98%
921
2 minutes
20
Background: The most near-term clinical application of genome-wide association studies in lung cancer is a polygenic risk score (PRS).
Methods: A case-control dataset was generated consisting of 4002 lung cancer cases from the LORD project and 20,010 ethnically matched controls from CARTaGENE. A genome-wide PRS including >1.1 million genetic variants was derived and validated in UK Biobank (n = 5419 lung cancer cases). The predictive ability and diagnostic discrimination performance of the PRS was tested in LORD/CARTaGENE and benchmarked against previous PRSs from the literature. Stratified analyses were performed by smoking status and genetic risk groups defined as low (<20th percentile), intermediate (20-80th percentile) and high (>80th percentile) PRS.
Findings: The phenotypic variance explained and the effect size of the genome-wide PRS numerically outperformed previous PRSs. Individuals with high genetic risk had a 2-fold odds of lung cancer compared to low genetic risk. The PRS was an independent predictor of lung cancer beyond conventional clinical risk factors, but its diagnostic discrimination performance was incremental in an integrated risk model. Smoking increased the odds of lung cancer by 7.7-fold in low genetic risk and by 11.3-fold in high genetic risk. Smoking with high genetic risk was associated with a 17-fold increase in the odds of lung cancer compared to individuals who never smoked and with low genetic risk.
Interpretation: Individuals at low genetic risk are not protected against the smoking-related risk of lung cancer. The joint multiplicative effect of PRS and smoking increases the odds of lung cancer by nearly 20-fold.
Funding: This work was supported by the CQDM and the IUCPQ Foundation owing to a generous donation from Mr. Normand Lord.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11282926 | PMC |
http://dx.doi.org/10.1016/j.ebiom.2024.105234 | DOI Listing |
JCO Precis Oncol
September 2025
Shu-Ning Li, MS, Jun-Nv Xu, MD, PhD,and Nan-Nan Ji, MD, PhD, Department of Radiation Oncology, Cancer Treatment Center, The Second Affiliated Hospital of Hainan Medical University, Haikou, China, Ming Xue, MS, Department of Outpatient, The Second Affiliated Hospital of Hainan Medical University, Hai
JCO Precis Oncol
September 2025
Division of Hematology and Oncology, University of California Los Angeles, Los Angeles, CA.
Purpose: mutations are classically seen in non-small cell lung cancers (NSCLCs), and EGFR-directed inhibitors have changed the therapeutic landscape in patients with -mutated NSCLC. The real-world prevalence of -mutated ovarian cancers has not been previously described. We aim to determine the prevalence of pathogenic or likely pathogenic mutations in ovarian cancer and describe a case of -mutated metastatic ovarian cancer with a durable response to osimertinib, an EGFR-directed targeted therapy.
View Article and Find Full Text PDFJCO Precis Oncol
September 2025
Monica F. Chen, MD, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, Daniel Gomez, MD, Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, and Helena A. Yu, MD, Division of Solid Tumor Oncology, Depart
J Bras Pneumol
September 2025
. Rede D'Or, São Paulo (SP), Brasil.
J Bras Pneumol
September 2025
. Departamento de Pneumologia, Centro Hospitalar Universitário de São João, Porto, Portugal.
Objectives: The 9th edition of the Tumor, Node, Metastasis (TNM-9) lung cancer classification is set to replace the 8th edition (TNM-8) starting in 2025. Key updates include the splitting of the mediastinal nodal category N2 into single- and multiple-station involvement, as well as the classification of multiple extrathoracic metastatic lesions as involving a single organ system (M1c1) or multiple organ systems (M1c2). This study aimed to assess how the TNM-9 revisions affect the final staging of lung cancer patients and how these changes correlate with overall survival (OS).
View Article and Find Full Text PDF