Cancer genomic research is a relatively new method.
It has shown great potential but faces certain challenges. Researchers often
have to deal with tens of thousands of genes with a relatively small sample
size of patient cases—a dilemma referred to as the “Curse of Dimensionality”[1]—and it makes it hard to learn the data well because
of relatively sparse data in high dimensional space. To deal with the dilemma,
this study uses p-values of individual genes for pathway enrichment to find
statistically significant pathways. The aim of this study is to find
significant genes and biological pathways that are related to lung cancer by
statistical method and pathway enrichment analysis. Several significant genes,
such as WNT2B, VAV2, and significant pathways, such as Metabolism of xenobiotics by cytochrome P450-Homo sapiens
(human) and Fatty acid degradation-Homo sapiens (human), are found to be both
statistically significant and biological studies supported. Significant genes-including TESK2, C5orf43, and ZSCAN21—and significant pathways such as Pentose and
glucoronate interconversions-Homo sapiens (human), are found to be new
cancer-related genes and pathways that worth laboratory studies. The idea and
method used in this research can be applied to find more significant genes and
pathways that worth study experimentally.
Hu, Z., Chen, J., Tian, T., Zhou, X., Gu, H., Xu, L., Chen, Y, et al. (2008) Genetic Variants of miRNA Sequences and Non-Small Cell Lung Cancer Survival. The Journal of Clinical Investigation, 118, 2600-2608.
Detterbeck, F.C., Boffa, D.J., Tanoue, L.T. and Wilson, L.D. (2010) Details and Difficulties regarding the New Lung Cancer Staging System. Chest, 137, 1172-1180.
https://doi.org/10.1378/chest.09-2626
The American Cancer Society Medical and Editorial Content Team (2017) Key Statistics for Lung Cancer. American Cancer Society.
https://www.cancer.org/cancer/non-small-cell-lung-cancer/about/key-statistics.html
Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., Mesirov, J.P., et al. (2005) Gene Set Enrichment Analysis: A Knowledge-Based Approach for Interpreting Genome-Wide Expression Profiles. Proceedings of the National Academy of Sciences, 102, 15545-15550.
https://doi.org/10.1073/pnas.0506580102
Benjamini, Y. and Hochberg, Y. (1995) Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological), 289-300.
Katoh, M. (2005) WNT2B: Comparative Integromics and Clinical Applications. International Journal of Molecular Medicine, 16, 1103-1108.
https://doi.org/10.3892/ijmm.16.6.1103
Li, S.J., Yang, X.N. and Qian, H.Y. (2015) Antitumor Effects of WNT2B Silencing in GLUT1 Overexpressing Cisplatin Resistant Head and Neck Squamous Cell Carcinoma. American Journal of Cancer Research, 5, 300-308.
Halford, S., Bellingham, J., Ocaka, L., Fox, M., Johnson, S., Foster, R.G. and Hunt, D.M. (2001) Assignment1 of Panopsin (OPN3) to Human Chromosome Band 1q43 by in Situ Hybridization and Somatic Cell Hybrids. Cytogenetic and Genome Research, 95, 234-235. https://doi.org/10.1159/000059351
Stewart, D.J. (2014) Wnt Signaling Pathway in Non-Small Cell Lung Cancer. Journal of the National Cancer Institute, 106, djt356. https://doi.org/10.1093/jnci/djt356
Al-Obaide, M.A.I., Abdel-Salam, A.S.G., Alobydi, H. and Srivenugopal, K.S. (2016) Bioinformatic Analysis of Human OPN3 Alternative Promoters Associated with Cancer. Applied Mathematics, 10, 1223-1229. https://doi.org/10.18576/amis/100402
Achsel, T., Brahms, H., Kastner, B., Bachi, A., Wilm, M. and Lührmann, R. (1999) A Doughnut-Shaped Heteromer of Human Sm-Like Proteins Binds to the 3’-end of U6 snRNA, Thereby Facilitating U4/U6 Duplex Formation in Vitro. The EMBO Journal, 18, 5789-5802. https://doi.org/10.1093/emboj/18.20.5789
Streicher, K.L., Yang, Z.Q., Draghici, S. and Ethier, S.P. (2007) Transforming Function of the LSM1 Oncogene in Human Breast Cancers with the 8p11-12 Amplicon. Oncogene, 26, 2104-2114. https://doi.org/10.1038/sj.onc.1210002
Watson, P.M., Miller, S.W., Fraig, M., Cole, D.J., Watson, D.K. and Boylan, A.M. (2008) CaSm (LSm-1) Overexpression in Lung Cancer and Mesothelioma Is Required for Transformed Phenotypes. American Journal of Respiratory Cell and Molecular Biology, 38, 671-678. https://doi.org/10.1165/rcmb.2007-0205OC
Henske, E.P., Short, M.P., Jozwiak, S., Bovey, C.M., Ramlakhan, S., Haines, J.L. and Kwiatkowski, D.J. (1995) Identification of VAV2 on 9q34 and Its Exclusion as the Tuberous Sclerosis Gene TSC1. Annals of Human Genetics, 59, 25-37.
https://doi.org/10.1111/j.1469-1809.1995.tb01603.x
Havel, L.S., Kline, E.R., Salgueiro, A.M. and Marcus, A.I. (2015) Vimentin Regulates Lung Cancer Cell Adhesion through a VAV2-Rac1 Pathway to Control Focal Adhesion Kinase Activity. Oncogene, 34, 1979-1990.
https://doi.org/10.1038/onc.2014.123
Chen, J.D. and Evans, R.M. (1995) A Transcriptional Co-Repressor That Interacts with Nuclear Hormone Receptors. Nature, 377, 454-457.
https://doi.org/10.1038/377454a0
Battaglia, S., Maguire, O. and Campbell, M.J. (2010) Transcription Factor Co-Repressors in Cancer Biology: Roles and Targeting. International Journal of Cancer, 126, 2511-2519. https://doi.org/10.1002/ijc.25181
Hla, T., Jackson, A.Q., Appleby, S.B. and Maciag, T. (1995) Characterization of edg-2, a Human Homologue of the Xenopus Maternal Transcript G10 from Endothelial Cells. Biochimica et Biophysica Acta (BBA)—Gene Structure and Expression, 1260, 227-229. https://doi.org/10.1016/0167-4781(94)00219-S
Hsu, T.Y.T., Simon, L.M., Neill, N.J., Marcotte, R., Sayad, A., Bland, C.S., Karlin, K.L., et al. (2015) The Spliceosome Is a Therapeutic Vulnerability in MYC-Driven Cancer. Nature, 525, 384-388. https://doi.org/10.1038/nature14985
Shivakumar, M., Lee, Y., Bang, L., Garg, T., Sohn, K.A. and Kim, D. (2017) Identification of Epigenetic Interactions between miRNA and DNA Methylation Associated with Gene Expression as Potential Prognostic Markers in Bladder Cancer. BMC Medical Genomics, 10, 30. https://doi.org/10.1186/s12920-017-0269-y
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. and Morishima, K. (2017) KEGG: New Perspectives on Genomes, Pathways, Diseases and Drugs. Nucleic Acids Research, 45, D353-D361. https://doi.org/10.1093/nar/gkw1092
Nebert, D.W. (1991) Role of Genetics and Drug Metabolism in Human Cancer Risk. Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, 247, 267-281. https://doi.org/10.1016/0027-5107(91)90022-G
Currie, E., Schulze, A., Zechner, R., Walther, T.C. and Farese, R.V. (2013) Cellular Fatty Acid Metabolism and Cancer. Cell Metabolism, 18, 153-161.
http://cancergenome.nih.gov/
https://doi.org/10.1016/j.cmet.2013.05.017
