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Abstract Immune checkpoint inhibitors (ICI) are highly effective in specific cancers where canonical markers of antitumor immunity are used for patient selection. Improved predictors of T cell-inflammation are needed to identify ICI-responsive tumor subsets in additional cancer types. We investigated associations of a 4-chemokine expression signature (c-Score: CCL4, CCL5, CXCL9, CXCL10) with metrics of antitumor immunity across tumor types. Across cancer entities from The Cancer Genome Atlas, subgroups of tumors displayed high expression of the c-Score (c-Scorehi) with increased expression of immune checkpoint (IC) genes and transcriptional hallmarks of the cancer-immunity cycle. There was an incomplete association of the c-Score with high tumor mutation burden (TMB), with only 15% of c-Scorehi tumors displaying ≥10 mutations per megabase. In a heterogeneous pan-cancer cohort of 82 patients, with advanced and previously treated solid cancers, c-Scorehi tumors had a longer median time to progression (103 versus 72 days, P = 0.012) and overall survival (382 versus 196 days, P = 0.038) following ICI therapy initiation, compared to patients with low c-Score expression. We also found c-Score stratification to outperform TMB assignment for overall survival prediction (HR = 0.42 [0.22–0.79], P = 0.008 versus HR = 0.60 [0.29-1.27], P = 0.18, respectively). Assessment of the c-Score using the TIDE and PredictIO databases, which include ICI treatment outcomes from 10 tumor types, provided further support for the c-Score as a predictive ICI therapeutic biomarker. In summary, the c-Score identifies patients with hallmarks of T cell-inflammation and potential response to ICI treatment across cancer types, which is missed by TMB assignment.

Targeting the RAS pathway remains the holy grail of precision oncology. In the case of pancreatic ductal adenocarcinomas (PDAC), 90–92% harbor mutations in the oncogene KRAS, triggering canonical MAPK signaling. The smooth structure of the altered KRAS protein without a binding pocket and its affinity for GTP have, in the past, hampered drug development. The emergence of KRASG12C covalent inhibitors has provided renewed enthusiasm for targeting KRAS. The numerous pathways implicated in RAS activation do, however, lead to the development of early resistance. In addition, the dense stromal niche and immunosuppressive microenvironment dictated by oncogenic KRAS can influence treatment responses, highlighting the need for a combination-based approach. Given that mutations in KRAS occur early in PDAC tumorigenesis, an understanding of its pleiotropic effects is key to progress in this disease. Herein, we review current perspectives on targeting KRAS with a focus on PDAC.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by a diverse tumor microenvironment. The heterogeneous cellular composition of PDAC makes it challenging to study molecular features of tumor cells using extracts from bulk tumor. The metabolic features in tumor cells from clinical samples are poorly understood, and their impact on clinical outcomes are unknown. Our objective was to identify the metabolic features in the tumor compartment that are most clinically impactful.Methods: A computational deconvolution approach using the DeMixT algorithm was applied to bulk RNASeq data from The Cancer Genome Atlas to determine the proportion of each gene’s expression that was attributable to the tumor compartment. A machine learning algorithm designed to identify features most closely associated with survival outcomes was used to identify the most clinically impactful metabolic genes.Results: Two metabolic subtypes (M1 and M2) were identified, based on the pattern of expression of the 26 most important metabolic genes. The M2 phenotype had a significantly worse survival, which was replicated in three external PDAC cohorts. This PDAC subtype was characterized by net glycogen catabolism, accelerated glycolysis, and increased proliferation and cellular migration. Single cell data demonstrated substantial intercellular heterogeneity in the metabolic features that typified this aggressive phenotype.Conclusion: By focusing on features within the tumor compartment, two novel and clinically impactful metabolic subtypes of PDAC were identified. Our study emphasizes the challenges of defining tumor phenotypes in the face of the significant intratumoral heterogeneity that typifies PDAC. Further studies are required to understand the microenvironmental factors that drive the appearance of the metabolic features characteristic of the aggressive M2 PDAC phenotype.

KRAS wildtype metastatic pancreatic ductal adenocarcinoma (mPDAC) could represent a distinct molecular entity from other PDACs. Here, the authors analyse KRAS wildtype mPDAC tumours using genomics and transcriptomics and find molecular similarities with cholangiocarcinomas.

Abstract Combination chemotherapy, either modified FOLFIRINOX (mFFX) or gemcitabine–nabpaclitaxel, are used in the treatment of most patients with advanced pancreatic ductal adenocarcinoma (PDAC), yet robust biomarkers of outcome are currently lacking to guide regimen selection. Here, we tested GATA6 immunohistochemistry (IHC) as a putative biomarker in advanced PDAC. GATA6 is a transcription factor in normal pancreas development. Two pathologists, blinded to clinical and molecular data, independently assessed GATA6 IHC in biopsy specimens of 130 patients with advanced PDAC, in 2 distinct phases (without and with computer assistance using the open source software QuPath). Low GATA6 IHC expression was associated with shorter overall survival [median OS 6.2 months for patients with GATA6 low tumors vs. 11.5 months for patients with GATA6 high tumors, HR 1.66 (95% CI 1.15–2.40), P = 0.007]. Progression appears to be higher in GATA6-low tumors compared to GATA6-high tumors in patients treated with mFFX (P = 0.024) but not in patients treated with gemcitabine regimens. GATA6 IHC expression was significantly associated with molecular subtypes (P = 0.0003). Digital assistance markedly improved interrater concordance (Cohen’s kappa scores of 0.32 vs. 0.95). Our results provide strong evidence that GATA6 IHC can be used as a single biomarker in the clinic to predict clinical outcome in advanced PDAC, warranting further investigation in prospective clinical trials. These results provide the basis for an improved classification of PDAC and future biomarker design using digital pathology workflow.

The immune contexture of pancreatic ductal adenocarcinoma (PDAC) is generally immunosuppressive. A role for immune checkpoint inhibitors (ICIs) in PDAC has only been demonstrated for the rare and hypermutated mismatch repair (MMR) deficient (MMR-d) subtype. Homologous recombination repair (HR) deficient (HR-d) PDAC is more prevalent and may encompass up to 20% of PDAC. Its genomic instability may promote a T-cell mediated anti-tumor response with therapeutic sensitivity to ICIs. To investigate the immunogenicity of HR-d PDAC, we used multiplex immunohistochemistry (IHC) to compare the density and spatial distribution of CD8+ cytotoxic T-cells, FOXP3+ regulatory T-cells (Tregs), and CD68+ tumor-associated macrophages (TAMs) in HR-d versus HR/MMR-intact PDAC. We also evaluated the IHC positivity of programmed death-ligand 1 (PD-L1) across the subgroups. 192 tumors were evaluated and classified as HR/MMR-intact (n=166), HR-d (n=25) or MMR-d (n=1) based on germline testing and tumor molecular hallmarks. Intra-tumoral CD8+ T-cell infiltration was higher in HR-d versus HR/MMR-intact PDAC (p=1, whereas none of the HR/MMR-intact cases met this threshold (p

Abstract Background As the treatment landscape in patients with non‐small cell lung cancer (NSCLC) harboring mutations in the epidermal growth factor receptor (EGFRm) continues to evolve, real‐world health utility scores (HUS) become increasingly important for economic analyses. Methods In an observational cohort study, questionnaires were completed in EGFRm NSCLC outpatients, to include demographics, EQ‐5D‐based HUS and patient‐reported toxicity and symptoms. Clinical and radiologic characteristics together with outcomes were extracted from chart review. The impact of health states, treatment type, toxicities, and clinical variables on HUS were evaluated. Results Between 2014 and 2018, a total of 260 patients completed 994 encounters. Across treatment groups, patients with disease progression had lower HUS compared to controlled disease (0.771 vs 0.803; P = .01). Patients predominantly received gefitinib as the first‐line EGFR tyrosine kinase inhibitor (TKI) (n = 157, mean‐HUS = 0.798), whereas osimertinib (n = 62, mean‐HUS = 0.806) and chemotherapy (n = 38, mean‐HUS = 0.721) were more likely used in subsequent treatment lines. In longitudinal analysis, TKIs retained high HUS (>0.78) compared to chemotherapy (HUS

Sensitizing mutations in the epidermal growth factor receptor (EGFR) predict response to EGFR tyrosine kinase inhibitors (TKIs) and both first- and second-generation TKIs are available as first-line treatment options in patients with advanced EGFR-mutant non-small cell lung cancer. Eventual resistance develops with multiple mechanisms identifiable both upon repeat biopsy and in plasma circulating tumor DNA. The T790M gatekeeper mutation is responsible for almost 60% of cases. A number of third-generation TKIs are in clinical development, and osimertinib has been approved by the US Food and Drug Administration for the treatment of patients with EGFR T790M mutant lung cancer after failure of initial EGFR kinase therapy. Resistance mechanisms are being identified to these novel agents, and the treatment landscape of EGFR-mutant lung cancer continues to evolve. The sequence of EGFR TKIs may change in the future and combination therapies targeting resistance appear highly promising.