Identification of laminin γ2 as a prognostic and predictive biomarker for determining response to gemcitabine-based therapy in pancreatic ductal adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33607476", "kind": "science-record", "revision": 5, "content_hash": "sha256:eced13fd3d4a9a0ab1b39671fa4ec9443b9a719fd6d2cc1bb5f63448fb6c2570", "created_at": "2026-11-01T17:34:45Z", "updated_at": "2026-11-01T22:46:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of laminin γ2 as a prognostic and predictive biomarker for determining response to gemcitabine-based therapy in pancreatic ductal adenocarcinoma.", "doi": "10.1016/j.ejca.2020.12.031", "pmid": "33607476", "authors": ["Yasuyuki Okada", "Satoshi Nishiwada", "Kensuke Yamamura", "Masayuki Sho", "Hideo Baba", "Tetsuji Takayama", "Ajay Goel"], "journal": "European journal of cancer (Oxford, England : 1990)", "year": 2021, "abstract": "BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. While the extracellular matrix component plays an integral role in PDAC pathogenesis and mediating chemoresistance, its role in predicting response to chemotherapy in patients with PDAC remains unclear.\nMETHODS: We performed a systematic biomarker discovery by analysing genome-wide transcriptomic profiling data from 423 patients (GSE71729, GSE21501 and The Cancer Genome Atlas [TCGA]) for predicting overall survival (OS). This was subsequently validated in two independent clinical cohorts of 270 patients with PDAC (training cohort, n = 121, and validation cohort, n = 149). In addition, we investigated endoscopic ultrasound-fine needle aspiration biopsy specimens from 51 patients with PDAC with an unresectable cancer for predicting therapeutic response to gemcitabine-based therapy.\nRESULTS: After rigorous bioinformatic analysis, we identified laminin γ2 (LAMC2) to be a significant prognostic factor in all three PDAC data sets (GSE71729: hazard ratio [HR] = 2.04, P = 0.002; GSE21501: HR = 2.17, P = 0.031; TCGA: HR = 2.57, P < 0.001). High LAMC2 expression in patients with PDAC was associated with a significantly poor OS and relapse-free survival in both the training (P < 0.001, P < 0.001) and validation cohorts (P = 0.001, P = 0.026). More importantly, LAMC2 expression robustly identified patients with PDAC and unresectable disease and those who responded to gemcitabine-based therapy (area under the curve = 0.79; 95% confidence interval [CI], 0.65-0.89). The univariate logistic regression analysis revealed that high LAMC2 expression was the only factor that predicted poor response to gemcitabine in patients with PDAC (odds ratio = 4.90; 95% CI, 1.45-16.6; P = 0.011).\nCONCLUSION: We conclude that LAMC2 is a novel prognostic and predictive biomarker for gemcitabine-based therapy in both the adjuvant and palliative setting; which could have significant impact on precision and individualised treatment of patients with PDAC.", "claims": [{"id": "claim-method", "statement": "For time-to-event analyses, survival estimates were calculated using the Kaplan–Meier analysis, and the survival differences between groups were compared using the log-rank test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33607476", "locator": "sections[5] \"Statistical analysis\" paragraph 2", "quote": "For time-to-event analyses, survival estimates were calculated using the Kaplan–Meier analysis, and the survival differences between groups were compared using the log-rank test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "During the biomarker discovery phase, GSE21501 (n=102) and GSE71729 (n=145) datasets were downloaded from the GEO database directly (https://www.ncbi.nlm.nih.gov, accessed on July 17, 2019).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33607476", "locator": "sections[3] \"Study design and patient cohorts\" paragraph 2", "quote": "During the biomarker discovery phase, GSE21501 (n=102) and GSE71729 (n=145) datasets were downloaded from the GEO database directly (https://www.ncbi.nlm.nih.gov, accessed on July 17, 2019)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Following rigorous bioinformatic analysis, we identified LAMC2 to be a significant prognostic factor in all three PDAC datasets (GSE71729, HR=2.04, P=0.002; GSE21501, HR=2.17, P=0.031; TCGA, HR=2.57, P<0.001).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:33607476", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Following rigorous bioinformatic analysis, we identified LAMC2 to be a significant prognostic factor in all three PDAC datasets (GSE71729, HR=2.04, P=0.002; GSE21501, HR=2.17, P=0.031; TCGA, HR=2.57, P<0.001)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Following rigorous bioinformatic analysis, we identified LAMC2 to be a significant prognostic factor in all three PDAC datasets (GSE71729, HR=2.04, P=0.002; GSE21501, HR=2.17, P=0.031; TCGA, HR=2.57, P<0.001).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33607476"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE21501"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE21501"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33607476", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.ejca.2020.12.031", "sha256": 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