The binding of T cell immune checkpoint proteins programmed death 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) to their ligands allows immune evasion by tumours. The development of therapeutic antibodies, termed checkpoint inhibitors, that bind these molecules or their ligands, has provided a means to release this brake on the host anti-tumour immune response. However, these drugs are costly, are associated with potentially severe side effects, and only benefit a small subset of patients. It is therefore important to identify biomarkers that discriminate between responders and non-responders. This review discusses the determinants for a successful response to antibodies that bind PD-1 or its ligand PD-L1, dividing them into markers found in the tumour biopsy and those in non-tumour samples. It provides an update on the established predictive biomarkers (tumour PD-L1 expression, tumour mismatch repair deficiency and tumour mutational burden) and assesses the evidence for new potential biomarkers.

Novel cell-free DNA whole-genome methylome sequencing method enables accurate cancer detection.

Pancreatic ductal adenocarcinoma has a dismal prognosis. A comprehensive analysis of single-cell multi-omic data from matched tumour-infiltrated CD45+ cells and peripheral blood in 12 patients, and two published datasets, reveals a complex immune infiltrate. Patients have either a myeloid-enriched or adaptive-enriched tumour microenvironment. Adaptive immune cell-enriched is intrinsically linked with highly distinct B and T cell clonal selection, diversification, and differentiation. Using TCR data, we see the largest clonal expansions in CD8 effector memory, senescent cells, and highly activated regulatory T cells which are induced within the tumour from naïve cells. We identify pathways that potentially lead to a suppressive microenvironment, including investigational targets TIGIT/PVR and SIRPA/CD47. Analysis of patients from the APACT clinical trial shows that myeloid enrichment had a shorter overall survival compared to those with adaptive cell enrichment. Strategies for rationale therapeutic development in this disease include boosting of B cell responses, targeting immunosuppressive macrophages, and specific Treg cell depletion approaches.

Pancreatic cancer has one of the worst prognoses of any human malignancy and leukocyte infiltration is a major prognostic marker of the disease. As current immunotherapies confer negligible survival benefits, there is a need to better characterise leukocytes in pancreatic cancer to identify better therapeutic strategies. In this study, we analysed 32 human pancreatic cancer patients from two independent cohorts. A multi-parameter mass-cytometry analysis was performed on 32,000 T-cells from eight patients. Single-cell RNA sequencing dataset analysis was performed on a cohort of 24 patients. Multiplex immunohistochemistry imaging and spatial analysis were performed to map immune infiltration into the tumour microenvironment. Regulatory T-cell populations demonstrated highly immunosuppressive states with high TIGIT, ICOS and CD39 expression. CD8⁺ T-cells were found to be either in senescence or an exhausted state. The exhausted CD8 T-cells had low PD-1 expression but high TIGIT and CD39 expression. These findings were corroborated in an independent pancreatic cancer single-cell RNA dataset. These data suggest that T-cells are major players in the suppressive microenvironment of pancreatic cancer. Our work identifies multiple novel therapeutic targets that should form the basis for rational design of a new generation of clinical trials in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of the pancreas and has one of the highest mortality rates of any cancer type with a 5‐year survival rate of <5%. Recent studies of PDAC have provided several transcriptomic classifications based on separate analyses of individual patient cohorts. There is a need to provide a unified transcriptomic PDAC classification driven by therapeutically relevant biologic rationale to inform future treatment strategies. Here, we used an integrative meta‐analysis of 353 patients from four different studies to derive a PDAC classification based on immunologic parameters. This consensus clustering approach indicated transcriptomic signatures based on immune infiltrate classified as adaptive, innate and immune‐exclusion subtypes. This reveals the existence of microenvironmental interpatient heterogeneity within PDAC and could serve to drive novel therapeutic strategies in PDAC including immune modulation approaches to treating this disease.

KRAS is the most frequently mutated gene in pancreatic ductal adenocarcinoma (PDAC), but the mechanisms underlying the transcriptional response to oncogenic KRAS are still not fully understood. We aimed to uncover transcription factors that regulate the transcriptional response of oncogenic KRAS in pancreatic cancer and to understand their clinical relevance. We applied a well-established network biology approach (master regulator analysis) to combine a transcriptional signature for oncogenic KRAS derived from a murine isogenic cell line with a coexpression network derived by integrating 560 human pancreatic cancer cases across seven studies. The datasets included the ICGC cohort (n = 242), the TCGA cohort (n = 178), and five smaller studies (n = 17, 25, 26, 36, and 36). 55 transcription factors were coexpressed with a significant number of genes in the transcriptional signature (gene set enrichment analysis [GSEA] p < 0.01). Community detection in the coexpression network identified 27 of the 55 transcription factors contributing to three major biological processes: Notch pathway, down-regulated Hedgehog/Wnt pathway, and cell cycle. The activities of these processes define three distinct subtypes of PDAC, which demonstrate differences in survival and mutational load as well as stromal and immune cell composition. The Hedgehog subgroup showed worst survival (hazard ratio 1.73, 95% CI 1.1 to 2.72, coxPH test p = 0.018) and the Notch subgroup the best (hazard ratio 0.62, 95% CI 0.42 to 0.93, coxPH test p = 0.019). The cell cycle subtype showed highest mutational burden (ANOVA p < 0.01) and the smallest amount of stromal admixture (ANOVA p < 2.2e–16). This study is limited by the information provided in published datasets, not all of which provide mutational profiles, survival data, or the specifics of treatment history. Our results characterize the regulatory mechanisms underlying the transcriptional response to oncogenic KRAS and provide a framework to develop strategies for specific subtypes of this disease using current therapeutics and by identifying targets for new groups.