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Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development.

ABSTRACT: The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,037 lung cancer patients and 20,401 healthy controls with Caucasian ancestry were analyzed in the study. Using a two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis, we identified significant genetic interactions between SNPs in RGL1:RAD51B (OR=0.44, p value=3.27x10-11 in overall lung cancer and OR=0.41, p value=9.71x10-11 in non-small cell lung cancer), SYNE1:RNF43 (OR=0.73, p value=1.01x10-12 in adenocarcinoma) and FHIT:TSPAN8 (OR=1.82, p value=7.62x10-11 in squamous cell carcinoma) in our analysis. None of these genes have been identified from previous main effect association studies in lung cancer. Further eQTL gene expression analysis in lung tissues provided information supporting the functional role of the identified epistasis in lung tumorigenesis. Gene set enrichment analysis revealed potential pathways and gene networks underlying molecular mechanisms in overall lung cancer as well as histology subtypes development. Our results provide evidence that genetic interactions between oncogenesis-related genes play an important role in lung tumorigenesis and epistasis analysis, combined with functional annotation, provides a valuable tool for uncovering functional novel susceptibility genes that contribute to lung cancer development by interacting with other modifier genes.

SUBMITTER: Li Y

PROVIDER: S-EPMC6442994 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development.

Li Yafang Y Xiao Xiangjun X Bossé Yohan Y Gorlova Olga O Gorlov Ivan I Han Younghun Y Byun Jinyoung J Leighl Natasha N Johansen Jakob S JS Barnett Matt M Chen Chu C Goodman Gary G Cox Angela A Taylor Fiona F Woll Penella P Wichmann H Erich HE Manz Judith J Muley Thomas T Risch Angela A Rosenberger Albert A Han Jiali J Siminovitch Katherine K Arnold Susanne M SM Haura Eric B EB Bolca Ciprian C Holcatova Ivana I Janout Vladimir V Kontic Milica M Lissowska Jolanta J Mukeria Anush A Ognjanovic Simona S Orlowski Tadeusz M TM Scelo Ghislaine G Swiatkowska Beata B Zaridze David D Bakke Per P Skaug Vidar V Zienolddiny Shanbeh S Duell Eric J EJ Butler Lesley M LM Houlston Richard R Artigas María Soler MS Grankvist Kjell K Johansson Mikael M Shepherd Frances A FA Marcus Michael W MW Brunnström Hans H Manjer Jonas J Melander Olle O Muller David C DC Overvad Kim K Trichopoulou Antonia A Tumino Rosario R Liu Geoffrey G Bojesen Stig E SE Wu Xifeng X Le Marchand Loic L Albanes Demetrios D Bickeböller Heike H Aldrich Melinda C MC Bush William S WS Tardon Adonina A Rennert Gad G Teare M Dawn MD Field John K JK Kiemeney Lambertus A LA Lazarus Philip P Haugen Aage A Lam Stephen S Schabath Matthew B MB Andrew Angeline S AS Bertazzi Pier Alberto PA Pesatori Angela C AC Christiani David C DC Caporaso Neil N Johansson Mattias M McKay James D JD Brennan Paul P Hung Rayjean J RJ Amos Christopher I CI

Oncotarget 20190305 19

The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,0 ...[more]

PMID: 30956756

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Project description:BACKGROUND:Hypertension and bronchial asthma are a major issue for people's health. As of 2014, approximately one billion adults, or ~?22% of the world population, have had hypertension. As of 2011, 235-330 million people globally have been affected by asthma and approximately 250,000-345,000 people have died each year from the disease. The development of the effective treatment therapies against these diseases is complicated by their comorbidity features. This is often a major problem in diagnosis and their treatment. Hence, in this study the bioinformatical methodology for the analysis of the comorbidity of these two diseases have been developed. As such, the search for candidate genes related to the comorbid conditions of asthma and hypertension can help in elucidating the molecular mechanisms underlying the comorbid condition of these two diseases, and can also be useful for genotyping and identifying new drug targets. RESULTS:Using ANDSystem, the reconstruction and analysis of gene networks associated with asthma and hypertension was carried out. The gene network of asthma included 755 genes/proteins and 62,603 interactions, while the gene network of hypertension - 713 genes/proteins and 45,479 interactions. Two hundred and five genes/proteins and 9638 interactions were shared between asthma and hypertension. An approach for ranking genes implicated in the comorbid condition of two diseases was proposed. The approach is based on nine criteria for ranking genes by their importance, including standard methods of gene prioritization (Endeavor, ToppGene) as well as original criteria that take into account the characteristics of an associative gene network and the presence of known polymorphisms in the analysed genes. According to the proposed approach, the genes IL10, TLR4, and CAT had the highest priority in the development of comorbidity of these two diseases. Additionally, it was revealed that the list of top genes is enriched with apoptotic genes and genes involved in biological processes related to the functioning of central nervous system. CONCLUSIONS:The application of methods of reconstruction and analysis of gene networks is a productive tool for studying the molecular mechanisms of comorbid conditions. The method put forth to rank genes by their importance to the comorbid condition of asthma and hypertension was employed that resulted in prediction of 10 genes, playing the key role in the development of the comorbid condition. The results can be utilised to plan experiments for identification of novel candidate genes along with searching for novel pharmacological targets.

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Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development.

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Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development.

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