How Driver Oncogenes Shape and Are Shaped by Alternative Splicing Mechanisms in Tumors.

The development of RNA sequencing methods has allowed us to study and better understand the landscape of aberrant pre-mRNA splicing in tumors. Altered splicing patterns are observed in many different tumors and affect all hallmarks of cancer: growth signal independence, avoidance of apoptosis, unlimited proliferation, invasiveness, angiogenesis, and metabolism. In this review, we focus on the interplay between driver oncogenes and alternative splicing in cancer. On one hand, oncogenic proteins-mutant p53, CMYC, KRAS, or PI3K-modify the alternative splicing landscape by regulating expression, phosphorylation, and interaction of splicing factors with spliceosome components. Some splicing factors-SRSF1 and hnRNPA1-are also driver oncogenes. At the same time, aberrant splicing activates key oncogenes and oncogenic pathways: p53 oncogenic isoforms, the RAS-RAF-MAPK pathway, the PI3K-mTOR pathway, the EGF and FGF receptor families, and SRSF1 splicing factor. The ultimate goal of cancer research is a better diagnosis and treatment of cancer patients. In the final part of this review, we discuss present therapeutic opportunities and possible directions of further studies aiming to design therapies targeting alternative splicing mechanisms in the context of driver oncogenes.

The molecular network of the proteasome machinery inhibition response is orchestrated by HSP70, revealing vulnerabilities in cancer cells.

Proteasome machinery is a major proteostasis control system in human cells, actively compensated upon its inhibition. To understand this compensation, we compared global protein landscapes upon the proteasome inhibition with carfilzomib, in normal fibroblasts, cells of multiple myeloma, and cancers of lung, colon, and pancreas. Molecular chaperones, autophagy, and endocytosis-related proteins are the most prominent vulnerabilities in combination with carfilzomib, while targeting of the HSP70 family chaperones HSPA1A/B most specifically sensitizes cancer cells to the proteasome inhibition. This suggests a central role of HSP70 in the suppression of the proteasome downregulation, allowing to identify pathways impinging on HSP70 upon the proteasome inhibition. HSPA1A/B indeed controls proteasome-inhibition-induced autophagy, unfolded protein response, and endocytic flux, and directly chaperones the proteasome machinery. However, it does not control the NRF1/2-driven proteasome subunit transcriptional bounce-back. Consequently, targeting of NRF1 proves effective in decreasing the viability of cancer cells with the inhibited proteasome and HSP70.

A Driver Never Works Alone-Interplay Networks of Mutant p53, MYC, RAS, and Other Universal Oncogenic Drivers in Human Cancer.

The knowledge accumulating on the occurrence and mechanisms of the activation of oncogenes in human neoplasia necessitates an increasingly detailed understanding of their systemic interactions. None of the known oncogenic drivers work in isolation from the other oncogenic pathways. The cooperation between these pathways is an indispensable element of a multistep carcinogenesis, which apart from inactivation of tumor suppressors, always includes the activation of two or more proto-oncogenes. In this review we focus on representative examples of the interaction of major oncogenic drivers with one another. The drivers are selected according to the following criteria: (1) the highest frequency of known activation in human neoplasia (by mutations or otherwise), (2) activation in a wide range of neoplasia types (universality) and (3) as a part of a distinguishable pathway, (4) being a known cause of phenotypic addiction of neoplastic cells and thus a promising therapeutic target. Each of these universal oncogenic factors-mutant p53, KRAS and CMYC proteins, telomerase ribonucleoprotein, proteasome machinery, HSP molecular chaperones, NF-κB and WNT pathways, AP-1 and YAP/TAZ transcription factors and non-coding RNAs-has a vast network of molecular interrelations and common partners. Understanding this network allows for the hunt for novel therapeutic targets and protocols to counteract drug resistance in a clinical neoplasia treatment.