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.

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.

Approximately 30% of triple-negative breast cancers (TNBCs) exhibit functional loss of the RB tumor suppressor, suggesting a target for precision intervention. Here, we use drug screens to identify agents specifically antagonized by the retinoblastoma tumor suppressor (RB) using CDK4/6 inhibitors. A number of candidate RB-synthetic lethal small molecules were identified, including anti-helmenthics, chemotherapeutic agents, and small-molecule inhibitors targeting DNA-damage checkpoints (e.g., CHK) and chromosome segregation (e.g., PLK1). Counter-screens using isogenic TNBC tumor cell lines and cell panels with varying endogenous RB statuses confirmed that therapeutic effects were robust and selective for RB loss of function. By analyzing TNBC clinical specimens, RB-deficient tumors were found to express high levels of CHK1 and PLK1. Loss of RB specifically resulted in loss of checkpoint functions governing DNA replication, yielding increased drug sensitivity. Xenograft models demonstrated RB-selective efficacy of CHK inhibitors. This study supports the possibility of selectively targeting RB loss in the treatment of TNBC.

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