Colorectal Cancer Study Identifies New Genetic Links to Disease
A multi-omic analysis of 200,000+ people with cancer and non-cancerous controls identified hundreds of risk associations and revealed 50 undiscovered genetic associations with colorectal cancer.
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By - A meta-analysis of colorectal cancer genome-wide associated studies (GWAS) published in Nature identified 37 single nucleotide polymorphisms (SNPs) at new loci and 13 independent new risk SNPs that will help build a better understanding of the genetic risk factors associated with colorectal cancer.
The 50 new SNPs identified represent nearly a quarter of the 205 total risk associations identified for colorectal cancer. SNPs assist in tracking the inheritance of disease-associated genetic variants and help researchers understand variations in drug response while informing the creation of genome-specific drugs. Several of the findings produced by the study had no previous functional link to colorectal cancer risk and represent a significant step forward in understanding colorectal cancer genetics.
To conduct the study, authors from the Edinburgh Cancer Research Centre in the UK and the Institute of Cancer Research worked with dozens of scientists spanning several continents to create a multi-omic analysis using data from 100,204 people diagnosed with colorectal cancer and 154,587 controls without cancer.
The study was twice as large as the previous largest colorectal cancer GWAS publication and contained data from European and Asian ancestral groups. Researchers concluded that another study using 500,000 or more cases and controls could provide comprehensive biological insights and information about the heritable risk of colorectal cancer.
“Extending GWASs to African and other populations may detect further risk SNPs, including population-specific ones,” shared researchers in the discussion section of their publication. “Overall, our findings demonstrate the power of multi-omics to provide new insights into the biological basis of CRC, including both the identification of candidate effector genes and the support for previously unsuspected functional mechanisms. Importantly, several of the genes and pathways we have identified are potential targets for CRC treatment or chemoprevention.”
Colorectal cancer is a leading cause of mortality worldwide and the fourth most prevalent form of cancer in the United States. In the US, nearly 150,000 people are diagnosed each year, and the disease is responsible for approximately 50,000 deaths. Lifestyle factors that produce a higher risk for the disease include lack of regular physical activity, overconsumption of processed foods, alcohol consumption, and tobacco use.
Clinicians rely on colonoscopies, fecal screenings, and at-home DNA-based tests to detect colorectal cancer. Artificial intelligence (AI) tools are also being utilized to improve screenings and reduce human error. And by applying AI-enabled modeling, researchers have been able to better predict the likelihood of colorectal cancer in patients and improve estimations of cancer recurrence.
