Stanford Researchers Identify 380 DNA Variants Linked to Cancer Prediction and Growth

Genetic variants regulate key genes involved in DNA repair, energy production, and immune interactions, offering fresh insights into inherited cancer risks. Surprisingly, inflammation-related genes also emerged as potential cancer drivers, marking a major step toward precise genetic screening and personalized prevention.

Thousands of tiny DNA sequence changes have been linked to cancer risk, but until now, their direct role in triggering uncontrolled cell growth remained unclear. Stanford researchers conducted the first large-scale analysis of these inherited genetic changes, called single nucleotide variants, identifying fewer than 400 that significantly contribute to cancer growth.

These variants influence critical biological pathways, including DNA repair, energy production, and cellular interactions. Their identification could drive new cancer prevention strategies and improve genetic screening for assessing lifetime risk.

“We analyzed data from millions of patients with the 13 most common cancers, covering over 90% of malignancies,” said Paul Khavari, MD, PhD, chair of dermatology. “This massive dataset helped us pinpoint 380 variants controlling cancer-related gene expression. Some inherited variants significantly raise the risk of multiple cancers.”

Published in Nature Genetics, the study was led by former graduate student Laura Kellman, PhD, with Khavari as senior author.

The Risks We Inherit

The study focused on germline DNA—sequences inherited at conception—rather than mutations acquired over a lifetime. Well-known examples include BRCA1 and BRCA2, which greatly increase breast and ovarian cancer risks. However, few high-profile mutations are currently used in risk prediction.

Unlike coding genes that produce proteins, the variants Kellman and Khavari identified reside in regulatory regions, controlling gene expression. These regions can influence both nearby and distant genes, shaping cancer risk.

In 2020, Khavari launched a National Human Genome Research Institute-funded project to map regulatory variants tied to 42 complex diseases, including cancers. The goal: create individualized risk scores for better screening, prevention, and treatment.

A New Approach to Cancer Risk

Traditional genome-wide association studies (GWAS) identify cancer-linked variants based on statistical correlation but fail to prove functional impact. They also do not clarify which genes are affected.

Kellman and Khavari took a different approach. They analyzed over 4,000 suspect variants across 13 cancers, attaching regulatory sequences to DNA barcodes. Using massively parallel reporter assays, they tested whether variants altered gene expression in relevant cell types—such as lung cancer variants in lung cells.

This strategy filtered thousands of potential variants down to a few hundred functional regulatory regions. By integrating existing genomic data, they identified about 1,100 genes likely involved in cancer development. Some drive specific cancers, while others influence multiple types.

“This makes sense given what we know about cancer,” Khavari said. “Some genes regulate cell death, others influence how cells interact with their environment, and mitochondrial genes play a key role in cell growth and division.”

“One pathway that stood out includes genes linked to inflammation,” Khavari noted. “While the cancer-inflammation connection is known, what drives it—cancer cells or the immune system—remains unclear. Our findings suggest cross talk between immune cells and cancer cells fuels chronic inflammation and elevates cancer risk.”

Future of Cancer Screening and Prevention

Using gene editing, the team confirmed that nearly half of the identified variants are essential for cancer growth. Their work paves the way for global research into inherited cancer risk and novel therapies.

“We now have a first-generation map of functional variants determining lifetime cancer risk,” Khavari said. “This information will soon enhance genetic screening tests, helping predict risk for complex diseases like cancer. Over the next decade, these insights could guide personalized interventions, from lifestyle changes to preventive treatments and early diagnostics.”

Read Original Article: Scitechdaily

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