Precision therapy in RAS mutant colorectal cancer.

Rat sarcoma virus (RAS) represents the most frequently mutated oncogene family across all malignancies and has therefore motivated decades of research aimed at understanding and targeting aberrant signaling elicited by oncogenic gain-of-function mutations. Of the 3 RAS genes (KRAS, NRAS, and HRAS), KRAS is most commonly mutated in pancreatic, colorectal, and lung adenocarcinomas, whereas NRAS and HRAS mutations are mostly found in selected hematologic malignancies, melanomas and thyroid cancers. In colorectal cancer (CRC), activating missense mutations in KRAS and NRAS have been reported at frequencies of approximately 40% and 4%, respectively, with more than 95% of mutations occurring in 1 of 3 major hotspots (residues G12, G13, and Q61). Non-G12 KRAS mutations are enriched in tumors of the right side of the colon, in those with microsatellite instability (MSI) and high tumor mutational burden. Interestingly, the overall frequency of KRAS mutations increases with age in microsatellite stable (MSS) CRC, particularly in males. In contrast, a reduced prevalence of KRAS mutations is observed in MSI/high mutational burden tumors in the elderly population

Additional file 2: of Cancer Genome Interpreter annotates the biological and clinical relevance of tumor alterations

Supplementary methods, use cases description, Table S2. and Figures S1–S3. (PDF 6267 kb

Additional file 1: of Cancer Genome Interpreter annotates the biological and clinical relevance of tumor alterations

Table S1. The features provided by different resources/methods and details about which of them are employed by the CGI. (XLS 21 kb

Molecular subtyping combined with biological pathway analyses to study regorafenib response in clinically relevant mouse models of colorectal cancer.

Purpose: Regorafenib (REG) is approved for the treatment of metastatic colorectal cancer, but has modest survival benefit and associated toxicities. Robust predictive/early response biomarkers to aid patient stratification are outstanding. We have exploited biological pathway analyses in a patient-derived xenograft (PDX) trial to study REG response mechanisms and elucidate putative biomarkers.Experimental design: Molecularly subtyped PDXs were annotated for REG response. Subtyping was based on gene expression (CMS, consensus molecular subtype) and copy-number alteration (CNA). Baseline tumor vascularization, apoptosis, and proliferation signatures were studied to identify predictive biomarkers within subtypes. Phospho-proteomic analysis was used to identify novel classifiers. Supervised RNA sequencing analysis was performed on PDXs that progressed, or did not progress, following REG treatment.Results:Improved REG response was observed in CMS4, although intra-subtype response was variable. Tumor vascularity did not correlate with outcome. In CMS4 tumors, reduced proliferation and higher sensitivity to apoptosis at baseline correlated with response. Reverse phase protein array (RPPA) analysis revealed 4 phospho-proteomic clusters, one of which was enriched with non-progressor models. A classification decision tree trained on RPPA- and CMS-based assignments discriminated non-progressors from progressors with 92% overall accuracy (97% sensitivity, 67% specificity). Supervised RNA sequencing revealed that higher basal EPHA2 expression is associated with REG resistance.Conclusions:Subtype classification systems represent canonical "termini a quo" (starting points) to support REG biomarker identification, and provide a platform to identify resistance mechanisms and novel contexts of vulnerability. Incorporating functional characterization of biological systems may optimize the biomarker identification process for multitargeted kinase inhibitors.</p