surrounding hepatocytes. ( H ) α-fetoprotein (AFP) showed no difference between the colony (dashed line) and the surrounding tissue. ( I ) Liver/body weight ratios after PHx. Means ± SEM from three or more mice analyzed for each time point and group are shown. ( J and K ) Immunofluorescent staining of SKO liver sections 3 weeks after PHx. Colonies were of various sizes and locations as shown by arrows in ( J ). Macroscopic colonies were found as shown by arrows and dashed lines in ( K ). Immunofluorescent image in ( K ) corresponds to the magenta arrow in the liver image. PV, portal vein; CV, central vein. ( L ) Vasculature shown by PECAM did not distinguish the colony (arrow). ( M ) HGF expressed by non-parenchymal cells (NPCs) was not concentrated in the colony (dashed line). Scale bars, 1 cm ( A ) 100 μm ( B, E–G, I–L ).

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Staining, Two Tailed Test

    ( A and B ) Immunofluorescence on liver tissue sections 2 days after PHx. HNF4α is a hepatocyte marker and Ki67 is a proliferation marker. Arrow in ( A ) points to an area enriched with proliferating hepatocytes. Dashed line in ( B ) shows an area with continuous CD133 expression. ( C ) Quantification of proliferating rate in hepatocytes in CD133-positive and -negative areas in Shp2 knockout (SKO) livers 2 days after PHx. Each dot indicates one area. Data were collected from 3 mice. Means ± SEM are shown. ****p<0.0001 (two-tailed unpaired t-test). ( D ) While WT hepatocytes proliferated at high frequency everywhere, proliferating hepatocytes in SKO liver were mostly located in patchy areas marked by CD133 expression. ( E ) Immunofluorescence of CD133 on liver tissues at day 0 or 2, and 3 weeks (0d, 2d, 3 wk) after PHx. CD133 + hepatocyte clusters were only found in SKO livers after PHx (light green arrows). In WT livers, CD133 expression was only seen in bile duct epithelial cells (arrowheads). Scale bars, 100 μm ( A and E ).

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: ( A and B ) Immunofluorescence on liver tissue sections 2 days after PHx. HNF4α is a hepatocyte marker and Ki67 is a proliferation marker. Arrow in ( A ) points to an area enriched with proliferating hepatocytes. Dashed line in ( B ) shows an area with continuous CD133 expression. ( C ) Quantification of proliferating rate in hepatocytes in CD133-positive and -negative areas in Shp2 knockout (SKO) livers 2 days after PHx. Each dot indicates one area. Data were collected from 3 mice. Means ± SEM are shown. ****p<0.0001 (two-tailed unpaired t-test). ( D ) While WT hepatocytes proliferated at high frequency everywhere, proliferating hepatocytes in SKO liver were mostly located in patchy areas marked by CD133 expression. ( E ) Immunofluorescence of CD133 on liver tissues at day 0 or 2, and 3 weeks (0d, 2d, 3 wk) after PHx. CD133 + hepatocyte clusters were only found in SKO livers after PHx (light green arrows). In WT livers, CD133 expression was only seen in bile duct epithelial cells (arrowheads). Scale bars, 100 μm ( A and E ).

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Immunofluorescence, Marker, Expressing, Knock-Out, Two Tailed Test

    ( A and B ) Immunofluorescence on in vitro colonies of primary hepatocytes from Shp2 knockout (SKO) liver. CD133 was localized at filament-like structures in E-Cad + colonies as shown by arrowheads in ( A ), which were connected between different hepatocytes as shown by arrows in ( B ). ( C ) 3D-reconstituted confocal image of immunofluorescence on PLC cells. Lower panel shows the Z-plane section of the orange box area. Arrowheads indicate the CD133 signal on continuous filament-like structures bridged between neighboring cells. Pink dashed lines indicate the cell surface. ( D ) Immunofluorescence of MCF10A cells treated with Shp2 inhibitor. ( E and F ) Super-resolution STORM images of immunofluorescence on PLC cells without ( E ) or with ( F ) CD133 overexpression. Colocalization of CD133 and β-tubulin was analyzed as Pearson’s coefficient. Mismatched green and magenta channels from shuffled ROIs were measured as controls (Figure S4E). Means ± SEM from six images are shown. **p<0.01, ***p<0.001 (two-tailed unpaired t-test). ( G ) Immunofluorescence and Immuno-Gold EM images of cryo-ultramicrotome sections of SKO liver tissue after partial hepatectomy (PHx). Cyan arrowheads and asterisk indicate apical lumens. White arrowheads indicate the CD133 signals aligned between the apical lumens of neighboring cells. Light green arrow, CD133 staining (12 nm colloidal gold); Magenta arrows, α-tubulin staining (18 nm colloidal gold). ( H ) Immunoblotting of CD133 + vesicles isolated from MEK inhibitor (MEKi) -treated PLC cells. Markers for different fractions were analyzed. CD133 antibody used for the vesicle isolation was IgG produced in mouse, which was detected by anti-mouse IgG antibody, showing efficient capture by the beads. Despite the efficient capture, the DMSO-treated PLC cells did not have much CD133 + vesicle to be bound with the antibody. ( I ) EM image of Immunogold staining on the isolated vesicle. Scale bars, 100 μm ( A ), 25 μm ( D ), 1 μm (E, F, Fluorescence in G), 100 nm (EM in G), 50 nm ( I ). Figure 5—source data 1. Source data for western blot in panel H.

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: ( A and B ) Immunofluorescence on in vitro colonies of primary hepatocytes from Shp2 knockout (SKO) liver. CD133 was localized at filament-like structures in E-Cad + colonies as shown by arrowheads in ( A ), which were connected between different hepatocytes as shown by arrows in ( B ). ( C ) 3D-reconstituted confocal image of immunofluorescence on PLC cells. Lower panel shows the Z-plane section of the orange box area. Arrowheads indicate the CD133 signal on continuous filament-like structures bridged between neighboring cells. Pink dashed lines indicate the cell surface. ( D ) Immunofluorescence of MCF10A cells treated with Shp2 inhibitor. ( E and F ) Super-resolution STORM images of immunofluorescence on PLC cells without ( E ) or with ( F ) CD133 overexpression. Colocalization of CD133 and β-tubulin was analyzed as Pearson’s coefficient. Mismatched green and magenta channels from shuffled ROIs were measured as controls (Figure S4E). Means ± SEM from six images are shown. **p<0.01, ***p<0.001 (two-tailed unpaired t-test). ( G ) Immunofluorescence and Immuno-Gold EM images of cryo-ultramicrotome sections of SKO liver tissue after partial hepatectomy (PHx). Cyan arrowheads and asterisk indicate apical lumens. White arrowheads indicate the CD133 signals aligned between the apical lumens of neighboring cells. Light green arrow, CD133 staining (12 nm colloidal gold); Magenta arrows, α-tubulin staining (18 nm colloidal gold). ( H ) Immunoblotting of CD133 + vesicles isolated from MEK inhibitor (MEKi) -treated PLC cells. Markers for different fractions were analyzed. CD133 antibody used for the vesicle isolation was IgG produced in mouse, which was detected by anti-mouse IgG antibody, showing efficient capture by the beads. Despite the efficient capture, the DMSO-treated PLC cells did not have much CD133 + vesicle to be bound with the antibody. ( I ) EM image of Immunogold staining on the isolated vesicle. Scale bars, 100 μm ( A ), 25 μm ( D ), 1 μm (E, F, Fluorescence in G), 100 nm (EM in G), 50 nm ( I ). Figure 5—source data 1. Source data for western blot in panel H.

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Immunofluorescence, In Vitro, Knock-Out, Over Expression, Two Tailed Test, Staining, Western Blot, Isolation, Produced, Fluorescence

    ( A–C ) Immunofluorescence on PLC cells transfected with CD133-Myc-tag fusion protein expression construct. Cells with different expression levels are shown as representatives. In ( A ) and ( C ), exposure times for the CD133 signals were adjusted separately to clearly demonstrate the patterns, rather than intensities. Note that cells with higher CD133 expression displayed bulky patterns of the filaments, with maintained colocalization with tubulin filaments. Arrowheads, CD133 + filaments. As shown in ( B ), the overexpressed CD133 primarily localizes to the filaments, without detectable membrane localization (arrowheads). With extreme overexpression, CD133 can also localize to the cellular membrane surface, altering the morphology of the surface (right panels). ( D ) Immunofluorescence on HeLa and MC38 cells. ( E ) Colocalization of CD133 and β-tubulin was analyzed as Pearson’s coefficient. Mismatched green and magenta channels from shuffled ROIs were measured as controls. ( F ) Immunofluorescence on PLC cells transfected with cMet-GFP. cMet, an HGF receptor, shows the cell surface. CD133 did not colocalize with cMet-GFP on the cell surface, but instead localized to the filaments. ( G ) Immuno-Gold EM images of cryo-ultramicrotome sections of Shp2 knockout (SKO) liver tissue after partial hepatectomy (PHx). Light green arrowheads, CD133 staining (12 nm colloidal gold); Magenta arrowheads, α-tubulin staining (18 nm colloidal gold). Scale bars, 5 μm ( A and C ), 50 μm ( B and D ), 25 μm ( F ), and 50 nm ( G ).

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: ( A–C ) Immunofluorescence on PLC cells transfected with CD133-Myc-tag fusion protein expression construct. Cells with different expression levels are shown as representatives. In ( A ) and ( C ), exposure times for the CD133 signals were adjusted separately to clearly demonstrate the patterns, rather than intensities. Note that cells with higher CD133 expression displayed bulky patterns of the filaments, with maintained colocalization with tubulin filaments. Arrowheads, CD133 + filaments. As shown in ( B ), the overexpressed CD133 primarily localizes to the filaments, without detectable membrane localization (arrowheads). With extreme overexpression, CD133 can also localize to the cellular membrane surface, altering the morphology of the surface (right panels). ( D ) Immunofluorescence on HeLa and MC38 cells. ( E ) Colocalization of CD133 and β-tubulin was analyzed as Pearson’s coefficient. Mismatched green and magenta channels from shuffled ROIs were measured as controls. ( F ) Immunofluorescence on PLC cells transfected with cMet-GFP. cMet, an HGF receptor, shows the cell surface. CD133 did not colocalize with cMet-GFP on the cell surface, but instead localized to the filaments. ( G ) Immuno-Gold EM images of cryo-ultramicrotome sections of Shp2 knockout (SKO) liver tissue after partial hepatectomy (PHx). Light green arrowheads, CD133 staining (12 nm colloidal gold); Magenta arrowheads, α-tubulin staining (18 nm colloidal gold). Scale bars, 5 μm ( A and C ), 50 μm ( B and D ), 25 μm ( F ), and 50 nm ( G ).

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Immunofluorescence, Transfection, Expressing, Construct, Membrane, Over Expression, Knock-Out, Staining

    ( A ) Agarose gel electrophoresis of total RNAs extracted from WT and Shp2 knockout (SKO) livers and CD133-positive vesicle and negative fractions from SKO liver after partial hepatectomy (PHx). Arrowheads show rRNAs and arrow shows microRNAs. ( B ) qRT-PCR analysis of RNAs extracted form WT (3 mice) and SKO tissues (3 mice) and from CD133 + vesicles and CD133 − fractions (four mice for both). Means ± SEM are shown. *p<0.05, **p<0.01 (uncorrected Dunn’s multiple comparison test, performed after Kruscal-Wallis test). n.s., not significant. ( C ) RNA-seq analysis of the different cell types and the whole cells. The bars indicate proportions between numbers of deficient and enriched gene transcripts in each RNA types. ( D ) Comparison of IEG contents between the different vesicle types with RNA-seq. Different lanes indicate independent vesicle isolations. ( E ) RNA-FISH for Myc mRNA and immunostaining for CD133. ( F ) Quantitative colocalization analysis of CD133 and MYC mRNA in PLC cells shown in ( E ). Means ± SEM from 14 images are shown. ( G ) Experimental design to detect the traffic of CD133 + vesicles between neighbor cells. ( H ) Immunostaining of Myc-tag and CD133 on GFP + and mCherry + PLC cells mixed as shown in ( G ). Note that Myc-tag only indicates exogenous CD133, while CD133 indicates both endogenous and exogenous CD133. Myc-tag was primarily detected in the GFP + cells, but also detected on the bridges (arrowheads) and in the mCherry + cells (arrows). GFP was not detected at the same locations (arrowheads and arrows), indicating the specific traffic of CD133-Myc-tag. Scale bars, 10 μm ( E ) and 50 μm ( H ).

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: ( A ) Agarose gel electrophoresis of total RNAs extracted from WT and Shp2 knockout (SKO) livers and CD133-positive vesicle and negative fractions from SKO liver after partial hepatectomy (PHx). Arrowheads show rRNAs and arrow shows microRNAs. ( B ) qRT-PCR analysis of RNAs extracted form WT (3 mice) and SKO tissues (3 mice) and from CD133 + vesicles and CD133 − fractions (four mice for both). Means ± SEM are shown. *p<0.05, **p<0.01 (uncorrected Dunn’s multiple comparison test, performed after Kruscal-Wallis test). n.s., not significant. ( C ) RNA-seq analysis of the different cell types and the whole cells. The bars indicate proportions between numbers of deficient and enriched gene transcripts in each RNA types. ( D ) Comparison of IEG contents between the different vesicle types with RNA-seq. Different lanes indicate independent vesicle isolations. ( E ) RNA-FISH for Myc mRNA and immunostaining for CD133. ( F ) Quantitative colocalization analysis of CD133 and MYC mRNA in PLC cells shown in ( E ). Means ± SEM from 14 images are shown. ( G ) Experimental design to detect the traffic of CD133 + vesicles between neighbor cells. ( H ) Immunostaining of Myc-tag and CD133 on GFP + and mCherry + PLC cells mixed as shown in ( G ). Note that Myc-tag only indicates exogenous CD133, while CD133 indicates both endogenous and exogenous CD133. Myc-tag was primarily detected in the GFP + cells, but also detected on the bridges (arrowheads) and in the mCherry + cells (arrows). GFP was not detected at the same locations (arrowheads and arrows), indicating the specific traffic of CD133-Myc-tag. Scale bars, 10 μm ( E ) and 50 μm ( H ).

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Agarose Gel Electrophoresis, Knock-Out, Quantitative RT-PCR, Comparison, RNA Sequencing Assay, Immunostaining

    ( A ) Correlative light and electron microscopy (CLEM) analysis of the intercellular traffic demonstrated in . Instead of co-transfection of lenti-GFP and lenti-CD133-Myc as in , lenti-CD133-GFP was used, and the CD133-GFP expressing cells were mixed with mCherry-expressing cells. CD133-GFP was double-labeled with nano-gold, which was enhanced by silver and fluorophore Alexa488. The gold/silver signals vary in sizes due to variable silver enhancement. The gold/silver signals were detected around the boundaries between the CD133-GFP + donor cells and the mCherry + recipient cells, indicating intercellular traffic of the exogenous CD133-GFP protein (arrows). Some filament-like structures were also observed (arrowheads). The dashed circles show a corresponding signal in the fluorescent image and electron-microscopy (EM) image. ( B ) Another representative image in the same experiment as in ( A ). The gold/silver signals were observed between the donor and recipients as well as inside the recipient cell (arrows).

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: ( A ) Correlative light and electron microscopy (CLEM) analysis of the intercellular traffic demonstrated in . Instead of co-transfection of lenti-GFP and lenti-CD133-Myc as in , lenti-CD133-GFP was used, and the CD133-GFP expressing cells were mixed with mCherry-expressing cells. CD133-GFP was double-labeled with nano-gold, which was enhanced by silver and fluorophore Alexa488. The gold/silver signals vary in sizes due to variable silver enhancement. The gold/silver signals were detected around the boundaries between the CD133-GFP + donor cells and the mCherry + recipient cells, indicating intercellular traffic of the exogenous CD133-GFP protein (arrows). Some filament-like structures were also observed (arrowheads). The dashed circles show a corresponding signal in the fluorescent image and electron-microscopy (EM) image. ( B ) Another representative image in the same experiment as in ( A ). The gold/silver signals were observed between the donor and recipients as well as inside the recipient cell (arrows).

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Electron Microscopy, Cotransfection, Expressing, Labeling

    ( A ) Immunoblotting of HuR in the CD133 + vesicles from Shp2 knockout (SKO) liver after partial hepatectomy (PHx). GAPDH and HNF4α were used as controls for cytoplasmic and nuclear fractions, respectively. ( B ) Immunofluorescence on PLC cells. Arrows, peri-nuclear areas enriched with HuR in the cytoplasm; Arrowheads show colocalization of HuR on the CD133 + filament bridging two cells. ( C ) Immunofluorescence on PLC cells treated with the Shp2 inhibitor (SHP099). Arrowheads show strong localization of HuR on the CD133 + filaments. ( D ) Immunofluorescence on PLC cells transfected with CD133 expression vector treated with a Shp2 inhibitor (SHP099). Arrowheads show strong localization of HuR on the CD133 + filaments. ( E ) Immunoblotting of CD133 + vesicles isolated from MEK inhibitor-treated PLC cells. ( F ) qRT-PCR analysis of PLC cell lysates after treatment with CD133 + vesicles isolated from MEK inhibitor-treated PLC cells. RNase and Triton X-100 were used to digest the RNA content of the vesicles. *p<0.05 (two-tailed unpaired t-test). n.s., not statistically significant. Means ± SD from three replicates are shown. ( G ) A model and predictions for single-cell RNA-seq data analysis. ( H ) Total immediate early-responsive gene (IEG) expression levels. Cyclin D1-positive and -negative cells were analyzed separately to evaluate the influence of the cell cycle on the IEG analysis. See the Methods section for what the bars and dots represent. ( I and J ) Box plots (Tukey’s) of IEG diversity within each cell (calculated as entropy) and IEG variations among cells. Analyses were focused on cyclin D1 + cells in all groups for fair comparison. ( K and L ) Plot of intracellular IEG diversity against total IEG expression levels in SKO hepatocytes 2 days after PHx. Blue color gradient indicates cyclin D1 expression levels. For the simulation in ( L ), the parameters used were: Group of 5 cells, X=1/12, model 3 (see also and Methods). Green and Black arrows show typical profiles of CD133-positive and -negative cells, respectively. ( M ) Box plot (Tukey’s) of intracellular IEG diversity after simulation. The analysis was not limited to cyclin D1-positive or -negative cells. Note the simulation of the IEG exchange attracted the cells from cyclin D1-low profile to cyclin D1-high profile ( K–M ). Statistics were performed by the Wilcoxon rank sum test adjusted by FDR in ( I ), ( J ), and ( M ). Scale bars, 50 μm ( B, C ), 5 μm ( D ). Figure 7—source code 1. Source code for the simulations in panels K-M. Figure 7—source data 1. Source data for western blots in panel A and E.

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: ( A ) Immunoblotting of HuR in the CD133 + vesicles from Shp2 knockout (SKO) liver after partial hepatectomy (PHx). GAPDH and HNF4α were used as controls for cytoplasmic and nuclear fractions, respectively. ( B ) Immunofluorescence on PLC cells. Arrows, peri-nuclear areas enriched with HuR in the cytoplasm; Arrowheads show colocalization of HuR on the CD133 + filament bridging two cells. ( C ) Immunofluorescence on PLC cells treated with the Shp2 inhibitor (SHP099). Arrowheads show strong localization of HuR on the CD133 + filaments. ( D ) Immunofluorescence on PLC cells transfected with CD133 expression vector treated with a Shp2 inhibitor (SHP099). Arrowheads show strong localization of HuR on the CD133 + filaments. ( E ) Immunoblotting of CD133 + vesicles isolated from MEK inhibitor-treated PLC cells. ( F ) qRT-PCR analysis of PLC cell lysates after treatment with CD133 + vesicles isolated from MEK inhibitor-treated PLC cells. RNase and Triton X-100 were used to digest the RNA content of the vesicles. *p<0.05 (two-tailed unpaired t-test). n.s., not statistically significant. Means ± SD from three replicates are shown. ( G ) A model and predictions for single-cell RNA-seq data analysis. ( H ) Total immediate early-responsive gene (IEG) expression levels. Cyclin D1-positive and -negative cells were analyzed separately to evaluate the influence of the cell cycle on the IEG analysis. See the Methods section for what the bars and dots represent. ( I and J ) Box plots (Tukey’s) of IEG diversity within each cell (calculated as entropy) and IEG variations among cells. Analyses were focused on cyclin D1 + cells in all groups for fair comparison. ( K and L ) Plot of intracellular IEG diversity against total IEG expression levels in SKO hepatocytes 2 days after PHx. Blue color gradient indicates cyclin D1 expression levels. For the simulation in ( L ), the parameters used were: Group of 5 cells, X=1/12, model 3 (see also and Methods). Green and Black arrows show typical profiles of CD133-positive and -negative cells, respectively. ( M ) Box plot (Tukey’s) of intracellular IEG diversity after simulation. The analysis was not limited to cyclin D1-positive or -negative cells. Note the simulation of the IEG exchange attracted the cells from cyclin D1-low profile to cyclin D1-high profile ( K–M ). Statistics were performed by the Wilcoxon rank sum test adjusted by FDR in ( I ), ( J ), and ( M ). Scale bars, 50 μm ( B, C ), 5 μm ( D ). Figure 7—source code 1. Source code for the simulations in panels K-M. Figure 7—source data 1. Source data for western blots in panel A and E.

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Western Blot, Knock-Out, Immunofluorescence, Transfection, Expressing, Plasmid Preparation, Isolation, Quantitative RT-PCR, Two Tailed Test, RNA Sequencing Assay, Comparison

    ( A ) Immunofluorescence on Shp2 knockout (SKO) liver 2 days after partial hepatectomy (PHx). Asterisks indicate vasculature. ( B ) Immunofluorescence on MCF10A cells treated with inhibitors. ( C ) qRT-PCR analysis of PLC cell lysates after treatment with CD133 + vesicles isolated from MEK inhibitor-treated PLC cells. RNase and Triton X-100 were used to digest the RNA content of the vesicles. *p<0.05, **p<0.01 (two-tailed unpaired t-test). n.s., not statistically significant. Means ± SD from three replicates are shown. ( D ) EM image of immunogold staining on the isolated vesicles. CD133 (arrows) and HuR (arrowheads) were double stained using secondary antibodies conjugated with different sizes of gold particles. Scale bars, 50 μm ( A and B ) and 50 nm ( D ).

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: ( A ) Immunofluorescence on Shp2 knockout (SKO) liver 2 days after partial hepatectomy (PHx). Asterisks indicate vasculature. ( B ) Immunofluorescence on MCF10A cells treated with inhibitors. ( C ) qRT-PCR analysis of PLC cell lysates after treatment with CD133 + vesicles isolated from MEK inhibitor-treated PLC cells. RNase and Triton X-100 were used to digest the RNA content of the vesicles. *p<0.05, **p<0.01 (two-tailed unpaired t-test). n.s., not statistically significant. Means ± SD from three replicates are shown. ( D ) EM image of immunogold staining on the isolated vesicles. CD133 (arrows) and HuR (arrowheads) were double stained using secondary antibodies conjugated with different sizes of gold particles. Scale bars, 50 μm ( A and B ) and 50 nm ( D ).

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Immunofluorescence, Knock-Out, Quantitative RT-PCR, Isolation, Two Tailed Test, Staining

    ( A ) Heatmap analysis of single hepatocytes. ( B ) Detection of CD133 expression in the single-cell RNA-seq data. ( C ) Expression levels of indicated hepatocyte subtype markers and stem cell-like markers. CD133 − and CD133 + hepatocytes in the SKO liver 2 days after PHx were compared. ( D ) Principal component analysis with the IEGs. ( E ) tSNE analysis. Clusters likely reflect spatial locations within the tissue.

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: ( A ) Heatmap analysis of single hepatocytes. ( B ) Detection of CD133 expression in the single-cell RNA-seq data. ( C ) Expression levels of indicated hepatocyte subtype markers and stem cell-like markers. CD133 − and CD133 + hepatocytes in the SKO liver 2 days after PHx were compared. ( D ) Principal component analysis with the IEGs. ( E ) tSNE analysis. Clusters likely reflect spatial locations within the tissue.

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Expressing, RNA Sequencing Assay

    ( A and B ) Immunofluorescence ( A ) on liver sections of WT and Prom1 KO mice 2 days after partial hepatectomy (PHx) with or without Shp2 deletion using AAV-Cre and quantification of Ki67 + ratio in hepatocytes in the indicated genotypes ( B ). Separate analyses of pericentral and periportal hepatocytes showed insignificance of zonal difference. **p<0.01, (two-tailed unpaired t-test). Means ± SEM are shown. n=3, 3, 4, and 5 mice, respectively. ( C and D ) Immunofluorescence ( C ) on primary hepatocytes isolated from Shp2 knockout (SKO) and Shp2/Prom1 double KO (DKO) mouse livers and quantification of Ki67 + ratio ( D ). Images of representative colonies are shown. ***p<0.001, (two-tailed unpaired t-test). Means ± SD from four wells are shown. ( E ) Experimental design with primary hepatocytes isolated from GFP-labeled SKO liver and unlabeled DKO liver. E-Cad + colonies were analyzed. ( F ) Immunofluorescence images of E-Cad + colonies in SKO, DKO, and mixed culture as shown in ( E ). The arrows show a GFP + SKO cell forming a part of the colony with the surrounding DKO cells. ( G ) Quantification of the Ki67 ratio in E-Cad + colony-forming cells is shown in ( F ). ***p<0.001 (two-tailed unpaired t-test). n.s., not statistically significant. Means ± SD from three wells are shown. ( H and I ) Immunofluorescence ( H ) on WT and Prom1 KO mouse intestinal organoids treated with MEK inhibitor (MEKi) and quantification of Ki67 + ratio in the crypt cells ( I ). Dashed lines indicate the crypt buds. *p<0.05, (two-tailed unpaired t-test). Means ± SD from three wells are shown. Each dot represents each crypt buds, and symbols indicate each well. Scale bars, 100 μm ( A, C, and F ) and 50 μm ( H ).

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: ( A and B ) Immunofluorescence ( A ) on liver sections of WT and Prom1 KO mice 2 days after partial hepatectomy (PHx) with or without Shp2 deletion using AAV-Cre and quantification of Ki67 + ratio in hepatocytes in the indicated genotypes ( B ). Separate analyses of pericentral and periportal hepatocytes showed insignificance of zonal difference. **p<0.01, (two-tailed unpaired t-test). Means ± SEM are shown. n=3, 3, 4, and 5 mice, respectively. ( C and D ) Immunofluorescence ( C ) on primary hepatocytes isolated from Shp2 knockout (SKO) and Shp2/Prom1 double KO (DKO) mouse livers and quantification of Ki67 + ratio ( D ). Images of representative colonies are shown. ***p<0.001, (two-tailed unpaired t-test). Means ± SD from four wells are shown. ( E ) Experimental design with primary hepatocytes isolated from GFP-labeled SKO liver and unlabeled DKO liver. E-Cad + colonies were analyzed. ( F ) Immunofluorescence images of E-Cad + colonies in SKO, DKO, and mixed culture as shown in ( E ). The arrows show a GFP + SKO cell forming a part of the colony with the surrounding DKO cells. ( G ) Quantification of the Ki67 ratio in E-Cad + colony-forming cells is shown in ( F ). ***p<0.001 (two-tailed unpaired t-test). n.s., not statistically significant. Means ± SD from three wells are shown. ( H and I ) Immunofluorescence ( H ) on WT and Prom1 KO mouse intestinal organoids treated with MEK inhibitor (MEKi) and quantification of Ki67 + ratio in the crypt cells ( I ). Dashed lines indicate the crypt buds. *p<0.05, (two-tailed unpaired t-test). Means ± SD from three wells are shown. Each dot represents each crypt buds, and symbols indicate each well. Scale bars, 100 μm ( A, C, and F ) and 50 μm ( H ).

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Immunofluorescence, Two Tailed Test, Isolation, Knock-Out, Labeling

    Immunofluorescence on WT and Prom1 KO mouse intestinal tissue sections and intestinal organoids. Scale bars, 20 μm.

    Journal: eLife

    Article Title: Identification of CD133 + intercellsomes in intercellular communication to offset intracellular signal deficit

    doi: 10.7554/eLife.86824

    Figure Lengend Snippet: Immunofluorescence on WT and Prom1 KO mouse intestinal tissue sections and intestinal organoids. Scale bars, 20 μm.

    Article Snippet: Cells were transfected with CD133-Myc-Tag expression vector (HG15024-CM; SinoBiological) using Lipofectamine 3000 transfection reagent (Invitrogen).

    Techniques: Immunofluorescence

    Generation and characterization of siPD-L1-loaded CD133-tEx. A, Schematic representation of the engineering process for creating siPD-L1-loaded CD133-tEx. The DNA sequence encoding the CD133-targeting peptide was inserted into the pDisplay vector, which contains a portion of the PDGFR transmembrane domain, using restriction enzymes. This recombinant vector was then used to transfect ASCs. The transfected ASCs expressed the CD133-targeting peptide on their cell membranes, resulting in exosomes (tEx) displaying the CD133-targeting peptide on their surface. Finally, siPD-L1 was encapsulated within these exosomes using a transfection kit, creating siPD-L1-loaded CD133-tEx, referred to as tEx(s). B, NTA using Zetaview, demonstrating the size distribution of Ex and CD133-tEx. Both types of exosomes exhibited similar size and distribution profiles, indicating that the genetic engineering did not significantly alter their physical properties. C, Western blot analysis showing CD133 expression across various pancreatic cancer cell lines, including AsPC-1, MIA PaCa-2, PANC-1, and Capan-2 cells. Elevated CD133 expression was observed in AsPC-1, PANC-1, and Capan-2 cells, while MIA PaCa-2 cells exhibited lower CD133 expression levels. D, Flow cytometry analysis of exosomes derived from ASCs (Ex) and transfected ASCs (tEx) using CD63 and Myc markers (top panel), and CD81 and Myc markers (bottom panel). The flow cytometry histograms display the expression levels of these markers. CD63 and CD81 demonstrated comparable expression levels in ASCs and tASCs, with no significant difference. However, Myc expression, indicating the presence of the CD133-targeting peptide, was significantly higher in tEx compared to Ex, confirming the successful generation of tEx. Values are presented as mean ± standard deviation of three independent experiments. * P < 0.05. E, Immunohistochemical analysis of CD133 expression in normal pancreatic tissue and pancreatic cancer tissues. The expression of CD133 in pancreatic cancer was significantly elevated compared to normal pancreatic tissue (P < 0.05).

    Journal: Pancreas

    Article Title: Enhancing Pancreatic Cancer Therapy With Targeted CD133-Exosome Delivery of PD-L1 siRNA

    doi: 10.1097/MPA.0000000000002419

    Figure Lengend Snippet: Generation and characterization of siPD-L1-loaded CD133-tEx. A, Schematic representation of the engineering process for creating siPD-L1-loaded CD133-tEx. The DNA sequence encoding the CD133-targeting peptide was inserted into the pDisplay vector, which contains a portion of the PDGFR transmembrane domain, using restriction enzymes. This recombinant vector was then used to transfect ASCs. The transfected ASCs expressed the CD133-targeting peptide on their cell membranes, resulting in exosomes (tEx) displaying the CD133-targeting peptide on their surface. Finally, siPD-L1 was encapsulated within these exosomes using a transfection kit, creating siPD-L1-loaded CD133-tEx, referred to as tEx(s). B, NTA using Zetaview, demonstrating the size distribution of Ex and CD133-tEx. Both types of exosomes exhibited similar size and distribution profiles, indicating that the genetic engineering did not significantly alter their physical properties. C, Western blot analysis showing CD133 expression across various pancreatic cancer cell lines, including AsPC-1, MIA PaCa-2, PANC-1, and Capan-2 cells. Elevated CD133 expression was observed in AsPC-1, PANC-1, and Capan-2 cells, while MIA PaCa-2 cells exhibited lower CD133 expression levels. D, Flow cytometry analysis of exosomes derived from ASCs (Ex) and transfected ASCs (tEx) using CD63 and Myc markers (top panel), and CD81 and Myc markers (bottom panel). The flow cytometry histograms display the expression levels of these markers. CD63 and CD81 demonstrated comparable expression levels in ASCs and tASCs, with no significant difference. However, Myc expression, indicating the presence of the CD133-targeting peptide, was significantly higher in tEx compared to Ex, confirming the successful generation of tEx. Values are presented as mean ± standard deviation of three independent experiments. * P < 0.05. E, Immunohistochemical analysis of CD133 expression in normal pancreatic tissue and pancreatic cancer tissues. The expression of CD133 in pancreatic cancer was significantly elevated compared to normal pancreatic tissue (P < 0.05).

    Article Snippet: According to The Human Protein Atlas, CD133 expression is observed in a notable subset of pancreatic cancer tissues, with expression levels varying from 3% to 75% in different samples., Numerous studies have consistently revealed a strong association between CD133 expression and adverse patient outcomes not only in pancreatic cancer but also in various other cancer types.

    Techniques: Sequencing, Plasmid Preparation, Recombinant, Transfection, Western Blot, Expressing, Flow Cytometry, Derivative Assay, Standard Deviation, Immunohistochemical staining

    Determination of in vitro targetability of CD133-tEx. A, In vitro targeting capabilities in AsPC-1 cells. Fluorescence microscopy analysis revealed that tEx exhibited a significantly higher DiL fluorescence signal compared to Ex in cells with elevated CD133 expression (AsPC-1 cells). Individual data points are shown, with each point representing a separate experiment. B, In vitro targeting capabilities in MIA PaCa-2 cells. There was no significant disparity in the DiL fluorescence signals between Ex and tEx in CD133-negative pancreatic cancer cells (MIA PaCa-2 cells). Individual data points are shown, with each point representing a separate experiment. Values are presented as mean ± standard deviation of three independent experiments. The number of data points for each group is indicated on the graph. * P < 0.05.

    Journal: Pancreas

    Article Title: Enhancing Pancreatic Cancer Therapy With Targeted CD133-Exosome Delivery of PD-L1 siRNA

    doi: 10.1097/MPA.0000000000002419

    Figure Lengend Snippet: Determination of in vitro targetability of CD133-tEx. A, In vitro targeting capabilities in AsPC-1 cells. Fluorescence microscopy analysis revealed that tEx exhibited a significantly higher DiL fluorescence signal compared to Ex in cells with elevated CD133 expression (AsPC-1 cells). Individual data points are shown, with each point representing a separate experiment. B, In vitro targeting capabilities in MIA PaCa-2 cells. There was no significant disparity in the DiL fluorescence signals between Ex and tEx in CD133-negative pancreatic cancer cells (MIA PaCa-2 cells). Individual data points are shown, with each point representing a separate experiment. Values are presented as mean ± standard deviation of three independent experiments. The number of data points for each group is indicated on the graph. * P < 0.05.

    Article Snippet: According to The Human Protein Atlas, CD133 expression is observed in a notable subset of pancreatic cancer tissues, with expression levels varying from 3% to 75% in different samples., Numerous studies have consistently revealed a strong association between CD133 expression and adverse patient outcomes not only in pancreatic cancer but also in various other cancer types.

    Techniques: In Vitro, Fluorescence, Microscopy, Expressing, Standard Deviation

    In vitro efficacy of PD-L1 siRNA-loaded CD133-tEx. A, Western blot analysis of PD-L1. Reduction in PD-L1 expression was assessed in pancreatic cancer cells, specifically AsPC-1 and MIA PaCa-2 cells, following PD-L1 siRNA treatment ( P < 0.05). B, Western blot analysis of apoptosis-related markers. The treatment groups were categorized as Ex, tEx, Ex(s), and tEx(s), with the target cells being AsPC-1 (left) and MIA PaCa-2 (right) pancreatic cancer cells. In both pancreatic cells, after 48 hours of treatment, the tEx(s) group exhibited the highest increase in the expression of proapoptotic markers, PARP, and c-caspase 3, along with the lowest expression of the antiapoptotic marker Mcl-1 ( P < 0.05). Relative densities of individual markers had been quantified using ImageJ software and then were normalized to that of β-actin in each group. Values are presented as mean ± standard deviation of three independent experiments. * P < 0.05.

    Journal: Pancreas

    Article Title: Enhancing Pancreatic Cancer Therapy With Targeted CD133-Exosome Delivery of PD-L1 siRNA

    doi: 10.1097/MPA.0000000000002419

    Figure Lengend Snippet: In vitro efficacy of PD-L1 siRNA-loaded CD133-tEx. A, Western blot analysis of PD-L1. Reduction in PD-L1 expression was assessed in pancreatic cancer cells, specifically AsPC-1 and MIA PaCa-2 cells, following PD-L1 siRNA treatment ( P < 0.05). B, Western blot analysis of apoptosis-related markers. The treatment groups were categorized as Ex, tEx, Ex(s), and tEx(s), with the target cells being AsPC-1 (left) and MIA PaCa-2 (right) pancreatic cancer cells. In both pancreatic cells, after 48 hours of treatment, the tEx(s) group exhibited the highest increase in the expression of proapoptotic markers, PARP, and c-caspase 3, along with the lowest expression of the antiapoptotic marker Mcl-1 ( P < 0.05). Relative densities of individual markers had been quantified using ImageJ software and then were normalized to that of β-actin in each group. Values are presented as mean ± standard deviation of three independent experiments. * P < 0.05.

    Article Snippet: According to The Human Protein Atlas, CD133 expression is observed in a notable subset of pancreatic cancer tissues, with expression levels varying from 3% to 75% in different samples., Numerous studies have consistently revealed a strong association between CD133 expression and adverse patient outcomes not only in pancreatic cancer but also in various other cancer types.

    Techniques: In Vitro, Western Blot, Expressing, Marker, Software, Standard Deviation

    Determination of in vivo targetability of CD133-tEx. A, Composition of groups for comparing in vivo targetability and efficacy. For the in vivo targetability test, we included three mice per group, consisting of Ct, Ex, and tEx groups. For the in vivo efficacy test, we included 5 mice per group, consisting of Ct, Ex, tEx, Ex(s), and tEx(s) groups. (B) IVIS imaging of mice conducted externally. DiL-labeled Ex and tEx were intravenously administered into the metastatic pancreatic cancer mouse model, respectively. The tEx group exhibited a significantly higher TRE compared to the Ex group ( P < 0.05). (C) Quantification of TRE in excised organs. The tEx group demonstrated a significantly higher TRE compared to the Ex group in both the liver and pancreas ( P < 0.05) (B).

    Journal: Pancreas

    Article Title: Enhancing Pancreatic Cancer Therapy With Targeted CD133-Exosome Delivery of PD-L1 siRNA

    doi: 10.1097/MPA.0000000000002419

    Figure Lengend Snippet: Determination of in vivo targetability of CD133-tEx. A, Composition of groups for comparing in vivo targetability and efficacy. For the in vivo targetability test, we included three mice per group, consisting of Ct, Ex, and tEx groups. For the in vivo efficacy test, we included 5 mice per group, consisting of Ct, Ex, tEx, Ex(s), and tEx(s) groups. (B) IVIS imaging of mice conducted externally. DiL-labeled Ex and tEx were intravenously administered into the metastatic pancreatic cancer mouse model, respectively. The tEx group exhibited a significantly higher TRE compared to the Ex group ( P < 0.05). (C) Quantification of TRE in excised organs. The tEx group demonstrated a significantly higher TRE compared to the Ex group in both the liver and pancreas ( P < 0.05) (B).

    Article Snippet: According to The Human Protein Atlas, CD133 expression is observed in a notable subset of pancreatic cancer tissues, with expression levels varying from 3% to 75% in different samples., Numerous studies have consistently revealed a strong association between CD133 expression and adverse patient outcomes not only in pancreatic cancer but also in various other cancer types.

    Techniques: In Vivo, Imaging, Labeling

    In vivo efficacy evaluation of PD-L1 siRNA-loaded CD133-tEx. A, Representative images of liver specimens demonstrating liver metastasis of pancreatic cancer. In the tEx(s) treatment group, the gross appearance of the liver indicated the most reduced tumor size. B, Real-time PCR comparing the mRNA expression of apoptosis-related markers. The tEx(s) group exhibited the most significant increase in Bax expression and the most significant decrease in Mcl-1 expression ( P < 0.05). C, Western blot analysis of apoptosis-related markers. In the tEx(s) group, c-caspase 3 expression increased the most, while Mcl-1 expression decreased the most ( P < 0.05). D, ELISA assessing serum concentration of systemic inflammatory markers. The serum levels of IL-6 and TNF-α did not show significant differences when compared to the control group in each respective treatment group. Relative densities of individual markers had been quantified using ImageJ software and then were normalized to that of β-actin in each group. Values are presented as mean ± standard deviation of three independent experiments. * P < 0.05.

    Journal: Pancreas

    Article Title: Enhancing Pancreatic Cancer Therapy With Targeted CD133-Exosome Delivery of PD-L1 siRNA

    doi: 10.1097/MPA.0000000000002419

    Figure Lengend Snippet: In vivo efficacy evaluation of PD-L1 siRNA-loaded CD133-tEx. A, Representative images of liver specimens demonstrating liver metastasis of pancreatic cancer. In the tEx(s) treatment group, the gross appearance of the liver indicated the most reduced tumor size. B, Real-time PCR comparing the mRNA expression of apoptosis-related markers. The tEx(s) group exhibited the most significant increase in Bax expression and the most significant decrease in Mcl-1 expression ( P < 0.05). C, Western blot analysis of apoptosis-related markers. In the tEx(s) group, c-caspase 3 expression increased the most, while Mcl-1 expression decreased the most ( P < 0.05). D, ELISA assessing serum concentration of systemic inflammatory markers. The serum levels of IL-6 and TNF-α did not show significant differences when compared to the control group in each respective treatment group. Relative densities of individual markers had been quantified using ImageJ software and then were normalized to that of β-actin in each group. Values are presented as mean ± standard deviation of three independent experiments. * P < 0.05.

    Article Snippet: According to The Human Protein Atlas, CD133 expression is observed in a notable subset of pancreatic cancer tissues, with expression levels varying from 3% to 75% in different samples., Numerous studies have consistently revealed a strong association between CD133 expression and adverse patient outcomes not only in pancreatic cancer but also in various other cancer types.

    Techniques: In Vivo, Real-time Polymerase Chain Reaction, Expressing, Western Blot, Enzyme-linked Immunosorbent Assay, Concentration Assay, Control, Software, Standard Deviation

    A Flow diagram detailing the methodology used to identify HCC driver gene signatures. B Venn diagram illustrating the overlap of significantly differentially expressed genes across the three datasets. C Serial pattern analysis of each dataset. The upper panels show line plots of gene expression patterns in different sample groups (NL, CH, LC, DN, eHCC, and aHCC) on the X-axis. The bottom panels display heat maps of the gene expression levels. NL, normal liver; CH, chronic hepatitis; LC, liver cirrhosis; DN, dysplastic nodules; eHCC, early HCC; aHCC, advanced HCC. D Venn diagram showing the overlap of common genes across the five RNA-seq datasets (TCGA, ICGC, GSE77314, GSE114564, and GSE124535). E Heatmap of the GSE114564 dataset showing gene expression patterns. Different genes are listed on the right side of the heatmap. F Box plots showing SORT1 expression at various stages of liver disease and cancer progression across the four datasets. The Y-axis represents SORT1 expression, whereas the X-axis represents different sample groups. G Paired plots showing the expression of SORT1 in HCC tumor (T) vs. non-tumoral (NT) tissues across four datasets: The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC), ICGC LIRI, GSE37991, and GSE77314. Each line connects the paired NT and T samples with a significant SORT1 upregulation in the tumor samples. H Kaplan–Meier survival analysis curve displaying survival probability over time for two groups: low and high SORT1 expression. The high SORT1 group showcases a reduced survival probability compared to the low SORT1 group, indicating the potential role of SORT1 as a prognostic marker. The hazard ratio (HR) of 1.44 (95% confidence interval (CI): 1.02–2.03) with a log-rank p -value of 0.039 suggests a significant association between high SORT1 expression and poor prognosis. I Bar graph showing fold-changes in SORT1 expression across a cohort of patients with HCC (n = 86), highlighting its differential expression in HCC. J Western blot analysis and quantitative optical density of SORT1 in paired HCC and adjacent normal tissues obtained from various patients. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as the loading control. Statistical significance is indicated as * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. The analysis was performed using one-way ANOVA.

    Journal: Cell Death & Disease

    Article Title: Effect of Sortilin1 on promoting angiogenesis and systemic metastasis in hepatocellular carcinoma via the Notch signaling pathway and CD133

    doi: 10.1038/s41419-024-07016-7

    Figure Lengend Snippet: A Flow diagram detailing the methodology used to identify HCC driver gene signatures. B Venn diagram illustrating the overlap of significantly differentially expressed genes across the three datasets. C Serial pattern analysis of each dataset. The upper panels show line plots of gene expression patterns in different sample groups (NL, CH, LC, DN, eHCC, and aHCC) on the X-axis. The bottom panels display heat maps of the gene expression levels. NL, normal liver; CH, chronic hepatitis; LC, liver cirrhosis; DN, dysplastic nodules; eHCC, early HCC; aHCC, advanced HCC. D Venn diagram showing the overlap of common genes across the five RNA-seq datasets (TCGA, ICGC, GSE77314, GSE114564, and GSE124535). E Heatmap of the GSE114564 dataset showing gene expression patterns. Different genes are listed on the right side of the heatmap. F Box plots showing SORT1 expression at various stages of liver disease and cancer progression across the four datasets. The Y-axis represents SORT1 expression, whereas the X-axis represents different sample groups. G Paired plots showing the expression of SORT1 in HCC tumor (T) vs. non-tumoral (NT) tissues across four datasets: The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC), ICGC LIRI, GSE37991, and GSE77314. Each line connects the paired NT and T samples with a significant SORT1 upregulation in the tumor samples. H Kaplan–Meier survival analysis curve displaying survival probability over time for two groups: low and high SORT1 expression. The high SORT1 group showcases a reduced survival probability compared to the low SORT1 group, indicating the potential role of SORT1 as a prognostic marker. The hazard ratio (HR) of 1.44 (95% confidence interval (CI): 1.02–2.03) with a log-rank p -value of 0.039 suggests a significant association between high SORT1 expression and poor prognosis. I Bar graph showing fold-changes in SORT1 expression across a cohort of patients with HCC (n = 86), highlighting its differential expression in HCC. J Western blot analysis and quantitative optical density of SORT1 in paired HCC and adjacent normal tissues obtained from various patients. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as the loading control. Statistical significance is indicated as * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. The analysis was performed using one-way ANOVA.

    Article Snippet: The SORT1 or CD133 expressing vectors were purchased from VectorBuilder (Chicago, IL, USA).

    Techniques: Gene Expression, RNA Sequencing, Expressing, Marker, Quantitative Proteomics, Western Blot, Control

    A Heatmap of SORT1 expression (z-score) in 24 datasets from the GepLiver DB. B SORT1 expression (log 2 (TPM + 1)) across tissues with different phenotypes. C Top: Representative hematoxylin and eosin (H&E) images. Middle: Spatial transcriptomics (ST) spots indicated by non-malignant (yellow) and malignant (purple) hepatocytes from tumor tissues. Bottom: SORT1 expression in the spatial sections. P: patient, T: tumor tissue. D Proportion of SORT1 + cells (%) (top) and SORT1 expression (bottom) in all analyzed tumor tissues. P: patient, T: tumor tissue. E UMAP plot of the GepLiver DB, an integrated liver scRNA-seq dataset. Each cell is colored according to the dataset (left) and major cell type (right). F UMAP plot of scAtlasLC. Each cell is colored by major cell type. G SORT1 expression (left) and proportion of SORT1 + cells (%) in hepatocytes of the GepLiver DB across different phenotypes. H SORT1 expression (left) and proportion of SORT1 + cells (%) in hepatocytes of the Single-cell Atlas in Liver Cancer (scAtlasLC) across different phenotypes. Statistical significance is indicated as ns, non-significant; * p < 0.05; **** p < 0.0001. Analyses were performed using the Welch’s t -test and one-way ANOVA.

    Journal: Cell Death & Disease

    Article Title: Effect of Sortilin1 on promoting angiogenesis and systemic metastasis in hepatocellular carcinoma via the Notch signaling pathway and CD133

    doi: 10.1038/s41419-024-07016-7

    Figure Lengend Snippet: A Heatmap of SORT1 expression (z-score) in 24 datasets from the GepLiver DB. B SORT1 expression (log 2 (TPM + 1)) across tissues with different phenotypes. C Top: Representative hematoxylin and eosin (H&E) images. Middle: Spatial transcriptomics (ST) spots indicated by non-malignant (yellow) and malignant (purple) hepatocytes from tumor tissues. Bottom: SORT1 expression in the spatial sections. P: patient, T: tumor tissue. D Proportion of SORT1 + cells (%) (top) and SORT1 expression (bottom) in all analyzed tumor tissues. P: patient, T: tumor tissue. E UMAP plot of the GepLiver DB, an integrated liver scRNA-seq dataset. Each cell is colored according to the dataset (left) and major cell type (right). F UMAP plot of scAtlasLC. Each cell is colored by major cell type. G SORT1 expression (left) and proportion of SORT1 + cells (%) in hepatocytes of the GepLiver DB across different phenotypes. H SORT1 expression (left) and proportion of SORT1 + cells (%) in hepatocytes of the Single-cell Atlas in Liver Cancer (scAtlasLC) across different phenotypes. Statistical significance is indicated as ns, non-significant; * p < 0.05; **** p < 0.0001. Analyses were performed using the Welch’s t -test and one-way ANOVA.

    Article Snippet: The SORT1 or CD133 expressing vectors were purchased from VectorBuilder (Chicago, IL, USA).

    Techniques: Expressing

    A Proliferation curves of Huh-7 and Hep3B cells post-treatment with NC and siSORT1 monitored over 96 h. B Microscopic images showing the morphology of Huh-7 and Hep3B liver cancer cell lines after treatment with negative control (NC) or siSORT1. The bar graphs on the right quantify the cell numbers for each condition. C Colony formation assay for Huh-7 and Hep3B cells treated with NC or siSORT1. The number of colonies is quantified in the bar graphs. D Wound-healing assay showing the migratory potential of Huh-7 and Hep3B cells in response to SORT1 silencing at 0 and 48 h post-wound creation. Quantification of wound closure is shown in bar graphs on the right. E Cell cycle distribution of Huh-7 and Hep3B cells after post-siSORT1 transfection, as assessed via propidium iodide (PI) staining and flow cytometry. Quantitative data for cells in different phases are shown on the right. F Flow cytometry analysis of Annexin V/PI-stained Huh-7 and Hep3B cells transfected with siSORT1 or control siRNA (NC). The quantification of apoptotic cells is shown on the right side. G Expression profiles of cell cycle-related proteins (p-Wee1, Cyclin B1, Cyclin D1, Cyclin D3, Cdc2, and Cdc25A) in Huh-7 and Hep3B cells after siSORT1 transfection, as detected via western blotting. The densitometric analysis of protein bands is shown on the right. H Western blot analysis of apoptosis-related proteins, including cleaved PARP, cleaved caspase 3, and cleaved caspase 9, in Huh-7 and Hep3B cells transfected with siSORT1 or NC. The densitometric quantification of bands is shown on the right. I Fluorescence microscopy images of Huh-7 and Hep3B cells stained with Hoechst33342 and PI after SORT1 silencing. Apoptotic nuclei (yellow arrowheads) and damaged DNA (white arrowheads) are highlighted. The merged images provide a comprehensive view of the cell status with zoomed-in insets for clarity. Scale bars represent 100 µm. All experiments were repeated at least three times, and representative data are shown. Statistical significance is indicated by * p < 0.05, ** p < 0.01, and *** p < 0.001. The analysis was performed using Welch’s t -test.

    Journal: Cell Death & Disease

    Article Title: Effect of Sortilin1 on promoting angiogenesis and systemic metastasis in hepatocellular carcinoma via the Notch signaling pathway and CD133

    doi: 10.1038/s41419-024-07016-7

    Figure Lengend Snippet: A Proliferation curves of Huh-7 and Hep3B cells post-treatment with NC and siSORT1 monitored over 96 h. B Microscopic images showing the morphology of Huh-7 and Hep3B liver cancer cell lines after treatment with negative control (NC) or siSORT1. The bar graphs on the right quantify the cell numbers for each condition. C Colony formation assay for Huh-7 and Hep3B cells treated with NC or siSORT1. The number of colonies is quantified in the bar graphs. D Wound-healing assay showing the migratory potential of Huh-7 and Hep3B cells in response to SORT1 silencing at 0 and 48 h post-wound creation. Quantification of wound closure is shown in bar graphs on the right. E Cell cycle distribution of Huh-7 and Hep3B cells after post-siSORT1 transfection, as assessed via propidium iodide (PI) staining and flow cytometry. Quantitative data for cells in different phases are shown on the right. F Flow cytometry analysis of Annexin V/PI-stained Huh-7 and Hep3B cells transfected with siSORT1 or control siRNA (NC). The quantification of apoptotic cells is shown on the right side. G Expression profiles of cell cycle-related proteins (p-Wee1, Cyclin B1, Cyclin D1, Cyclin D3, Cdc2, and Cdc25A) in Huh-7 and Hep3B cells after siSORT1 transfection, as detected via western blotting. The densitometric analysis of protein bands is shown on the right. H Western blot analysis of apoptosis-related proteins, including cleaved PARP, cleaved caspase 3, and cleaved caspase 9, in Huh-7 and Hep3B cells transfected with siSORT1 or NC. The densitometric quantification of bands is shown on the right. I Fluorescence microscopy images of Huh-7 and Hep3B cells stained with Hoechst33342 and PI after SORT1 silencing. Apoptotic nuclei (yellow arrowheads) and damaged DNA (white arrowheads) are highlighted. The merged images provide a comprehensive view of the cell status with zoomed-in insets for clarity. Scale bars represent 100 µm. All experiments were repeated at least three times, and representative data are shown. Statistical significance is indicated by * p < 0.05, ** p < 0.01, and *** p < 0.001. The analysis was performed using Welch’s t -test.

    Article Snippet: The SORT1 or CD133 expressing vectors were purchased from VectorBuilder (Chicago, IL, USA).

    Techniques: Negative Control, Colony Assay, Wound Healing Assay, Transfection, Staining, Flow Cytometry, Control, Expressing, Western Blot, Fluorescence, Microscopy

    A Representative images showing tumor progression on day 15 in mice after SORT1 silencing, highlighting the reduced tumor size in the siSORT1 group compared to that in the NC group. B Body weight changes in mice over 15 d; NC vs. siSORT1 conditions. C Quantitative analysis of tumor growth over 15 d, highlighting a marked reduction in tumor size following SORT1 silencing (left). Comparative assessment of tumor weights between NC and siSORT1 mice (right). D Relative SORT1 mRNA expression in tumor tissues (left) and protein expression levels in NC versus siSORT1 conditions (right). E Histopathological examination of the tumors. Hematoxylin and eosin (H&E) staining showed the tumor architecture (leftmost). Subsequent panels display immunohistochemical staining for SORT1, Ki-67, and PCNA in both the NC and siSORT1 groups, with quantification of the stained areas on the right. F Visual representation of mouse liver on days 0 and 27 after siRNA treatment. G Gross anatomy of excised tumors from NC and siSORT1 mice. H Comparative display of metastatic nodules excised from the livers of the NC and siSORT1 groups (left). Quantitative analysis of the weights of these nodules indicated a decrease in metastatic potential upon SORT1 silencing (right). I Tumor histological assessment post-metastasis: H&E staining of metastatic nodules (left), followed by immunohistochemical analyses for SORT1, Ki-67, and PCNA. The right panel shows the quantification of the stained regions, confirming the reduced metastatic potential and cell proliferation upon SORT1 silencing. Scale bars represent 50 µm. All experiments were repeated at least three times, and representative data are shown. Statistical significance is indicated by * p < 0.05, ** p < 0.01, and *** p < 0.001. The analysis was performed using Welch’s t -test.

    Journal: Cell Death & Disease

    Article Title: Effect of Sortilin1 on promoting angiogenesis and systemic metastasis in hepatocellular carcinoma via the Notch signaling pathway and CD133

    doi: 10.1038/s41419-024-07016-7

    Figure Lengend Snippet: A Representative images showing tumor progression on day 15 in mice after SORT1 silencing, highlighting the reduced tumor size in the siSORT1 group compared to that in the NC group. B Body weight changes in mice over 15 d; NC vs. siSORT1 conditions. C Quantitative analysis of tumor growth over 15 d, highlighting a marked reduction in tumor size following SORT1 silencing (left). Comparative assessment of tumor weights between NC and siSORT1 mice (right). D Relative SORT1 mRNA expression in tumor tissues (left) and protein expression levels in NC versus siSORT1 conditions (right). E Histopathological examination of the tumors. Hematoxylin and eosin (H&E) staining showed the tumor architecture (leftmost). Subsequent panels display immunohistochemical staining for SORT1, Ki-67, and PCNA in both the NC and siSORT1 groups, with quantification of the stained areas on the right. F Visual representation of mouse liver on days 0 and 27 after siRNA treatment. G Gross anatomy of excised tumors from NC and siSORT1 mice. H Comparative display of metastatic nodules excised from the livers of the NC and siSORT1 groups (left). Quantitative analysis of the weights of these nodules indicated a decrease in metastatic potential upon SORT1 silencing (right). I Tumor histological assessment post-metastasis: H&E staining of metastatic nodules (left), followed by immunohistochemical analyses for SORT1, Ki-67, and PCNA. The right panel shows the quantification of the stained regions, confirming the reduced metastatic potential and cell proliferation upon SORT1 silencing. Scale bars represent 50 µm. All experiments were repeated at least three times, and representative data are shown. Statistical significance is indicated by * p < 0.05, ** p < 0.01, and *** p < 0.001. The analysis was performed using Welch’s t -test.

    Article Snippet: The SORT1 or CD133 expressing vectors were purchased from VectorBuilder (Chicago, IL, USA).

    Techniques: Expressing, Staining, Immunohistochemical staining

    A Pathway analysis showing the most significant pathways related to SORT1 from the MSigDB Hallmark 2020 and Panther 2016 databases sorted by combined score. The p value is represented by color intensity. B Tube-formation assay in NC or siSORT1 transfected HUVECs and Hep3B cells. Images are shown at 4× and 10× magnifications. A quantitative analysis of the total tube length is shown on the right. C Western blot analysis of various epithelial-to-mesenchymal transition (EMT) markers in NC- or siSORT1-treated Huh-7 and Hep3B cells. Densitometric quantification is shown on the right-hand side. D Scatter plots illustrating the correlation between SORT1 and CDH2 (N-cadherin) and SORT1 and FN1 (fibronectin) based on TCGA LIHC data. The correlation coefficients (r) and p -value are provided. E Immunohistochemical staining of CD31, VEGF, ZO-1, and vimentin in tumors from mice with subcutaneous and orthotopic xenograft injections of either NC or siSORT1-transfected cells. F Body weight of mice subjected to either NC or siSORT1 treatment over a specified period. G Representative images of lung tumor nodules in mice on days 23, 35, 55, and 65 post-injection with either NC or siSORT1-transfected cells. Yellow arrows indicate precancerous blood dots and red arrows indicate tumors. H Quantitative analysis of the number of nodules formed in the lungs of mice treated with NC or siSORT1. Scale bars represent 50 µm. All experiments were repeated at least thrice, and representative data are shown. Statistical significance is indicated by * p < 0.05, ** p < 0.01, and *** p < 0.001. The analysis was performed using Welch’s t -test.

    Journal: Cell Death & Disease

    Article Title: Effect of Sortilin1 on promoting angiogenesis and systemic metastasis in hepatocellular carcinoma via the Notch signaling pathway and CD133

    doi: 10.1038/s41419-024-07016-7

    Figure Lengend Snippet: A Pathway analysis showing the most significant pathways related to SORT1 from the MSigDB Hallmark 2020 and Panther 2016 databases sorted by combined score. The p value is represented by color intensity. B Tube-formation assay in NC or siSORT1 transfected HUVECs and Hep3B cells. Images are shown at 4× and 10× magnifications. A quantitative analysis of the total tube length is shown on the right. C Western blot analysis of various epithelial-to-mesenchymal transition (EMT) markers in NC- or siSORT1-treated Huh-7 and Hep3B cells. Densitometric quantification is shown on the right-hand side. D Scatter plots illustrating the correlation between SORT1 and CDH2 (N-cadherin) and SORT1 and FN1 (fibronectin) based on TCGA LIHC data. The correlation coefficients (r) and p -value are provided. E Immunohistochemical staining of CD31, VEGF, ZO-1, and vimentin in tumors from mice with subcutaneous and orthotopic xenograft injections of either NC or siSORT1-transfected cells. F Body weight of mice subjected to either NC or siSORT1 treatment over a specified period. G Representative images of lung tumor nodules in mice on days 23, 35, 55, and 65 post-injection with either NC or siSORT1-transfected cells. Yellow arrows indicate precancerous blood dots and red arrows indicate tumors. H Quantitative analysis of the number of nodules formed in the lungs of mice treated with NC or siSORT1. Scale bars represent 50 µm. All experiments were repeated at least thrice, and representative data are shown. Statistical significance is indicated by * p < 0.05, ** p < 0.01, and *** p < 0.001. The analysis was performed using Welch’s t -test.

    Article Snippet: The SORT1 or CD133 expressing vectors were purchased from VectorBuilder (Chicago, IL, USA).

    Techniques: Tube Formation Assay, Transfection, Western Blot, Immunohistochemical staining, Staining, Injection

    A GSEA hallmark pathways analysis identifying the Notch signaling pathway as one of the top-ranked pathways in SORT1 high samples. B GO enrichment analysis confirming the enrichment of Notch signaling-related gene sets in SORT1 high samples. C Wilcoxon rank-sum test results showing ssGSEA scores of each Notch signaling pathway in samples stratified by SORT1 expression (top: scRNA-seq; bottom: bulk RNA-seq data). D Scatter plots representing the positive correlation between SORT1 and PROM1 (CD133), PROM1 and NOTCH1 , and SORT1 and NOTCH1 expression in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC) and ICGC LIRI datasets. Each dot represents a single sample. Pearson’s correlation coefficients (r) and p values are indicated for each plot. E Heatmap illustrating the correlation between SORT1 and selected genes involved in the Notch signaling pathway derived from the KEGG, Hallmark, and BIOCARTA datasets. Genes were chosen based on their established role in the Notch pathway and their significant positive correlation with SORT1 in TCGA LIHC dataset. The color intensities of the circles are proportional to the correlation coefficients. F Western blot analyses of Huh-7 and Hep3B cells treated with NC or siSORT1 showing the expression levels of Notch1, cleaved Notch1, and other pivotal Notch signaling molecules, along with CD133, in HCC cells. Statistical significance is indicated by ** p < 0.01, *** p < 0.001. The analysis was performed using Welch’s t -test.

    Journal: Cell Death & Disease

    Article Title: Effect of Sortilin1 on promoting angiogenesis and systemic metastasis in hepatocellular carcinoma via the Notch signaling pathway and CD133

    doi: 10.1038/s41419-024-07016-7

    Figure Lengend Snippet: A GSEA hallmark pathways analysis identifying the Notch signaling pathway as one of the top-ranked pathways in SORT1 high samples. B GO enrichment analysis confirming the enrichment of Notch signaling-related gene sets in SORT1 high samples. C Wilcoxon rank-sum test results showing ssGSEA scores of each Notch signaling pathway in samples stratified by SORT1 expression (top: scRNA-seq; bottom: bulk RNA-seq data). D Scatter plots representing the positive correlation between SORT1 and PROM1 (CD133), PROM1 and NOTCH1 , and SORT1 and NOTCH1 expression in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC) and ICGC LIRI datasets. Each dot represents a single sample. Pearson’s correlation coefficients (r) and p values are indicated for each plot. E Heatmap illustrating the correlation between SORT1 and selected genes involved in the Notch signaling pathway derived from the KEGG, Hallmark, and BIOCARTA datasets. Genes were chosen based on their established role in the Notch pathway and their significant positive correlation with SORT1 in TCGA LIHC dataset. The color intensities of the circles are proportional to the correlation coefficients. F Western blot analyses of Huh-7 and Hep3B cells treated with NC or siSORT1 showing the expression levels of Notch1, cleaved Notch1, and other pivotal Notch signaling molecules, along with CD133, in HCC cells. Statistical significance is indicated by ** p < 0.01, *** p < 0.001. The analysis was performed using Welch’s t -test.

    Article Snippet: The SORT1 or CD133 expressing vectors were purchased from VectorBuilder (Chicago, IL, USA).

    Techniques: Expressing, RNA Sequencing, Derivative Assay, Western Blot

    A SORT1 mRNA expression level based on gene copy number status from TCGA LIHC cohort (n = 371, left). Scatter plot illustrating the correlation between SORT1 mRNA expression and copy number (GISTIC) in TCGA LIHC cohort (n = 364, right). B Scatter plot illustrating the correlation between SORT1 mRNA expression and methylation in TCGA LIHC cohort (n = 371, left). Density plot displaying the methylation beta values for the (NT) and tumor (T) groups from the same cohort (right). C Genome-wide association between SORT1 copy number variations and differential mRNA expression in HCC tumor tissues. The red line indicates the 5′ promoter region corresponding to SORT1 . D Dot plots displaying differential methylation levels for four significant CpG sites related to SORT1 between non-tumoral (NT) and tumoral (T) liver tissues, with significance values presented for each site. E Kaplan–Meier survival curves comparing overall survival (OS) and disease-free survival (DFS) between HCC patients with high and low SORT1 expression from The Cancer Genome Atlas (TCGA) database, accompanied by hazard ratio (HR) and log-rank p values. F Methylation levels at multiple CpG sites of SORT1 in non-tumoral (NT) and tumoral (T) liver tissues, assessed in both the test (left) and validation cohorts (middle) from Ajou University Hospital. Violin plot of SORT1 methylation in non-tumor (NT) and tumor (T) liver tissues in the total cohort from Ajou University Hospital (right). G Receiver operating characteristic (ROC) curve assessing the diagnostic performance of SORT1 methylation in differentiating T from NT tissues. H Violin plot of SORT1 methylation based on the vascular invasion status (left) and HCC stage (right). I Scatter plot depicting the inverse correlation between SORT1 expression and its methylation level in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC) and AJOU_HCC cohorts. Statistical significance is indicated by * p < 0.05, ** p < 0.01, and *** p < 0.001. The analysis was performed using Student’s t -test and Welch’s t -test.

    Journal: Cell Death & Disease

    Article Title: Effect of Sortilin1 on promoting angiogenesis and systemic metastasis in hepatocellular carcinoma via the Notch signaling pathway and CD133

    doi: 10.1038/s41419-024-07016-7

    Figure Lengend Snippet: A SORT1 mRNA expression level based on gene copy number status from TCGA LIHC cohort (n = 371, left). Scatter plot illustrating the correlation between SORT1 mRNA expression and copy number (GISTIC) in TCGA LIHC cohort (n = 364, right). B Scatter plot illustrating the correlation between SORT1 mRNA expression and methylation in TCGA LIHC cohort (n = 371, left). Density plot displaying the methylation beta values for the (NT) and tumor (T) groups from the same cohort (right). C Genome-wide association between SORT1 copy number variations and differential mRNA expression in HCC tumor tissues. The red line indicates the 5′ promoter region corresponding to SORT1 . D Dot plots displaying differential methylation levels for four significant CpG sites related to SORT1 between non-tumoral (NT) and tumoral (T) liver tissues, with significance values presented for each site. E Kaplan–Meier survival curves comparing overall survival (OS) and disease-free survival (DFS) between HCC patients with high and low SORT1 expression from The Cancer Genome Atlas (TCGA) database, accompanied by hazard ratio (HR) and log-rank p values. F Methylation levels at multiple CpG sites of SORT1 in non-tumoral (NT) and tumoral (T) liver tissues, assessed in both the test (left) and validation cohorts (middle) from Ajou University Hospital. Violin plot of SORT1 methylation in non-tumor (NT) and tumor (T) liver tissues in the total cohort from Ajou University Hospital (right). G Receiver operating characteristic (ROC) curve assessing the diagnostic performance of SORT1 methylation in differentiating T from NT tissues. H Violin plot of SORT1 methylation based on the vascular invasion status (left) and HCC stage (right). I Scatter plot depicting the inverse correlation between SORT1 expression and its methylation level in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC) and AJOU_HCC cohorts. Statistical significance is indicated by * p < 0.05, ** p < 0.01, and *** p < 0.001. The analysis was performed using Student’s t -test and Welch’s t -test.

    Article Snippet: The SORT1 or CD133 expressing vectors were purchased from VectorBuilder (Chicago, IL, USA).

    Techniques: Expressing, Methylation, GWAS, Biomarker Discovery, Diagnostic Assay

    ( A ) qRT-PCR analysis of triplicate RNA samples from Dox-induced vs. uninduced BAKP cells were subjected to RNA-seq analysis. ( B ) Volcano plot of RNA-seq analysis shows top upregulated genes (top panel), while differential expression table shows fold increase in PROM1 and AREG expression (bottom panel). An adjusted p value (q-value < 0.05) and fold change (log2 fold change ≥ ±2) were used to identify significantly up- or downregulated genes. The top significantly upregulated genes (FDR < 0.01) are shown in the volcano plot.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: ( A ) qRT-PCR analysis of triplicate RNA samples from Dox-induced vs. uninduced BAKP cells were subjected to RNA-seq analysis. ( B ) Volcano plot of RNA-seq analysis shows top upregulated genes (top panel), while differential expression table shows fold increase in PROM1 and AREG expression (bottom panel). An adjusted p value (q-value < 0.05) and fold change (log2 fold change ≥ ±2) were used to identify significantly up- or downregulated genes. The top significantly upregulated genes (FDR < 0.01) are shown in the volcano plot.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: Quantitative RT-PCR, RNA Sequencing Assay, Expressing

    Validation of RNA-seq data ( A ) by immunoblot analysis ( B ) showing upregulation of CD133, AREG, SEMA3A, and SREBF1, and downregulation of differentiation genes RARB , TYRP1 , and TYRP2 in Dox-induced BAKP cells. Cells were seeded in 100 mm plates, incubated with or without 1 µg/mL Dox for 24 h, and subjected to immunoblot analysis with antibodies to CD133. Immunoblots were stripped of antibodies and re-probed with antibodies to AREG, SEMA3A, SREBF1, RARB, TYRP1, TYRP2, and β-actin for loading control. After normalizing to β-actin, densitometric analysis comparing intensities of protein bands relative to bands with the highest intensities, is shown in immunoblots.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: Validation of RNA-seq data ( A ) by immunoblot analysis ( B ) showing upregulation of CD133, AREG, SEMA3A, and SREBF1, and downregulation of differentiation genes RARB , TYRP1 , and TYRP2 in Dox-induced BAKP cells. Cells were seeded in 100 mm plates, incubated with or without 1 µg/mL Dox for 24 h, and subjected to immunoblot analysis with antibodies to CD133. Immunoblots were stripped of antibodies and re-probed with antibodies to AREG, SEMA3A, SREBF1, RARB, TYRP1, TYRP2, and β-actin for loading control. After normalizing to β-actin, densitometric analysis comparing intensities of protein bands relative to bands with the highest intensities, is shown in immunoblots.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: RNA Sequencing Assay, Western Blot, Incubation

    Reactome pathway analysis of DEGs from RNA-seq analysis of Dox-induced vs. uninduced BAKP cells. ( A ) Most significantly upregulated and downregulated pathway. ( B ) Most significantly upregulated DEGs included in the “TNFα signaling via NF-κB” pathway. Blue arrow indicates AREG. ( C – E ) Expression of NF-κB pathway ( C ) is upregulated, while pathway expression for melanin biosynthesis ( D ) and caspase activation via the apoptosome ( E ) are both downregulated in CD133-expressing BAKP melanoma cells.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: Reactome pathway analysis of DEGs from RNA-seq analysis of Dox-induced vs. uninduced BAKP cells. ( A ) Most significantly upregulated and downregulated pathway. ( B ) Most significantly upregulated DEGs included in the “TNFα signaling via NF-κB” pathway. Blue arrow indicates AREG. ( C – E ) Expression of NF-κB pathway ( C ) is upregulated, while pathway expression for melanin biosynthesis ( D ) and caspase activation via the apoptosome ( E ) are both downregulated in CD133-expressing BAKP melanoma cells.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: RNA Sequencing Assay, Expressing, Activation Assay

    ( A ) Upregulated expression of CD133 ( left panel) and AREG ( right panel) mRNA in Dox-induced BAKP cells was verified by qRT-PCR analysis. Cells were incubated with or without 1 µg/mL Dox for 24 h; total RNA was extracted and subjected to qPCR. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; **** p < 0.0001. ( B ) CD133 and intracellular AREG precursor protein levels were compared between control and Dox-induced BAKP cells by immunoblot analysis of total cell lysates with antibodies to CD133; membranes were stripped and re-probed with antibodies to AREG and β-actin as loading control. Densitometric analysis is shown in immunoblots, comparing intensities of protein bands relative to those of control -Dox, after normalizing to β-actin. ( C ) Cell culture media was collected, concentrated and subjected to immunoblot analysis with antibodies to AREG to detect secreted ligand forms of AREG. ( D ) AREG localization in the cytoplasm and cell membrane, not in the nucleus, is verified by immunofluorescence staining with antibodies to AREG. Representative images of BAKP cells uninduced (-Dox, upper panel) or induced with Dox (+Dox; lower panel) for 24 h, fixed, and subjected to immunofluorescence staining with antibodies to AREG, followed by DAPI for nuclear staining.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: ( A ) Upregulated expression of CD133 ( left panel) and AREG ( right panel) mRNA in Dox-induced BAKP cells was verified by qRT-PCR analysis. Cells were incubated with or without 1 µg/mL Dox for 24 h; total RNA was extracted and subjected to qPCR. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; **** p < 0.0001. ( B ) CD133 and intracellular AREG precursor protein levels were compared between control and Dox-induced BAKP cells by immunoblot analysis of total cell lysates with antibodies to CD133; membranes were stripped and re-probed with antibodies to AREG and β-actin as loading control. Densitometric analysis is shown in immunoblots, comparing intensities of protein bands relative to those of control -Dox, after normalizing to β-actin. ( C ) Cell culture media was collected, concentrated and subjected to immunoblot analysis with antibodies to AREG to detect secreted ligand forms of AREG. ( D ) AREG localization in the cytoplasm and cell membrane, not in the nucleus, is verified by immunofluorescence staining with antibodies to AREG. Representative images of BAKP cells uninduced (-Dox, upper panel) or induced with Dox (+Dox; lower panel) for 24 h, fixed, and subjected to immunofluorescence staining with antibodies to AREG, followed by DAPI for nuclear staining.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: Expressing, Quantitative RT-PCR, Incubation, Western Blot, Cell Culture, Membrane, Immunofluorescence, Staining

    ( A ) Upregulated expression of CD133 ( left panel) and AREG ( right panel) in Dox-induced POT cells (+Dox), as verified by qRT-PCR analysis. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; ***, **** represent p < 0.001 and p < 0.0001, respectively. ( B ) CD133 and intracellular AREG precursor protein levels were compared between control and Dox-induced POT cells by immunoblot analysis of total cell extracts with antibodies to CD133; membranes were stripped and re-probed with antibodies to AREG and β-actin as loading control. ( C ) Cell culture media was collected, concentrated and subjected to immunoblot analysis with anti-AREG to detect secreted ligand forms of AREG. Densitometric analysis is shown in immunoblots, comparing intensities of protein bands relative to bands with the highest intensity, after normalizing to β-actin.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: ( A ) Upregulated expression of CD133 ( left panel) and AREG ( right panel) in Dox-induced POT cells (+Dox), as verified by qRT-PCR analysis. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; ***, **** represent p < 0.001 and p < 0.0001, respectively. ( B ) CD133 and intracellular AREG precursor protein levels were compared between control and Dox-induced POT cells by immunoblot analysis of total cell extracts with antibodies to CD133; membranes were stripped and re-probed with antibodies to AREG and β-actin as loading control. ( C ) Cell culture media was collected, concentrated and subjected to immunoblot analysis with anti-AREG to detect secreted ligand forms of AREG. Densitometric analysis is shown in immunoblots, comparing intensities of protein bands relative to bands with the highest intensity, after normalizing to β-actin.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: Expressing, Quantitative RT-PCR, Western Blot, Cell Culture

    CD133-expressing Dox-induced BAKP cells exhibit increased ( A , B ) cell growth, and ( C ) percentage of cells in S-phase, compared to uninduced BAKP cells. Cells were seeded in equal numbers in 6-well plates in triplicates, and incubated for 24 h with 1 µg/mL Dox to induce CD133 expression. Cell growth assays: ( A , B ), GFP-expressing BAKP cells were seeded in equal numbers in 6-well plates +/− Dox, and then imaged and counted daily for 5 days in triplicate wells, in 3 random microscope fields per well ( n = 9); representative images of cells ( A ) and cell counts ( B ) over 5 days. ( C ) Cell cycle analysis: cells were collected at indicated times, fixed in 95% ethanol, stained with PI, and the percentage (%) of cells in S-phase of the cell cycle was quantified by flow cytometric analysis. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; *, **, ***, **** represent p < 0.05, p < 0.01, and p < 0.001, and p < 0.0001, respectively.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: CD133-expressing Dox-induced BAKP cells exhibit increased ( A , B ) cell growth, and ( C ) percentage of cells in S-phase, compared to uninduced BAKP cells. Cells were seeded in equal numbers in 6-well plates in triplicates, and incubated for 24 h with 1 µg/mL Dox to induce CD133 expression. Cell growth assays: ( A , B ), GFP-expressing BAKP cells were seeded in equal numbers in 6-well plates +/− Dox, and then imaged and counted daily for 5 days in triplicate wells, in 3 random microscope fields per well ( n = 9); representative images of cells ( A ) and cell counts ( B ) over 5 days. ( C ) Cell cycle analysis: cells were collected at indicated times, fixed in 95% ethanol, stained with PI, and the percentage (%) of cells in S-phase of the cell cycle was quantified by flow cytometric analysis. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; *, **, ***, **** represent p < 0.05, p < 0.01, and p < 0.001, and p < 0.0001, respectively.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: Expressing, Incubation, Microscopy, Cell Cycle Assay, Staining

    CD133-expressing Dox-induced BAKP cells exhibit increased DNA replication, as assesed by BrdU incorporation into newly synthesized DNA. Cells were induced with Dox for 24 h, synchronize in the cell cycle by serum starvation for 48 h, and stimulated to proliferate and reenter S-phase by serum addition. Cells were pulsed with BrdU 24 h after release into the S-phase, and subjected to immunofluorescence imaging using antibodies specific for BrdU and CD133. ( A ) Representative images of CD133-expressing cells (green) in Dox-induced, but not uninduced cells ( top panel); and DAPI-stained (blue) BrdU-positive cells (red; bottom panels) at 24 h after release from sterum starvation. ( B ) Quantification of BrdU positivity (percent (%) ratio of BrdU positive to DAPI stained cells). Fluorescent cells were imaged and counted using Image J. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; ** represents p < 0.01.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: CD133-expressing Dox-induced BAKP cells exhibit increased DNA replication, as assesed by BrdU incorporation into newly synthesized DNA. Cells were induced with Dox for 24 h, synchronize in the cell cycle by serum starvation for 48 h, and stimulated to proliferate and reenter S-phase by serum addition. Cells were pulsed with BrdU 24 h after release into the S-phase, and subjected to immunofluorescence imaging using antibodies specific for BrdU and CD133. ( A ) Representative images of CD133-expressing cells (green) in Dox-induced, but not uninduced cells ( top panel); and DAPI-stained (blue) BrdU-positive cells (red; bottom panels) at 24 h after release from sterum starvation. ( B ) Quantification of BrdU positivity (percent (%) ratio of BrdU positive to DAPI stained cells). Fluorescent cells were imaged and counted using Image J. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; ** represents p < 0.01.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: Expressing, BrdU Incorporation Assay, Synthesized, Immunofluorescence, Imaging, Staining

    Two melanoma cell lines BAKP and POT, exhibit higher levels of phosphorylation and activation of EGFR and members of the MAPK pathway (p-MEK, p-ERK, p-BAD compared to total MEK, ERK, BAD) ( A ) as well as the cell proliferation marker PCNA and cyclin D1 ( B ) in Dox-induced vs. uninduced cells. ( A ) Cell lysates of BAKP and POT cells incubated with or without 1 µg/mL Dox for 24 h were subjected to immunoblot analysis with antibodies to pEGFR. Immunoblots were stripped of antibodies and re-probed with antibodies to p-MEK, MEK, p-ERK, ERK, p-BAD, and β-actin for loading control. ( B ) Cell lysates of BAKP and POT cells incubated with or without 1 µg/mL Dox for 24 h were subjected to immunoblot analysis with antibodies to the proliferation marker PCNA, then β-actin for loading control. ( C ) BAKP cells incubated with or without 1 µg/mL Dox for 24 h were subjected to Western blot analysis with antibodies to CD133, then stripped of antibodies and re-probed with antibodies to TOP2 and β-actin, as loading control. Immunoblots loaded with the same lysates were likewise probed with antibodies to Cyclin D1, followed by β-actin. Densitometric analysis is shown in immunoblots, comparing intensities of protein bands relative to that of control −Dox cells, after normalizing to β-actin.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: Two melanoma cell lines BAKP and POT, exhibit higher levels of phosphorylation and activation of EGFR and members of the MAPK pathway (p-MEK, p-ERK, p-BAD compared to total MEK, ERK, BAD) ( A ) as well as the cell proliferation marker PCNA and cyclin D1 ( B ) in Dox-induced vs. uninduced cells. ( A ) Cell lysates of BAKP and POT cells incubated with or without 1 µg/mL Dox for 24 h were subjected to immunoblot analysis with antibodies to pEGFR. Immunoblots were stripped of antibodies and re-probed with antibodies to p-MEK, MEK, p-ERK, ERK, p-BAD, and β-actin for loading control. ( B ) Cell lysates of BAKP and POT cells incubated with or without 1 µg/mL Dox for 24 h were subjected to immunoblot analysis with antibodies to the proliferation marker PCNA, then β-actin for loading control. ( C ) BAKP cells incubated with or without 1 µg/mL Dox for 24 h were subjected to Western blot analysis with antibodies to CD133, then stripped of antibodies and re-probed with antibodies to TOP2 and β-actin, as loading control. Immunoblots loaded with the same lysates were likewise probed with antibodies to Cyclin D1, followed by β-actin. Densitometric analysis is shown in immunoblots, comparing intensities of protein bands relative to that of control −Dox cells, after normalizing to β-actin.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: Activation Assay, Marker, Incubation, Western Blot

    CD133 expression in +Dox cells significantly stimulates cell growth ( A ) and activates the MAPK (p-MEK and p-ERK) and p-BAD pathways, through upregulation of AREG ( B ). This is reversed by the EGFR inhibitor gefitinib, which suppresses cell growth as well as activation of the MAPK pathway. Cells were seeded in equal densities, treated with or without 1 µg/mL Dox for 24 h, and incubated or not with 10 µM gefitinib. ( A ) For cell growth assays, GFP-expressing BAKP cells were seeded in equal numbers in 6-well plates, and then imaged and counted daily for 5 days in triplicate wells, in 3 random microscope fields per well ( n = 9). Cell growth curves are shown and compared between treatment groups. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; **** represents p < 0.0001. ( B ) Cell extracts were subjected to immunoblot analysis with antibodies to AREG. Immunoblots were then stripped and re-probed with antibodies to activated forms of members of the MAPK pathway (p-MEK, p-ERK), p-BAD, and β-actin for loading control. Densitometric analysis is shown in immunoblots, comparing intensities of protein bands relative to bands with the highest intensity, after normalizing to β-actin.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: CD133 expression in +Dox cells significantly stimulates cell growth ( A ) and activates the MAPK (p-MEK and p-ERK) and p-BAD pathways, through upregulation of AREG ( B ). This is reversed by the EGFR inhibitor gefitinib, which suppresses cell growth as well as activation of the MAPK pathway. Cells were seeded in equal densities, treated with or without 1 µg/mL Dox for 24 h, and incubated or not with 10 µM gefitinib. ( A ) For cell growth assays, GFP-expressing BAKP cells were seeded in equal numbers in 6-well plates, and then imaged and counted daily for 5 days in triplicate wells, in 3 random microscope fields per well ( n = 9). Cell growth curves are shown and compared between treatment groups. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; **** represents p < 0.0001. ( B ) Cell extracts were subjected to immunoblot analysis with antibodies to AREG. Immunoblots were then stripped and re-probed with antibodies to activated forms of members of the MAPK pathway (p-MEK, p-ERK), p-BAD, and β-actin for loading control. Densitometric analysis is shown in immunoblots, comparing intensities of protein bands relative to bands with the highest intensity, after normalizing to β-actin.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: Expressing, Activation Assay, Incubation, Microscopy, Western Blot

    siRNA knockdown of AREG expression in BAKP cells as confirmed by immunoblot analysis ( A ), reverses the CD133-induced stimulation of cell growth ( B ) and increased percentage of cells in S-phase. Cells were seeded in equal densities, treated with or without 1 µg/mL Dox for 24 h, and incubated with scrambled control or AREG siRNA. ( A ) Cell extracts were derived and subjected to immunoblot analysis with antibodies to CD133. Immunoblots were stripped and re-probed with antibodies to AREG, and β-actin for loading control. Densitometric analysis is shown in immunoblots, comparing intensities of protein bands relative to bands with the highest intensity, after normalizing to β-actin. ( B ) GFP-expressing BAKP cells were seeded in equal numbers in 6-well plates +/−Dox, and then imaged and counted daily for 5 days, as described in Materials and Methods ( n = 9). Cell growth curves are shown and compared between treatment groups. ( C ) Cells were collected at indicated times, fixed in 95% ethanol, stained with PI, and the percentage (%) of cells in S-phase was quantified by flow cytometry. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; *, **, ***, **** represent p < 0.05, p < 0.01, p < 0.001, and p < 0.0001, respectively.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: siRNA knockdown of AREG expression in BAKP cells as confirmed by immunoblot analysis ( A ), reverses the CD133-induced stimulation of cell growth ( B ) and increased percentage of cells in S-phase. Cells were seeded in equal densities, treated with or without 1 µg/mL Dox for 24 h, and incubated with scrambled control or AREG siRNA. ( A ) Cell extracts were derived and subjected to immunoblot analysis with antibodies to CD133. Immunoblots were stripped and re-probed with antibodies to AREG, and β-actin for loading control. Densitometric analysis is shown in immunoblots, comparing intensities of protein bands relative to bands with the highest intensity, after normalizing to β-actin. ( B ) GFP-expressing BAKP cells were seeded in equal numbers in 6-well plates +/−Dox, and then imaged and counted daily for 5 days, as described in Materials and Methods ( n = 9). Cell growth curves are shown and compared between treatment groups. ( C ) Cells were collected at indicated times, fixed in 95% ethanol, stained with PI, and the percentage (%) of cells in S-phase was quantified by flow cytometry. Results shown are the means ± SEM of three replicates of a representative experiment; essentially the same results were obtained in three independent experiments. p < 0.05 was considered significant; *, **, ***, **** represent p < 0.05, p < 0.01, p < 0.001, and p < 0.0001, respectively.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: Expressing, Western Blot, Incubation, Derivative Assay, Staining, Flow Cytometry

    CD133 stimulates cell proliferation and promotes melanoma progression via a novel CD133-AREG-EGFR-MAPK activation pathway in CD133-positive melanoma-initiating stem cells (MICs), summarized as follows: (1) CD133 upregulates AREG, (2) AREG is cleaved to its ligand form by metalloproteinase ADAMS, (3) AREG ligand binds to and activates EGFR, (4) EGFR activates the MAPK pathway (by phosphorylating MEK, which phosphorylates ERK), (5) ERK phosphorylates and inactivates apoptotic protein BAD, leading to increased cell survival, (6) activation of the MEK/ERK pathway upregulates cyclin D1, (7) resulting in activation of E2F1, 8), which in turn binds to and upregulates the S-phase gene promoters, including those of PCNA.

    Journal: Cells

    Article Title: CD133 Stimulates Cell Proliferation via the Upregulation of Amphiregulin in Melanoma

    doi: 10.3390/cells13090777

    Figure Lengend Snippet: CD133 stimulates cell proliferation and promotes melanoma progression via a novel CD133-AREG-EGFR-MAPK activation pathway in CD133-positive melanoma-initiating stem cells (MICs), summarized as follows: (1) CD133 upregulates AREG, (2) AREG is cleaved to its ligand form by metalloproteinase ADAMS, (3) AREG ligand binds to and activates EGFR, (4) EGFR activates the MAPK pathway (by phosphorylating MEK, which phosphorylates ERK), (5) ERK phosphorylates and inactivates apoptotic protein BAD, leading to increased cell survival, (6) activation of the MEK/ERK pathway upregulates cyclin D1, (7) resulting in activation of E2F1, 8), which in turn binds to and upregulates the S-phase gene promoters, including those of PCNA.

    Article Snippet: To characterize and target CD133-positive cancer stem cells, the patient-derived de-identified melanoma cell line, BAK parental (BAKP), harboring a refractory NRAS driver mutation and expressing low basal CD133 levels, was transduced with a Tet activator (rtTA3, Addgene) and a Tet-on vector expressing CD133 (TRE3G-CD133, VectorBuilder).

    Techniques: Activation Assay