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Spatial whole-transcriptome profiling of ESPL and <t>ESCC</t> samples (A) Workflow of DSP experimental process. (B) The UMAP plot displaying the clustering results of AOIs from different compartments at multiple stages of ESCC. (C) The heatmap displaying the expression levels of AOI characteristic markers RNA in different compartments. (D) The boxplots showing the expression levels of marker genes in five different compartments at different stages of ESCC. Box plot shows the median and interquartile range, whiskers extend to 1.5 × IQR. DSP, digital spatial profiling; UMAP, uniform manifold approximation and projection; AOI, area of interest; EP, epithelial-cell-enriched; MC, macrophage-cell-enriched; NC, neutrophil-cell-enriched; ST, stroma-enriched; LS, lymphoid structure; CAFs, cancer-associated fibroblasts; ESPL, esophageal squamous precancerous lesion; non-mESCC, non-metastasis esophageal squamous cell carcinoma; mESCC, metastasis esophageal squamous cell carcinoma; mLN, lymph node metastasis tissues.
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Spatial whole-transcriptome profiling of ESPL and <t>ESCC</t> samples (A) Workflow of DSP experimental process. (B) The UMAP plot displaying the clustering results of AOIs from different compartments at multiple stages of ESCC. (C) The heatmap displaying the expression levels of AOI characteristic markers RNA in different compartments. (D) The boxplots showing the expression levels of marker genes in five different compartments at different stages of ESCC. Box plot shows the median and interquartile range, whiskers extend to 1.5 × IQR. DSP, digital spatial profiling; UMAP, uniform manifold approximation and projection; AOI, area of interest; EP, epithelial-cell-enriched; MC, macrophage-cell-enriched; NC, neutrophil-cell-enriched; ST, stroma-enriched; LS, lymphoid structure; CAFs, cancer-associated fibroblasts; ESPL, esophageal squamous precancerous lesion; non-mESCC, non-metastasis esophageal squamous cell carcinoma; mESCC, metastasis esophageal squamous cell carcinoma; mLN, lymph node metastasis tissues.
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Baseline patient characteristics of the different cohorts.
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Baseline patient characteristics of the different cohorts.
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Baseline patient characteristics of the different cohorts.
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Image Search Results


Spatial whole-transcriptome profiling of ESPL and ESCC samples (A) Workflow of DSP experimental process. (B) The UMAP plot displaying the clustering results of AOIs from different compartments at multiple stages of ESCC. (C) The heatmap displaying the expression levels of AOI characteristic markers RNA in different compartments. (D) The boxplots showing the expression levels of marker genes in five different compartments at different stages of ESCC. Box plot shows the median and interquartile range, whiskers extend to 1.5 × IQR. DSP, digital spatial profiling; UMAP, uniform manifold approximation and projection; AOI, area of interest; EP, epithelial-cell-enriched; MC, macrophage-cell-enriched; NC, neutrophil-cell-enriched; ST, stroma-enriched; LS, lymphoid structure; CAFs, cancer-associated fibroblasts; ESPL, esophageal squamous precancerous lesion; non-mESCC, non-metastasis esophageal squamous cell carcinoma; mESCC, metastasis esophageal squamous cell carcinoma; mLN, lymph node metastasis tissues.

Journal: Cell Reports Medicine

Article Title: Spatial omics study reveals molecular-cellular dynamics of tumor ecosystem in esophageal squamous-cell carcinoma initiation and progression

doi: 10.1016/j.xcrm.2026.102650

Figure Lengend Snippet: Spatial whole-transcriptome profiling of ESPL and ESCC samples (A) Workflow of DSP experimental process. (B) The UMAP plot displaying the clustering results of AOIs from different compartments at multiple stages of ESCC. (C) The heatmap displaying the expression levels of AOI characteristic markers RNA in different compartments. (D) The boxplots showing the expression levels of marker genes in five different compartments at different stages of ESCC. Box plot shows the median and interquartile range, whiskers extend to 1.5 × IQR. DSP, digital spatial profiling; UMAP, uniform manifold approximation and projection; AOI, area of interest; EP, epithelial-cell-enriched; MC, macrophage-cell-enriched; NC, neutrophil-cell-enriched; ST, stroma-enriched; LS, lymphoid structure; CAFs, cancer-associated fibroblasts; ESPL, esophageal squamous precancerous lesion; non-mESCC, non-metastasis esophageal squamous cell carcinoma; mESCC, metastasis esophageal squamous cell carcinoma; mLN, lymph node metastasis tissues.

Article Snippet: KYSE450 human ESCC cell line , Servicebio , STCC11902P.

Techniques: Expressing, Marker

Changes in gene expression patterns in the EP compartment during the initiation of ESCC (A) Volcano plot showed significant DEGs during the formation of ESPL. (B) Pathway enrichment analysis of DEGs in ESPL and normal stages. (C) Changes in gene expression across epidermis development and keratinocyte differentiation pathways during ESPL formation. (D) Interaction plot of ESPL-formation-related genes. Each circle represents a protein, and the interactions are connected by solid lines. The types of interactions were shown on the right side of the figure. (E) The four-quadrant plot illustrates the significant differences in gene expression patterns among four distinct types during the initiation of ESCC. (F) The boxplot shows the expression levels of the presented genes across the four patterns during ESCC initiation. Pattern 1 to 4 were tagged in blue, pink, yellow, and purple, respectively. Box plot shows the interquartile, whiskers extend to1.5 × IQR. (G) Pathway enrichment results for genes in the four patterns. (H) The line graph depicts changes in the signature scores of the indicated pathways during the initiation and development of ESCC. DEGs, differentially expressed genes.

Journal: Cell Reports Medicine

Article Title: Spatial omics study reveals molecular-cellular dynamics of tumor ecosystem in esophageal squamous-cell carcinoma initiation and progression

doi: 10.1016/j.xcrm.2026.102650

Figure Lengend Snippet: Changes in gene expression patterns in the EP compartment during the initiation of ESCC (A) Volcano plot showed significant DEGs during the formation of ESPL. (B) Pathway enrichment analysis of DEGs in ESPL and normal stages. (C) Changes in gene expression across epidermis development and keratinocyte differentiation pathways during ESPL formation. (D) Interaction plot of ESPL-formation-related genes. Each circle represents a protein, and the interactions are connected by solid lines. The types of interactions were shown on the right side of the figure. (E) The four-quadrant plot illustrates the significant differences in gene expression patterns among four distinct types during the initiation of ESCC. (F) The boxplot shows the expression levels of the presented genes across the four patterns during ESCC initiation. Pattern 1 to 4 were tagged in blue, pink, yellow, and purple, respectively. Box plot shows the interquartile, whiskers extend to1.5 × IQR. (G) Pathway enrichment results for genes in the four patterns. (H) The line graph depicts changes in the signature scores of the indicated pathways during the initiation and development of ESCC. DEGs, differentially expressed genes.

Article Snippet: KYSE450 human ESCC cell line , Servicebio , STCC11902P.

Techniques: Gene Expression, Expressing

Spatial transcriptome analysis of the TME during ESCC initiation process (A) Quantitative analysis of immune cells in non-EP compartments during the initiation process of ESCC using TME_consense algorithm. (B) Comparison of B, plasma, CD4 + T, and CD8 + T cells during the initiation process of ESCC. (C) Analyze the immune cell changes in non-EP compartments during the initiation process of ESCC using SpatialDecon algorithm. (D) mIF staining of CD20, CD8, and CD4 on tumor tissues in ESCC initiation stages. Scale bar, 200 μm. (E) Comparison of the percentages of CD20-, CD8-, and CD4-positive cells across the ESCC initiation stages. (F) Pathway enrichment analysis of significantly differential expression genes in non-EP compartments during the initial stage of ESCC. (G) The heatmap shows the differential genes in the MC and NC compartments during the initial stage of ESCC. (H) Comparison of the proportion of tumor-associated macrophage and neutrophile cells across the ESCC development. (I) The heatmap shows the differential genes in TLS compartments during the initial stage of ESCC. (J) mIF staining on TLS compartment of ESCC initiation stage. Scale bar, 100 μm. (K) Comparison of the percentages of APOBEC3A-positive cells between ESPL and non-mESCC stages in the TLS. NE, normal epithelia; ESCC, esophageal squamous cell carcinoma; mIF, multiplex immunofluorescence; MC, macrophage-cell-enriched compartment; NC, neutrophil-cell-enriched compartment; TLS, tertiary lymphoid structures. Box plots show the median and interquartile range, whiskers extend to 1.5×IQR. ∗p < 0.05 , ∗∗ p < 0.01,∗∗∗ p < 0.001, p values were calculated using a two-sided Wilcoxon rank-sum test.

Journal: Cell Reports Medicine

Article Title: Spatial omics study reveals molecular-cellular dynamics of tumor ecosystem in esophageal squamous-cell carcinoma initiation and progression

doi: 10.1016/j.xcrm.2026.102650

Figure Lengend Snippet: Spatial transcriptome analysis of the TME during ESCC initiation process (A) Quantitative analysis of immune cells in non-EP compartments during the initiation process of ESCC using TME_consense algorithm. (B) Comparison of B, plasma, CD4 + T, and CD8 + T cells during the initiation process of ESCC. (C) Analyze the immune cell changes in non-EP compartments during the initiation process of ESCC using SpatialDecon algorithm. (D) mIF staining of CD20, CD8, and CD4 on tumor tissues in ESCC initiation stages. Scale bar, 200 μm. (E) Comparison of the percentages of CD20-, CD8-, and CD4-positive cells across the ESCC initiation stages. (F) Pathway enrichment analysis of significantly differential expression genes in non-EP compartments during the initial stage of ESCC. (G) The heatmap shows the differential genes in the MC and NC compartments during the initial stage of ESCC. (H) Comparison of the proportion of tumor-associated macrophage and neutrophile cells across the ESCC development. (I) The heatmap shows the differential genes in TLS compartments during the initial stage of ESCC. (J) mIF staining on TLS compartment of ESCC initiation stage. Scale bar, 100 μm. (K) Comparison of the percentages of APOBEC3A-positive cells between ESPL and non-mESCC stages in the TLS. NE, normal epithelia; ESCC, esophageal squamous cell carcinoma; mIF, multiplex immunofluorescence; MC, macrophage-cell-enriched compartment; NC, neutrophil-cell-enriched compartment; TLS, tertiary lymphoid structures. Box plots show the median and interquartile range, whiskers extend to 1.5×IQR. ∗p < 0.05 , ∗∗ p < 0.01,∗∗∗ p < 0.001, p values were calculated using a two-sided Wilcoxon rank-sum test.

Article Snippet: KYSE450 human ESCC cell line , Servicebio , STCC11902P.

Techniques: Comparison, Clinical Proteomics, Staining, Quantitative Proteomics, Multiplex Assay, Immunofluorescence

Characteristic changes in transcription patterns during the progression of ESCC (A) The volcano plot shows significant differences in genes between the early (ESPL and non-mESCC) and advanced (mESCC and mLN) stages of ESCC. (B) Pathway enrichment analysis of differentially expressed genes in the early and advanced stages of ESCC. (C) The gene expression levels associated with significantly enriched pathways throughout the occurrence and development of ESCC. (D) mIF staining of CCND1, LAMB1, and IL-18 on ESCC tissues. Scale bar, 200 μm. (E) Comparison of the percentages of CCND1, LAMB1, and IL-18-positive cells on ESCC tissues. Box plots show the median and interquartile range, whiskers extend to 1.5 × IQR. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, p values were calculated using a two-sided Wilcoxon rank-sum test. (F) The heatmap of gradient-changed DEGs based on pseudotime and ESCC progression of EP.

Journal: Cell Reports Medicine

Article Title: Spatial omics study reveals molecular-cellular dynamics of tumor ecosystem in esophageal squamous-cell carcinoma initiation and progression

doi: 10.1016/j.xcrm.2026.102650

Figure Lengend Snippet: Characteristic changes in transcription patterns during the progression of ESCC (A) The volcano plot shows significant differences in genes between the early (ESPL and non-mESCC) and advanced (mESCC and mLN) stages of ESCC. (B) Pathway enrichment analysis of differentially expressed genes in the early and advanced stages of ESCC. (C) The gene expression levels associated with significantly enriched pathways throughout the occurrence and development of ESCC. (D) mIF staining of CCND1, LAMB1, and IL-18 on ESCC tissues. Scale bar, 200 μm. (E) Comparison of the percentages of CCND1, LAMB1, and IL-18-positive cells on ESCC tissues. Box plots show the median and interquartile range, whiskers extend to 1.5 × IQR. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, p values were calculated using a two-sided Wilcoxon rank-sum test. (F) The heatmap of gradient-changed DEGs based on pseudotime and ESCC progression of EP.

Article Snippet: KYSE450 human ESCC cell line , Servicebio , STCC11902P.

Techniques: Gene Expression, Staining, Comparison

OGT promotes ESCC progression through regulating proliferation, migration, invasion, and apoptosis in vitro and in vivo (A) Representative images of immunohistochemical staining for OGT in cancer and adjacent tissues, magnified at 200× and 400×; scale bars, 100 μm. (B) Paired comparison of OGT IHC scores in tumor and peritumor tissues. p value was calculated using a two-sided Wilcoxon signed-rank test (paired samples, n = 76). (C) Representative WB images of OGT and O-GlcNAc level in all transient transfection groups, including knockdown in KYSE30 and KYSE450 (transfected with siNC, si OGT #1, or si OGT #2) and overexpress in KYSE150 and KYSE410 (transfected with oeVector, oe OGT , or oe OGT and treated with OSMI-1). Images are representative of three independent experiments ( n = 3). (D) OGT and O-GlcNAc level in lentiviral-mediated knockdown KYSE450 and overexpress KYSE150. Representative protein images of three independent experiments were shown ( n = 3). (E and F) Representative images and quantification of plate clone formation assay of lentiviral-mediated knockdown KYSE450 and overexpress KYSE150 cell lines. Data are mean ± SD from three independent experiments ( n = 3). p values were calculated using one-way ANOVA. (G) Cell proliferation measured by the CCK8 assay and relative cell proliferation quantified by OD value at 450 nm of KYSE30, KYSE450, KYSE150, and KYSE410 cell lines. Data are presented as mean ± SD from three independent experiments ( n = 3). p values were calculated using two-way ANOVA with Tukey's multiple-comparisons test. (H) Representative images of cell migration and invasion assays in the KYSE30, KYSE450, KYSE150, and KYSE410 cell lines ( n = 3). Scale bars, 200 μm. (I) Stably transfected shNC/sh OGT KYSE450 cell subcutaneously injected into nude mice. Representative image of xenograft tumors and tumor volume from day 5 to day 30. Data are presented as mean ± SD, n = 5 mice per group. p values were calculated using two-way repeated-measures ANOVA with Sidak's multiple-comparisons test. (J) Bioluminescence imaging of lung metastatic foci at the 7th week in a lung metastasis model. Luciferase activity is measured in photons per cm2 per second per steradian (p/s/cm2/sr). (K) Representative images and quantitative analysis of metastasis nodules on the lung surface. Arrowheads denote the metastasis nodules on the lung surface. (L) Representative images of HE staining of lung metastasis and quantitative analysis of lung metastasis area. Arrowheads denote the metastasis nodules. Scale bars, 200 μm. (J–L) Data are presented as mean ± SD, n = 5 mice per group. p values were calculated using a two-sided Wilcoxon rank-sum test. (M) The results of enriched pathways affected by OGT expression detected across different omics. In the RNA-seq dataset, siOGT cells were defined as the OGT low group, while siNC cells were defined as the OGT-high group. In both the proteomic and glycoproteomic datasets, oeVector cells were defined as the OGT-low group, and oeOGT cells were defined as the OGT-high group. Pathways activated in the OGT-high group are marked in green, while pathways inhibited are marked in red. (N) Comparison of apoptosis rate between KYSE450 siNC and si OGT groups. Data are presented as mean ± SD, n = 3 per group. p values were calculated using unpaired Student's t test. (O) Flow cytometry analysis of cell cycle distribution of KYSE450 cells across siNC and si OGT . ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. NC, negative control group.

Journal: Cell Reports Medicine

Article Title: Spatial omics study reveals molecular-cellular dynamics of tumor ecosystem in esophageal squamous-cell carcinoma initiation and progression

doi: 10.1016/j.xcrm.2026.102650

Figure Lengend Snippet: OGT promotes ESCC progression through regulating proliferation, migration, invasion, and apoptosis in vitro and in vivo (A) Representative images of immunohistochemical staining for OGT in cancer and adjacent tissues, magnified at 200× and 400×; scale bars, 100 μm. (B) Paired comparison of OGT IHC scores in tumor and peritumor tissues. p value was calculated using a two-sided Wilcoxon signed-rank test (paired samples, n = 76). (C) Representative WB images of OGT and O-GlcNAc level in all transient transfection groups, including knockdown in KYSE30 and KYSE450 (transfected with siNC, si OGT #1, or si OGT #2) and overexpress in KYSE150 and KYSE410 (transfected with oeVector, oe OGT , or oe OGT and treated with OSMI-1). Images are representative of three independent experiments ( n = 3). (D) OGT and O-GlcNAc level in lentiviral-mediated knockdown KYSE450 and overexpress KYSE150. Representative protein images of three independent experiments were shown ( n = 3). (E and F) Representative images and quantification of plate clone formation assay of lentiviral-mediated knockdown KYSE450 and overexpress KYSE150 cell lines. Data are mean ± SD from three independent experiments ( n = 3). p values were calculated using one-way ANOVA. (G) Cell proliferation measured by the CCK8 assay and relative cell proliferation quantified by OD value at 450 nm of KYSE30, KYSE450, KYSE150, and KYSE410 cell lines. Data are presented as mean ± SD from three independent experiments ( n = 3). p values were calculated using two-way ANOVA with Tukey's multiple-comparisons test. (H) Representative images of cell migration and invasion assays in the KYSE30, KYSE450, KYSE150, and KYSE410 cell lines ( n = 3). Scale bars, 200 μm. (I) Stably transfected shNC/sh OGT KYSE450 cell subcutaneously injected into nude mice. Representative image of xenograft tumors and tumor volume from day 5 to day 30. Data are presented as mean ± SD, n = 5 mice per group. p values were calculated using two-way repeated-measures ANOVA with Sidak's multiple-comparisons test. (J) Bioluminescence imaging of lung metastatic foci at the 7th week in a lung metastasis model. Luciferase activity is measured in photons per cm2 per second per steradian (p/s/cm2/sr). (K) Representative images and quantitative analysis of metastasis nodules on the lung surface. Arrowheads denote the metastasis nodules on the lung surface. (L) Representative images of HE staining of lung metastasis and quantitative analysis of lung metastasis area. Arrowheads denote the metastasis nodules. Scale bars, 200 μm. (J–L) Data are presented as mean ± SD, n = 5 mice per group. p values were calculated using a two-sided Wilcoxon rank-sum test. (M) The results of enriched pathways affected by OGT expression detected across different omics. In the RNA-seq dataset, siOGT cells were defined as the OGT low group, while siNC cells were defined as the OGT-high group. In both the proteomic and glycoproteomic datasets, oeVector cells were defined as the OGT-low group, and oeOGT cells were defined as the OGT-high group. Pathways activated in the OGT-high group are marked in green, while pathways inhibited are marked in red. (N) Comparison of apoptosis rate between KYSE450 siNC and si OGT groups. Data are presented as mean ± SD, n = 3 per group. p values were calculated using unpaired Student's t test. (O) Flow cytometry analysis of cell cycle distribution of KYSE450 cells across siNC and si OGT . ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. NC, negative control group.

Article Snippet: KYSE450 human ESCC cell line , Servicebio , STCC11902P.

Techniques: Migration, In Vitro, In Vivo, Immunohistochemical staining, Staining, Comparison, Transfection, Knockdown, Tube Formation Assay, CCK-8 Assay, Stable Transfection, Injection, Imaging, Luciferase, Activity Assay, Expressing, RNA Sequencing, Flow Cytometry, Negative Control

Changes in TME during the progression of ESCC (A) Abundance of 17 cells estimated by SpatialDecon algorithm in non-EP compartments between the early (ESPL and non-mESCC) and advanced stages (mESCC and mLN) of ESCC. (B) Comparison of proportion of presented cells between the early and advanced stages of ESCC. Box plot shows the median and interquartile range, whiskers extend to 1.5 × IQR. p values were calculated using two-sided Wilcoxon rank-sum test. ∗ p < 0.05, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. (C) Volcano plot showing the DEGs between early and advanced stages in ST compartment. (D) Volcano plot showing the DEGs between early and advanced stages in MC compartment. (E) Volcano plot showing the DEGs between early and advanced stages in NC compartment. (F) Cell-cell interactions based on significant ligand-receptor pairs in advanced stages of ESCC. (G) Interaction relationships of the ACTIVIN, CHEMERIN, and PERIOSTIN pathways among compartments in advanced ESCC. (H) Cell-cell interactions between ST compartments and other compartments via the ACTIVIN, CHEMERIN, and PERIOSTIN pathways during ESCC initiation and progression. (I) The four-quadrant diagram showed the significant differences in gene expression patterns among three different types in the TLS during the ESCC process. Genes showing continuous increase were marked in red, while genes showing continuous decrease were marked in blue. (J) Volcano plot showed significant differentially expressed genes between the TLS of tumor and the lymph follicles of lymph nodules.

Journal: Cell Reports Medicine

Article Title: Spatial omics study reveals molecular-cellular dynamics of tumor ecosystem in esophageal squamous-cell carcinoma initiation and progression

doi: 10.1016/j.xcrm.2026.102650

Figure Lengend Snippet: Changes in TME during the progression of ESCC (A) Abundance of 17 cells estimated by SpatialDecon algorithm in non-EP compartments between the early (ESPL and non-mESCC) and advanced stages (mESCC and mLN) of ESCC. (B) Comparison of proportion of presented cells between the early and advanced stages of ESCC. Box plot shows the median and interquartile range, whiskers extend to 1.5 × IQR. p values were calculated using two-sided Wilcoxon rank-sum test. ∗ p < 0.05, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. (C) Volcano plot showing the DEGs between early and advanced stages in ST compartment. (D) Volcano plot showing the DEGs between early and advanced stages in MC compartment. (E) Volcano plot showing the DEGs between early and advanced stages in NC compartment. (F) Cell-cell interactions based on significant ligand-receptor pairs in advanced stages of ESCC. (G) Interaction relationships of the ACTIVIN, CHEMERIN, and PERIOSTIN pathways among compartments in advanced ESCC. (H) Cell-cell interactions between ST compartments and other compartments via the ACTIVIN, CHEMERIN, and PERIOSTIN pathways during ESCC initiation and progression. (I) The four-quadrant diagram showed the significant differences in gene expression patterns among three different types in the TLS during the ESCC process. Genes showing continuous increase were marked in red, while genes showing continuous decrease were marked in blue. (J) Volcano plot showed significant differentially expressed genes between the TLS of tumor and the lymph follicles of lymph nodules.

Article Snippet: KYSE450 human ESCC cell line , Servicebio , STCC11902P.

Techniques: Comparison, Gene Expression

Downregulation of TSPO in ESCC and its role in suppressing tumor cell proliferation. (A) The expression of TSPO across various cancer types, as analyzed from the TCGA and GTEx datasets, reveals a notable reduction in ESCC, which is highlighted for emphasis. (B) The Kaplan–Meier survival curve demonstrates that lower TSPO expression is associated with poorer overall survival outcomes in the TCGA-ESCA cohort of ESCC patients. (C) Western blot analysis reveals TSPO expression levels in normal esophageal epithelial cells (HET-1A) compared to ESCC cell lines (KYSE30, KYSE450, EC1). (D) Western blot results confirm the efficiency of TSPO overexpression (OV-TSPO) in ESCC cells. (E–G) Colony formation assays conducted in KYSE30 (E) , KYSE450 (F) , and EC1 (G) cells indicate that TSPO overexpression significantly inhibits clonogenic ability. (H–J) CCK-8 assays demonstrate a reduction in proliferation in TSPO-overexpressing KYSE30 (H) , KYSE450 (I) , and EC1 (J) cells, with statistical significance indicated as *** P < 0.001. (K) Western blot analysis of key apoptotic and DNA damage-related proteins (PPARα, c-PARP, Bcl-2, Noxa, and γH2AX) in TSPO-overexpressing ESCC cells. β-actin was used as the loading control. All data were representative of at least three independent experiments (n = 3; error bar, SD). Statistical significance: P < 0.05 (*), P < 0.01 (**), P < 0.001 (**), P < 0.0001 (****).

Journal: Frontiers in Oncology

Article Title: Integration of single-cell and bulk RNA sequencing to identify unique tumor stem cells and construct novel prognostic markers for assessing ESCA prognosis and drug sensitivity

doi: 10.3389/fonc.2025.1649877

Figure Lengend Snippet: Downregulation of TSPO in ESCC and its role in suppressing tumor cell proliferation. (A) The expression of TSPO across various cancer types, as analyzed from the TCGA and GTEx datasets, reveals a notable reduction in ESCC, which is highlighted for emphasis. (B) The Kaplan–Meier survival curve demonstrates that lower TSPO expression is associated with poorer overall survival outcomes in the TCGA-ESCA cohort of ESCC patients. (C) Western blot analysis reveals TSPO expression levels in normal esophageal epithelial cells (HET-1A) compared to ESCC cell lines (KYSE30, KYSE450, EC1). (D) Western blot results confirm the efficiency of TSPO overexpression (OV-TSPO) in ESCC cells. (E–G) Colony formation assays conducted in KYSE30 (E) , KYSE450 (F) , and EC1 (G) cells indicate that TSPO overexpression significantly inhibits clonogenic ability. (H–J) CCK-8 assays demonstrate a reduction in proliferation in TSPO-overexpressing KYSE30 (H) , KYSE450 (I) , and EC1 (J) cells, with statistical significance indicated as *** P < 0.001. (K) Western blot analysis of key apoptotic and DNA damage-related proteins (PPARα, c-PARP, Bcl-2, Noxa, and γH2AX) in TSPO-overexpressing ESCC cells. β-actin was used as the loading control. All data were representative of at least three independent experiments (n = 3; error bar, SD). Statistical significance: P < 0.05 (*), P < 0.01 (**), P < 0.001 (**), P < 0.0001 (****).

Article Snippet: KYSE30 and KYSE450 cells were cultured in RPMI-1640 medium (Solarbio, China), and EC1 cells were maintained in DMEM medium (Solarbio, China), both supplemented with 10% fetal bovine serum (FBS; Solarbio, China), 100 U/mL penicillin, and 100 μg/mL streptomycin.

Techniques: Expressing, Western Blot, Over Expression, CCK-8 Assay, Control

Construction of a risk signature using the least absolute shrinkage and selection operator (LASSO) analysis. Partial likelihood deviances for (A) oesophageal squamous cell carcinoma (ESCC) and (B) oesophageal adenocarcinoma (EAC). Coefficient profiles of senescence‐related gene pairs for (C) ESCC and (D) EAC.

Journal: Journal of Cellular and Molecular Medicine

Article Title: Multi‐Omics Analysis of Aberrances and Functional Implications of IRF5 in Digestive Tract Tumours

doi: 10.1111/jcmm.70433

Figure Lengend Snippet: Construction of a risk signature using the least absolute shrinkage and selection operator (LASSO) analysis. Partial likelihood deviances for (A) oesophageal squamous cell carcinoma (ESCC) and (B) oesophageal adenocarcinoma (EAC). Coefficient profiles of senescence‐related gene pairs for (C) ESCC and (D) EAC.

Article Snippet: Human ESCC cell lines (KYSE150, KYSE180, KYSE410 and KYSE450) and the human embryonic oesophageal cell line (SHEE) were purchased from iCell Bioscience Inc. (Shanghai, China).

Techniques: Selection

Kaplan–Meier analysis of high‐ and low‐risk patients (red and blue, respectively) with (A) oesophageal squamous cell carcinoma (ESCC) and (B) oesophageal adenocarcinoma (EAC). Receiver operating characteristic curves for (C) ESCC and (D) EAC. Survival risk curves (top) and sand scatter plots (bottom) for (E) ESCC and (F) EAC.

Journal: Journal of Cellular and Molecular Medicine

Article Title: Multi‐Omics Analysis of Aberrances and Functional Implications of IRF5 in Digestive Tract Tumours

doi: 10.1111/jcmm.70433

Figure Lengend Snippet: Kaplan–Meier analysis of high‐ and low‐risk patients (red and blue, respectively) with (A) oesophageal squamous cell carcinoma (ESCC) and (B) oesophageal adenocarcinoma (EAC). Receiver operating characteristic curves for (C) ESCC and (D) EAC. Survival risk curves (top) and sand scatter plots (bottom) for (E) ESCC and (F) EAC.

Article Snippet: Human ESCC cell lines (KYSE150, KYSE180, KYSE410 and KYSE450) and the human embryonic oesophageal cell line (SHEE) were purchased from iCell Bioscience Inc. (Shanghai, China).

Techniques:

Correlations of immune microenvironments evaluated using ESTIMATE. (A) Immune score and (B) ESTIMATE score for oesophageal squamous cell carcinoma (ESCC). (C) Immune score and (D) ESTIMATE score for oesophageal adenocarcinoma (EAC). Relationships between risk and immune scores for (E) ESCC and (H) EAC. Relationships between risk and ESTIMATE scores for (F) ESCC and (G) EAC.

Journal: Journal of Cellular and Molecular Medicine

Article Title: Multi‐Omics Analysis of Aberrances and Functional Implications of IRF5 in Digestive Tract Tumours

doi: 10.1111/jcmm.70433

Figure Lengend Snippet: Correlations of immune microenvironments evaluated using ESTIMATE. (A) Immune score and (B) ESTIMATE score for oesophageal squamous cell carcinoma (ESCC). (C) Immune score and (D) ESTIMATE score for oesophageal adenocarcinoma (EAC). Relationships between risk and immune scores for (E) ESCC and (H) EAC. Relationships between risk and ESTIMATE scores for (F) ESCC and (G) EAC.

Article Snippet: Human ESCC cell lines (KYSE150, KYSE180, KYSE410 and KYSE450) and the human embryonic oesophageal cell line (SHEE) were purchased from iCell Bioscience Inc. (Shanghai, China).

Techniques:

Random forest error rates (left graphs) and relative importance (right graphs) for (A) oesophageal squamous cell carcinoma (ESCC) and (B) oesophageal adenocarcinoma (EAC). Expression of IRF5 and BMI1 in (C) ESCC, (D) EAC and (E) EC.

Journal: Journal of Cellular and Molecular Medicine

Article Title: Multi‐Omics Analysis of Aberrances and Functional Implications of IRF5 in Digestive Tract Tumours

doi: 10.1111/jcmm.70433

Figure Lengend Snippet: Random forest error rates (left graphs) and relative importance (right graphs) for (A) oesophageal squamous cell carcinoma (ESCC) and (B) oesophageal adenocarcinoma (EAC). Expression of IRF5 and BMI1 in (C) ESCC, (D) EAC and (E) EC.

Article Snippet: Human ESCC cell lines (KYSE150, KYSE180, KYSE410 and KYSE450) and the human embryonic oesophageal cell line (SHEE) were purchased from iCell Bioscience Inc. (Shanghai, China).

Techniques: Expressing

Expression analyses of IRF5 in four ESCC cell lines using western blotting (A, B). The efficiency of IRF5 ‐knockdown in KYSE150 cells was determined using western blotting (C, D). Ctrl: No siRNA infection; NC: Negative control. Statistical analyses of n = 3 independent experiments were assessed. Results are shown as mean ± SD, ns p ≥ 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001.

Journal: Journal of Cellular and Molecular Medicine

Article Title: Multi‐Omics Analysis of Aberrances and Functional Implications of IRF5 in Digestive Tract Tumours

doi: 10.1111/jcmm.70433

Figure Lengend Snippet: Expression analyses of IRF5 in four ESCC cell lines using western blotting (A, B). The efficiency of IRF5 ‐knockdown in KYSE150 cells was determined using western blotting (C, D). Ctrl: No siRNA infection; NC: Negative control. Statistical analyses of n = 3 independent experiments were assessed. Results are shown as mean ± SD, ns p ≥ 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001.

Article Snippet: Human ESCC cell lines (KYSE150, KYSE180, KYSE410 and KYSE450) and the human embryonic oesophageal cell line (SHEE) were purchased from iCell Bioscience Inc. (Shanghai, China).

Techniques: Expressing, Western Blot, Knockdown, Infection, Negative Control

Baseline patient characteristics of the different cohorts.

Journal: eBioMedicine

Article Title: DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities

doi: 10.1016/j.ebiom.2023.104801

Figure Lengend Snippet: Baseline patient characteristics of the different cohorts.

Article Snippet: The human ESCC cell lines KYSE30 (CVCL_1351), KYSE410 (CVCL_1352) and KYSE450 (CVCL_1353) were provided by Dr. Yutaka Shimada (Kyoto University, Kyoto, Japan) and cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS).

Techniques:

Clustering analysis of ESCC tumors based on DDR gene profiles. (a) Heatmap of the expression fold changes in DDR genes between DDR subtypes. The red bar represents the DDR active subtype, and the green bar represents the DDR silent subtype. The DDR subtypes are classified by the consensus clustering method. (b) Kaplan–Meier curves comparing OS between DDR active subtype and DDR silent subtype for all ESCC patients. (c) Kaplan–Meier curves comparing OS among the locoregional ESCC DDR active subtype, locoregional ESCC DDR silent subtype and metastatic ESCC tumors. (d) Kaplan–Meier curves comparing OS between DDR active subtype and DDR silent subtype only for metastatic ESCC patients. (e) Kaplan–Meier curves comparing OS between DDR active subtype and DDR silent subtype only for locoregional ESCC patients in TCGA-ESCC cohort and Chen cohort.

Journal: eBioMedicine

Article Title: DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities

doi: 10.1016/j.ebiom.2023.104801

Figure Lengend Snippet: Clustering analysis of ESCC tumors based on DDR gene profiles. (a) Heatmap of the expression fold changes in DDR genes between DDR subtypes. The red bar represents the DDR active subtype, and the green bar represents the DDR silent subtype. The DDR subtypes are classified by the consensus clustering method. (b) Kaplan–Meier curves comparing OS between DDR active subtype and DDR silent subtype for all ESCC patients. (c) Kaplan–Meier curves comparing OS among the locoregional ESCC DDR active subtype, locoregional ESCC DDR silent subtype and metastatic ESCC tumors. (d) Kaplan–Meier curves comparing OS between DDR active subtype and DDR silent subtype only for metastatic ESCC patients. (e) Kaplan–Meier curves comparing OS between DDR active subtype and DDR silent subtype only for locoregional ESCC patients in TCGA-ESCC cohort and Chen cohort.

Article Snippet: The human ESCC cell lines KYSE30 (CVCL_1351), KYSE410 (CVCL_1352) and KYSE450 (CVCL_1353) were provided by Dr. Yutaka Shimada (Kyoto University, Kyoto, Japan) and cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS).

Techniques: Expressing

BRCA1 and HFM1 are independent prognostic factors in locoregional ESCC. (a) Forest plot showing the univariable and multivariable Cox regression analysis of eight significant prognostic DDR genes and clinicopathological features based on OS in the SCH cohort with a two-sided Wald test. The box represents HR, and the vertical bar represents ±95% CIs. (b) Forest plots of a meta-analysis showing the robust prognostic effect in three cohorts for prognostic DDR genes. The box represents HR, and the vertical bar represents ±95% CIs. The red diamond represents the common effect model of the meta-analysis. (c–e) Kaplan–Meier curves comparing OS between high BRCA1 and low BRCA1 and high HFM1 and low HFM1. The HRs and 95% CIs were calculated by a two-sided Wald test using univariable Cox regression.

Journal: eBioMedicine

Article Title: DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities

doi: 10.1016/j.ebiom.2023.104801

Figure Lengend Snippet: BRCA1 and HFM1 are independent prognostic factors in locoregional ESCC. (a) Forest plot showing the univariable and multivariable Cox regression analysis of eight significant prognostic DDR genes and clinicopathological features based on OS in the SCH cohort with a two-sided Wald test. The box represents HR, and the vertical bar represents ±95% CIs. (b) Forest plots of a meta-analysis showing the robust prognostic effect in three cohorts for prognostic DDR genes. The box represents HR, and the vertical bar represents ±95% CIs. The red diamond represents the common effect model of the meta-analysis. (c–e) Kaplan–Meier curves comparing OS between high BRCA1 and low BRCA1 and high HFM1 and low HFM1. The HRs and 95% CIs were calculated by a two-sided Wald test using univariable Cox regression.

Article Snippet: The human ESCC cell lines KYSE30 (CVCL_1351), KYSE410 (CVCL_1352) and KYSE450 (CVCL_1353) were provided by Dr. Yutaka Shimada (Kyoto University, Kyoto, Japan) and cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS).

Techniques:

BRCA1 promotes DDR, while HFM1 suppresses DDR in ESCC cells. (a) KYSE410 and KYSE450 cells were transfected with siRNAs targeting BRCA1 and control siRNAs and then treated with 2 μg/ml DDP. The expression of BRCA1 and γH2AX was analyzed by Western blotting. (b) KYSE410 and KYSE450 cells were transfected with siRNAs targeting BRCA1 and control siRNAs, exposed to X-IR (4 Gy), and harvested at the indicated times. The expression of BRCA1 and γH2AX was analyzed by Western blotting. (c, d) Representative pictures and quantification analysis of γH2AX foci in BRCA1-depleted KYSE410 and KYSE450 cells and control cells treated with 2 μg/ml DDP (c) or X-IR (4 Gy) (d) at the indicated times. Scale bars, 5 μm. (e) KYSE30 and KYSE450 cells were transfected with siRNAs targeting HFM1 and control siRNAs and then treated with 2 μg/ml DDP. The expression of HFM1 and γH2AX was analyzed by Western blotting. (f) KYSE30 and KYSE450 cells were transfected with siRNAs targeting HFM1 and control siRNAs, exposed to X-IR (4 Gy), and harvested at the indicated times. The expression of HFM1 and γH2AX was analyzed by Western blotting. (g, h) Representative pictures and quantification analysis of γH2AX foci in HFM1-depleted KYSE410 and KYSE450 cells and control cells treated with 2 μg/ml DDP (g) or X-IR (4 Gy) (h) at the indicated times. Scale bars, 5 μm. Data in c and d and g and h are representative of three independent experiments and represent the mean ± SD. Each dot represents a single cell, and ImageJ was used to count 50 cells in each group for this experiment. P values were determined by the Mann–Whitney U test.

Journal: eBioMedicine

Article Title: DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities

doi: 10.1016/j.ebiom.2023.104801

Figure Lengend Snippet: BRCA1 promotes DDR, while HFM1 suppresses DDR in ESCC cells. (a) KYSE410 and KYSE450 cells were transfected with siRNAs targeting BRCA1 and control siRNAs and then treated with 2 μg/ml DDP. The expression of BRCA1 and γH2AX was analyzed by Western blotting. (b) KYSE410 and KYSE450 cells were transfected with siRNAs targeting BRCA1 and control siRNAs, exposed to X-IR (4 Gy), and harvested at the indicated times. The expression of BRCA1 and γH2AX was analyzed by Western blotting. (c, d) Representative pictures and quantification analysis of γH2AX foci in BRCA1-depleted KYSE410 and KYSE450 cells and control cells treated with 2 μg/ml DDP (c) or X-IR (4 Gy) (d) at the indicated times. Scale bars, 5 μm. (e) KYSE30 and KYSE450 cells were transfected with siRNAs targeting HFM1 and control siRNAs and then treated with 2 μg/ml DDP. The expression of HFM1 and γH2AX was analyzed by Western blotting. (f) KYSE30 and KYSE450 cells were transfected with siRNAs targeting HFM1 and control siRNAs, exposed to X-IR (4 Gy), and harvested at the indicated times. The expression of HFM1 and γH2AX was analyzed by Western blotting. (g, h) Representative pictures and quantification analysis of γH2AX foci in HFM1-depleted KYSE410 and KYSE450 cells and control cells treated with 2 μg/ml DDP (g) or X-IR (4 Gy) (h) at the indicated times. Scale bars, 5 μm. Data in c and d and g and h are representative of three independent experiments and represent the mean ± SD. Each dot represents a single cell, and ImageJ was used to count 50 cells in each group for this experiment. P values were determined by the Mann–Whitney U test.

Article Snippet: The human ESCC cell lines KYSE30 (CVCL_1351), KYSE410 (CVCL_1352) and KYSE450 (CVCL_1353) were provided by Dr. Yutaka Shimada (Kyoto University, Kyoto, Japan) and cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS).

Techniques: Transfection, Control, Expressing, Western Blot, MANN-WHITNEY

Immune microenvironment characterization of DDR subtypes identified GITR and BTLA as potential targets for immunotherapy. (a) Heatmap of the expression fold changes in DDR genes among DDR subtypes in locoregional ESCC patients. The red bar represents the DDR active subtype, the yellow bar represents the DDR moderate subtype, and the green bar represents the DDR silent subtype. The DDR subtypes are classified by the consensus clustering method. (b) Kaplan–Meier curves comparing OS among the DDR active subtype, DDR moderate subtype and DDR silent subtype in locoregional ESCC patients (log-rank test P = 0.053). (c) Volcano plot showing genes that are differentially expressed between the DDR active subtype and DDR silent subtype (DDR active vs. DDR silent ). Red points represent overexpressed DEGs in the DDR active subtype, and blue points represent 212 underexpressed DEGs in the DDR silent subtype. Gray points represent insignificant DEGs. The P value was calculated by empirical Bayes moderation from limma. (d) Bar plot showing the enrichment level of 50 hallmark gene sets between the DDR active subtype and DDR silent subtype. Red bars represent the significantly enriched hallmark gene sets in DDR active . Blue bars represent the significantly enriched hallmark gene sets in DDR silent . (e) Heatmap of the activity scores of 29 Fges among DDR subtypes in locoregional ESCC patients. (f, g) Box plots showing the distribution of immune checkpoint gene expression and exhausted T cell signature score among DDR subtypes (Kruskal–Wallis test). (h) T-distributed stochastic neighbor embedding (t-SNE) visualization of 7 T-cell clusters (32,918 T cells were collected from 31 locoregional ESCC patients) with specific markers, showing the annotation and color nodes for T-cell subpopulations in the tumor ecosystem. (i) Dot plot showing the expression of marker gene signatures of the seven T-cell subpopulations. Both color and size represent the effect size. (j) T-SNE visualization showing immune checkpoint gene expression in each T-cell subpopulation of locoregional ESCC.

Journal: eBioMedicine

Article Title: DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities

doi: 10.1016/j.ebiom.2023.104801

Figure Lengend Snippet: Immune microenvironment characterization of DDR subtypes identified GITR and BTLA as potential targets for immunotherapy. (a) Heatmap of the expression fold changes in DDR genes among DDR subtypes in locoregional ESCC patients. The red bar represents the DDR active subtype, the yellow bar represents the DDR moderate subtype, and the green bar represents the DDR silent subtype. The DDR subtypes are classified by the consensus clustering method. (b) Kaplan–Meier curves comparing OS among the DDR active subtype, DDR moderate subtype and DDR silent subtype in locoregional ESCC patients (log-rank test P = 0.053). (c) Volcano plot showing genes that are differentially expressed between the DDR active subtype and DDR silent subtype (DDR active vs. DDR silent ). Red points represent overexpressed DEGs in the DDR active subtype, and blue points represent 212 underexpressed DEGs in the DDR silent subtype. Gray points represent insignificant DEGs. The P value was calculated by empirical Bayes moderation from limma. (d) Bar plot showing the enrichment level of 50 hallmark gene sets between the DDR active subtype and DDR silent subtype. Red bars represent the significantly enriched hallmark gene sets in DDR active . Blue bars represent the significantly enriched hallmark gene sets in DDR silent . (e) Heatmap of the activity scores of 29 Fges among DDR subtypes in locoregional ESCC patients. (f, g) Box plots showing the distribution of immune checkpoint gene expression and exhausted T cell signature score among DDR subtypes (Kruskal–Wallis test). (h) T-distributed stochastic neighbor embedding (t-SNE) visualization of 7 T-cell clusters (32,918 T cells were collected from 31 locoregional ESCC patients) with specific markers, showing the annotation and color nodes for T-cell subpopulations in the tumor ecosystem. (i) Dot plot showing the expression of marker gene signatures of the seven T-cell subpopulations. Both color and size represent the effect size. (j) T-SNE visualization showing immune checkpoint gene expression in each T-cell subpopulation of locoregional ESCC.

Article Snippet: The human ESCC cell lines KYSE30 (CVCL_1351), KYSE410 (CVCL_1352) and KYSE450 (CVCL_1353) were provided by Dr. Yutaka Shimada (Kyoto University, Kyoto, Japan) and cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS).

Techniques: Expressing, Activity Assay, Gene Expression, Marker

GITR triggering or BTLA blockade potentiates the efficacy of anti-PD-1 antibody and cisplatin in murine ESCC models. Schematic representation of the therapy schedule for α-GITR, α-PD-1, or combination therapy (a), for α-BTLA, α-PD-1, or combination therapy (b), for α-GITR, DDP, or combination therapy (c) and for α-BTLA, DDP, or combination therapy (d). Tumor images and the statistical results of tumor weights from syngeneic mEC25 models that received the indicated treatments (n = 8 in a and b, n = 10 in c and d). Data in a-d represent the mean ± SD and were analyzed by the Mann–Whitney U test.

Journal: eBioMedicine

Article Title: DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities

doi: 10.1016/j.ebiom.2023.104801

Figure Lengend Snippet: GITR triggering or BTLA blockade potentiates the efficacy of anti-PD-1 antibody and cisplatin in murine ESCC models. Schematic representation of the therapy schedule for α-GITR, α-PD-1, or combination therapy (a), for α-BTLA, α-PD-1, or combination therapy (b), for α-GITR, DDP, or combination therapy (c) and for α-BTLA, DDP, or combination therapy (d). Tumor images and the statistical results of tumor weights from syngeneic mEC25 models that received the indicated treatments (n = 8 in a and b, n = 10 in c and d). Data in a-d represent the mean ± SD and were analyzed by the Mann–Whitney U test.

Article Snippet: The human ESCC cell lines KYSE30 (CVCL_1351), KYSE410 (CVCL_1352) and KYSE450 (CVCL_1353) were provided by Dr. Yutaka Shimada (Kyoto University, Kyoto, Japan) and cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS).

Techniques: MANN-WHITNEY