# Novel treatment-specific causal biomarkers for colorectal cancer by omics integration

## TL;DR

This study identifies new biomarkers for colorectal cancer patients treated with specific drugs, using genetic and RNA data to improve treatment outcomes.

## Contribution

The study introduces treatment-specific causal biomarkers for colorectal cancer through omics data integration.

## Key findings

- WDR62 overexpression is linked to shorter survival in cetuximab-treated CRC patients.
- WDR62 overexpression is enriched in CMS1 and low in CMS4, suggesting CMS4 patients may benefit more from cetuximab.
- Integration of omics data reveals promising biomarkers specific to cancer subtypes and treatments.

## Abstract

While monoclonal antibody-based targeted therapies have substantially improved progression-free survival in cancer patients, the variability in individual responses poses a significant challenge in patient care. Therefore, identifying cancer subtypes and their associated biomarkers is required for assigning effective treatment. In this study, we integrated genotype and pre-treatment tissue RNA-seq data and identified biomarkers causally associated with the overall survival (OS) of colorectal cancer (CRC) patients treated with either cetuximab or bevacizumab. We performed enrichment analysis for specific consensus molecular subtypes (CMS) of CRC and evaluated differential expression of identified genes using paired tumor and normal tissue from an external cohort. In addition, we replicated the causal effect of these genes on OS using a validation cohort and assessed their association with The Cancer Genome Atlas Program data as an external cohort. One of the replicated findings was WDR62, whose overexpression shortened OS of patients treated with cetuximab. Enrichment of its overexpression in CMS1 and low expression in CMS4 suggests that patients with the CMS4 subtype may derive greater benefit from cetuximab. In summary, this study highlights the importance of integrating different omics data for identifying promising biomarkers specific to a treatment or a cancer subtype.