Abstract 7478: Lung cancer gene regulatory networks reflect smoking history and age-related metabolic pathway alterations
Authors: Camila Lopes-Ramos, Enakshi Saha, Jeong Yun, Craig Hersh, Edwin Silverman, Dawn DeMeo, John Quackenbush, Kimberly Glass
Journal: Cancer Research (2025)

Abstract Background: The rising incidence of lung cancer among individuals without a history of smoking highlights the need to explore biological mechanisms underlying this phenomenon. Our study aims to identify gene regulatory mechanisms that drive lung cancer risk among never-smokers by analyzing how gene regulatory networks differ between individuals with and without lung cancer, depending on their smoking history. Methods: We used RNA-Seq data from the Lung Tissue Research Consortium (LTRC) collected via TOPMed, comprising non-cancerous lung tissue samples from 344 individuals with non-small cell carcinoma and 329 lung tissue samples from individuals without cancer. Across all, 18% reported no history of smoking. We ran differential gene expression analysis by voom, adjusting for age, sex, COPD status, and examining statistical interactions between smoking (never/former) and cancer status. We analyzed sample-specific transcription factor-gene regulatory networks generated by PANDA-LIONESS. We used linear regression to evaluate the association between gene targeting score (measured by gene indegree) and the interaction between smoking and cancer status. We ran gene set enrichment analysis with genes ranked by the corresponding smoking by cancer interaction coefficients. Results: Differential expression analysis of lung tissues from individuals with and without cancer showed that genes overexpressed in cancer are enriched for canonical cancer pathways, such as p53, MAPK, and WNT signaling pathways (FDR&amp;lt;0.05). We found a significant interaction between cancer and smoking status, indicating these cancer-related pathways had higher enrichment in former-smokers compared to never smokers. Gene regulatory network analysis indicated that these differential expression patterns are possibly driven by increased transcriptional targeting of these cancer-related pathways. Among never-smokers, individuals with cancer showed higher targeting of metabolic pathways (e.g., fructose and mannose, glutathione, phenylalanine, histidine, arginine, and proline metabolism) compared to lung tissue from individuals without cancer (FDR&amp;lt;0.05), highlighting a possible role of metabolic pathways in tumor development, uniquely among never-smokers. A negative correlation between metabolic pathway targeting scores and age was observed exclusively in individuals with cancer without a history of smoking (Mean Pearson R=-0.24). Conclusion: Our findings reveal transcriptional targeting differences in lung cancer by smoking history. Among individuals without a history of smoking, the increased targeting of metabolic pathways in cancer, which is pronounced in younger compared to older individuals, may contribute to the higher risk of early-onset lung cancer among never-smokers, offering new avenues for understanding and addressing the disease in populations without a history of smoking. Citation Format: Camila Lopes-Ramos, Enakshi Saha, Jeong Yun, Craig Hersh, Edwin Silverman, Dawn DeMeo, John Quackenbush, Kimberly Glass. Lung cancer gene regulatory networks reflect smoking history and age-related metabolic pathway alterations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7478.