A PRS FOR LUNG CANCER

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Lung cancer remains the leading cause of cancer death globally, with over 2 million new cases and nearly 1.8 million deaths annually. The high mortality rate underscores the critical importance of early detection and prevention strategies. Given lung cancer's aggressive nature and the late stage at which it is often diagnosed, there's a pressing need for innovative approaches to identify individuals at high risk more effectively. 

The development of lung cancer is influenced by a complex interplay of genetic and non-genetic factors. This multifactorial etiology suggests that both inherited predispositions and environmental exposures play crucial roles in the disease's onset and progression. Understanding these factors is essential for developing targeted prevention and early detection strategies. 

Among the most significant non-genetic risk factors for lung cancer are smoking, exposure to radon gas, asbestos, and pollution, as well as chronic infections and a history of lung diseases. Smoking, in particular, is the most well-known and substantial risk factor, responsible for a large majority of lung cancer cases worldwide. Lifestyle modifications, including smoking cessation, can significantly reduce the risk of developing lung cancer. 

While certain monogenic factors, such as mutations in the TP53 gene or those associated with familial cancer syndromes, have been identified, these account for a small fraction of lung cancer cases. More commonly, lung cancer risk is influenced by polygenic factors, which involve multiple genes contributing small effects individually. This polygenic nature suggests a broader, more nuanced genetic landscape influencing lung cancer risk. 

Integrating polygenic risk scores (PRS) into lung cancer risk assessment represents a promising advancement. PRS can improve the prediction accuracy of disease risk, enhance risk stratification, and better align screening and prevention strategies with an individual's genetic risk profile. Studies like Lebrett et al. (2023) have demonstrated that incorporating a PRS for lung cancer improves risk prediction and screening selection in high-risk populations that are likely to be targeted for screening. 

Previous landmark trials, such as the National Lung Screening Trial (NLST) and the Dutch-Belgian Lung Cancer Screening (NELSON) trial, have demonstrated the efficacy of low-dose computed tomography (LDCT) screening in LC prevention. Hung et al. showed that the integration of a PRS for lung cancer into the screening process significantly enhances the precision of identifying individuals at high risk. This method allows for a more nuanced risk assessment by considering an individual's genetic background alongside traditional factors like age and smoking history. PRS can inform the optimal timing for initiating LDCT screening, potentially enabling earlier detection for those at highest risk and delaying screening for those at lower risk. 

Such tailored screening recommendations could lead to more efficient use of healthcare resources, reduce unnecessary radiation exposure, and improve lung cancer prevention efforts. Additionally, an effective PRS could potentially lower the overall number of individuals eligible for screening and decrease the frequency of screenings, thereby enhancing program efficiency. By offering a personalized approach to lung cancer risk assessment, PRS contributes to a more effective and targeted screening strategy, optimizing early detection and reducing the overall healthcare burden.