Lung cancer is the most common cancer with a poor prognosis due to the fact that most patients are diagnosed at advanced stages. To reduce lung cancer mortality by early diagnosis, low-dose spiral computed tomography (LDCT) scans have been recommended for people who are 55 to 74 years old and currently smoke or have quit in the past 15 years. The current guideline for screening is limited by the accuracy of lung cancer risk assessment models. To further improve the guideline, it is necessary to consider additional lung cancer risk factors that can be easily tested. Recently, lung cancer-associated genetic variants have been added to the risk models but resulted in only modest improvement. Cl...

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Lung cancer is the most common cancer with a poor prognosis due to the fact that most patients are diagnosed at advanced stages. To reduce lung cancer mortality by early diagnosis, low-dose spiral computed tomography (LDCT) scans have been recommended for people who are 55 to 74 years old and currently smoke or have quit in the past 15 years. The current guideline for screening is limited by the accuracy of lung cancer risk assessment models. To further improve the guideline, it is necessary to consider additional lung cancer risk factors that can be easily tested. Recently, lung cancer-associated genetic variants have been added to the risk models but resulted in only modest improvement. Clonal hematopoiesis (CH) is the phenomenon of clonal expansion in blood cells caused by mutations in blood cells, which can be easily detected. In our recent publications, we have shown that CH and mosaic chromosome alterations are associated with increased risk of lung cancer after adjusting aging, sex, and smoking factors. In this project, we hypothesize that CH can be used as a new biomarker for improving lung cancer risk prediction and therefore has the potential to improve early lung cancer screening programs. We propose to use the genetic data from the retrospective INTEGRAL-ILCCO and the prospective United Kingdom Biobank (UKBB) cohorts to further establish the association between CH and lung cancer risk and evaluate its additional contribution to lung cancer risk prediction and prevention. To elucidate the genetic contribution to CH, we will identify genetic variants that are associated with CH phenotypes. To understand the potential mechanisms by which CH contributes to increased lung cancer risk, we will investigate the effect of CH on blood lymphocyte/T cell levels. Our results will pave the road for using CH as a new biomarker to improve lung cancer risk assessment models with the final goal for promoting more effective lung cancer screening.

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