Clinical Implications of NRAS Overexpression in Resectable Pancreatic Adenocarcinoma Patients

Mutant K-Ras in Pancreatic Cancer: An Insight on the Role of Wild-Type N-Ras and K-Ras-Dependent Cell Cycle Regulation

The development of K-Ras independence may explain the failure of targeted therapy for pancreatic cancer (PC). In this paper, active N as well as K-Ras was shown in all human cell lines tested. In a cell line dependent on mutant K-Ras, it was shown that depleting K-Ras reduced total Ras activity, while cell lines described as independent had no significant decline in total Ras activity. The knockdown of N-Ras showed it had an important role in controlling the relative level of oxidative metabolism, but only K-Ras depletion caused a decrease in G2 cyclins. Proteasome inhibition reversed this, and other targets of APC/c were also decreased by K-Ras depletion. K-Ras depletion did not cause an increase in ubiquitinated G2 cyclins but instead caused exit from the G2 phase to slow relative to completion of the S-phase, suggesting that the mutant K-Ras may inhibit APC/c prior to anaphase and stabilise G2 cyclins independently of this. We propose that, during tumorigenesis, cancer cells expressing wild-type N-Ras protein are selected because the protein protects cancer cells from the deleterious effects of the cell cycle-independent induction of cyclins by mutant K-Ras. Mutation independence results when N-Ras activity becomes adequate to drive cell division, even in cells where K-Ras is inhibited.

Mutation-specific effects of NRAS oncogenes in colorectal cancer cells

In colorectal cancer (CRC), the prevalence of NRAS mutations (5-9%) is inferior to that of KRAS mutations (40-50%). NRAS mutations feature lately during tumour progression and drive resistance to anti-EGFR therapy in KRAS wild-type tumours. To elucidate specific functions of NRAS mutations in CRC, we expressed doxycycline-inducible G12D and Q61K mutations in the CRC cell line Caco-2. A focused phospho-proteome analysis based on the Bio-Plex platform, which interrogated the activity of MAPK, PI3K, mTOR, STAT, p38, JNK and ATF2, did not reveal significant differences between Caco-2 cells expressing NRAS^G12D, NRAS^Q61K and KRAS^G12V. However, phenotypic read-outs were different. The NRAS Q61K mutation promoted anchorage-independent proliferation and tumorigenicity, similar to features driven by canonical KRAS mutations. In contrast, expression of NRAS^G12D resulted in reduced proliferation and apoptosis. At the transcriptome level, we saw upregulation of cytokines and chemokines. IL1A, IL11, CXCL8 (IL-8) and CCL20 exhibited enhanced secretion into the culture medium. In addition, RNA sequencing results indicated activation of the IL1-, JAK/STAT-, NFκB- and TNFα signalling pathways. These results form the basis for an NRAS^G12D-driven inflammatory phenotype in CRC.

miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancer

BACKGROUND

MicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. In silico-based functional analysis of miRNAs usually consists of miRNA target prediction and functional enrichment analysis of miRNA targets. Since miRNA target prediction methods generate a large number of false positive target genes, further validation to narrow down interesting candidate miRNA targets is needed. One commonly used method correlates miRNA and mRNA expression to assess the regulatory effect of a particular miRNA. The aim of this study was to build a bioinformatics pipeline in R for miRNA functional analysis including correlation analyses between miRNA expression levels and its targets on mRNA and protein expression levels available from the cancer genome atlas (TCGA) and the cancer proteome atlas (TCPA). TCGA-derived expression data of specific mature miRNA isoforms from pancreatic cancer tissue was used.

RESULTS

Fifteen circulating miRNAs with significantly altered expression levels detected in pancreatic cancer patients were queried separately in the pipeline. The pipeline generated predicted miRNA target genes, enriched gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) pathways. Predicted miRNA targets were evaluated by correlation analyses between each miRNA and its predicted targets. MiRNA functional analysis in combination with Kaplan-Meier survival analysis suggest that hsa-miR-885-5p could act as a tumor suppressor and should be validated as a potential prognostic biomarker in pancreatic cancer.

CONCLUSIONS

Our miRNA functional analysis (miRFA) pipeline can serve as a valuable tool in biomarker discovery involving mature miRNAs associated with pancreatic cancer and could be developed to cover additional cancer types. Results for all mature miRNAs in TCGA pancreatic adenocarcinoma dataset can be studied and downloaded through a shiny web application at https://emmbor.shinyapps.io/mirfa/ .