Lung cancer is the leading cause of cancer deaths worldwide. Population-based risk screening is effective in reducing lung cancer incidence and mortality. Both genetic and non-genetic factors influence the development and progression of lung cancer. Genome-wide association studies have identified many genetic susceptibility loci for lung cancer. Polygenic risk scores (PRS) constructed by combining these susceptibility loci have been shown to be effective in quantifying the individual risk of lung cancer. However, the predictive performance of PRS varies widely among individuals due to non-genetic factors. Therefore, combining PRS with other non-genetic factors may help to improve the individualized risk prediction performance of lung cancer.

Recently, a research team from Nanjing Medical University in China published a paper entitled "Association of the interaction between mosaic chromosomal alterations and polygenic risk score with the risk of lung cancer" in the journal The Lancet Oncology. risk score with the risk of lung cancer: an array-based case-control association and prospective cohort study", which links PRS with non-genetic factors -The article, "Chimeric autosomal variants (mCAs) in blood to improve individualized risk prediction performance of lung cancer.

The study analyzed mCAs in the Nanjing Lung Cancer Cohort (NJLCC) and the UK Biosample Bank (UKB) cohort, which included 10,248 individuals with 9,298 lung cancer and 450,821 individuals with 2088 lung cancer in the UKB. The results of the study showed that individuals carrying mCAs in the NJLCC cohort and UKB cohort had a 19% and 24% increased risk of developing lung cancer, respectively, compared to those who did not carry mCAs. Further analysis of this study found an approximately 6-fold increased risk of lung cancer (OR 6-40 [95% CI 3.22 - 12.69]) in the NJLCC cohort with low genetic risk of PRS and no mCAs compared to those with high genetic risk of PRS and participants carrying mCAs, and a nearly 4-fold increased risk of lung cancer in the UKB cohort (HR 3.75 [95% CI 1.86 - 7.55]). The results of this study suggest that mCAs, a new endogenous indicator of lung cancer risk, can be used in combination with PRS to optimize individualized risk stratification and improve individualized risk prediction performance of lung cancer. The findings of this study can help improve screening strategies for high-risk groups of lung cancer and provide an important theoretical basis for accurate diagnosis and treatment of lung cancer.

Link to the paper:
https://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(22)00600-3/fulltext