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

Area of Science:

• Genomics
• Cancer Biology
• Molecular Diagnostics

Background:

• Cancer cells exhibit diverse genomic and epigenomic alterations, forming distinct molecular signatures.
• Insertion/deletion (INDEL) mutations are a key type of genomic alteration, potentially altering protein function and linked to numerous diseases.
• Traditional low-throughput methods for INDEL detection are being complemented by high-throughput sequencing.

Purpose of the Study:

• To review the application of high-throughput sequencing (DNA-Seq and RNA-Seq) for investigating INDELs in human gene coding regions.
• To highlight the potential of RNA-Seq in identifying disease-associated INDELs and novel drug targets.
• To explore the relationship between INDELs and clinical outcomes in cancer patients.

Main Methods:

• Review of studies utilizing DNA-Seq and RNA-Seq for INDEL detection in coding regions.
• Analysis of RNA-Seq data for identifying disease-causing INDELs.
• Examination of associations between small INDELs, structural variants, and patient outcomes.

Main Results:

• RNA-Seq has been successfully employed to identify disease-associated INDELs.
• Small INDELs are linked to chemo-resistance and poor patient outcomes.
• Structural variants may be associated with better clinical outcomes.

Conclusions:

• RNA-Seq data is more abundant than DNA-Seq data in public repositories, making it a valuable resource.
• RNA-Seq is a promising strategy for investigating drug resistance mechanisms in cancer.
• This approach facilitates the discovery of potential novel drug targets through the identification of proteins affected by INDELs.