The value of genomics in dissecting the RAS-network and in guiding therapeutics for RAS-driven cancers

Abstract

The rise in genomic knowledge over the past decade has revealed the molecular etiology of many diseases, and has identified intricate signaling network activity in human cancers. Genomics provides the opportunity to determine genome structure and capture the activity of thousands of molecular events concurrently, which is important for deciphering highly complex genetic diseases such as cancer. In this review, we focus on genomic efforts directed towards one of cancer's most frequently mutated networks, the RAS pathway. Genomic tools such as gene expression signatures and assessment of mutations across the RAS network enable the capture of RAS signaling complexity. Due to this high level of interaction and cross-talk within the network, efforts to target RAS signaling in the clinic have generally failed, and we currently lack the ability to directly inhibit the RAS protein with high efficacy. We propose that the use of gene expression data can identify effective treatments that broadly inhibit the RAS network as this approach measures pathway activity independent of mutation status or any single mechanism of activation. Here, we review the genomic studies that map the complexity of the RAS network in cancer, and that show how genomic measurements of RAS pathway activation can identify effective RAS inhibition strategies. We also address the challenges and future directions for treating RAS-driven tumors. In summary, genomic assessment of RAS signaling provides a level of complexity necessary to accurately map the network that matches the intricacy of RAS pathway interactions in cancer.

Keywords: Cancer; Gene expression signature; Genomics; RAS; Targeted therapy.

Figure 1

RAS pathway aberrations in human cancers. The RAS pathway can be activated by mutation (green) or by overexpression (blue) of pathway proteins. In some cancers, proteins are both mutated and overexpressed (red). Dysregulation can occur in downstream effector molecules including RAF, MEK, PI3K, and AKT. RAS is also activated by the loss of function of RAS regulators such as GAPs (yellow).

Figure 2

Scaled pathway activation scores for the EGFR, RAF, and RAS pathway from patient TCGA data. (A) head and neck squamous cell carcinoma, (B) rectum adenocarcinoma, (C) uterine carcinoma, (D) lung adenocarcinoma, (E) ovarian serous cystadenocarcinoma, (F) breast invasive carcinoma, (G) bladder urothelial carcinoma, and (H) kidney renal clear cell carcinoma. Red values indicate high pathway activity and blue represent low pathway activity. Color bars on the right side represent different gene mutations in KRAS (pink), EGFR (light blue), and BRAF (green). Black bars in gene columns indicate presence of mutations.