Pancreatic ductal adenocarcinoma (PDA) has a dismal prognosis and insights into both disease etiology and targeted intervention are needed. A total of 109 micro-dissected PDA cases were subjected to whole-exome sequencing. Microdissection enriches tumour cellularity and enhances mutation calling. Here we show that environmental stress and alterations in DNA repair genes associate with distinct mutation spectra. Copy number alterations target multiple tumour suppressive/oncogenic loci; however, amplification of MYC is uniquely associated with poor outcome and adenosquamous subtype. We identify multiple novel mutated genes in PDA, with select genes harbouring prognostic significance. RBM10 mutations associate with longer survival in spite of histological features of aggressive disease. KRAS mutations are observed in >90% of cases, but codon Q61 alleles are selectively associated with improved survival. Oncogenic BRAF mutations are mutually exclusive with KRAS and define sensitivity to vemurafenib in PDA models. High-frequency alterations in Wnt signalling, chromatin remodelling, Hedgehog signalling, DNA repair and cell cycle processes are observed. Together, these data delineate new genetic diversity of PDA and provide insights into prognostic determinants and therapeutic targets.

Purpose Pancreatic ductal adenocarcinoma (PDAC) is associated with an immunosuppressive milieu that supports immune system evasion and disease progression. Here, we interrogated genetic, stromal, and immunological features of PDAC to delineate impact on prognosis and means to more effectively employ immunotherapy. Experimental design A cohort of 109 PDAC cases annotated for overall survival was utilized as a primary discovery cohort. Gene expression analysis defined immunological subtypes of PDAC that were confirmed in the Cancer Genome Atlas data set. Stromal and metabolic characteristics of PDAC cases were evaluated by histological analysis and immunostaining. Enumeration of lymphocytes, as well as staining for CD8, FOXP3, CD68, CD163, PDL1, and CTLA4 characterized immune infiltrate. Neo-antigens were determined by analysis of whole exome sequencing data. Random-forest clustering was employed to define multi-marker subtypes, with univariate and multivariate analyses interrogating prognostic significance. Results PDAC cases exhibited distinct stromal phenotypes that were associated with prognosis, glycolytic and hypoxic biomarkers and immune infiltrate composition. Immune infiltrate was diverse among PDAC cases and enrichment for M2 macrophages and select immune checkpoints regulators were specifically associated with survival. Composite analysis with neo-antigen burden, immunological, and stromal features defined novel subtypes of PDAC that could have bearing on sensitivity to immunological therapy approaches. Additionally, a subtype with low levels of neo-antigens and minimal lymphocyte infiltrate was associated with improved overall survival. Conclusions The mutational burden of PDAC is associated with distinct immunosuppressive mechanisms that are conditioned by the tumor stromal environment. The defined subtypes have significance for utilizing immunotherapy in the treatment of PDAC.

Due to loss of p16ink4a in pancreatic ductal adenocarcinoma (PDA), pharmacological suppression of CDK4/6 could represent a potent target for treatment. In PDA models CDK4/6 inhibition had variable effect on cell cycle, but yielded accumulation of ATP and mitochondria. Pharmacological CDK4/6 inhibitors induce cyclin D1 protein levels; however, RB activation was required and sufficient for mitochondrial accumulation. CDK4/6 inhibition stimulated glycolytic and oxidative metabolism and was associated with an increase in mTORC1 activity. MTOR and MEK inhibitors potently cooperate with CDK4/6 inhibition in eliciting cell cycle exit. However, MTOR inhibition fully suppressed metabolism and yielded apoptosis and suppression of tumor growth. The metabolic state mediated by CDK4/6 inhibition increases mitochondrial number and ROS. Concordantly, the suppression of ROS scavenging or BCL2-antagonists cooperated with CDK4/6 inhibition. Together, these data define the impact of therapeutics on PDA metabolism and provide strategies for converting cytostatic response to tumor cell killing.

ObjectivePancreatic ductal adenocarcinoma (PDAC) is a therapy recalcitrant disease with the worst survival rate of common solid tumours. Preclinical models that accurately reflect the genetic and biological diversity of PDAC will be important for delineating features of tumour biology and therapeutic vulnerabilities.Design27 primary PDAC tumours were employed for genetic analysis and development of tumour models. Tumour tissue was used for derivation of xenografts and cell lines. Exome sequencing was performed on the originating tumour and developed models. RNA sequencing, histological and functional analyses were employed to determine the relationship of the patient-derived models to clinical presentation of PDAC.ResultsThe cohort employed captured the genetic diversity of PDAC. From most cases, both cell lines and xenograft models were developed. Exome sequencing confirmed preservation of the primary tumour mutations in developed cell lines, which remained stable with extended passaging. The level of genetic conservation in the cell lines was comparable to that observed with patient-derived xenograft (PDX) models. Unlike historically established PDAC cancer cell lines, patient-derived models recapitulated the histological architecture of the primary tumour and exhibited metastatic spread similar to that observed clinically. Detailed genetic analyses of tumours and derived models revealed features of ex vivo evolution and the clonal architecture of PDAC. Functional analysis was used to elucidate therapeutic vulnerabilities of relevance to treatment of PDAC.ConclusionsThese data illustrate that with the appropriate methods it is possible to develop cell lines that maintain genetic features of PDAC. Such models serve as important substrates for analysing the significance of genetic variants and create a unique biorepository of annotated cell lines and xenografts that were established simultaneously from same primary tumour. These models can be used to infer genetic and empirically determined therapeutic sensitivities that would be germane to the patient.

Pancreatic ductal adenocarcinoma (PDAC) harbors the worst prognosis of any common solid tumor, and multiple failed clinical trials indicate therapeutic recalcitrance. Here we use exome sequencing of patient tumors and find multiple conserved genetic alterations. However, the majority of tumors exhibit no clearly defined therapeutic target. High-throughput drug screens using patient-derived cell lines found rare examples of sensitivity to monotherapy, with most requiring combination therapy. Using PDX models, we confirmed the effectiveness and selectivity of the identified treatment responses. Out of greater than 500 single and combination drug regimens tested, no single treatment was effective for the majority of PDAC tumors, and each case had unique sensitivity profiles that could not be predicted using genetic analyses. These data indicate a shortcoming of reliance on genetic analysis to predict efficacy of currently available agents against PDAC, and that sensitivity profiling of patient-derived models could inform personalized therapy design for PDAC.