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BMC Cancer

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Open Access 01-12-2020 | Research article

Systematical identifications of prognostic meaningful lung adenocarcinoma subtypes and the underlying mutational and expressional characters

Authors: Zhenyang Lv, Ting Lei

Published in: BMC Cancer | Issue 1/2020

Abstract

Background

Lung adenocarcinoma (LUAD) is one of the most common cancer types, threatening the human health around the world. However, the high heterogeneity and complexity of LUAD limit the benefits of targeted therapies. This study aimed to identify the key prognosis impacting genes and relevant subtypes for LUAD.

Methods

We recognized significant mutations and prognosis-relevant genes based on the omics data of 515 LUAD samples from The Cancer Genome Atlas. Mutation significance was estimated by MutSigCV. Prognosis analysis was based on the cox proportional hazards regression (Coxph) model. Specifically, the Coxph model was combined with a causal regulatory network to help reveal which genes play master roles among numerous prognosis impacting genes. Based on expressional profiles of the master genes, LUAD patients were clustered into different sub-types by a consensus clustering method and the importance of master genes were further evaluated by random forest.

Results

Significant mutations did not influence the prognosis directly. However, a collection of prognosis relevant genes were recognized, where 75 genes like GAPDH and GGA2 which are involved in mTOR signaling, lysosome or other key pathways are further identified as the master ones. Interestingly, the master gene expressions help separate LUAD patients into two sub-types displaying remarkable differences in expressional profiles, prognostic outcomes and genomic mutations in certain genes, like SMARCA4 and COL11A1. Meanwhile, the subtypes were re-discovered from two additional LUAD cohorts based on the top-10 important master genes.

Conclusions

This study can promote precision treatment of LUAD by providing a comprehensive description on the key prognosis-relevant genes and an alternative way to classify LUAD subtypes.

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Torre LA, Siegel RL, Jemal A. Lung Cancer statistics. Adv Exp Med Biol. 2016;893:1–19.PubMedCrossRef

Malhotra J, Malvezzi M, Negri E, La Vecchia C, Boffetta P. Risk factors for lung cancer worldwide. Eur Respir J. 2016;48(3):889–902.PubMedCrossRef

Paez JG, Janne PA, Lee JC, Tracy S, Greulich H, Gabriel S, Herman P, Kaye FJ, Lindeman N, Boggon TJ, et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science. 2004;304(5676):1497–500.PubMedCrossRef

Muller IB, de Langen AJ, Giovannetti E, Peters GJ. Anaplastic lymphoma kinase inhibition in metastatic non-small cell lung cancer: clinical impact of alectinib. Onco Targets Ther. 2017;10:4535–41.PubMedPubMedCentralCrossRef

Kwak EL, Bang YJ, Camidge DR, Shaw AT, Solomon B, Maki RG, Ou SH, Dezube BJ, Janne PA, Costa DB, et al. Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N Engl J Med. 2010;363(18):1693–703.PubMedPubMedCentralCrossRef

Drilon A, Wang L, Hasanovic A, Suehara Y, Lipson D, Stephens P, Ross J, Miller V, Ginsberg M, Zakowski MF, et al. Response to Cabozantinib in patients with RET fusion-positive lung adenocarcinomas. Cancer Discov. 2013;3(6):630–5.PubMedPubMedCentralCrossRef

Bergethon K, Shaw AT, Ou SH, Katayama R, Lovly CM, McDonald NT, Massion PP, Siwak-Tapp C, Gonzalez A, Fang R, et al. ROS1 rearrangements define a unique molecular class of lung cancers. J Clin Oncol. 2012;30(8):863–70.PubMedPubMedCentralCrossRef

Riely GJ, Brahmer JR, Planchard D. A randomized discontinuation phase II trial of ridaforolimus in non-small cell lung cancer (NSCLC) patients with KRAS mutations. J Clin Oncol. 2012;30(\):abstract):7531.

Ou SH, Kwak EL, Siwak-Tapp C, Dy J, Bergethon K, Clark JW, Camidge DR, Solomon BJ, Maki RG, Bang YJ, et al. Activity of crizotinib (PF02341066), a dual mesenchymal-epithelial transition (MET) and anaplastic lymphoma kinase (ALK) inhibitor, in a non-small cell lung cancer patient with de novo MET amplification. J Thorac Oncol. 2011;6(5):942–6.PubMedCrossRef

10.

Cancer Genome Atlas Research N. Comprehensive molecular profiling of lung adenocarcinoma. Nature. 2014;511(7511):543–50.CrossRef

11.

Okayama H, Kohno T, Ishii Y, Shimada Y, Shiraishi K, Iwakawa R, Furuta K, Tsuta K, Shibata T, Yamamoto S, et al. Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas. Cancer Res. 2012;72(1):100–11.PubMedCrossRef

12.

Rousseaux S, Debernardi A, Jacquiau B, Vitte AL, Vesin A, Nagy-Mignotte H, Moro-Sibilot D, Brichon PY, Lantuejoul S, Hainaut P, et al. Ectopic activation of germline and placental genes identifies aggressive metastasis-prone lung cancers. Sci Transl Med. 2013;5(186):186ra166.CrossRef

13.

Chen HY, Yu SL, Chen CH, Chang GC, Chen CY, Yuan A, Cheng CL, Wang CH, Terng HJ, Kao SF, et al. A five-gene signature and clinical outcome in non-small-cell lung cancer. N Engl J Med. 2007;356(1):11–20.PubMedCrossRef

14.

Lau SK, Boutros PC, Pintilie M, Blackhall FH, Zhu CQ, Strumpf D, Johnston MR, Darling G, Keshavjee S, Waddell TK, et al. Three-gene prognostic classifier for early-stage non small-cell lung cancer. J Clin Oncol. 2007;25(35):5562–9.PubMedCrossRef

15.

Cancer Genome Atlas Research N. Comprehensive genomic characterization of squamous cell lung cancers. Nature. 2012;489(7417):519–25.CrossRef

16.

Floyd SR, Pacold ME, Huang Q, Clarke SM, Lam FC, Cannell IG, Bryson BD, Rameseder J, Lee MJ, Blake EJ, et al. The bromodomain protein Brd4 insulates chromatin from DNA damage signalling. Nature. 2013;498(7453):246–50.PubMedPubMedCentralCrossRef

17.

Law CW, Chen Y, Shi W, Smyth GK. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 2014;15(2):R29.PubMedPubMedCentralCrossRef

18.

Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.PubMedPubMedCentralCrossRef

19.

Liberzon A, Birger C, Thorvaldsdottir H, Ghandi M, Mesirov JP, Tamayo P. The molecular signatures database (MSigDB) hallmark gene set collection. Cell Syst. 2015;1(6):417–25.PubMedPubMedCentralCrossRef

20.

Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, Carter SL, Stewart C, Mermel CH, Roberts SA, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013;499(7457):214–8.PubMedPubMedCentralCrossRef

21.

Therneau TM, Grambsch PM. Modeling survival data: extending the cox model. New York: Springer; 2000.CrossRef

22.

Langfelder P, Horvath S. Fast R functions for robust correlations and hierarchical clustering. J Stat Softw. 2012;46(11):1–17.CrossRef

23.

Kalisch M, Machler M, Colombo D, Maathuis MH, Buhlmann P. Causal inference using graphical models with the R package pcalg. J Stat Softw. 2012;47(11):1–26.CrossRef

24.

Wilkerson MD, Hayes DN. ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics. 2010;26(12):1572–3.PubMedPubMedCentralCrossRef

25.

Liaw A, Wiener M. Classification and regression by randomForest. R News. 2002;2(3):5.

26.

Sean D, Meltzer PS. GEOquery: a bridge between the gene expression omnibus (GEO) and BioConductor. Bioinformatics. 2007;23(14):1846–7.CrossRef

27.

Simon N, Friedman J, Hastie T, Tibshirani R. Regularization paths for Cox's proportional hazards model via coordinate descent. J Stat Softw. 2011;39(5):1–13.PubMedPubMedCentralCrossRef

28.

Griffith M, Griffith OL, Coffman AC, Weible JV, McMichael JF, Spies NC, Koval J, Das I, Callaway MB, Eldred JM, et al. DGIdb: mining the druggable genome. Nat Methods. 2013;10(12):1209 −+.PubMedPubMedCentralCrossRef

29.

Cancer Genome Atlas Research N, Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, Ellrott K, Shmulevich I, Sander C, Stuart JM. The cancer genome atlas pan-Cancer analysis project. Nat Genet. 2013;45(10):1113–20.CrossRef

30.

Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545–50.PubMedPubMedCentralCrossRef

31.

Chong IW, Chang MY, Chang HC, Yu YP, Sheu CC, Tsai JR, Hung JY, Chou SH, Tsai MS, Hwang JJ, et al. Great potential of a panel of multiple hMTH1, SPD, ITGA11 and COL11A1 markers for diagnosis of patients with non-small cell lung cancer. Oncol Rep. 2006;16(5):981–8.PubMed

32.

Rizou T, Perlikos F, Lagiou M, Karaglani M, Nikolopoulos S, Toumpoulis I, Kroupis C. Development of novel real-time RT-qPCR methodologies for quantification of the COL11A1 mRNA general and C transcripts and evaluation in non-small cell lung cancer specimens. J BUON. 2018;23(6):1699–710.PubMed

33.

Shen L, Yang M, Lin Q, Zhang Z, Zhu B, Miao C. COL11A1 is overexpressed in recurrent non-small cell lung cancer and promotes cell proliferation, migration, invasion and drug resistance. Oncol Rep. 2016;36(2):877–85.PubMedCrossRef

34.

van Buul JD, Allingham MJ, Samson T, Meller J, Boulter E, Garcia-Mata R, Burridge K. RhoG regulates endothelial apical cup assembly downstream from ICAM1 engagement and is involved in leukocyte trans-endothelial migration. J Cell Biol. 2007;178(7):1279–93.PubMedPubMedCentralCrossRef

35.

Zhang X, Berger FG, Yang J, Lu X. USP4 inhibits p53 through deubiquitinating and stabilizing ARF-BP1. EMBO J. 2011;30(11):2177–89.PubMedPubMedCentralCrossRef

36.

Guo W, Ma J, Pei T, Zhao T, Guo S, Yi X, Liu Y, Wang S, Zhu G, Jian Z. Up-regulated deubiquitinase USP4 plays an oncogenic role in melanoma. J Cell Mol Med. 2018;22(5):2944–54.PubMedPubMedCentralCrossRef

37.

Gill KS, Fernandes P, O'Donovan TR, McKenna SL, Doddakula KK, Power DG, Soden DM, Forde PF. Glycolysis inhibition as a cancer treatment and its role in an anti-tumour immune response. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 2016;1866(1):87–105.CrossRef

38.

Lin P, Ye RD. The lysophospholipid receptor G2A activates a specific combination of G proteins and promotes apoptosis. J Biol Chem. 2003;278(16):14379–86.PubMedCrossRef

39.

Felip E, Gridelli C, Baas P, Rosell R, Stahel R, Panel M. Metastatic non-small-cell lung cancer: consensus on pathology and molecular tests, first-line, second-line, and third-line therapy: 1st ESMO consensus conference in lung Cancer; Lugano 2010. Ann Oncol. 2011;22(7):1507–19.PubMedCrossRef

40.

Choi M, Kadara H, Zhang J, Parra ER, Rodriguez-Canales J, Gaffney SG, Zhao Z, Behrens C, Fujimoto J, Chow C, et al. Mutation profiles in early-stage lung squamous cell carcinoma with clinical follow-up and correlation with markers of immune function. Ann Oncol. 2017;28(1):83–9.PubMedCrossRef

41.

Nelson HH, Wilkojmen M, Marsit CJ, Kelsey KT. TP53 mutation, allelism and survival in non-small cell lung cancer. Carcinogenesis. 2005;26(10):1770–3.PubMedCrossRef

Title: Systematical identifications of prognostic meaningful lung adenocarcinoma subtypes and the underlying mutational and expressional characters
Authors: Zhenyang Lv
Ting Lei
Publication date: 01-12-2020
Publisher: BioMed Central
Published in: BMC Cancer / Issue 1/2020
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-019-6462-y

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