en.Wedoany.com Reported - Dr. Yixuan He, Assistant Professor of Epidemiology at the University of Texas Health Science Center, Houston, and Ms. Jiawei Tu, a doctoral student, have developed a gene mutation-based scoring system to predict patient survival by analyzing genetic sequencing data from over 30,000 cancer patients. This study is the first to simultaneously consider the impact of genetic ancestry, socioeconomic status, and environmental factors such as air pollution on cancer prognosis in such a large sample.
The research team analyzed genetic data from breast cancer, colorectal cancer, glioma, pancreatic cancer, and lung cancer patients at the Dana-Farber Cancer Institute and MD Anderson Cancer Center. While detecting gene mutations, the researchers incorporated socioeconomic status and air pollution factors into the analysis for correction, and established a scoring system based on gene mutations to predict the risk of patients dying from cancer, testing whether adding ancestry information could improve predictive performance.
Dr. He stated that previous predictive scoring studies were limited to small sample groups of single populations and single tumor types, and often did not consider environmental factors or long-term clinical outcomes. By expanding the scope of the study, they hope to demonstrate the real, measurable impact of genetic ancestry on cancer genomics and clinical outcomes.
The study results showed that the frequencies of dozens of gene mutations varied significantly among patients of different ancestral backgrounds, with approximately half of these mutations targetable by existing therapies. The scoring system was able to predict patient survival, with particularly notable effects in breast cancer and glioma. After incorporating ancestry information, the accuracy of survival prediction further improved, with the most prominent performance in pancreatic cancer.
Tumor sequencing is relatively common in modern cancer treatment, genetic ancestry data can be estimated through gene sequencing, and environmental factors can be simply assessed based on patient residence. Dr. He pointed out that the challenge of integration lies not in the lack of suitable technology, but in the need for a workflow that can derive these important factors from existing routine data collection. The team is collaborating with oncologists, hoping to overcome these obstacles.
The research team plans to expand the analysis to other cancers in the future and include more environmental factors, such as smoking and other pollutants. They identified several new associations, such as enrichment of the cell proliferation control gene CDK6 in African American breast cancer patients, and deletion of the cell proliferation control gene SMAD2 in colorectal cancer patients of mixed ancestry in the United States. Dr. He concluded that although the two biobanks differ geographically and in population, observing consistent ancestry-related signals repeatedly is very encouraging; by identifying specific genetic markers related to ancestry, targetable mutations can be precisely located, helping doctors choose treatment plans that lead to better survival outcomes, and validating these signals across different populations ensures that specific therapies are suitable for diverse patient groups.
Professor Alexandre Reymond, conference chair who was not involved in the study, stated that this research convincingly demonstrates that to truly achieve personalized medicine and help as many patients as possible, it is necessary to assess disease risk across different populations.
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