Using high-throughput sequencing transcriptome data for INDEL detection: challenges for cancer drug discovery.

Expert opinion on drug discovery

PubMedID: 26787005

Wajnberg G, Passetti F. Using high-throughput sequencing transcriptome data for INDEL detection: challenges for cancer drug discovery. Expert Opin Drug Discov. 2016;.
INTRODUCTION
A cancer cell is a mosaic of genomic and epigenomic alterations. Distinct cancer molecular signatures can be observed depending on tumor type or patient genetic background. One type of genomic alteration is the insertion and/or deletion (INDEL) of nucleotides in the DNA sequence, which may vary in length, and may change the encoded protein or modify protein domains. INDELs are associated to a large number of diseases and their detection is done based on low-throughput techniques. However, high-throughput sequencing has also started to be used for detection of novel disease-causing INDELs. This search may identify novel drug targets.

AREAS COVERED
This review presents examples of using high-throughput sequencing (DNA-Seq and RNA-Seq) to investigate the incidence of INDELs in coding regions of human genes. Some of these examples successfully utilized RNA-Seq to identify INDELs associated to diseases. In addition, other studies have described small INDELs related to chemo-resistance or poor outcome of patients, while structural variants were associated with a better clinical outcome.

EXPERT OPINION
On average, there is twice as much RNA-Seq data available at the most used repositories for such data compared to DNA-Seq. Therefore, using RNA-Seq data is a promising strategy for studying cancer samples with unknown mechanisms of drug resistance, aiming at the discovery of proteins with potential as novel drug targets.