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human pancreatic cancer cell lines panc 1  (ATCC)


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    ATCC human pancreatic cancer cell lines panc 1
    Human Pancreatic Cancer Cell Lines Panc 1, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 8112 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/pancreatic+cancer+cell+line+panc/PANC-1/pm42823159-35-1-9
    Average 99 stars, based on 8112 article reviews
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    Cell Culture:

    Article Title: Diazobutanone-assisted isobaric labelling of phospholipids and sulfated glycolipids enables multiplexed quantitative lipidomics using tandem mass spectrometry.
    Article Snippet: Mass spectrometry-based quantitative lipidomics is an emerging field aiming to uncover the intricate relationships between lipidomes and disease development.. However, quantifying lipidomes comprehensively in a high-throughput manner remains challenging owing to the diverse lipid structures.. Here we propose a diazobutanone-assisted isobaric labelling strategy as a rapid and robust platform for multiplexed quantitative lipidomics across a broad range of lipid classes, including various phospholipids and glycolipids.

    Article Title: Lymphocyte Antigen 6 Family Member D (LY6D) affects stem cell phenotype and progression of pancreatic adenocarcinoma
    Article Snippet: .. The cell culture and quality maintenance techniques have been previously described.13,14 The human pancreatic cancer cell line Panc-1 was obtained from American Type Culture Collection (Manassas, VA). .. Cell lines were cultured in Dulbecco's modi ed Eagle’s medium (DMEM, 08456–36; Nacalai Tesque, Kyoto, Japan) supplemented with 10% fetal bovine serum (Life Technologies, Carlsbad, CA ).

    Article Title: Vitamin D and Sulforaphane Decrease Inflammatory Oxidative Stress and Restore the Markers of Epithelial Integrity in an In Vitro Model of Age-Related Macular Degeneration
    Article Snippet: .. Spontaneously arising human retinal pigment epithelium (ARPE-19) cells and pancreatic cancer cell line PANC-1 were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA) and were cultured in Dulbecco’s modified Eagles medium supplemented with 10% fetal bovine serum and 1% antibiotics (penicillin-streptomycin) at 37 °C in a humidified 5% CO 2 atmosphere. ..

    Modification:

    Article Title: Vitamin D and Sulforaphane Decrease Inflammatory Oxidative Stress and Restore the Markers of Epithelial Integrity in an In Vitro Model of Age-Related Macular Degeneration
    Article Snippet: .. Spontaneously arising human retinal pigment epithelium (ARPE-19) cells and pancreatic cancer cell line PANC-1 were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA) and were cultured in Dulbecco’s modified Eagles medium supplemented with 10% fetal bovine serum and 1% antibiotics (penicillin-streptomycin) at 37 °C in a humidified 5% CO 2 atmosphere. ..

    other:

    Article Title: The abscopal effect of IRE combined with anti–PD-1 achieves local ablation and systemic control of PDAC
    Article Snippet: The murine PDAC cell line HY19636 with a Kras G12D mutation was provided by Dr. Haoqiang Ying (MD Anderson).



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    ATCC pancreatic cancer cell line panc
    ( A ) Mitochondrial oxygen consumption rate (OCR) and ( B ) extracellular acidification rate (ECAR) in KRAS* cells 4 h after 10p IRE or 20p IRE (400 V). ( C ) Effect of IRE on mitochondrial ATP production. Data are normalized to cell number at the end of the assay (pmol/min/1000 cells). Data are expressed as mean ± SD (n=6/group). *p<0.05, **p<0.01, ***p<0.001 (one-way ANOVA). ( D ) Representative confocal fluorescence microscopic images of cytoplasmic dsDNA and corresponding quantification of fluorescence (FL) signal intensity in cytosol and <t>nuclei.</t> <t>PANC-1</t> cells were stained with PicoGreen for dsDNA 24 h after IRE (400 V, 20 pulses). Untreated cells were used as a control. The negative control was cells not stained with PicoGreen. Data are expressed as mean ± SD (n=4). *p<0.05, *p<0.01, (Student’s t test). ( E ) Analysis of dsDNA from IRE-treated KRAS* tumors using the Qubit dsDNA HS assay kits. KRAS* tumor tissues were collected on day 1 and day 4 after IRE (1200 V, 99 pulses) and processed for dsDNA assays. *p<0.05, ****p<0.0001 (Student’s t test). ( F ) Real-time PCR analysis of the interferon-stimulated genes Irf1 , Cxcl10 , and Isg15 downstream of the cGAS-STING pathway. KRAS* cells were collected 4 h after IRE (400 V, 20 pulses). *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001 (one-way ANOVA). Data are expressed as mean ± SD (n=3/group).
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    ATCC pancreatic cancer cell line panc 1
    (A) Clinical and molecular characterization of six pancreatic cancer patients (n=6) stratified by unsupervised hierarchical clustering of serum sEV miRNA expression profiles. Three clusters were resolved: Cluster 1 (P1, P3, P5; red), Cluster 2 (P4; blue), and Cluster 3 (P2, P6; green). Diagnoses are indicated above each patient identifier: PDAC, pancreatic ductal adenocarcinoma; NET, neuroendocrine tumor; Mesoth., malignant mesothelioma of the pancreas. Clinical parameters shown include age at diagnosis (dot plot, years), number of prior treatment lines (bar chart, top right), and comorbidity burden (bar chart, bottom right). The Jaccard similarity index between within-cluster patient pairs (CPM>0) is plotted for Clusters 1 and 3, demonstrating high intra-cluster miRNA-profile similarity (range 0.588–0.644). A Venn diagram illustrates the overlap between miRNAs detected in patient serum sEVs (T=428) and <t>in</t> <t>PANC-1</t> sEVs across 9 time-points (T=1,426); 359 miRNAs are shared between the two datasets. Bar charts indicate the percentage of cluster-specific patient miRNAs detectable in the PANC-1 sEV secretome: Cluster 1, 84.6%; Cluster 2, 84.2%; Cluster 3, 83.9%. ( B ) UpSet plot (top) displaying the combinatorial overlap of miRNAs detected in each patient’s serum sEVs. Vertical bars indicate the number of miRNAs shared by each intersecting patient combination defined in the connected dot matrix below; horizontal bars on the right show the total number of miRNAs detected per patient. Below the UpSet plot, a heatmap shows expression levels (log2(CPM+1)) of the 11 candidate miRNAs functionally validated in this study across all six patients. Rows are ordered by hierarchical clustering of miRNA expression profiles; columns are arranged by patient cluster assignment (Cluster 1, red; Cluster 2, blue; Cluster 3, green). Color scale ranges from blue (low expression) to dark red (high expression). ( C ) Frequency of the 11 candidate miRNAs among the top 50 most highly expressed miRNAs in pancreatic cancer tumor specimens. For each of 495 tumor samples from the GDC data portal (TCGA-PAAD, CPTAC-3, and HCMI-CMDC), miRNAs were ranked by RPM, and a given miRNA was classified as highly expressed if any of its corresponding precursors ranked within the top 50. Bars show the percentage of samples meeting this criterion; absolute sample counts are given in parentheses. ( D ) Proposed mechanistic model. Within the PDAC tumor cell, a dysregulated clock (BMAL1↓, altered rhythmic output) drives miRNA sorting into EVs during biogenesis; miR-27b-3p is uniquely (among those tested) and rhythmically packaged, while other sEV miRNAs are loaded constitutively. Secreted sEVs exhibit variable particle number with stable size, and these miRNAs are detectable in patient serum (84– 85% overlap with PANC-1 sEV miRNAs). In the recipient skeletal muscle cell, the full sEV miRNA cargo collectively disrupts the circadian clock, altering period, phase, and amplitude. In parallel, individual miRNAs reprogram bioenergetics along four non-redundant trajectories: Energetic (miR-27b-3p + others; ↑OCR, aerobic/oxidative, ↑spare respiratory capacity); High metabolic (miR-191-5p + others; ↑OCR, ↑ECAR, high respiratory capacity); Quiescent (others; ↓OCR, ↓ECAR, low metabolic capacity); and Glycolytic (miR-183-5p + others; ↓OCR, ↑ECAR, glycolytic drift). The integration of circadian disruption, bioenergetic reprogramming, and proteostatic dysregulation collectively drives muscle-cell atrophy in vitro ; whether and how these molecularly distinct insults produce a systemic cachexia phenotype in vivo remains to be determined (gray box).
    Pancreatic Cancer Cell Line Panc 1, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    ATCC cell culture human pancreatic cancer cell lines
    (A) Clinical and molecular characterization of six pancreatic cancer patients (n=6) stratified by unsupervised hierarchical clustering of serum sEV miRNA expression profiles. Three clusters were resolved: Cluster 1 (P1, P3, P5; red), Cluster 2 (P4; blue), and Cluster 3 (P2, P6; green). Diagnoses are indicated above each patient identifier: PDAC, pancreatic ductal adenocarcinoma; NET, neuroendocrine tumor; Mesoth., malignant mesothelioma of the pancreas. Clinical parameters shown include age at diagnosis (dot plot, years), number of prior treatment lines (bar chart, top right), and comorbidity burden (bar chart, bottom right). The Jaccard similarity index between within-cluster patient pairs (CPM>0) is plotted for Clusters 1 and 3, demonstrating high intra-cluster miRNA-profile similarity (range 0.588–0.644). A Venn diagram illustrates the overlap between miRNAs detected in patient serum sEVs (T=428) and <t>in</t> <t>PANC-1</t> sEVs across 9 time-points (T=1,426); 359 miRNAs are shared between the two datasets. Bar charts indicate the percentage of cluster-specific patient miRNAs detectable in the PANC-1 sEV secretome: Cluster 1, 84.6%; Cluster 2, 84.2%; Cluster 3, 83.9%. ( B ) UpSet plot (top) displaying the combinatorial overlap of miRNAs detected in each patient’s serum sEVs. Vertical bars indicate the number of miRNAs shared by each intersecting patient combination defined in the connected dot matrix below; horizontal bars on the right show the total number of miRNAs detected per patient. Below the UpSet plot, a heatmap shows expression levels (log2(CPM+1)) of the 11 candidate miRNAs functionally validated in this study across all six patients. Rows are ordered by hierarchical clustering of miRNA expression profiles; columns are arranged by patient cluster assignment (Cluster 1, red; Cluster 2, blue; Cluster 3, green). Color scale ranges from blue (low expression) to dark red (high expression). ( C ) Frequency of the 11 candidate miRNAs among the top 50 most highly expressed miRNAs in pancreatic cancer tumor specimens. For each of 495 tumor samples from the GDC data portal (TCGA-PAAD, CPTAC-3, and HCMI-CMDC), miRNAs were ranked by RPM, and a given miRNA was classified as highly expressed if any of its corresponding precursors ranked within the top 50. Bars show the percentage of samples meeting this criterion; absolute sample counts are given in parentheses. ( D ) Proposed mechanistic model. Within the PDAC tumor cell, a dysregulated clock (BMAL1↓, altered rhythmic output) drives miRNA sorting into EVs during biogenesis; miR-27b-3p is uniquely (among those tested) and rhythmically packaged, while other sEV miRNAs are loaded constitutively. Secreted sEVs exhibit variable particle number with stable size, and these miRNAs are detectable in patient serum (84– 85% overlap with PANC-1 sEV miRNAs). In the recipient skeletal muscle cell, the full sEV miRNA cargo collectively disrupts the circadian clock, altering period, phase, and amplitude. In parallel, individual miRNAs reprogram bioenergetics along four non-redundant trajectories: Energetic (miR-27b-3p + others; ↑OCR, aerobic/oxidative, ↑spare respiratory capacity); High metabolic (miR-191-5p + others; ↑OCR, ↑ECAR, high respiratory capacity); Quiescent (others; ↓OCR, ↓ECAR, low metabolic capacity); and Glycolytic (miR-183-5p + others; ↓OCR, ↑ECAR, glycolytic drift). The integration of circadian disruption, bioenergetic reprogramming, and proteostatic dysregulation collectively drives muscle-cell atrophy in vitro ; whether and how these molecularly distinct insults produce a systemic cachexia phenotype in vivo remains to be determined (gray box).
    Cell Culture Human Pancreatic Cancer Cell Lines, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Average 99 stars, based on 1 article reviews
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    ATCC human pancreatic cancer cell lines
    (A) Clinical and molecular characterization of six pancreatic cancer patients (n=6) stratified by unsupervised hierarchical clustering of serum sEV miRNA expression profiles. Three clusters were resolved: Cluster 1 (P1, P3, P5; red), Cluster 2 (P4; blue), and Cluster 3 (P2, P6; green). Diagnoses are indicated above each patient identifier: PDAC, pancreatic ductal adenocarcinoma; NET, neuroendocrine tumor; Mesoth., malignant mesothelioma of the pancreas. Clinical parameters shown include age at diagnosis (dot plot, years), number of prior treatment lines (bar chart, top right), and comorbidity burden (bar chart, bottom right). The Jaccard similarity index between within-cluster patient pairs (CPM>0) is plotted for Clusters 1 and 3, demonstrating high intra-cluster miRNA-profile similarity (range 0.588–0.644). A Venn diagram illustrates the overlap between miRNAs detected in patient serum sEVs (T=428) and <t>in</t> <t>PANC-1</t> sEVs across 9 time-points (T=1,426); 359 miRNAs are shared between the two datasets. Bar charts indicate the percentage of cluster-specific patient miRNAs detectable in the PANC-1 sEV secretome: Cluster 1, 84.6%; Cluster 2, 84.2%; Cluster 3, 83.9%. ( B ) UpSet plot (top) displaying the combinatorial overlap of miRNAs detected in each patient’s serum sEVs. Vertical bars indicate the number of miRNAs shared by each intersecting patient combination defined in the connected dot matrix below; horizontal bars on the right show the total number of miRNAs detected per patient. Below the UpSet plot, a heatmap shows expression levels (log2(CPM+1)) of the 11 candidate miRNAs functionally validated in this study across all six patients. Rows are ordered by hierarchical clustering of miRNA expression profiles; columns are arranged by patient cluster assignment (Cluster 1, red; Cluster 2, blue; Cluster 3, green). Color scale ranges from blue (low expression) to dark red (high expression). ( C ) Frequency of the 11 candidate miRNAs among the top 50 most highly expressed miRNAs in pancreatic cancer tumor specimens. For each of 495 tumor samples from the GDC data portal (TCGA-PAAD, CPTAC-3, and HCMI-CMDC), miRNAs were ranked by RPM, and a given miRNA was classified as highly expressed if any of its corresponding precursors ranked within the top 50. Bars show the percentage of samples meeting this criterion; absolute sample counts are given in parentheses. ( D ) Proposed mechanistic model. Within the PDAC tumor cell, a dysregulated clock (BMAL1↓, altered rhythmic output) drives miRNA sorting into EVs during biogenesis; miR-27b-3p is uniquely (among those tested) and rhythmically packaged, while other sEV miRNAs are loaded constitutively. Secreted sEVs exhibit variable particle number with stable size, and these miRNAs are detectable in patient serum (84– 85% overlap with PANC-1 sEV miRNAs). In the recipient skeletal muscle cell, the full sEV miRNA cargo collectively disrupts the circadian clock, altering period, phase, and amplitude. In parallel, individual miRNAs reprogram bioenergetics along four non-redundant trajectories: Energetic (miR-27b-3p + others; ↑OCR, aerobic/oxidative, ↑spare respiratory capacity); High metabolic (miR-191-5p + others; ↑OCR, ↑ECAR, high respiratory capacity); Quiescent (others; ↓OCR, ↓ECAR, low metabolic capacity); and Glycolytic (miR-183-5p + others; ↓OCR, ↑ECAR, glycolytic drift). The integration of circadian disruption, bioenergetic reprogramming, and proteostatic dysregulation collectively drives muscle-cell atrophy in vitro ; whether and how these molecularly distinct insults produce a systemic cachexia phenotype in vivo remains to be determined (gray box).
    Human Pancreatic Cancer Cell Lines, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    ( A ) Mitochondrial oxygen consumption rate (OCR) and ( B ) extracellular acidification rate (ECAR) in KRAS* cells 4 h after 10p IRE or 20p IRE (400 V). ( C ) Effect of IRE on mitochondrial ATP production. Data are normalized to cell number at the end of the assay (pmol/min/1000 cells). Data are expressed as mean ± SD (n=6/group). *p<0.05, **p<0.01, ***p<0.001 (one-way ANOVA). ( D ) Representative confocal fluorescence microscopic images of cytoplasmic dsDNA and corresponding quantification of fluorescence (FL) signal intensity in cytosol and nuclei. PANC-1 cells were stained with PicoGreen for dsDNA 24 h after IRE (400 V, 20 pulses). Untreated cells were used as a control. The negative control was cells not stained with PicoGreen. Data are expressed as mean ± SD (n=4). *p<0.05, *p<0.01, (Student’s t test). ( E ) Analysis of dsDNA from IRE-treated KRAS* tumors using the Qubit dsDNA HS assay kits. KRAS* tumor tissues were collected on day 1 and day 4 after IRE (1200 V, 99 pulses) and processed for dsDNA assays. *p<0.05, ****p<0.0001 (Student’s t test). ( F ) Real-time PCR analysis of the interferon-stimulated genes Irf1 , Cxcl10 , and Isg15 downstream of the cGAS-STING pathway. KRAS* cells were collected 4 h after IRE (400 V, 20 pulses). *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001 (one-way ANOVA). Data are expressed as mean ± SD (n=3/group).

    Journal: bioRxiv

    Article Title: The abscopal effect of IRE combined with anti–PD-1 achieves local ablation and systemic control of PDAC

    doi: 10.64898/2026.05.04.722535

    Figure Lengend Snippet: ( A ) Mitochondrial oxygen consumption rate (OCR) and ( B ) extracellular acidification rate (ECAR) in KRAS* cells 4 h after 10p IRE or 20p IRE (400 V). ( C ) Effect of IRE on mitochondrial ATP production. Data are normalized to cell number at the end of the assay (pmol/min/1000 cells). Data are expressed as mean ± SD (n=6/group). *p<0.05, **p<0.01, ***p<0.001 (one-way ANOVA). ( D ) Representative confocal fluorescence microscopic images of cytoplasmic dsDNA and corresponding quantification of fluorescence (FL) signal intensity in cytosol and nuclei. PANC-1 cells were stained with PicoGreen for dsDNA 24 h after IRE (400 V, 20 pulses). Untreated cells were used as a control. The negative control was cells not stained with PicoGreen. Data are expressed as mean ± SD (n=4). *p<0.05, *p<0.01, (Student’s t test). ( E ) Analysis of dsDNA from IRE-treated KRAS* tumors using the Qubit dsDNA HS assay kits. KRAS* tumor tissues were collected on day 1 and day 4 after IRE (1200 V, 99 pulses) and processed for dsDNA assays. *p<0.05, ****p<0.0001 (Student’s t test). ( F ) Real-time PCR analysis of the interferon-stimulated genes Irf1 , Cxcl10 , and Isg15 downstream of the cGAS-STING pathway. KRAS* cells were collected 4 h after IRE (400 V, 20 pulses). *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001 (one-way ANOVA). Data are expressed as mean ± SD (n=3/group).

    Article Snippet: The human pancreatic cancer cell line PANC-1 was purchased from American Type Culture Collection.

    Techniques: Fluorescence, Staining, Control, Negative Control, Real-time Polymerase Chain Reaction

    (A) Clinical and molecular characterization of six pancreatic cancer patients (n=6) stratified by unsupervised hierarchical clustering of serum sEV miRNA expression profiles. Three clusters were resolved: Cluster 1 (P1, P3, P5; red), Cluster 2 (P4; blue), and Cluster 3 (P2, P6; green). Diagnoses are indicated above each patient identifier: PDAC, pancreatic ductal adenocarcinoma; NET, neuroendocrine tumor; Mesoth., malignant mesothelioma of the pancreas. Clinical parameters shown include age at diagnosis (dot plot, years), number of prior treatment lines (bar chart, top right), and comorbidity burden (bar chart, bottom right). The Jaccard similarity index between within-cluster patient pairs (CPM>0) is plotted for Clusters 1 and 3, demonstrating high intra-cluster miRNA-profile similarity (range 0.588–0.644). A Venn diagram illustrates the overlap between miRNAs detected in patient serum sEVs (T=428) and in PANC-1 sEVs across 9 time-points (T=1,426); 359 miRNAs are shared between the two datasets. Bar charts indicate the percentage of cluster-specific patient miRNAs detectable in the PANC-1 sEV secretome: Cluster 1, 84.6%; Cluster 2, 84.2%; Cluster 3, 83.9%. ( B ) UpSet plot (top) displaying the combinatorial overlap of miRNAs detected in each patient’s serum sEVs. Vertical bars indicate the number of miRNAs shared by each intersecting patient combination defined in the connected dot matrix below; horizontal bars on the right show the total number of miRNAs detected per patient. Below the UpSet plot, a heatmap shows expression levels (log2(CPM+1)) of the 11 candidate miRNAs functionally validated in this study across all six patients. Rows are ordered by hierarchical clustering of miRNA expression profiles; columns are arranged by patient cluster assignment (Cluster 1, red; Cluster 2, blue; Cluster 3, green). Color scale ranges from blue (low expression) to dark red (high expression). ( C ) Frequency of the 11 candidate miRNAs among the top 50 most highly expressed miRNAs in pancreatic cancer tumor specimens. For each of 495 tumor samples from the GDC data portal (TCGA-PAAD, CPTAC-3, and HCMI-CMDC), miRNAs were ranked by RPM, and a given miRNA was classified as highly expressed if any of its corresponding precursors ranked within the top 50. Bars show the percentage of samples meeting this criterion; absolute sample counts are given in parentheses. ( D ) Proposed mechanistic model. Within the PDAC tumor cell, a dysregulated clock (BMAL1↓, altered rhythmic output) drives miRNA sorting into EVs during biogenesis; miR-27b-3p is uniquely (among those tested) and rhythmically packaged, while other sEV miRNAs are loaded constitutively. Secreted sEVs exhibit variable particle number with stable size, and these miRNAs are detectable in patient serum (84– 85% overlap with PANC-1 sEV miRNAs). In the recipient skeletal muscle cell, the full sEV miRNA cargo collectively disrupts the circadian clock, altering period, phase, and amplitude. In parallel, individual miRNAs reprogram bioenergetics along four non-redundant trajectories: Energetic (miR-27b-3p + others; ↑OCR, aerobic/oxidative, ↑spare respiratory capacity); High metabolic (miR-191-5p + others; ↑OCR, ↑ECAR, high respiratory capacity); Quiescent (others; ↓OCR, ↓ECAR, low metabolic capacity); and Glycolytic (miR-183-5p + others; ↓OCR, ↑ECAR, glycolytic drift). The integration of circadian disruption, bioenergetic reprogramming, and proteostatic dysregulation collectively drives muscle-cell atrophy in vitro ; whether and how these molecularly distinct insults produce a systemic cachexia phenotype in vivo remains to be determined (gray box).

    Journal: bioRxiv

    Article Title: Pancreatic cancer extracellular vesicles carry a time-of-day-regulated miRNA cargo that disrupts the skeletal muscle clock and bioenergetics

    doi: 10.64898/2026.05.03.722338

    Figure Lengend Snippet: (A) Clinical and molecular characterization of six pancreatic cancer patients (n=6) stratified by unsupervised hierarchical clustering of serum sEV miRNA expression profiles. Three clusters were resolved: Cluster 1 (P1, P3, P5; red), Cluster 2 (P4; blue), and Cluster 3 (P2, P6; green). Diagnoses are indicated above each patient identifier: PDAC, pancreatic ductal adenocarcinoma; NET, neuroendocrine tumor; Mesoth., malignant mesothelioma of the pancreas. Clinical parameters shown include age at diagnosis (dot plot, years), number of prior treatment lines (bar chart, top right), and comorbidity burden (bar chart, bottom right). The Jaccard similarity index between within-cluster patient pairs (CPM>0) is plotted for Clusters 1 and 3, demonstrating high intra-cluster miRNA-profile similarity (range 0.588–0.644). A Venn diagram illustrates the overlap between miRNAs detected in patient serum sEVs (T=428) and in PANC-1 sEVs across 9 time-points (T=1,426); 359 miRNAs are shared between the two datasets. Bar charts indicate the percentage of cluster-specific patient miRNAs detectable in the PANC-1 sEV secretome: Cluster 1, 84.6%; Cluster 2, 84.2%; Cluster 3, 83.9%. ( B ) UpSet plot (top) displaying the combinatorial overlap of miRNAs detected in each patient’s serum sEVs. Vertical bars indicate the number of miRNAs shared by each intersecting patient combination defined in the connected dot matrix below; horizontal bars on the right show the total number of miRNAs detected per patient. Below the UpSet plot, a heatmap shows expression levels (log2(CPM+1)) of the 11 candidate miRNAs functionally validated in this study across all six patients. Rows are ordered by hierarchical clustering of miRNA expression profiles; columns are arranged by patient cluster assignment (Cluster 1, red; Cluster 2, blue; Cluster 3, green). Color scale ranges from blue (low expression) to dark red (high expression). ( C ) Frequency of the 11 candidate miRNAs among the top 50 most highly expressed miRNAs in pancreatic cancer tumor specimens. For each of 495 tumor samples from the GDC data portal (TCGA-PAAD, CPTAC-3, and HCMI-CMDC), miRNAs were ranked by RPM, and a given miRNA was classified as highly expressed if any of its corresponding precursors ranked within the top 50. Bars show the percentage of samples meeting this criterion; absolute sample counts are given in parentheses. ( D ) Proposed mechanistic model. Within the PDAC tumor cell, a dysregulated clock (BMAL1↓, altered rhythmic output) drives miRNA sorting into EVs during biogenesis; miR-27b-3p is uniquely (among those tested) and rhythmically packaged, while other sEV miRNAs are loaded constitutively. Secreted sEVs exhibit variable particle number with stable size, and these miRNAs are detectable in patient serum (84– 85% overlap with PANC-1 sEV miRNAs). In the recipient skeletal muscle cell, the full sEV miRNA cargo collectively disrupts the circadian clock, altering period, phase, and amplitude. In parallel, individual miRNAs reprogram bioenergetics along four non-redundant trajectories: Energetic (miR-27b-3p + others; ↑OCR, aerobic/oxidative, ↑spare respiratory capacity); High metabolic (miR-191-5p + others; ↑OCR, ↑ECAR, high respiratory capacity); Quiescent (others; ↓OCR, ↓ECAR, low metabolic capacity); and Glycolytic (miR-183-5p + others; ↓OCR, ↑ECAR, glycolytic drift). The integration of circadian disruption, bioenergetic reprogramming, and proteostatic dysregulation collectively drives muscle-cell atrophy in vitro ; whether and how these molecularly distinct insults produce a systemic cachexia phenotype in vivo remains to be determined (gray box).

    Article Snippet: The human pancreatic cancer cell line PANC-1, the murine fibroblast cell line NIH3T3, and the murine myoblast cell line C2C12 were purchased from American Type Culture Collection (ATCC, Manassas, VA).

    Techniques: Expressing, Biomarker Discovery, Disruption, In Vitro, In Vivo

    (A) Bioluminescence recording, ( B ) period analysis, and ( C ) phase and amplitude analysis of U2OS BMAL1 :Luc reporter cells treated with PANC-1 CM at 12.5%, 25%, 50%, and 100% of the recording media. ( D ) Bioluminescence recording, ( E ) period analysis, and ( F ) phase and amplitude analysis of NIH3T3 Bmal1 :Luc reporter cells treated with PANC-1 CM at the same concentrations. For all bioluminescence experiments, at least three complete oscillations were included in the period estimation, excluding the first 24 h. Mean ± SD of relative mRNA expression of NIH3T3 core clock genes Bmal1 ( G ), Per2 ( H ), and Cry2 ( I ) measured over 36 h in response to PANC-1 CM. Relative mRNA levels of core clock genes in synchronized C2C12 myotubes over 32 h following treatment with PANC-1 CM: ( J ) Bmal1 , ( K ) Per2 , and ( L ) Cry2 . Cosine curves were fit for visualization purposes only; solid lines represent rhythmic oscillations (p<0.05) detected by MetaCycle, while dashed lines indicate loss of statistical rhythmicity (Suppl. Table 1). ( G–L ) Black: Control; ( G–I ) Red: PANC-1 CM; ( J–L ) Blue: PANC-1 CM. ( M ) Schematic representation and representative images of mature C2C12 myotube atrophy in response to NIH3T3 or PANC-1 released factors using a Transwell co-culture system; three measurements per myotube (yellow arrows) were used to quantify shortening. ( N ) Quantification of normalized myotube diameter under NIH3T3 vs PANC-1 co-culture, normalized to NIH3T3 co-culture control. One-way ANOVA: ( B ) p=0.0009, ( E ) p=0.0087. ( B, E ) Dunnett’s post-hoc test: *p<0.05; **p<0.01; ***p<0.001. (N) Student’s t-test: ***p<0.001.

    Journal: bioRxiv

    Article Title: Pancreatic cancer extracellular vesicles carry a time-of-day-regulated miRNA cargo that disrupts the skeletal muscle clock and bioenergetics

    doi: 10.64898/2026.05.03.722338

    Figure Lengend Snippet: (A) Bioluminescence recording, ( B ) period analysis, and ( C ) phase and amplitude analysis of U2OS BMAL1 :Luc reporter cells treated with PANC-1 CM at 12.5%, 25%, 50%, and 100% of the recording media. ( D ) Bioluminescence recording, ( E ) period analysis, and ( F ) phase and amplitude analysis of NIH3T3 Bmal1 :Luc reporter cells treated with PANC-1 CM at the same concentrations. For all bioluminescence experiments, at least three complete oscillations were included in the period estimation, excluding the first 24 h. Mean ± SD of relative mRNA expression of NIH3T3 core clock genes Bmal1 ( G ), Per2 ( H ), and Cry2 ( I ) measured over 36 h in response to PANC-1 CM. Relative mRNA levels of core clock genes in synchronized C2C12 myotubes over 32 h following treatment with PANC-1 CM: ( J ) Bmal1 , ( K ) Per2 , and ( L ) Cry2 . Cosine curves were fit for visualization purposes only; solid lines represent rhythmic oscillations (p<0.05) detected by MetaCycle, while dashed lines indicate loss of statistical rhythmicity (Suppl. Table 1). ( G–L ) Black: Control; ( G–I ) Red: PANC-1 CM; ( J–L ) Blue: PANC-1 CM. ( M ) Schematic representation and representative images of mature C2C12 myotube atrophy in response to NIH3T3 or PANC-1 released factors using a Transwell co-culture system; three measurements per myotube (yellow arrows) were used to quantify shortening. ( N ) Quantification of normalized myotube diameter under NIH3T3 vs PANC-1 co-culture, normalized to NIH3T3 co-culture control. One-way ANOVA: ( B ) p=0.0009, ( E ) p=0.0087. ( B, E ) Dunnett’s post-hoc test: *p<0.05; **p<0.01; ***p<0.001. (N) Student’s t-test: ***p<0.001.

    Article Snippet: The human pancreatic cancer cell line PANC-1, the murine fibroblast cell line NIH3T3, and the murine myoblast cell line C2C12 were purchased from American Type Culture Collection (ATCC, Manassas, VA).

    Techniques: Expressing, Control, Co-Culture Assay

    (A) Concentration of sEVs and ( B ) mean particle size of sEVs isolated from CM of circadian-synchronized PANC-1 cells collected every 4 h for 32 h (n=3 biological replicates per time-point). ( C ) Heatmap displaying z-score-normalized log2(CPM+1) expression of 1,426 miRNAs detected in PANC-1 sEVs collected at 9 consecutive time-points. Hierarchical clustering used Ward.D2 linkage with Euclidean distance. Rows represent individual miRNAs; columns represent time-points. Color scale: red = above-mean expression; blue = below-mean expression. The dendrogram on the left shows hierarchical relationships among miRNAs. Five clusters were identified with distinct temporal expression patterns: C1 (Red, n=352), C2 (Blue, n=200), C3 (Green, n=426), C4 (Orange, n=181), and C5 (Purple, n=267). The optimal number of clusters (k=5) was determined by combining the elbow method and silhouette analysis (mean silhouette score = 0.187). ( D ) Dot plots showing KEGG enrichment for miRNA clusters C1–C5. Target genes were predicted using miRDB (score ≥80) for each cluster’s miRNA set. The x-axis represents Gene Ratio; dot size represents the number of genes enriched in each pathway (Gene count). Dot color (C1: Red, C2: Blue, C3: Green, C4: Orange, C5: Purple) indicates statistical significance as −log10(padj); only the top 20 significant terms are shown. ( E ) Representative bioluminescence curves of synchronized NIH3T3 Bmal1 :Luc cells transfected with 25 nM of miRNA mimics: hsa-miR-27b-3p, hsa-miR-99b-5p, hsa-miR-127-3p, hsa-miR-191-5p, hsa-miR-615-3p, or negative-transfection control (cel-miR-67). ( F ) Period, ( G ) phase, and ( H ) amplitude analyses of NIH3T3 Bmal1 :Luc cells transfected with the miRNAs in panel E. ( I ) Representative bioluminescence curves of synchronized NIH3T3 Bmal1 :Luc cells transfected with 25 nM of: hsa-let-7f-5p, hsa-miR-10a-5p, hsa-miR-26a-5p, hsa-miR-30c-5p, hsa-miR-92a-3p, hsa-miR-183-5p, or negative-transfection control (cel-miR-67). ( J ) Period, ( K ) phase, and ( L ) amplitude analyses of NIH3T3 Bmal1 :Luc cells transfected with the miRNAs in panel I. All data are presented as mean ± SD. Circadian period, phase, and amplitude were calculated using the FFT-NLLS algorithm in BioDare2 ( https://biodare2.ed.ac.uk/ ). Statistical analyses of period, phase, and amplitude were performed by one-way ANOVA with Dunnett’s post-hoc test in GraphPad Prism. *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001; n.s., not significant.

    Journal: bioRxiv

    Article Title: Pancreatic cancer extracellular vesicles carry a time-of-day-regulated miRNA cargo that disrupts the skeletal muscle clock and bioenergetics

    doi: 10.64898/2026.05.03.722338

    Figure Lengend Snippet: (A) Concentration of sEVs and ( B ) mean particle size of sEVs isolated from CM of circadian-synchronized PANC-1 cells collected every 4 h for 32 h (n=3 biological replicates per time-point). ( C ) Heatmap displaying z-score-normalized log2(CPM+1) expression of 1,426 miRNAs detected in PANC-1 sEVs collected at 9 consecutive time-points. Hierarchical clustering used Ward.D2 linkage with Euclidean distance. Rows represent individual miRNAs; columns represent time-points. Color scale: red = above-mean expression; blue = below-mean expression. The dendrogram on the left shows hierarchical relationships among miRNAs. Five clusters were identified with distinct temporal expression patterns: C1 (Red, n=352), C2 (Blue, n=200), C3 (Green, n=426), C4 (Orange, n=181), and C5 (Purple, n=267). The optimal number of clusters (k=5) was determined by combining the elbow method and silhouette analysis (mean silhouette score = 0.187). ( D ) Dot plots showing KEGG enrichment for miRNA clusters C1–C5. Target genes were predicted using miRDB (score ≥80) for each cluster’s miRNA set. The x-axis represents Gene Ratio; dot size represents the number of genes enriched in each pathway (Gene count). Dot color (C1: Red, C2: Blue, C3: Green, C4: Orange, C5: Purple) indicates statistical significance as −log10(padj); only the top 20 significant terms are shown. ( E ) Representative bioluminescence curves of synchronized NIH3T3 Bmal1 :Luc cells transfected with 25 nM of miRNA mimics: hsa-miR-27b-3p, hsa-miR-99b-5p, hsa-miR-127-3p, hsa-miR-191-5p, hsa-miR-615-3p, or negative-transfection control (cel-miR-67). ( F ) Period, ( G ) phase, and ( H ) amplitude analyses of NIH3T3 Bmal1 :Luc cells transfected with the miRNAs in panel E. ( I ) Representative bioluminescence curves of synchronized NIH3T3 Bmal1 :Luc cells transfected with 25 nM of: hsa-let-7f-5p, hsa-miR-10a-5p, hsa-miR-26a-5p, hsa-miR-30c-5p, hsa-miR-92a-3p, hsa-miR-183-5p, or negative-transfection control (cel-miR-67). ( J ) Period, ( K ) phase, and ( L ) amplitude analyses of NIH3T3 Bmal1 :Luc cells transfected with the miRNAs in panel I. All data are presented as mean ± SD. Circadian period, phase, and amplitude were calculated using the FFT-NLLS algorithm in BioDare2 ( https://biodare2.ed.ac.uk/ ). Statistical analyses of period, phase, and amplitude were performed by one-way ANOVA with Dunnett’s post-hoc test in GraphPad Prism. *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001; n.s., not significant.

    Article Snippet: The human pancreatic cancer cell line PANC-1, the murine fibroblast cell line NIH3T3, and the murine myoblast cell line C2C12 were purchased from American Type Culture Collection (ATCC, Manassas, VA).

    Techniques: Concentration Assay, Isolation, Expressing, Transfection, Control

    (A) Top 35 miRNAs by mean expression in PANC-1-derived sEVs. Bar plot of mean log2 CPM across 9 time-points (4–36 h). Red bars: miRNAs selected from the top 35 to be tested in the BMAL1 :Luc reporter and atrophy assays; grey bars: remaining top-35 miRNAs. miRNAs are ranked in descending order of EV expression. ( B ) GO Biological Process enrichment of the experimentally validated targets (miRTarBase) of the 11 selected miRNAs. Terms are grouped into functional categories. Dot size represents the number of validated target genes associated with each term; dot color indicates Gene Ratio (proportion of input genes annotated to the term), from light pink (low) to dark red (high). Analysis performed with clusterProfiler. ( C , top panel) Normalized C2C12 myotube diameter at 0, 24, and 48 h post-transfection with miR-27b-3p, miR-615-3p, miR-191-5p, miR-127-3p, miR-99b-5p, or negative-transfection control (NTC); dexamethasone (Dexa) included as positive control. ( C , lower panel) Normalized C2C12 myotube diameter at the same time-points after transfection with hsa-let-7f-5p, miR-183-5p, miR-92a-3p, miR-30c-5p, miR-26a-5p, miR-10a-5p, NTC, or Dexa. ( D ) Oxygen consumption rate (OCR; top), resting-phenotype plot of basal OCR vs ECAR (middle), and metabolic-capacity plot of maximal OCR vs ECAR following FCCP (lower) for mature C2C12 myotubes 48 h post-transfection with miR-27b-3p, miR-615-3p, miR-191-5p, or NTC (Control). ( E ) Same panels for myotubes transfected with miR-127-3p, miR-99b-5p, miR-183-5p, or NTC. Sequential injections of oligomycin, FCCP, and rotenone/antimycin A were used to dissect mitochondrial respiration. Data are presented as mean ± SEM. ( C ) Measurements were taken from at least 5 random fields per well in N=3 wells; statistical analysis used 2-way ANOVA with Dunnett’s post-hoc correction: *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001.

    Journal: bioRxiv

    Article Title: Pancreatic cancer extracellular vesicles carry a time-of-day-regulated miRNA cargo that disrupts the skeletal muscle clock and bioenergetics

    doi: 10.64898/2026.05.03.722338

    Figure Lengend Snippet: (A) Top 35 miRNAs by mean expression in PANC-1-derived sEVs. Bar plot of mean log2 CPM across 9 time-points (4–36 h). Red bars: miRNAs selected from the top 35 to be tested in the BMAL1 :Luc reporter and atrophy assays; grey bars: remaining top-35 miRNAs. miRNAs are ranked in descending order of EV expression. ( B ) GO Biological Process enrichment of the experimentally validated targets (miRTarBase) of the 11 selected miRNAs. Terms are grouped into functional categories. Dot size represents the number of validated target genes associated with each term; dot color indicates Gene Ratio (proportion of input genes annotated to the term), from light pink (low) to dark red (high). Analysis performed with clusterProfiler. ( C , top panel) Normalized C2C12 myotube diameter at 0, 24, and 48 h post-transfection with miR-27b-3p, miR-615-3p, miR-191-5p, miR-127-3p, miR-99b-5p, or negative-transfection control (NTC); dexamethasone (Dexa) included as positive control. ( C , lower panel) Normalized C2C12 myotube diameter at the same time-points after transfection with hsa-let-7f-5p, miR-183-5p, miR-92a-3p, miR-30c-5p, miR-26a-5p, miR-10a-5p, NTC, or Dexa. ( D ) Oxygen consumption rate (OCR; top), resting-phenotype plot of basal OCR vs ECAR (middle), and metabolic-capacity plot of maximal OCR vs ECAR following FCCP (lower) for mature C2C12 myotubes 48 h post-transfection with miR-27b-3p, miR-615-3p, miR-191-5p, or NTC (Control). ( E ) Same panels for myotubes transfected with miR-127-3p, miR-99b-5p, miR-183-5p, or NTC. Sequential injections of oligomycin, FCCP, and rotenone/antimycin A were used to dissect mitochondrial respiration. Data are presented as mean ± SEM. ( C ) Measurements were taken from at least 5 random fields per well in N=3 wells; statistical analysis used 2-way ANOVA with Dunnett’s post-hoc correction: *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001.

    Article Snippet: The human pancreatic cancer cell line PANC-1, the murine fibroblast cell line NIH3T3, and the murine myoblast cell line C2C12 were purchased from American Type Culture Collection (ATCC, Manassas, VA).

    Techniques: Expressing, Derivative Assay, Functional Assay, Transfection, Control, Positive Control

    ( A ) Representative western blot for Calnexin, TSG101, CD9, and ApoA2 in PANC-1 whole-cell lysates (WCL) and isolated sEVs. ( B ) Negative-stain electron microscopy of PANC-1 sEVs resuspended in PBS, showing the characteristic cup-shaped morphology typical of EVs. Black arrows: representative sEVs displaying cup-shaped morphology. ( C ) Calcein acetoxymethyl-ester (Calcein-AM) staining of PANC-1 sEVs showing distinct fluorescent puncta indicative of intact vesicular membranes. (D) Representative fluorescent NTA (fNTA) of PANC-1 sEVs incubated with a fluorescently conjugated antibody against CD9. CMDR: CellMask Deep Red; Scatter: total particles; CD9-AF488: CD9-conjugated fluorescent-antibody-labeled particles. ( E ) Period, phase, and amplitude analyses of BMAL1:Luc oscillations in U2OS reporter cells treated with sEVs isolated from PANC-1 CM. ( F ) Period, phase, and amplitude analyses of Bmal1:Luc oscillations in NIH3T3 reporter cells treated with sEVs isolated from PANC-1 CM. For all bioluminescence experiments, at least three complete oscillations were included in the period estimation, excluding the first 24 h. Student’s t-test: ( E ) period p<0.01, amplitude p=0.0074; (F) period p<0.05, amplitude p<0.0001. ( G ) Myotube atrophy in response to PANC-1 sEVs over 72 h. Measurements were taken from at least 10 random fields in n=3 wells and normalized to control (without sEVs) for each time-point. Dexamethasone (Dexa) is included as a positive control for atrophy. ****p<0.0001; ***p<0.001.

    Journal: bioRxiv

    Article Title: Pancreatic cancer extracellular vesicles carry a time-of-day-regulated miRNA cargo that disrupts the skeletal muscle clock and bioenergetics

    doi: 10.64898/2026.05.03.722338

    Figure Lengend Snippet: ( A ) Representative western blot for Calnexin, TSG101, CD9, and ApoA2 in PANC-1 whole-cell lysates (WCL) and isolated sEVs. ( B ) Negative-stain electron microscopy of PANC-1 sEVs resuspended in PBS, showing the characteristic cup-shaped morphology typical of EVs. Black arrows: representative sEVs displaying cup-shaped morphology. ( C ) Calcein acetoxymethyl-ester (Calcein-AM) staining of PANC-1 sEVs showing distinct fluorescent puncta indicative of intact vesicular membranes. (D) Representative fluorescent NTA (fNTA) of PANC-1 sEVs incubated with a fluorescently conjugated antibody against CD9. CMDR: CellMask Deep Red; Scatter: total particles; CD9-AF488: CD9-conjugated fluorescent-antibody-labeled particles. ( E ) Period, phase, and amplitude analyses of BMAL1:Luc oscillations in U2OS reporter cells treated with sEVs isolated from PANC-1 CM. ( F ) Period, phase, and amplitude analyses of Bmal1:Luc oscillations in NIH3T3 reporter cells treated with sEVs isolated from PANC-1 CM. For all bioluminescence experiments, at least three complete oscillations were included in the period estimation, excluding the first 24 h. Student’s t-test: ( E ) period p<0.01, amplitude p=0.0074; (F) period p<0.05, amplitude p<0.0001. ( G ) Myotube atrophy in response to PANC-1 sEVs over 72 h. Measurements were taken from at least 10 random fields in n=3 wells and normalized to control (without sEVs) for each time-point. Dexamethasone (Dexa) is included as a positive control for atrophy. ****p<0.0001; ***p<0.001.

    Article Snippet: The human pancreatic cancer cell line PANC-1, the murine fibroblast cell line NIH3T3, and the murine myoblast cell line C2C12 were purchased from American Type Culture Collection (ATCC, Manassas, VA).

    Techniques: Western Blot, Isolation, Staining, Electron Microscopy, Incubation, Labeling, Control, Positive Control