Serum levels of iCAF-derived osteoglycin predict favorable outcome in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by abundant stroma, the main cellular constituents of which are cancer-associated fibroblasts (CAFs). Stroma-targeting agents have been proposed to improve the poor outcome of current treatments. However, clinical trials using these agents showed disappointing results. Heterogeneity in the PDAC CAF population was recently delineated demonstrating that both tumor-promoting and tumor-suppressive activities co-exist in the stroma. Here, we aimed to identify biomarkers for the CAF population that contribute to a favorable outcome. RNA-sequencing reads from patient-derived xenografts (PDXs) were mapped to the human and mouse genome to allocate the expression of genes to the tumor or stroma. Survival meta-analysis for stromal genes was performed and applied to human protein atlas data to identify circulating biomarkers. The candidate protein was perturbed in co-cultures and assessed in existing and novel single-cell gene expression analysis from control, pancreatitis, pancreatitis-recovered and PDAC mouse models. Serum levels of the candidate biomarker were measured in two independent cohorts totaling 148 PDAC patients and related them to overall survival. Osteoglycin (OGN) was identified as a candidate serum prognostic marker. Single-cell analysis indicated that Ogn is derived from a subgroup of inflammatory CAFs. Ogn-expressing fibroblasts are distinct from resident healthy pancreatic stellate cells and arise during pancreatitis. Serum OGN levels were prognostic for favorable overall survival in two independent PDAC cohorts (HR = 0.47, P = .042 and HR = 0.53, P = .006). Altogether, we conclude that high circulating OGN levels inform on a previously unrecognized subgroup of CAFs and predict favorable outcomes in resectable PDAC.

Transcriptome-based classification to predict FOLFIRINOX response in a real-world metastatic pancreatic cancer cohort.

Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at metastatic stage and typically treated with fluorouracil, leucovorin, irinotecan and oxaliplatin (FOLFIRINOX). Few patients benefit from this treatment. Molecular subtypes are prognostic in particularly resectable PDAC and might predict treatment response. This study aims to correlate molecular subtypes in metastatic PDAC with FOLFIRINOX responses using real-world data, providing assistance in counselling patients. We collected 131 RNA-sequenced metastatic biopsies and applied a network-based meta-analysis using published PDAC classifiers. Subsequent survival analysis was performed using the most suitable classifier. For validation, we developed an immunohistochemistry (IHC) classifier using GATA6 and keratin-17 (KRT17), and applied it to 86 formalin-fixed paraffin-embedded samples of advanced PDAC. Lastly, GATA6 knockdown models were generated in PDAC organoids and cell lines. We showed that the PurIST classifier was the most suitable classifier. With this classifier, classical tumors had longer PFS and OS than basal-like tumors (PFS: 216 vs. 78 days, p = 0.0002; OS: 251 vs. 195 days, p = 0.049). The validation cohort showed a similar trend. Importantly, IHC GATA6low patients had significantly shorter survival with FOLFIRINOX (323 vs. 746 days, p = 0.006), but no difference in non-treated patients (61 vs. 54 days, p = 0.925). This suggests that GATA6 H-score predicts therapy response. GATA6 knockdown models did not lead to increased FOLFIRINOX responsiveness. These data suggest a predictive role for subtyping (transcriptomic and GATA6 IHC), though no direct causal relationship was found between GATA6 expression and chemoresistance. GATA6 immunohistochemistry should be seamlessly added to current diagnostics and integrated into upcoming clinical trials.

The pluripotency factor NANOG contributes to mesenchymal plasticity and is predictive for outcome in esophageal adenocarcinoma.

BACKGROUND: Despite the advent of neoadjuvant chemoradiotherapy (CRT), overall survival rates of esophageal adenocarcinoma (EAC) remain low. A readily induced mesenchymal transition of EAC cells contributes to resistance to CRT. METHODS: In this study, we aimed to chart the heterogeneity in cell state transition after CRT and to identify its underpinnings. A panel of 12 esophageal cultures were treated with CRT and ranked by their relative epithelial-mesenchymal plasticity. RNA-sequencing was performed on 100 pre-treatment biopsies. After RNA-sequencing, Ridge regression analysis was applied to correlate gene expression to ranked plasticity, and models were developed to predict mesenchymal transitions in patients. Plasticity score predictions of the three highest significant predictive models were projected on the pre-treatment biopsies and related to clinical outcome data. Motif enrichment analysis of the genes associated with all three models was performed. RESULTS: This study reveals NANOG as the key associated transcription factor predicting mesenchymal plasticity in EAC. Expression of NANOG in pre-treatment biopsies is highly associated with poor response to neoadjuvant chemoradiation, the occurrence of recurrences, and median overall survival difference in EAC patients (>48 months). Perturbation of NANOG reduces plasticity and resensitizes cell lines, organoid cultures, and patient-derived in vivo grafts. CONCLUSIONS: In conclusion, NANOG is a key transcription factor in mesenchymal plasticity in EAC and a promising predictive marker for outcome.

Esophageal cancer is the sixth most common cause of cancer-related death worldwide. Although chemotherapy combined with radiotherapy (chemoradiotherapy) followed by surgery has improved survival, tumor recurrence and metastatic disease (that has spread to other parts of the body) are often observed after several months. In this study, we assessed the effect of chemoradiotherapy on esophageal cells in the lab to predict the effect in patients with esophageal cancer. To investigate this, genes were assessed from 12 different cell lines and 100 patient tissues. We revealed that levels of one of the genes, NANOG, associates with poor response in patients. NANOG could be a promising marker to predict outcome in patients with esophageal cancer. This knowledge might help clinicians to treat patients with esophageal cancer appropriately, or may lead to new or optimized treatments.

Phosphoproteomics guides effective low-dose drug combinations against pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a limited set of known driver mutations but considerable cancer cell heterogeneity. Phosphoproteomics provides a readout of aberrant signaling and has the potential to identify new targets and guide treatment decisions. Using two-step sequential phosphopeptide enrichment, we generate a comprehensive phosphoproteome and proteome of nine PDAC cell lines, encompassing more than 20,000 phosphosites on 5,763 phospho-proteins, including 316 protein kinases. By using integrative inferred kinase activity (INKA) scoring, we identify multiple (parallel) activated kinases that are subsequently matched to kinase inhibitors. Compared with high-dose single-drug treatments, INKA-tailored low-dose 3-drug combinations against multiple targets demonstrate superior efficacy against PDAC cell lines, organoid cultures, and patient-derived xenografts. Overall, this approach is particularly more effective against the aggressive mesenchymal PDAC model compared with the epithelial model in both preclinical settings and may contribute to improved treatment outcomes in PDAC patients.

The Cellular Origins of Cancer-Associated Fibroblasts and Their Opposing Contributions to Pancreatic Cancer Growth.

Pancreatic tumors are known to harbor an abundant and highly desmoplastic stroma. Among the various cell types that reside within tumor stroma, cancer-associated fibroblasts (CAFs) have gained a lot of attention in the cancer field due to their contributions to carcinogenesis and tumor architecture. These cells are not a homogeneous population, but have been shown to have different origins, phenotypes, and contributions. In pancreatic tumors, CAFs generally emerge through the activation and/or recruitment of various cell types, most notably resident fibroblasts, pancreatic stellate cells (PSCs), and tumor-infiltrating mesenchymal stem cells (MSCs). In recent years, single cell transcriptomic studies allowed the identification of distinct CAF populations in pancreatic tumors. Nonetheless, the exact sources and functions of those different CAF phenotypes remain to be fully understood. Considering the importance of stromal cells in pancreatic cancer, many novel approaches have aimed at targeting the stroma but current stroma-targeting therapies have yielded subpar results, which may be attributed to heterogeneity in the fibroblast population. Thus, fully understanding the roles of different subsets of CAFs within the stroma, and the cellular dynamics at play that contribute to heterogeneity in CAF subsets may be essential for the design of novel therapies and improving clinical outcomes. Fortunately, recent advances in technologies such as microfluidics and bio-printing have made it possible to establish more advanced ex vivo models that will likely prove useful. In this review, we will present the different roles of stromal cells in pancreatic cancer, focusing on CAF origin as a source of heterogeneity, and the role this may play in therapy failure. We will discuss preclinical models that could be of benefit to the field and that may contribute to further clinical development.