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Purpose: To determine the impact of basal-like and classical subtypes in advanced pancreatic ductal adenocarcinoma (PDAC) and to explore GATA6 expression as a surrogate biomarker., Experimental Design: Within the COMPASS trial, patients proceeding to chemotherapy for advanced PDAC undergo tumor biopsy for RNA-sequencing (RNA-seq). Overall response rate (ORR) and overall survival (OS) were stratified by subtypes and according to chemotherapy received. Correlation of GATA6 with the subtypes using gene expression profiling, in situ hybridization (ISH) was explored., Results: Between December 2015 and May 2019, 195 patients (95%) had enough tissue for RNA-seq; 39 (20%) were classified as basal-like and 156 (80%) as classical. RECIST response data were available for 157 patients; 29 basal-like and 128 classical where the ORR was 10% versus 33%, respectively ( P = 0.02). In patients with basal-like tumors treated with modified FOLFIRINOX ( n = 22), the progression rate was 60% compared with 15% in classical PDAC ( P = 0.0002). Median OS in the intention-to-treat population ( n = 195) was 9.3 months for classical versus 5.9 months for basal-like PDAC (HR, 0.47; 95% confidence interval, 0.32-0.69; P = 0.0001). GATA6 expression by RNA-seq highly correlated with the classifier ( P < 0.001) and ISH predicted the subtypes with sensitivity of 89% and specificity of 83%. In a multivariate analysis, GATA6 expression was prognostic ( P = 0.02). In exploratory analyses, basal-like tumors, could be identified by keratin 5, were more hypoxic and enriched for a T-cell-inflamed gene expression signature., Conclusions: The basal-like subtype is chemoresistant and can be distinguished from classical PDAC by GATA6 expression. See related commentary by Collisson, p. 4715 ., (©2020 American Association for Cancer Research.)

Pancreatic adenocarcinoma presents as a spectrum of a highly aggressive disease in patients. The basis of this disease heterogeneity has proved difficult to resolve due to poor tumor cellularity and extensive genomic instability. To address this, a dataset of whole genomes and transcriptomes was generated from purified epithelium of primary and metastatic tumors. Transcriptome analysis demonstrated that molecular subtypes are a product of a gene expression continuum driven by a mixture of intratumoral subpopulations, which was confirmed by single-cell analysis. Integrated whole-genome analysis uncovered that molecular subtypes are linked to specific copy number aberrations in genes such as mutant KRAS and GATA6. By mapping tumor genetic histories, tetraploidization emerged as a key mutational process behind these events. Taken together, these data support the premise that the constellation of genomic aberrations in the tumor gives rise to the molecular subtype, and that disease heterogeneity is due to ongoing genomic instability during progression.

Purpose: To perform real-time whole genome sequencing (WGS) and RNA sequencing (RNASeq) of advanced pancreatic ductal adenocarcinoma (PDAC) to identify predictive mutational and transcriptional features for better treatment selection. Experimental Design: Patients with advanced PDAC were prospectively recruited prior to first-line combination chemotherapy. Fresh tumor tissue was acquired by image-guided percutaneous core biopsy for WGS and RNASeq. Laser capture microdissection was performed for all cases. Primary endpoint was feasibility to report WGS results prior to first disease assessment CT scan at 8 weeks. The main secondary endpoint was discovery of patient subsets with predictive mutational and transcriptional signatures. Results: Sixty-three patients underwent a tumor biopsy between December 2015 and June 2017. WGS and RNASeq were successful in 62 (98%) and 60 (95%), respectively. Genomic results were reported at a median of 35 days (range, 19-52 days) from biopsy, meeting the primary feasibility endpoint. Objective responses to first-line chemotherapy were significantly better in patients with the classical PDAC RNA subtype compared with those with the basal-like subtype ( P = 0.004). The best progression-free survival was observed in those with classical subtype treated with m-FOLFIRINOX. GATA6 expression in tumor measured by RNA in situ hybridization was found to be a robust surrogate biomarker for differentiating classical and basal-like PDAC subtypes. Potentially actionable genetic alterations were found in 30% of patients. Conclusions: Prospective genomic profiling of advanced PDAC is feasible, and our early data indicate that chemotherapy response differs among patients with different genomic/transcriptomic subtypes. Clin Cancer Res; 24(6); 1344-54. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Unlabelled: Genomic analyses are yielding a host of new information on the multiple genetic abnormalities associated with specific types of cancer. A comprehensive description of cancer-associated genetic abnormalities can improve our ability to classify tumors into clinically relevant subgroups and, on occasion, identify mutant genes that drive the cancer phenotype ("drivers"). More often, though, the functional significance of cancer-associated mutations is difficult to discern. Genome-wide pooled short hairpin RNA (shRNA) screens enable global identification of the genes essential for cancer cell survival and proliferation, providing a "functional genomic" map of human cancer to complement genomic studies. Using a lentiviral shRNA library targeting ~16,000 genes and a newly developed, dynamic scoring approach, we identified essential gene profiles in 72 breast, pancreatic, and ovarian cancer cell lines. Integrating our results with current and future genomic data should facilitate the systematic identification of drivers, unanticipated synthetic lethal relationships, and functional vulnerabilities of these tumor types., Significance: This study presents a resource of genome-scale, pooled shRNA screens for 72 breast, pancreatic, and ovarian cancer cell lines that will serve as a functional complement to genomics data, facilitate construction of essential gene profiles, help uncover synthetic lethal relationships, and identify uncharacterized genetic vulnerabilities in these tumor types., Significance: This study presents a resource of genome-scale, pooled shRNA screens for 72 breast, pancreatic, and ovarian cancer cell lines that will serve as a functional complement to genomics data, facilitate construction of essential gene profiles, help uncover synthetic lethal relationships, and identify uncharacterized genetic vulnerabilities in these tumor types., (©2011 AACR.)