For many years, scientists have struggled to understand and cure cancer. The study of the genome of multiple tumors has been fundamental to detect relevant alterations in cancer. These studies have highlighted the heterogeneity of genetic alterations in patients suffering from the same type of cancer, motivating the development of individualized treatments. Tumors frequently lack known actionable alterations, making thus necessary to expand the catalogue of cancer signatures to integrate other molecular alterations.
There is increasing evidence that alterations in the splicing regulatory program play an important role in tumor transformation. Splicing is a process by which the long RNA molecule transcribed from the gene in the genome is processed to remove segments called introns, giving rise to an RNA transcript. Alternative splicing provides a mechanism to generate multiple RNA transcripts from the same gene by eliminating introns in different ways. This process is tightly regulated and can give rise to molecules with very different functions. This dramatic change is generally called a splicing switch.
Splicing switches can induce altered cellular states, leading to disease. Accordingly, the identification of these switches can be fundamental for prognosis and therapy. This analysis is generally hindered by the heterogeneity of tumors of the same origin from different individuals, as well as by the normal variability between individuals. We have developed a new computational method, robust to biological and technical variability, which identifies significant splicing switches across a large number of tumor samples and shows high accuracy.
This is the first published large-scale analysis describing the splicing alterations in 9 cancer types using RNA sequencing data for more than 4000 patient samples. In this work, we have discovered that there exist many splicing switches in patients with the same cancer type that can separate with high accuracy tumor and normal samples, and different types of cancer from each other, providing potential novel molecular targets for prognosis and therapy.