Does biology determine survival in pancreatic cancer?

Overcoming the Fibrotic Fortress in Pancreatic Ductal Adenocarcinoma: Challenges and Opportunities

An overabundance of desmoplasia in the tumour microenvironment (TME) is one of the defining features that influences pancreatic ductal adenocarcinoma (PDAC) development, progression, metastasis, and treatment resistance. Desmoplasia is characterised by the recruitment and activation of fibroblasts, heightened extracellular matrix deposition (ECM) and reduced blood supply, as well as increased inflammation through an influx of inflammatory cells and cytokines, creating an intrinsically immunosuppressive TME with low immunogenic potential. Herein, we review the development of PDAC, the drivers that initiate and/or sustain the progression of the disease and the complex and interwoven nature of the cellular and acellular components that come together to make PDAC one of the most aggressive and difficult to treat cancers. We review the challenges in delivering drugs into the fortress of PDAC tumours in concentrations that are therapeutic due to the presence of a highly fibrotic and immunosuppressive TME. Taken together, we present further support for continued/renewed efforts focusing on aspects of the extremely dense and complex TME of PDAC to improve the efficacy of therapy for better patient outcomes.

A cancer-associated fibroblast gene signature predicts prognosis and therapy response in patients with pancreatic cancer

Pancreatic cancer is a lethal malignancy with a 5-year survival rate of about 10% in the United States, and it is becoming an increasingly prominent cause of cancer death. Among pancreatic cancer patients, pancreatic ductal adenocarcinoma (PDAC) accounts for more than 90% of all cases and has a very poor prognosis with an average survival of only 1 year in about 18% of all tumor stages. In the past years, there has been an increasing interest in cancer-associated fibroblasts (CAFs) and their roles in PDAC. Recent data reveals that CAFs in PDAC are heterogeneous and various CAF subtypes have been demonstrated to promote tumor development while others hinder cancer proliferation. Furthermore, CAFs and other stromal populations can be potentially used as novel prognostic markers in cancer. In the present study, in order to evaluate the prognostic value of CAFs in PDAC, CAF infiltration rate was evaluated in 4 PDAC datasets of TCGA, GEO, and ArrayExpress databases and differentially expressed genes (DEGs) between CAF-high and CAF-low patients were identified. Subsequently, a CAF-based gene expression signature was developed and studied for its association with overall survival (OS). Additionally, functional enrichment analysis, somatic alteration analysis, and prognostic risk model construction was conducted on the identified DEGs. Finally, oncoPredict algorithm was implemented to assess drug sensitivity prediction between high- and low-risk cohorts. Our results revealed that CAF risk-high patients have a worse survival rate and increased CAF infiltration is a poor prognostic indicator in pancreatic cancer. Functional enrichment analysis also revealed that "extracellular matrix organization" and "vasculature development" were the top enriched pathways among the identified DEGs. We also developed a panel of 12 genes, which in additional to its prognostic value, could predict higher chemotherapy resistance rate. This CAF-based panel can be potentially utilized alone or in conjunction with other clinical parameters to make early predictions and prognosticate responsiveness to treatment in PDAC patients. Indeed, it is necessary to conduct extensive prospective investigations to confirm the clinical utility of these findings.

Down-regulation of metabolic pathways could offset the poor prognosis conferred by co-existent diabetes mellitus in pancreatic (head) adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) patients with diabetes mellitus (DM) have poor overall survival. Underlying mechanisms have not been fully clarified. This presents an opportunity for precision-oncology for which we systematically analysed publicly-available PDAC transcriptome data.

METHODS

PDAC TCGA RNASeq data were used. Analyses were restricted to only 'high purity' and 'head' as anatomical site. Patients were characterised by: (1) Gene expression classification, and (2) Weighted gene correlation network analysis (WGCNA) to identify co-expression patterns of genes. Newly identified gene signature subclasses of pancreatic head PDAC were associated with clinical and functional characteristics of patients.

RESULTS

Consensus clustering identified two patient subclasses within PDAC involving pancreatic head. WGCNA identified 11 distinct networks of gene expression patterns across two sub-classes. Class 1 patients demonstrated a significant upregulation of Module 5 and Module 6 gene expression compared to Class 2. Class 1 predominantly expressed the acinar, ductal and islet cell gene signatures. There were significantly less patients with DM in Class 1 subclass compared to Class 2 (p < 0.037). Patients with DM had significant downregulation of pathways involved in cellular metabolism, hormone secretion and paucity of islet cell markers with no reduced survival compared with non-diabetics.

CONCLUSIONS

A significant proportion of patients with PDAC of pancreatic head and DM exhibit downregulation of pathways involved in cellular metabolism, hormone secretion and signalling accompanied by a paucity of islet expression. Investigating the relationship between DM and gene expression profiles in patients with PDAC presents opportunities to improve overall survival in diabetics with PDAC.