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1,090 results on '"Schabath, Matthew B"'

1. Embedding-based Multimodal Learning on Pan-Squamous Cell Carcinomas for Improved Survival Outcomes

Author

Waqas, Asim, Tripathi, Aakash, Stewart, Paul, Naeini, Mia, Schabath, Matthew B., and Rasool, Ghulam

Subjects
Quantitative Biology - Cell Behavior, Computer Science - Machine Learning
Abstract

Cancer clinics capture disease data at various scales, from genetic to organ level. Current bioinformatic methods struggle to handle the heterogeneous nature of this data, especially with missing modalities. We propose PARADIGM, a Graph Neural Network (GNN) framework that learns from multimodal, heterogeneous datasets to improve clinical outcome prediction. PARADIGM generates embeddings from multi-resolution data using foundation models, aggregates them into patient-level representations, fuses them into a unified graph, and enhances performance for tasks like survival analysis. We train GNNs on pan-Squamous Cell Carcinomas and validate our approach on Moffitt Cancer Center lung SCC data. Multimodal GNN outperforms other models in patient survival prediction. Converging individual data modalities across varying scales provides a more insightful disease view. Our solution aims to understand the patient's circumstances comprehensively, offering insights on heterogeneous data integration and the benefits of converging maximum data views.

Published
2024

2. HoneyBee: A Scalable Modular Framework for Creating Multimodal Oncology Datasets with Foundational Embedding Models

Author

Tripathi, Aakash, Waqas, Asim, Schabath, Matthew B., Yilmaz, Yasin, and Rasool, Ghulam

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Databases
Abstract

Developing accurate machine learning models for oncology requires large-scale, high-quality multimodal datasets. However, creating such datasets remains challenging due to the complexity and heterogeneity of medical data. To address this challenge, we introduce HoneyBee, a scalable modular framework for building multimodal oncology datasets that leverages foundation models to generate representative embeddings. HoneyBee integrates various data modalities, including clinical diagnostic and pathology imaging data, medical notes, reports, records, and molecular data. It employs data preprocessing techniques and foundation models to generate embeddings that capture the essential features and relationships within the raw medical data. The generated embeddings are stored in a structured format using Hugging Face datasets and PyTorch dataloaders for accessibility. Vector databases enable efficient querying and retrieval for machine learning applications. We demonstrate the effectiveness of HoneyBee through experiments assessing the quality and representativeness of these embeddings. The framework is designed to be extensible to other medical domains and aims to accelerate oncology research by providing high-quality, machine learning-ready datasets. HoneyBee is an ongoing open-source effort, and the code, datasets, and models are available at the project repository.

Published
2024

3. Self-Normalizing Foundation Model for Enhanced Multi-Omics Data Analysis in Oncology

Author

Waqas, Asim, Tripathi, Aakash, Ahmed, Sabeen, Mukund, Ashwin, Farooq, Hamza, Schabath, Matthew B., Stewart, Paul, Naeini, Mia, and Rasool, Ghulam

Subjects
Computer Science - Machine Learning
Abstract

Multi-omics research has enhanced our understanding of cancer heterogeneity and progression. Investigating molecular data through multi-omics approaches is crucial for unraveling the complex biological mechanisms underlying cancer, thereby enabling more effective diagnosis, treatment, and prevention strategies. However, predicting patient outcomes through the integration of all available multi-omics data is still an under-study research direction. Here, we present SeNMo, a foundation model that has been trained on multi-omics data across 33 cancer types. SeNMo is particularly efficient in handling multi-omics data characterized by high-width and low-length attributes. We trained SeNMo for the task of overall survival of patients using pan-cancer multi-omics data involving 33 cancer sites from the GDC. The training multi-omics data includes gene expression, DNA methylation, miRNA expression, DNA mutations, protein expression modalities, and clinical data. SeNMo was validated on two independent cohorts: Moffitt Cancer Center and CPTAC lung squamous cell carcinoma. We evaluated the model's performance in predicting patient's overall survival using the C-Index. SeNMo performed consistently well in the training regime, reflected by the validation C-Index of 0.76 on GDC's public data. In the testing regime, SeNMo performed with a C-Index of 0.758 on a held-out test set. The model showed an average accuracy of 99.8% on the task of classifying the primary cancer type on the pan-cancer test cohort. SeNMo demonstrated robust performance on the classification task of predicting the primary cancer type of patients. SeNMo further demonstrated significant performance in predicting tertiary lymph structures from multi-omics data, showing generalizability across cancer types, molecular data types, and clinical endpoints.

Published
2024

4. Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification

Author

Wang, Xinan, Zhang, Ziwei, Ding, Yi, Chen, Tony, Mucci, Lorelei, Albanes, Demetrios, Landi, Maria Teresa, Caporaso, Neil E., Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Johansson, Mattias, Risch, Angela, Bickeböller, Heike, Wichmann, H-Erich, Rennert, Gadi, Arnold, Susanne, Brennan, Paul, McKay, James D., Field, John K., Shete, Sanjay S., Le Marchand, Loic, Liu, Geoffrey, Andrew, Angeline S., Kiemeney, Lambertus A., Zienolddiny-Narui, Shan, Behndig, Annelie, Johansson, Mikael, Cox, Angie, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Hung, Rayjean J., Amos, Christopher I., Lin, Xihong, and Christiani, David C.

Published
2024
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7. Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer.

Author

Byun, Jinyoung, Han, Younghun, Li, Yafang, Xia, Jun, Long, Erping, Choi, Jiyeon, Xiao, Xiangjun, Zhu, Meng, Zhou, Wen, Sun, Ryan, Bossé, Yohan, Song, Zhuoyi, Schwartz, Ann, Lusk, Christine, Rafnar, Thorunn, Stefansson, Kari, Zhang, Tongwu, Zhao, Wei, Pettit, Rowland W, Liu, Yanhong, Li, Xihao, Zhou, Hufeng, Walsh, Kyle M, Gorlov, Ivan, Gorlova, Olga, Zhu, Dakai, Rosenberg, Susan M, Pinney, Susan, Bailey-Wilson, Joan E, Mandal, Diptasri, de Andrade, Mariza, Gaba, Colette, Willey, James C, You, Ming, Anderson, Marshall, Wiencke, John K, Albanes, Demetrius, Lam, Stephan, Tardon, Adonina, Chen, Chu, Goodman, Gary, Bojeson, Stig, Brenner, Hermann, Landi, Maria Teresa, Chanock, Stephen J, Johansson, Mattias, Muley, Thomas, Risch, Angela, Wichmann, H-Erich, Bickeböller, Heike, Christiani, David C, Rennert, Gad, Arnold, Susanne, Field, John K, Shete, Sanjay, Le Marchand, Loic, Melander, Olle, Brunnstrom, Hans, Liu, Geoffrey, Andrew, Angeline S, Kiemeney, Lambertus A, Shen, Hongbing, Zienolddiny, Shanbeh, Grankvist, Kjell, Johansson, Mikael, Caporaso, Neil, Cox, Angela, Hong, Yun-Chul, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B, Aldrich, Melinda C, Patel, Alpa, Lan, Qing, Rothman, Nathaniel, Taylor, Fiona, Kachuri, Linda, Witte, John S, Sakoda, Lori C, Spitz, Margaret, Brennan, Paul, Lin, Xihong, McKay, James, Hung, Rayjean J, and Amos, Christopher I

Subjects
Humans, Lung Neoplasms, Genetic Predisposition to Disease, RNA-Binding Proteins, DNA-Binding Proteins, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, Human Genome, Cancer, Genetics, Lung, 2.1 Biological and endogenous factors, Aetiology, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

Published
2022

9. Accounting for EGFR mutations in epidemiological analyses of non-small cell lung cancers: Examples based on the International Lung Cancer Consortium data

Author

Schmid, Sabine, Jiang, Mei, Brown, M Catherine, Fares, Aline, Garcia, Miguel, Soriano, Joelle, Dong, Mei, Thomas, Sera, Kohno, Takashi, Leal, Leticia Ferro, Diao, Nancy, Xie, Juntao, Wang, Zhichao, Zaridze, David, Holcatova, Ivana, Lissowska, Jolanta, Świątkowska, Beata, Mates, Dana, Savic, Milan, Wenzlaff, Angela S, Harris, Curtis C, Caporaso, Neil E, Ma, Hongxia, Fernandez-Tardon, Guillermo, Barnett, Matthew J, Goodman, Gary, Davies, Michael PA, Pérez-Ríos, Mónica, Taylor, Fiona, Duell, Eric J, Schoettker, Ben, Brenner, Hermann, Andrew, Angeline, Cox, Angela, Ruano-Ravina, Alberto, Field, John K, Marchand, Loic Le, Wang, Ying, Chen, Chu, Tardon, Adonina, Shete, Sanjay, Schabath, Matthew B, Shen, Hongbing, Landi, Maria Teresa, Ryan, Brid M, Schwartz, Ann G, Qi, Lihong, Sakoda, Lori C, Brennan, Paul, Yang, Ping, Zhang, Jie, Christiani, David C, Reis, Rui Manuel, Shiraishi, Kouya, Hung, Rayjean J, Xu, Wei, and Liu, Geoffrey

Subjects
Lung, Lung Cancer, Cancer, Prevention, Carcinoma, Non-Small-Cell Lung, ErbB Receptors, Humans, Lung Neoplasms, Mutation, Survival Analysis, Medical and Health Sciences, Epidemiology
Abstract

BackgroundSomatic EGFR mutations define a subset of non-small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches.MethodsThrough analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status.ResultsOf 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74-0.77) in the training and 0.77 (95% CI, 0.74-0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients.ConclusionsWe introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC.ImpactThe proposed method is generalizable in the common occurrence in which EGFR-status data are missing.

Published
2022

10. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

Author

Landi, Maria Teresa, Stevens, Victoria, Wang, Ying, Albanes, Demetrios, Caporaso, Neil, Brennan, Paul, Amos, Christopher I., Shete, Sanjay, Hung, Rayjean J., Bickeböller, Heike, Risch, Angela, Houlston, Richard, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Johansson, Mattias, Wichmann, H-Erich, Christiani, David, Rennert, Gadi, Arnold, Susanne, Field, John K., Le Marchand, Loic, Melander, Olle, Brunnström, Hans, Liu, Geoffrey, Andrew, Angeline, Kiemeney, Lambertus A., Shen, Hongbing, Zienolddiny, Shan, Grankvist, Kjell, Johansson, Mikael, Teare, M. Dawn, Hong, Yun-Chul, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Al Olama, Ali Amin, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Chanock, Stephen, Tangen, Catherine M., Batra, Jyotsna, Clements, Judith A., Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie J., Wolk, Alicja, West, Catharine M.L., Mucci, Lorelei A., Cancel-Tassin, Géraldine, Koutros, Stella, Sørensen, Karina Dalsgaard, Grindedal, Eli Marie, Neal, David E., Hamdy, Freddie C., Donovan, Jenny L., Travis, Ruth C., Hamilton, Robert J., Ingles, Sue Ann, Rosenstein, Barry S., Lu, Yong-Jie, Giles, Graham G., MacInnis, Robert J., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Stanfrod, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Logothetis, Christopher J., John, Esther M., Teixeira, Manuel R., Neuhausen, Susan L., De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F., Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A., Castelao, Jose Esteban, Roobol, Monique J., Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Hunter, David J., Kraft, Peter, Blot, William J., Riboli, Elio, Yarmolinsky, James, Robinson, Jamie W., Mariosa, Daniela, Karhunen, Ville, Huang, Jian, Dimou, Niki, Murphy, Neil, Burrows, Kimberley, Bouras, Emmanouil, Smith-Byrne, Karl, Lewis, Sarah J., Galesloot, Tessel E., Vermeulen, Sita, Martin, Paul, Hou, Lifang, Newcomb, Polly A., White, Emily, Wu, Anna H., Le Marchand, Loïc, Phipps, Amanda I., Buchanan, Daniel D., Zhao, Sizheng Steven, Gill, Dipender, Chanock, Stephen J., Purdue, Mark P., Davey Smith, George, Herzig, Karl-Heinz, Järvelin, Marjo-Riitta, Amos, Chris I., Dehghan, Abbas, Gunter, Marc J., Tsilidis, Kostas K., and Martin, Richard M.

Published
2024
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13. Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Author

Shi, Jianxin, Shiraishi, Kouya, Choi, Jiyeon, Matsuo, Keitaro, Chen, Tzu-Yu, Dai, Juncheng, Hung, Rayjean J., Chen, Kexin, Shu, Xiao-Ou, Kim, Young Tae, Landi, Maria Teresa, Lin, Dongxin, Zheng, Wei, Yin, Zhihua, Zhou, Baosen, Song, Bao, Wang, Jiucun, Seow, Wei Jie, Song, Lei, Chang, I-Shou, Hu, Wei, Chien, Li-Hsin, Cai, Qiuyin, Hong, Yun-Chul, Kim, Hee Nam, Wu, Yi-Long, Wong, Maria Pik, Richardson, Brian Douglas, Funderburk, Karen M., Li, Shilan, Zhang, Tongwu, Breeze, Charles, Wang, Zhaoming, Blechter, Batel, Bassig, Bryan A., Kim, Jin Hee, Albanes, Demetrius, Wong, Jason Y. Y., Shin, Min-Ho, Chung, Lap Ping, Yang, Yang, An, She-Juan, Zheng, Hong, Yatabe, Yasushi, Zhang, Xu-Chao, Kim, Young-Chul, Caporaso, Neil E., Chang, Jiang, Ho, James Chung Man, Kubo, Michiaki, Daigo, Yataro, Song, Minsun, Momozawa, Yukihide, Kamatani, Yoichiro, Kobayashi, Masashi, Okubo, Kenichi, Honda, Takayuki, Hosgood, Dean H., Kunitoh, Hideo, Patel, Harsh, Watanabe, Shun-ichi, Miyagi, Yohei, Nakayama, Haruhiko, Matsumoto, Shingo, Horinouchi, Hidehito, Tsuboi, Masahiro, Hamamoto, Ryuji, Goto, Koichi, Ohe, Yuichiro, Takahashi, Atsushi, Goto, Akiteru, Minamiya, Yoshihiro, Hara, Megumi, Nishida, Yuichiro, Takeuchi, Kenji, Wakai, Kenji, Matsuda, Koichi, Murakami, Yoshinori, Shimizu, Kimihiro, Suzuki, Hiroyuki, Saito, Motonobu, Ohtaki, Yoichi, Tanaka, Kazumi, Wu, Tangchun, Wei, Fusheng, Dai, Hongji, Machiela, Mitchell J., Su, Jian, Kim, Yeul Hong, Oh, In-Jae, Lee, Victor Ho Fun, Chang, Gee-Chen, Tsai, Ying-Huang, Chen, Kuan-Yu, Huang, Ming-Shyan, Su, Wu-Chou, Chen, Yuh-Min, Seow, Adeline, Park, Jae Yong, Kweon, Sun-Seog, Chen, Kun-Chieh, Gao, Yu-Tang, Qian, Biyun, Wu, Chen, Lu, Daru, Liu, Jianjun, Schwartz, Ann G., Houlston, Richard, Spitz, Margaret R., Gorlov, Ivan P., Wu, Xifeng, Yang, Ping, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Johansson, Mattias, Risch, Angela, Bickeböller, Heike, Ji, Bu-Tian, Wichmann, H-Erich, Christiani, David C., Rennert, Gadi, Arnold, Susanne, Brennan, Paul, McKay, James, Field, John K., Shete, Sanjay S., Le Marchand, Loic, Liu, Geoffrey, Andrew, Angeline, Kiemeney, Lambertus A., Zienolddiny-Narui, Shan, Grankvist, Kjell, Johansson, Mikael, Cox, Angela, Taylor, Fiona, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Jeon, Hyo-Sung, Jiang, Shih Sheng, Sung, Jae Sook, Chen, Chung-Hsing, Hsiao, Chin-Fu, Jung, Yoo Jin, Guo, Huan, Hu, Zhibin, Burdett, Laurie, Yeager, Meredith, Hutchinson, Amy, Hicks, Belynda, Liu, Jia, Zhu, Bin, Berndt, Sonja I., Wu, Wei, Wang, Junwen, Li, Yuqing, Choi, Jin Eun, Park, Kyong Hwa, Sung, Sook Whan, Liu, Li, Kang, Chang Hyun, Wang, Wen-Chang, Xu, Jun, Guan, Peng, Tan, Wen, Yu, Chong-Jen, Yang, Gong, Sihoe, Alan Dart Loon, Chen, Ying, Choi, Yi Young, Kim, Jun Suk, Yoon, Ho-Il, Park, In Kyu, Xu, Ping, He, Qincheng, Wang, Chih-Liang, Hung, Hsiao-Han, Vermeulen, Roel C. H., Cheng, Iona, Wu, Junjie, Lim, Wei-Yen, Tsai, Fang-Yu, Chan, John K. C., Li, Jihua, Chen, Hongyan, Lin, Hsien-Chih, Jin, Li, Liu, Jie, Sawada, Norie, Yamaji, Taiki, Wyatt, Kathleen, Li, Shengchao A., Ma, Hongxia, Zhu, Meng, Wang, Zhehai, Cheng, Sensen, Li, Xuelian, Ren, Yangwu, Chao, Ann, Iwasaki, Motoki, Zhu, Junjie, Jiang, Gening, Fei, Ke, Wu, Guoping, Chen, Chih-Yi, Chen, Chien-Jen, Yang, Pan-Chyr, Yu, Jinming, Stevens, Victoria L., Fraumeni, Jr, Joseph F., Chatterjee, Nilanjan, Gorlova, Olga Y., Hsiung, Chao Agnes, Amos, Christopher I., Shen, Hongbing, Chanock, Stephen J., Rothman, Nathaniel, Kohno, Takashi, and Lan, Qing

Published
2023
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14. The relationship between body-mass index and overall survival in non-small cell lung cancer by sex, smoking status, and race: A pooled analysis of 20,937 International lung Cancer consortium (ILCCO) patients

Author

Jiang, Mei, Fares, Aline F, Shepshelovich, Daniel, Yang, Ping, Christiani, David, Zhang, Jie, Shiraishi, Kouya, Ryan, Brid M, Chen, Chu, Schwartz, Ann G, Tardon, Adonina, Shete, Sanjay, Schabath, Matthew B, Teare, M Dawn, Le Marchand, Loic, Zhang, Zuo-Feng, Field, John K, Brenner, Hermann, Diao, Nancy, Xie, Juntao, Kohno, Takashi, Harris, Curtis C, Wenzlaff, Angela S, Fernandez-Tardon, Guillermo, Ye, Yuanqing, Taylor, Fiona, Wilkens, Lynne R, Davies, Michael, Liu, Yi, Barnett, Matt J, Goodman, Gary E, Morgenstern, Hal, Holleczek, Bernd, Thomas, Sera, Brown, M Catherine, Hung, Rayjean J, Xu, Wei, and Liu, Geoffrey

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Obesity, Lung, Lung Cancer, Cancer, Nutrition, Clinical Research, Stroke, Body Mass Index, Carcinoma, Non-Small-Cell Lung, Female, Humans, Lung Neoplasms, Male, Overweight, Risk Factors, Smoking, Body mass index, Lung cancer, Interaction, Clinical Sciences, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis
Abstract

IntroductionThe relationship between Body-Mass-Index (BMI) and lung cancer prognosis is heterogeneous. We evaluated the impact of sex, smoking and race on the relationship between BMI and overall survival (OS) in non-small-cell-lung-cancer (NSCLC).MethodsData from 16 individual ILCCO studies were pooled to assess interactions between BMI and the following factors on OS: self-reported race, smoking status and sex, using Cox models (adjusted hazard ratios; aHR) with interaction terms and adjusted penalized smoothing spline plots in stratified analyses.ResultsAmong 20,937 NSCLC patients with BMI values, females = 47 %; never-smokers = 14 %; White-patients = 76 %. BMI showed differential survival according to race whereby compared to normal-BMI patients, being underweight was associated with poor survival among white patients (OS, aHR = 1.66) but not among black patients (aHR = 1.06; pinteraction = 0.02). Comparing overweight/obese to normal weight patients, Black NSCLC patients who were overweight/obese also had relatively better OS (pinteraction = 0.06) when compared to White-patients. BMI was least associated with survival in Asian-patients and never-smokers. The outcomes of female ever-smokers at the extremes of BMI were associated with worse outcomes in both the underweight (pinteraction

Published
2021

15. Association between duration of smoking abstinence before non-small-cell lung cancer diagnosis and survival: a retrospective, pooled analysis of cohort studies

Author

Fares, Aline F, Li, Yao, Jiang, Mei, Brown, M Catherine, Lam, Andrew C L, Aggarwal, Reenika, Schmid, Sabine, Leighl, Natasha B, Shepherd, Frances A, Wang, Zhichao, Diao, Nancy, Wenzlaff, Angela S, Xie, Juntao, Kohno, Takashi, Caporaso, Neil E, Harris, Curtis, Ma, Hongxia, Barnett, Matthew J, Leal, Leticia Ferro, Fernandez-Tardon, G, Pérez-Ríos, Mónica, Davies, Michael P A, Taylor, Fiona, Schöttker, Ben, Brennan, Paul, Zaridze, David, Holcatova, Ivana, Lissowska, Jolanta, Świątkowska, Beata, Mates, Dana, Savic, Milan, Brenner, Hermann, Andrew, Angeline, Cox, Angela, Field, John K, Ruano-Ravina, Alberto, Shete, Sanjay S, Tardon, Adonina, Wang, Ying, Le Marchand, Loic, Reis, Rui Manuel, Schabath, Matthew B, Chen, Chu, Shen, Hongbing, Ryan, Brid M, Landi, Maria Teresa, Shiraishi, Kouya, Zhang, Jie, Schwartz, Ann G, Tsao, Ming S, Christiani, David C, Yang, Ping, Hung, Rayjean J, Xu, Wei, and Liu, Geoffrey

Published
2023
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16. Mosaic Chromosomal Alterations Are Associated With Increased Lung Cancer Risk: Insight From the INTEGRAL-ILCCO Cohort Analysis

Author

Cheng, Chao, Hong, Wei, Li, Yafang, Xiao, Xiangjun, McKay, James, Han, Younghun, Byun, Jinyoung, Peng, Bo, Albanes, Demetrios, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Landi, Maria T., Johansson, Mattias, Risch, Angela, Bickeböller, Heike, Wichmann, H-Erich, Christiani, David C., Rennert, Gad, Arnold, Susanne, Goodman, Gary, Field, John K., Davies, Michael P.A., Shete, Sanjay S., Le Marchand, Loic, Liu, Geoffrey, Hung, Rayjean J., Andrew, Angeline S., Kiemeney, Lambertus A., Zhu, Meng, Shen, Hongbing, Zienolddiny, Shan, Grankvist, Kjell, Johansson, Mikael, Cox, Angela, Hong, Yun-Chul, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Brennan, Paul, Li, Yong, Gorlova, Olga, Gorlov, Ivan, and Amos, Christopher I.

Published
2023
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17. Immune-mediated genetic pathways resulting in pulmonary function impairment increase lung cancer susceptibility.

Author

Kachuri, Linda, Johansson, Mattias, Rashkin, Sara R, Graff, Rebecca E, Bossé, Yohan, Manem, Venkata, Caporaso, Neil E, Landi, Maria Teresa, Christiani, David C, Vineis, Paolo, Liu, Geoffrey, Scelo, Ghislaine, Zaridze, David, Shete, Sanjay S, Albanes, Demetrius, Aldrich, Melinda C, Tardón, Adonina, Rennert, Gad, Chen, Chu, Goodman, Gary E, Doherty, Jennifer A, Bickeböller, Heike, Field, John K, Davies, Michael P, Dawn Teare, M, Kiemeney, Lambertus A, Bojesen, Stig E, Haugen, Aage, Zienolddiny, Shanbeh, Lam, Stephen, Le Marchand, Loïc, Cheng, Iona, Schabath, Matthew B, Duell, Eric J, Andrew, Angeline S, Manjer, Jonas, Lazarus, Philip, Arnold, Susanne, McKay, James D, Emami, Nima C, Warkentin, Matthew T, Brhane, Yonathan, Obeidat, Ma'en, Martin, Richard M, Relton, Caroline, Davey Smith, George, Haycock, Philip C, Amos, Christopher I, Brennan, Paul, Witte, John S, and Hung, Rayjean J

Subjects
Lung, Humans, Lung Neoplasms, Genetic Predisposition to Disease, Respiratory Function Tests, Vital Capacity, Forced Expiratory Volume, Prospective Studies, Phenotype, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, Female, Male, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide
Abstract

Impaired lung function is often caused by cigarette smoking, making it challenging to disentangle its role in lung cancer susceptibility. Investigation of the shared genetic basis of these phenotypes in the UK Biobank and International Lung Cancer Consortium (29,266 cases, 56,450 controls) shows that lung cancer is genetically correlated with reduced forced expiratory volume in one second (FEV1: rg = 0.098, p = 2.3 × 10-8) and the ratio of FEV1 to forced vital capacity (FEV1/FVC: rg = 0.137, p = 2.0 × 10-12). Mendelian randomization analyses demonstrate that reduced FEV1 increases squamous cell carcinoma risk (odds ratio (OR) = 1.51, 95% confidence intervals: 1.21-1.88), while reduced FEV1/FVC increases the risk of adenocarcinoma (OR = 1.17, 1.01-1.35) and lung cancer in never smokers (OR = 1.56, 1.05-2.30). These findings support a causal role of pulmonary impairment in lung cancer etiology. Integrative analyses reveal that pulmonary function instruments, including 73 novel variants, influence lung tissue gene expression and implicate immune-related pathways in mediating the observed effects on lung carcinogenesis.

Published
2020

18. Respiratory and Cardiometabolic Comorbidities and Stages I to III NSCLC Survival: A Pooled Analysis From the International Lung Cancer Consortium

Author

García-Pardo, Miguel, Chang, Amy, Schmid, Sabine, Dong, Mei, Brown, M. Catherine, Christiani, David, Tindel, Hilary Aurora, Brennan, Paul, Chen, Chu, Zhang, Jie, Ryan, Brid M., Zaridze, David, Schabath, Matthew B., Leal, Leticia Ferro, Reis, Rui Manuel, Tardon, Adonina, Fernández-Tardon, Guillermo, Shete, Sanjay S., Andrew, Angeline, Brenner, Hermann, Xu, Wei, Hung, Rayjean J., and Liu, Geoffrey

Published
2023
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19. Body Mass Index (BMI), BMI Change, and Overall Survival in Patients With SCLC and NSCLC: A Pooled Analysis of the International Lung Cancer Consortium

Author

Shepshelovich, Daniel, Xu, Wei, Lu, Lin, Fares, Aline, Yang, Ping, Christiani, David, Zhang, Jie, Shiraishi, Kouya, Ryan, Brid M, Chen, Chu, Schwartz, Ann G, Tardon, Adonina, Wu, Xifeng, Schabath, Matthew B, Teare, M Dawn, Le Marchand, Loic, Zhang, Zuo-Feng, Field, John K, Brenner, Hermann, Diao, Nancy, Xie, Juntao, Kohno, Takashi, Harris, Curtis C, Wenzlaff, Angela S, Fernandez-Tardon, Guillermo, Ye, Yuanqing, Taylor, Fiona, Wilkens, Lynne R, Davies, Michael, Liu, Yi, Barnett, Matt J, Goodman, Gary E, Morgenstern, Hal, Holleczek, Bernd, Brown, M Catherine, Liu, Geoffrey, and Hung, Rayjean J

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Obesity, Lung Cancer, Lung, Nutrition, Prevention, Cancer, Adolescent, Adult, Aged, Aged, 80 and over, Body Mass Index, Carcinoma, Non-Small-Cell Lung, Female, Humans, Lung Neoplasms, Male, Middle Aged, Risk Factors, Small Cell Lung Carcinoma, Survival Analysis, Young Adult, Body mass index, Lung cancer, Survival, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis
Abstract

IntroductionThe relationships between morbid obesity, changes in body mass index (BMI) before cancer diagnosis, and lung cancer outcomes by histology (SCLC and NSCLC) have not been well studied.MethodsIndividual level data analysis was performed on 25,430 patients with NSCLC and 2787 patients with SCLC from 16 studies of the International Lung Cancer Consortium evaluating the association between various BMI variables and lung cancer overall survival, reported as adjusted hazard ratios (aHRs) from Cox proportional hazards models and adjusted penalized smoothing spline plots.ResultsOverall survival of NSCLC had putative U-shaped hazard ratio relationships with BMI based on spline plots: being underweight (BMI < 18.5 kg/m2; aHR = 1.56; 95% confidence interval [CI]:1.43-1.70) or morbidly overweight (BMI > 40 kg/m2; aHR = 1.09; 95% CI: 0.95-1.26) at the time of diagnosis was associated with worse stage-specific prognosis, whereas being overweight (25 kg/m2 ≤ BMI < 30 kg/m2; aHR = 0.89; 95% CI: 0.85-0.95) or obese (30 kg/m2 ≤ BMI ≤ 40 kg/m2; aHR = 0.86; 95% CI: 0.82-0.91) was associated with improved survival. Although not significant, a similar pattern was seen with SCLC. Compared with an increased or stable BMI from the period between young adulthood until date of diagnosis, a decreased BMI was associated with worse outcomes in NSCLC (aHR = 1.24; 95% CI: 1.2-1.3) and SCLC patients (aHR=1.26 (95% CI: 1.0-1.6). Decreased BMI was consistently associated with worse outcome, across clinicodemographic subsets.ConclusionsBoth being underweight or morbidly obese at time of diagnosis is associated with lower stage-specific survival in independent assessments of NSCLC and SCLC patients. In addition, a decrease in BMI at lung cancer diagnosis relative to early adulthood is a consistent marker of poor survival.

Published
2019

20. Lung Cancer Risk in Never-Smokers of European Descent is Associated With Genetic Variation in the 5p15.33 TERT-CLPTM1Ll Region

Author

Hung, Rayjean J, Spitz, Margaret R, Houlston, Richard S, Schwartz, Ann G, Field, John K, Ying, Jun, Li, Yafang, Han, Younghun, Ji, Xuemei, Chen, Wei, Wu, Xifeng, Gorlov, Ivan P, Na, Jie, de Andrade, Mariza, Liu, Geoffrey, Brhane, Yonathan, Diao, Nancy, Wenzlaff, Angela, Davies, Michael PA, Liloglou, Triantafillos, Timofeeva, Maria, Muley, Thomas, Rennert, Hedy, Saliba, Walid, Ryan, Bríd M, Bowman, Elise, Barros-Dios, Juan-Miguel, Pérez-Ríos, Mónica, Morgenstern, Hal, Zienolddiny, Shanbeh, Skaug, Vidar, Ugolini, Donatella, Bonassi, Stefano, van der Heijden, Erik HFM, Tardon, Adonina, Bojesen, Stig E, Landi, Maria Teresa, Johansson, Mattias, Bickeböller, Heike, Arnold, Susanne, Le Marchand, Loic, Melander, Olle, Andrew, Angeline, Grankvist, Kjell, Caporaso, Neil, Teare, M Dawn, Schabath, Matthew B, Aldrich, Melinda C, Kiemeney, Lambertus A, Wichmann, H-Erich, Lazarus, Philip, Mayordomo, Jose, Neri, Monica, Haugen, Aage, Zhang, Zuo-Feng, Ruano-Raviña, Alberto, Brenner, Hermann, Harris, Curtis C, Orlow, Irene, Rennert, Gadi, Risch, Angela, Brennan, Paul, Christiani, David C, Amos, Christopher I, Yang, Ping, and Gorlova, Olga Y

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Human Genome, Lung Cancer, Tobacco, Prevention, Cancer, Genetics, Clinical Research, Tobacco Smoke and Health, Lung, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Case-Control Studies, Chromosomes, Human, Pair 5, Europe, Female, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genotyping Techniques, Humans, Lung Neoplasms, Membrane Proteins, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors, Telomerase, Lung cancer, Never smokers, Genome-wide association study, Genetic susceptibility, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis
Abstract

IntroductionInherited susceptibility to lung cancer risk in never-smokers is poorly understood. The major reason for this gap in knowledge is that this disease is relatively uncommon (except in Asians), making it difficult to assemble an adequate study sample. In this study we conducted a genome-wide association study on the largest, to date, set of European-descent never-smokers with lung cancer.MethodsWe conducted a two-phase (discovery and replication) genome-wide association study in never-smokers of European descent. We further augmented the sample by performing a meta-analysis with never-smokers from the recent OncoArray study, which resulted in a total of 3636 cases and 6295 controls. We also compare our findings with those in smokers with lung cancer.ResultsWe detected three genome-wide statistically significant single nucleotide polymorphisms rs31490 (odds ratio [OR]: 0.769, 95% confidence interval [CI]: 0.722-0.820; p value 5.31 × 10-16), rs380286 (OR: 0.770, 95% CI: 0.723-0.820; p value 4.32 × 10-16), and rs4975616 (OR: 0.778, 95% CI: 0.730-0.829; p value 1.04 × 10-14). All three mapped to Chromosome 5 CLPTM1L-TERT region, previously shown to be associated with lung cancer risk in smokers and in never-smoker Asian women, and risk of other cancers including breast, ovarian, colorectal, and prostate.ConclusionsWe found that genetic susceptibility to lung cancer in never-smokers is associated to genetic variants with pan-cancer risk effects. The comparison with smokers shows that top variants previously shown to be associated with lung cancer risk only confer risk in the presence of tobacco exposure, underscoring the importance of gene-environment interactions in the etiology of this disease.

Published
2019

21. A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians

Author

Zhang, Ruyang, Shen, Sipeng, Wei, Yongyue, Zhu, Ying, Li, Yi, Chen, Jiajin, Guan, Jinxing, Pan, Zoucheng, Wang, Yuzhuo, Zhu, Meng, Xie, Junxing, Xiao, Xiangjun, Zhu, Dakai, Li, Yafang, Albanes, Demetrios, Landi, Maria Teresa, Caporaso, Neil E., Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Johansson, Mattias, Risch, Angela, Bickeböller, Heike, Wichmann, H-Erich, Rennert, Gadi, Arnold, Susanne, Brennan, Paul, McKay, James D., Field, John K., Shete, Sanjay S., Le Marchand, Loic, Liu, Geoffrey, Andrew, Angeline S., Kiemeney, Lambertus A., Zienolddiny-Narui, Shan, Behndig, Annelie, Johansson, Mikael, Cox, Angela, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Dai, Juncheng, Ma, Hongxia, Zhao, Yang, Hu, Zhibin, Hung, Rayjean J., Amos, Christopher I., Shen, Hongbing, Chen, Feng, and Christiani, David C.

Published
2022
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24. Gene–gene interaction of AhRwith and within the Wntcascade affects susceptibility to lung cancer

Author

Rosenberger, Albert, Muttray, Nils, Hung, Rayjean J., Christiani, David C., Caporaso, Neil E., Liu, Geoffrey, Bojesen, Stig E., Le Marchand, Loic, Albanes, Demetrios, Aldrich, Melinda C., Tardon, Adonina, Fernández-Tardón, Guillermo, Rennert, Gad, Field, John K., Davies, Michael P. A., Liloglou, Triantafillos, Kiemeney, Lambertus A., Lazarus, Philip, Wendel, Bernadette, Haugen, Aage, Zienolddiny, Shanbeh, Lam, Stephen, Schabath, Matthew B., Andrew, Angeline S., Duell, Eric J., Arnold, Susanne M., Goodman, Gary E., Chen, Chu, Doherty, Jennifer A., Taylor, Fiona, Cox, Angela, Woll, Penella J., Risch, Angela, Muley, Thomas R., Johansson, Mikael, Brennan, Paul, Landi, Maria Teresa, Shete, Sanjay S., Amos, Christopher I., and Bickeböller, Heike

Published
2022
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27. The association of body composition phenotypes before chemotherapy with epithelial ovarian cancer mortality

Author

Davis, Evan W, primary, Attwood, Kristopher, additional, Prunier, Joseph, additional, Paragh, Gyorgy, additional, Joseph, Janine M, additional, Klein, André, additional, Roche, Charles, additional, Barone, Nancy, additional, Etter, John Lewis, additional, Ray, Andrew D, additional, Trabert, Britton, additional, Schabath, Matthew B, additional, Peres, Lauren C, additional, and Cannioto, Rikki, additional

Published
2024
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29. Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study

Author

Carreras-Torres, Robert, Johansson, Mattias, Haycock, Philip C, Wade, Kaitlin H, Relton, Caroline L, Martin, Richard M, Smith, George Davey, Albanes, Demetrius, Aldrich, Melinda C, Andrew, Angeline, Arnold, Susanne M, Bickeböller, Heike, Bojesen, Stig E, Brunnström, Hans, Manjer, Jonas, Brüske, Irene, Caporaso, Neil E, Chen, Chu, Christiani, David C, Christian, W Jay, Doherty, Jennifer A, Duell, Eric J, Field, John K, Davies, Michael PA, Marcus, Michael W, Goodman, Gary E, Grankvist, Kjell, Haugen, Aage, Hong, Yun-Chul, Kiemeney, Lambertus A, van der Heijden, Erik HFM, Kraft, Peter, Johansson, Mikael B, Lam, Stephen, Landi, Maria Teresa, Lazarus, Philip, Le Marchand, Loïc, Liu, Geoffrey, Melander, Olle, Park, Sungshim L, Rennert, Gad, Risch, Angela, Haura, Eric B, Scelo, Ghislaine, Zaridze, David, Mukeriya, Anush, Savić, Milan, Lissowska, Jolanta, Swiatkowska, Beata, Janout, Vladimir, Holcatova, Ivana, Mates, Dana, Schabath, Matthew B, Shen, Hongbing, Tardon, Adonina, Teare, M Dawn, Woll, Penella, Tsao, Ming-Sound, Wu, Xifeng, Yuan, Jian-Min, Hung, Rayjean J, Amos, Christopher I, McKay, James, and Brennan, Paul

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Oncology and Carcinogenesis, Genetics, Lung, Nutrition, Tobacco Smoke and Health, Prevention, Cancer, Tobacco, Obesity, Clinical Research, Lung Cancer, Aetiology, 2.1 Biological and endogenous factors, Body Mass Index, Fasting, Humans, Insulin, Insulin Resistance, Likelihood Functions, Lipids, Lung Neoplasms, Mendelian Randomization Analysis, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, General Science & Technology
Abstract

BackgroundAssessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer.Methods and findingsWe identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79-1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results.ConclusionsOur results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.

Published
2017

30. Genomic and evolutionary classification of lung cancer in never smokers

Author

Zhang, Tongwu, Joubert, Philippe, Ansari-Pour, Naser, Zhao, Wei, Hoang, Phuc H., Lokanga, Rachel, Moye, Aaron L., Rosenbaum, Jennifer, Gonzalez-Perez, Abel, Martínez-Jiménez, Francisco, Castro, Andrea, Muscarella, Lucia Anna, Hofman, Paul, Consonni, Dario, Pesatori, Angela C., Kebede, Michael, Li, Mengying, Gould Rothberg, Bonnie E., Peneva, Iliana, Schabath, Matthew B., Poeta, Maria Luana, Costantini, Manuela, Hirsch, Daniela, Heselmeyer-Haddad, Kerstin, Hutchinson, Amy, Olanich, Mary, Lawrence, Scott M., Lenz, Petra, Duggan, Maire, Bhawsar, Praphulla M. S., Sang, Jian, Kim, Jung, Mendoza, Laura, Saini, Natalie, Klimczak, Leszek J., Islam, S. M. Ashiqul, Otlu, Burcak, Khandekar, Azhar, Cole, Nathan, Stewart, Douglas R., Choi, Jiyeon, Brown, Kevin M., Caporaso, Neil E., Wilson, Samuel H., Pommier, Yves, Lan, Qing, Rothman, Nathaniel, Almeida, Jonas S., Carter, Hannah, Ried, Thomas, Kim, Carla F., Lopez-Bigas, Nuria, Garcia-Closas, Montserrat, Shi, Jianxin, Bossé, Yohan, Zhu, Bin, Gordenin, Dmitry A., Alexandrov, Ludmil B., Chanock, Stephen J., Wedge, David C., and Landi, Maria Teresa

Published
2021
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32. Lung cancer in ever- and never-smokers : findings from multi-population GWAS studies

Author

Li, Yafang, Xiao, Xiangjun, Li, Jianrong, Han, Younghun, Cheng, Chao, Fernandes, Gail F., Slewitzke, Shannon E., Rosenberg, Susan M., Zhu, Meng, Byun, Jinyoung, Bossé, Yohan, McKay, James D., Albanes, Demetrios, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Landi, Maria T., Johansson, Mattias, Risch, Angela, Bickeböller, Heike, Wichmann, H-Erich, Christiani, David C., Rennert, Gad, Arnold, Susanne M., Goodman, Gary E., Field, John K., Davies, Michael P A, Shete, Sanjay, Marchand, Loïc Le, Liu, Geoffrey, Hung, Rayjean J., Andrew, Angeline S., Kiemeney, Lambertus A., Sun, Ryan, Zienolddiny, Shanbeh, Grankvist, Kjell, Johansson, Mikael, Caporaso, Neil E., Cox, Angela, Hong, Yun-Chul, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Schwartz, Ann G., Gorlov, Ivan, Purrington, Kristen S., Yang, Ping, Liu, Yanhong, Bailey-Wilson, Joan E., Pinney, Susan M., Mandal, Diptasri, Willey, James C., Gaba, Colette, Brennan, Paul, Xia, Jun, Shen, Hongbing, Amos, Christopher I., Li, Yafang, Xiao, Xiangjun, Li, Jianrong, Han, Younghun, Cheng, Chao, Fernandes, Gail F., Slewitzke, Shannon E., Rosenberg, Susan M., Zhu, Meng, Byun, Jinyoung, Bossé, Yohan, McKay, James D., Albanes, Demetrios, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Landi, Maria T., Johansson, Mattias, Risch, Angela, Bickeböller, Heike, Wichmann, H-Erich, Christiani, David C., Rennert, Gad, Arnold, Susanne M., Goodman, Gary E., Field, John K., Davies, Michael P A, Shete, Sanjay, Marchand, Loïc Le, Liu, Geoffrey, Hung, Rayjean J., Andrew, Angeline S., Kiemeney, Lambertus A., Sun, Ryan, Zienolddiny, Shanbeh, Grankvist, Kjell, Johansson, Mikael, Caporaso, Neil E., Cox, Angela, Hong, Yun-Chul, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Schwartz, Ann G., Gorlov, Ivan, Purrington, Kristen S., Yang, Ping, Liu, Yanhong, Bailey-Wilson, Joan E., Pinney, Susan M., Mandal, Diptasri, Willey, James C., Gaba, Colette, Brennan, Paul, Xia, Jun, Shen, Hongbing, and Amos, Christopher I.

Abstract

BACKGROUND: Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer. METHODS: We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer. RESULTS: Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10-8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior. CONCLUSIONS: We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. IMPACT: Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

Published
2024
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33. SeNMo: A Self-Normalizing Deep Learning Model for Enhanced Multi-Omics Data Analysis in Oncology

Author

Waqas, Asim, Tripathi, Aakash, Ahmed, Sabeen, Mukund, Ashwin, Farooq, Hamza, Schabath, Matthew B., Stewart, Paul, Naeini, Mia, Rasool, Ghulam, Waqas, Asim, Tripathi, Aakash, Ahmed, Sabeen, Mukund, Ashwin, Farooq, Hamza, Schabath, Matthew B., Stewart, Paul, Naeini, Mia, and Rasool, Ghulam

Abstract

Multi-omics research has enhanced our understanding of cancer heterogeneity and progression. Investigating molecular data through multi-omics approaches is crucial for unraveling the complex biological mechanisms underlying cancer, thereby enabling effective diagnosis, treatment, and prevention strategies. However, predicting patient outcomes through integration of all available multi-omics data is an under-study research direction. Here, we present SeNMo (Self-normalizing Network for Multi-omics), a deep neural network trained on multi-omics data across 33 cancer types. SeNMo is efficient in handling multi-omics data characterized by high-width (many features) and low-length (fewer samples) attributes. We trained SeNMo for the task of overall survival using pan-cancer data involving 33 cancer sites from Genomics Data Commons (GDC). The training data includes gene expression, DNA methylation, miRNA expression, DNA mutations, protein expression modalities, and clinical data. We evaluated the model's performance in predicting overall survival using concordance index (C-Index). SeNMo performed consistently well in training regime, with the validation C-Index of 0.76 on GDC's public data. In the testing regime, SeNMo performed with a C-Index of 0.758 on a held-out test set. The model showed an average accuracy of 99.8% on the task of classifying the primary cancer type on the pan-cancer test cohort. SeNMo proved to be a mini-foundation model for multi-omics oncology data because it demonstrated robust performance, and adaptability not only across molecular data types but also on the classification task of predicting the primary cancer type of patients. SeNMo can be further scaled to any cancer site and molecular data type. We believe SeNMo and similar models are poised to transform the oncology landscape, offering hope for more effective, efficient, and patient-centric cancer care.

Published
2024

34. Comprehensive functional annotation of susceptibility variants identifies genetic heterogeneity between lung adenocarcinoma and squamous cell carcinoma

Author

Qin, Na, Li, Yuancheng, Wang, Cheng, Zhu, Meng, Dai, Juncheng, Hong, Tongtong, Albanes, Demetrius, Lam, Stephen, Tardon, Adonina, Chen, Chu, Goodman, Gary, Bojesen, Stig E., Landi, Maria Teresa, Johansson, Mattias, Risch, Angela, Wichmann, H-Erich, Bickeboller, Heike, Rennert, Gadi, Arnold, Susanne, Brennan, Paul, Field, John K., Shete, Sanjay, Le Marchand, Loic, Melander, Olle, Brunnstrom, Hans, Liu, Geoffrey, Hung, Rayjean J., Andrew, Angeline, Kiemeney, Lambertus A., Zienolddiny, Shan, Grankvist, Kjell, Johansson, Mikael, Caporaso, Neil, Woll, Penella, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Stevens, Victoria L., Jin, Guangfu, Christiani, David C., Hu, Zhibin, Amos, Christopher I., Ma, Hongxia, and Shen, Hongbing

Published
2021
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35. On the informative value of community‐based indoor radon values in relation to lung cancer.

Author

Rosenberger, Albert, Bickeböller, Heike, Christiani, David C., Liu, Geoffrey, Schabath, Matthew B., Duarte, Luisa F., Le Marchand, Loic, Haiman, Christopher, Landi, Teresa, Consonni, Dario, Field, John K., Davies, Michael P. A., Albanes, Demetrios, Tardón, Adonina, Fernández‐Tardón, Guillermo, Rennert, Gad, Amos, Christopher I., and Hung, Rayjean J.

Subjects
SMALL cell lung cancer, LUNG cancer, SQUAMOUS cell carcinoma, RADON, RESIDENTIAL areas
Abstract

Background: Radon is a radioactive gas and a major risk factor for lung cancer (LC). Methods: We investigated the dose–response relationship between radon and LC risk in the International Lung Cancer Consortium with 8927 cases and 5562 controls from Europe, North America, and Israel, conducted between 1992 and 2016. Spatial indoor radon exposure in the residential area (sIR) obtained from national surveys was linked to the participants' residential geolocation. Parametric linear and spline functions were fitted within a logistic regression framework. Results: We observed a non‐linear spatial‐dose response relationship for sIR < 200 Bq/m3. The lowest risk was observed for areas of mean exposure of 58 Bq/m3 (95% CI: 56.1–59.2 Bq/m3). The relative risk of lung cancer increased to the same degree in areas averaging 25 Bq/m3 (OR = 1.31, 95% CI: 1.01–1.59) as in areas with a mean of 100 Bq/m3 (OR = 1.34, 95% CI: 1.20–1.45). The strongest association was observed for small cell lung cancer and the weakest for squamous cell carcinoma. A stronger association was also observed in men, but only at higher exposure levels. The non‐linear association is primarily observed among the younger population (age < 69 years), but not in the older population, which can potentially represent different biological radiation responses. Conclusions: The sIR is useful as proxy of individual radon exposure in epidemiological studies on lung cancer. The usual assumption of a linear, no‐threshold dose–response relationship, as can be made for individual radon exposures, may not be optimal for sIR values of less than 200 Bq/m3. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Defining and Addressing Research Priorities in Cancer Cachexia through Transdisciplinary Collaboration.

Author

Park, Margaret A., Whelan, Christopher J., Ahmed, Sabeen, Boeringer, Tabitha, Brown, Joel, Crowder, Sylvia L., Gage, Kenneth, Gregg, Christopher, Jeong, Daniel K., Jim, Heather S. L., Judge, Andrew R., Mason, Tina M., Parker, Nathan, Pillai, Smitha, Qayyum, Aliya, Rajasekhara, Sahana, Rasool, Ghulam, Tinsley, Sara M., Schabath, Matthew B., and Stewart, Paul

Subjects
CACHEXIA treatment, RISK assessment, WEIGHT loss, INTERPROFESSIONAL relations, RESEARCH evaluation, BODY composition, CANCER patient medical care, EXERCISE therapy, ONCOLOGY, TUMOR markers, EATING disorders, PRIORITY (Philosophy), QUALITY of life, LEAN body mass, HEALTH behavior, CACHEXIA, TUMORS, HEALTH outcome assessment, MACHINE learning, SOCIAL support, HEALTH care teams, OVERALL survival, HOSPITAL wards, DISEASE progression, NUTRITION, EVALUATION, DISEASE risk factors, DISEASE complications
Abstract

Simple Summary: Cachexia occurs in up to 80% of patients with cancer. Although cancer-associated cachexia dramatically decreases overall survival and quality of life, it is often overlooked. To make meaningful progress in identifying cancer cachexia earlier and finding treatments for this condition, Moffitt Cancer Center held its first Cachexia Working Group Retreat in 2022. This manuscript describes the priorities discussed at the retreat and highlights collaborations that arose afterward. For many patients, the cancer continuum includes a syndrome known as cancer-associated cachexia (CAC), which encompasses the unintended loss of body weight and muscle mass, and is often associated with fat loss, decreased appetite, lower tolerance and poorer response to treatment, poor quality of life, and reduced survival. Unfortunately, there are no effective therapeutic interventions to completely reverse cancer cachexia and no FDA-approved pharmacologic agents; hence, new approaches are urgently needed. In May of 2022, researchers and clinicians from Moffitt Cancer Center held an inaugural retreat on CAC that aimed to review the state of the science, identify knowledge gaps and research priorities, and foster transdisciplinary collaborative research projects. This review summarizes research priorities that emerged from the retreat, examples of ongoing collaborations, and opportunities to move science forward. The highest priorities identified include the need to (1) evaluate patient-reported outcome (PRO) measures obtained in clinical practice and assess their use in improving CAC-related outcomes; (2) identify biomarkers (imaging, molecular, and/or behavioral) and novel analytic approaches to accurately predict the early onset of CAC and its progression; and (3) develop and test interventions (pharmacologic, nutritional, exercise-based, and through mathematical modeling) to prevent CAC progression and improve associated symptoms and outcomes. [ABSTRACT FROM AUTHOR]

Published
2024
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39. Supplementary Table S6 from Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies

Author

Li, Yafang, primary, Xiao, Xiangjun, primary, Li, Jianrong, primary, Han, Younghun, primary, Cheng, Chao, primary, Fernandes, Gail F., primary, Slewitzke, Shannon E., primary, Rosenberg, Susan M., primary, Zhu, Meng, primary, Byun, Jinyoung, primary, Bossé, Yohan, primary, McKay, James D., primary, Albanes, Demetrios, primary, Lam, Stephen, primary, Tardon, Adonina, primary, Chen, Chu, primary, Bojesen, Stig E., primary, Landi, Maria T., primary, Johansson, Mattias, primary, Risch, Angela, primary, Bickeböller, Heike, primary, Wichmann, H-Erich, primary, Christiani, David C., primary, Rennert, Gad, primary, Arnold, Susanne M., primary, Goodman, Gary E., primary, Field, John K., primary, Davies, Michael P.A., primary, Shete, Sanjay, primary, Marchand, Loïc Le, primary, Liu, Geoffrey, primary, Hung, Rayjean J., primary, Andrew, Angeline S., primary, Kiemeney, Lambertus A., primary, Sun, Ryan, primary, Zienolddiny, Shanbeh, primary, Grankvist, Kjell, primary, Johansson, Mikael, primary, Caporaso, Neil E., primary, Cox, Angela, primary, Hong, Yun-Chul, primary, Lazarus, Philip, primary, Schabath, Matthew B., primary, Aldrich, Melinda C., primary, Schwartz, Ann G., primary, Gorlov, Ivan, primary, Purrington, Kristen S., primary, Yang, Ping, primary, Liu, Yanhong, primary, Bailey-Wilson, Joan E., primary, Pinney, Susan M., primary, Mandal, Diptasri, primary, Willey, James C., primary, Gaba, Colette, primary, Brennan, Paul, primary, Xia, Jun, primary, Shen, Hongbing, primary, and Amos, Christopher I., primary

Published
2024
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40. Data from Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies

Author

Li, Yafang, primary, Xiao, Xiangjun, primary, Li, Jianrong, primary, Han, Younghun, primary, Cheng, Chao, primary, Fernandes, Gail F., primary, Slewitzke, Shannon E., primary, Rosenberg, Susan M., primary, Zhu, Meng, primary, Byun, Jinyoung, primary, Bossé, Yohan, primary, McKay, James D., primary, Albanes, Demetrios, primary, Lam, Stephen, primary, Tardon, Adonina, primary, Chen, Chu, primary, Bojesen, Stig E., primary, Landi, Maria T., primary, Johansson, Mattias, primary, Risch, Angela, primary, Bickeböller, Heike, primary, Wichmann, H-Erich, primary, Christiani, David C., primary, Rennert, Gad, primary, Arnold, Susanne M., primary, Goodman, Gary E., primary, Field, John K., primary, Davies, Michael P.A., primary, Shete, Sanjay, primary, Marchand, Loïc Le, primary, Liu, Geoffrey, primary, Hung, Rayjean J., primary, Andrew, Angeline S., primary, Kiemeney, Lambertus A., primary, Sun, Ryan, primary, Zienolddiny, Shanbeh, primary, Grankvist, Kjell, primary, Johansson, Mikael, primary, Caporaso, Neil E., primary, Cox, Angela, primary, Hong, Yun-Chul, primary, Lazarus, Philip, primary, Schabath, Matthew B., primary, Aldrich, Melinda C., primary, Schwartz, Ann G., primary, Gorlov, Ivan, primary, Purrington, Kristen S., primary, Yang, Ping, primary, Liu, Yanhong, primary, Bailey-Wilson, Joan E., primary, Pinney, Susan M., primary, Mandal, Diptasri, primary, Willey, James C., primary, Gaba, Colette, primary, Brennan, Paul, primary, Xia, Jun, primary, Shen, Hongbing, primary, and Amos, Christopher I., primary

Published
2024
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41. Figure S4 from Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies

Author

Li, Yafang, primary, Xiao, Xiangjun, primary, Li, Jianrong, primary, Han, Younghun, primary, Cheng, Chao, primary, Fernandes, Gail F., primary, Slewitzke, Shannon E., primary, Rosenberg, Susan M., primary, Zhu, Meng, primary, Byun, Jinyoung, primary, Bossé, Yohan, primary, McKay, James D., primary, Albanes, Demetrios, primary, Lam, Stephen, primary, Tardon, Adonina, primary, Chen, Chu, primary, Bojesen, Stig E., primary, Landi, Maria T., primary, Johansson, Mattias, primary, Risch, Angela, primary, Bickeböller, Heike, primary, Wichmann, H-Erich, primary, Christiani, David C., primary, Rennert, Gad, primary, Arnold, Susanne M., primary, Goodman, Gary E., primary, Field, John K., primary, Davies, Michael P.A., primary, Shete, Sanjay, primary, Marchand, Loïc Le, primary, Liu, Geoffrey, primary, Hung, Rayjean J., primary, Andrew, Angeline S., primary, Kiemeney, Lambertus A., primary, Sun, Ryan, primary, Zienolddiny, Shanbeh, primary, Grankvist, Kjell, primary, Johansson, Mikael, primary, Caporaso, Neil E., primary, Cox, Angela, primary, Hong, Yun-Chul, primary, Lazarus, Philip, primary, Schabath, Matthew B., primary, Aldrich, Melinda C., primary, Schwartz, Ann G., primary, Gorlov, Ivan, primary, Purrington, Kristen S., primary, Yang, Ping, primary, Liu, Yanhong, primary, Bailey-Wilson, Joan E., primary, Pinney, Susan M., primary, Mandal, Diptasri, primary, Willey, James C., primary, Gaba, Colette, primary, Brennan, Paul, primary, Xia, Jun, primary, Shen, Hongbing, primary, and Amos, Christopher I., primary

Published
2024
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42. Supplementary Materials from CYP2A6 Activity and Cigarette Consumption Interact in Smoking-Related Lung Cancer Susceptibility

Author

Du, Mulong, primary, Xin, Junyi, primary, Zheng, Rui, primary, Yuan, Qianyu, primary, Wang, Zhihui, primary, Liu, Hongliang, primary, Liu, Hanting, primary, Cai, Guoshuai, primary, Albanes, Demetrius, primary, Lam, Stephen, primary, Tardon, Adonina, primary, Chen, Chu, primary, Bojesen, Stig E., primary, Landi, Maria Teresa, primary, Johansson, Mattias, primary, Risch, Angela, primary, Bickeböller, Heike, primary, Wichmann, H-Erich, primary, Rennert, Gad, primary, Arnold, Susanne, primary, Brennan, Paul, primary, Field, John K., primary, Shete, Sanjay S., primary, Le Marchand, Loïc, primary, Liu, Geoffrey, primary, Andrew, Angeline S., primary, Kiemeney, Lambertus A., primary, Zienolddiny, Shan, primary, Grankvist, Kjell, primary, Johansson, Mikael, primary, Caporaso, Neil E., primary, Cox, Angela, primary, Hong, Yun-Chul, primary, Yuan, Jian-Min, primary, Schabath, Matthew B., primary, Aldrich, Melinda C., primary, Wang, Meilin, primary, Shen, Hongbing, primary, Chen, Feng, primary, Zhang, Zhengdong, primary, Hung, Rayjean J., primary, Amos, Christopher I., primary, Wei, Qingyi, primary, Lazarus, Philip, primary, and Christiani, David C., primary

Published
2024
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43. Data from CYP2A6 Activity and Cigarette Consumption Interact in Smoking-Related Lung Cancer Susceptibility

Author

Du, Mulong, primary, Xin, Junyi, primary, Zheng, Rui, primary, Yuan, Qianyu, primary, Wang, Zhihui, primary, Liu, Hongliang, primary, Liu, Hanting, primary, Cai, Guoshuai, primary, Albanes, Demetrius, primary, Lam, Stephen, primary, Tardon, Adonina, primary, Chen, Chu, primary, Bojesen, Stig E., primary, Landi, Maria Teresa, primary, Johansson, Mattias, primary, Risch, Angela, primary, Bickeböller, Heike, primary, Wichmann, H-Erich, primary, Rennert, Gad, primary, Arnold, Susanne, primary, Brennan, Paul, primary, Field, John K., primary, Shete, Sanjay S., primary, Le Marchand, Loïc, primary, Liu, Geoffrey, primary, Andrew, Angeline S., primary, Kiemeney, Lambertus A., primary, Zienolddiny, Shan, primary, Grankvist, Kjell, primary, Johansson, Mikael, primary, Caporaso, Neil E., primary, Cox, Angela, primary, Hong, Yun-Chul, primary, Yuan, Jian-Min, primary, Schabath, Matthew B., primary, Aldrich, Melinda C., primary, Wang, Meilin, primary, Shen, Hongbing, primary, Chen, Feng, primary, Zhang, Zhengdong, primary, Hung, Rayjean J., primary, Amos, Christopher I., primary, Wei, Qingyi, primary, Lazarus, Philip, primary, and Christiani, David C., primary

Published
2024
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44. Supplementary Tables1-11 from CYP2A6 Activity and Cigarette Consumption Interact in Smoking-Related Lung Cancer Susceptibility

Author

Du, Mulong, primary, Xin, Junyi, primary, Zheng, Rui, primary, Yuan, Qianyu, primary, Wang, Zhihui, primary, Liu, Hongliang, primary, Liu, Hanting, primary, Cai, Guoshuai, primary, Albanes, Demetrius, primary, Lam, Stephen, primary, Tardon, Adonina, primary, Chen, Chu, primary, Bojesen, Stig E., primary, Landi, Maria Teresa, primary, Johansson, Mattias, primary, Risch, Angela, primary, Bickeböller, Heike, primary, Wichmann, H-Erich, primary, Rennert, Gad, primary, Arnold, Susanne, primary, Brennan, Paul, primary, Field, John K., primary, Shete, Sanjay S., primary, Le Marchand, Loïc, primary, Liu, Geoffrey, primary, Andrew, Angeline S., primary, Kiemeney, Lambertus A., primary, Zienolddiny, Shan, primary, Grankvist, Kjell, primary, Johansson, Mikael, primary, Caporaso, Neil E., primary, Cox, Angela, primary, Hong, Yun-Chul, primary, Yuan, Jian-Min, primary, Schabath, Matthew B., primary, Aldrich, Melinda C., primary, Wang, Meilin, primary, Shen, Hongbing, primary, Chen, Feng, primary, Zhang, Zhengdong, primary, Hung, Rayjean J., primary, Amos, Christopher I., primary, Wei, Qingyi, primary, Lazarus, Philip, primary, and Christiani, David C., primary

Published
2024
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45. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

Author

Yarmolinsky, James, primary, Robinson, Jamie W., additional, Mariosa, Daniela, additional, Karhunen, Ville, additional, Huang, Jian, additional, Dimou, Niki, additional, Murphy, Neil, additional, Burrows, Kimberley, additional, Bouras, Emmanouil, additional, Smith-Byrne, Karl, additional, Lewis, Sarah J., additional, Galesloot, Tessel E., additional, Kiemeney, Lambertus A., additional, Vermeulen, Sita, additional, Martin, Paul, additional, Albanes, Demetrius, additional, Hou, Lifang, additional, Newcomb, Polly A., additional, White, Emily, additional, Wolk, Alicja, additional, Wu, Anna H., additional, Le Marchand, Loïc, additional, Phipps, Amanda I., additional, Buchanan, Daniel D., additional, Zhao, Sizheng Steven, additional, Gill, Dipender, additional, Chanock, Stephen J., additional, Purdue, Mark P., additional, Davey Smith, George, additional, Brennan, Paul, additional, Herzig, Karl-Heinz, additional, Järvelin, Marjo-Riitta, additional, Amos, Chris I., additional, Hung, Rayjean J., additional, Dehghan, Abbas, additional, Johansson, Mattias, additional, Gunter, Marc J., additional, Tsilidis, Kostas K., additional, Martin, Richard M., additional, Landi, Maria Teresa, additional, Stevens, Victoria, additional, Wang, Ying, additional, Albanes, Demetrios, additional, Caporaso, Neil, additional, Amos, Christopher I., additional, Shete, Sanjay, additional, Bickeböller, Heike, additional, Risch, Angela, additional, Houlston, Richard, additional, Lam, Stephen, additional, Tardon, Adonina, additional, Chen, Chu, additional, Bojesen, Stig E., additional, Wichmann, H-Erich, additional, Christiani, David, additional, Rennert, Gadi, additional, Arnold, Susanne, additional, Field, John K., additional, Le Marchand, Loic, additional, Melander, Olle, additional, Brunnström, Hans, additional, Liu, Geoffrey, additional, Andrew, Angeline, additional, Shen, Hongbing, additional, Zienolddiny, Shan, additional, Grankvist, Kjell, additional, Johansson, Mikael, additional, Teare, M. Dawn, additional, Hong, Yun-Chul, additional, Yuan, Jian-Min, additional, Lazarus, Philip, additional, Schabath, Matthew B., additional, Aldrich, Melinda C., additional, Eeles, Rosalind A., additional, Haiman, Christopher A., additional, Kote-Jarai, Zsofia, additional, Schumacher, Fredrick R., additional, Benlloch, Sara, additional, Al Olama, Ali Amin, additional, Muir, Kenneth R., additional, Berndt, Sonja I., additional, Conti, David V., additional, Wiklund, Fredrik, additional, Chanock, Stephen, additional, Tangen, Catherine M., additional, Batra, Jyotsna, additional, Clements, Judith A., additional, Grönberg, Henrik, additional, Pashayan, Nora, additional, Schleutker, Johanna, additional, Weinstein, Stephanie J., additional, West, Catharine M.L., additional, Mucci, Lorelei A., additional, Cancel-Tassin, Géraldine, additional, Koutros, Stella, additional, Sørensen, Karina Dalsgaard, additional, Grindedal, Eli Marie, additional, Neal, David E., additional, Hamdy, Freddie C., additional, Donovan, Jenny L., additional, Travis, Ruth C., additional, Hamilton, Robert J., additional, Ingles, Sue Ann, additional, Rosenstein, Barry S., additional, Lu, Yong-Jie, additional, Giles, Graham G., additional, MacInnis, Robert J., additional, Kibel, Adam S., additional, Vega, Ana, additional, Kogevinas, Manolis, additional, Penney, Kathryn L., additional, Park, Jong Y., additional, Stanfrod, Janet L., additional, Cybulski, Cezary, additional, Nordestgaard, Børge G., additional, Nielsen, Sune F., additional, Brenner, Hermann, additional, Maier, Christiane, additional, Logothetis, Christopher J., additional, John, Esther M., additional, Teixeira, Manuel R., additional, Neuhausen, Susan L., additional, De Ruyck, Kim, additional, Razack, Azad, additional, Newcomb, Lisa F., additional, Lessel, Davor, additional, Kaneva, Radka, additional, Usmani, Nawaid, additional, Claessens, Frank, additional, Townsend, Paul A., additional, Castelao, Jose Esteban, additional, Roobol, Monique J., additional, Menegaux, Florence, additional, Khaw, Kay-Tee, additional, Cannon-Albright, Lisa, additional, Pandha, Hardev, additional, Thibodeau, Stephen N., additional, Hunter, David J., additional, Kraft, Peter, additional, Blot, William J., additional, and Riboli, Elio, additional

Published
2024
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46. Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies

Author

Li, Yafang, primary, Xiao, Xiangjun, additional, Li, Jianrong, additional, Han, Younghun, additional, Cheng, Chao, additional, Fernandes, Gail F., additional, Slewitzke, Shannon E., additional, Rosenberg, Susan M., additional, Zhu, Meng, additional, Byun, Jinyoung, additional, Bossé, Yohan, additional, McKay, James D., additional, Albanes, Demetrios, additional, Lam, Stephen, additional, Tardon, Adonina, additional, Chen, Chu, additional, Bojesen, Stig E., additional, Landi, Maria T., additional, Johansson, Mattias, additional, Risch, Angela, additional, Bickeböller, Heike, additional, Wichmann, H-Erich, additional, Christiani, David C., additional, Rennert, Gad, additional, Arnold, Susanne M., additional, Goodman, Gary E., additional, Field, John K., additional, Davies, Michael P.A., additional, Shete, Sanjay, additional, Marchand, Loïc Le, additional, Liu, Geoffrey, additional, Hung, Rayjean J., additional, Andrew, Angeline S., additional, Kiemeney, Lambertus A., additional, Sun, Ryan, additional, Zienolddiny, Shanbeh, additional, Grankvist, Kjell, additional, Johansson, Mikael, additional, Caporaso, Neil E., additional, Cox, Angela, additional, Hong, Yun-Chul, additional, Lazarus, Philip, additional, Schabath, Matthew B., additional, Aldrich, Melinda C., additional, Schwartz, Ann G., additional, Gorlov, Ivan, additional, Purrington, Kristen S., additional, Yang, Ping, additional, Liu, Yanhong, additional, Bailey-Wilson, Joan E., additional, Pinney, Susan M., additional, Mandal, Diptasri, additional, Willey, James C., additional, Gaba, Colette, additional, Brennan, Paul, additional, Xia, Jun, additional, Shen, Hongbing, additional, and Amos, Christopher I., additional

Published
2024
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47. Real-World Comparative Outcomes of Egfr-Tkis for First-Line Treatment of Metastatic Non–Small-Cell Lung Cancer

Author

Kim, Kibum, primary, Syeed, M. Sakil, additional, Au, Trang, additional, Diaz, Amber, additional, Schabath, Matthew B., additional, Cass, Amanda, additional, Hall, Richard, additional, Pai, Lori, additional, Li, Chenghui, additional, Balmaceda, Nicole, additional, Palumbo, Alison, additional, Carey, Autumn, additional, Lalla, Mumtu, additional, Henry, Matthew, additional, Brixner, Diana, additional, and Stenehjem, David, additional

Published
2024
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48. Differences in Patient Outcomes of Prevalence, Interval, and Screen-Detected Lung Cancers in the CT Arm of the National Lung Screening Trial.

Author

Schabath, Matthew B, Massion, Pierre P, Thompson, Zachary J, Eschrich, Steven A, Balagurunathan, Yoganand, Goldof, Dmitry, Aberle, Denise R, and Gillies, Robert J

Subjects
Humans, Lung Neoplasms, Tomography, X-Ray Computed, Mass Screening, Neoplasm Staging, Disease-Free Survival, Prevalence, Proportional Hazards Models, Risk, Smoking, Demography, Aged, Middle Aged, Female, Male, Early Detection of Cancer, Kaplan-Meier Estimate, Tomography, X-Ray Computed, General Science & Technology
Abstract

Lung cancer screening identifies cancers with heterogeneous behaviors. Some lung cancers will be identified among patients who had prior negative CT screens and upon follow-up scans develop a de novo nodule that was determined to be cancerous. Other lung cancers will be identified among patients who had one or more prior stable positive scans that were not determined to be lung cancer (indeterminate pulmonary nodules), but in follow-up scans was diagnosed with an incidence lung cancer. Using data from the CT arm of the National Lung Screening Trial, this analysis investigated differences in patient characteristics and survival endpoints between prevalence-, interval-, and screen-detected lung cancers, characterized based on sequence of screening results. Lung cancers immediately following a positive baseline (T0), and prior to the T1 screen, formed the prevalence cohort. Interval cancers were diagnosed following a negative screen at any time point prior to the next screening round. Two cohorts of screen-detected lung cancers (SDLC) were identified that had a baseline positive screen that was that was not determined to be lung cancer (i.e., an indeterminate pulmonary nodule), but in follow-up scans was diagnosed with an incidence lung cancer 12 (SDLC1) or 24 (SDLC2) months later. Two other incidence cohorts had screen-detected lung cancers that had baseline negative screen and upon follow-up scans developed a de novo nodule determined to be cancerous at 12 (SDLC3) or 24 (SDLC4) months later. Differences in patient characteristics, progression-free survival (PFS), and overall survival (OS) were assessed. The lung cancer-specific death rate was higher for SDLC3/SDLC4 compared to SDLC1/SDLC2 lung cancers (136.6/1,000 person-years vs. 71.3/1,000 person-years, P < 0.001). Moreover, PFS and OS were significantly lower for SDLC3/SDLC4 compared to SDLC1/SDLC2 (P < 0.004; P < 0.002, respectively). The findings were consistent when stratified by stage and histology. Multivariable Cox proportional models revealed that the SDLC3/SDLC4 case groups were associated with significantly poorer PFS (HR = 1.89; 95% CI 1.31-2.74) and OS (HR = 1.80; 95% CI 1.21-2.67) compared to SDLC1/SDLC2 lung cancers (HR = 1.00). Lung cancer patients who develop a de novo nodule that determined to be cancerous (i.e., at least one negative CT screen prior to cancer diagnosis) had poorer survival outcomes compared to patients who had at least one positive screen prior to cancer diagnosis. As such, the observation that de novo screen-detected are associated with poorer survival could be attributed to faster growing, more aggressive cancers that arose from a lung environment previously lacking focal abnormalities.

Published
2016

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