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Transcriptomics Analysis on Comparing Non-Small Cell Lung Cancer versus Normal Lung, and Early Stage Compared versus Late-Stages of Non-Small Cell Lung Cancer

Authors: Achitphol Chookaew, Paramee Thongsukhsai, Patamarerk Engsontia, Narongwit Nakwan, Pritsana Raugrut


Lung cancer is one of the most common malignancies and primary cause of death due to cancer worldwide. Non-small cell lung cancer (NSCLC) is the main subtype in which majority of patients present with advanced-stage disease. Herein, we analyzed differentially expressed genes to find potential biomarkers for lung cancer diagnosis as well as prognostic markers. We used transcriptome data from our 2 NSCLC patients and public data (GSE81089) composing of 8 NSCLC and 10 normal lung tissues. Differentially expressed genes (DEGs) between NSCLC and normal tissue and between early-stage and late-stage NSCLC were analyzed by the DESeq2. Pairwise correlation was used to find the DEGs with false discovery rate (FDR) adjusted p-value £ 0.05 and |log2 fold change| ³ 4 for NSCLC versus normal and FDR adjusted p-value £ 0.05 with |log2 fold change| ³ 2 for early versus late-stage NSCLC. Bioinformatic tools were used for functional and pathway analysis. Moreover, the top ten genes in each comparison group were verified the expression and survival analysis via GEPIA. We found 150 up-regulated and 45 down-regulated genes in NSCLC compared to normal tissues. Many immnunoglobulin-related genes e.g., IGHV4-4, IGHV5-10-1, IGHV4-31, IGHV4-61, and IGHV1-69D were significantly up-regulated. 22 genes were up-regulated, and five genes were down-regulated in late-stage compared to early-stage NSCLC. The top five DEGs genes were KRT6B, SPRR1A, KRT13, KRT6A and KRT5. Keratin 6B (KRT6B) was the most significantly increased gene in the late-stage NSCLC. From GEPIA analysis, we concluded that IGHV4-31 and IGKV1-9 might be used as diagnostic biomarkers, while KRT6B and KRT6A might be used as prognostic biomarkers. However, further clinical validation is needed.

Keywords: Bioinformatics, differentially expressed genes, non-small cell lung cancer, transcriptomics.

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[1] R. Siegel, D. Naishadham, A. Jemal, “Cancer statistics, 2013” CA Cancer J Clin, vol. 63, no.1, pp. 11-30, Jan. 2013.
[2] F. Bray, J. Ferlay, I. Soerjomataram, R. Siegel, L. Torre, A. Jemal, “Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries” CA Cancer J Clin, vol. 68, no. 6, pp. 394-424, Jul. 2018.
[3] S. Ramalingam, C. Belani, “Systemic Chemotherapy for Advanced Non‐Small Cell Lung Cancer: Recent Advances and Future Directions” The Oncologist, vol. 13, no. S1, pp. 5-13, Jan. 2008.
[4] Z. Fan, W. Xue, L. Li, C. Zhang, J. Lu, Y. Zhai, “Identification of an early diagnostic biomarker of lung adenocarcinoma based on co-expression similarity and construction of a diagnostic model” J Transl Med, vol. 16, no. 1, Jul. 2018.
[5] Z. Wang, M, Gerstein, M. Snyder, “RNA-Seq: a revolutionary tool for transcriptomics” Nat. Rev. Genet, vol. 10, no. 1, pp. 57-63, Jan. 2009.
[6] D. Carvajal-Hausdorf, K. Schalper, V. Neumeister, “Quantitative measurement of cancer tissue biomarkers in the lab and in the clinic” Lab Invest, vol. 95, pp. 385-396, Apr. 2015.
[7] Quigen. Total RNA purification from animal tissue, in: RNeasy® Mini Handbook. Elsevier, 2009, pp. 45-52.
[8] S. Pfeifer, “From next-generation resequencing reads to a high-quality variant data set” Heredity, vol. 118, pp. 111-124, Oct. 2017.
[9] M. Lefranc, “Immunoglobulin and T Cell Receptor Genes: IMGT(®) and the Birth and Rise of Immunoinformatics” Front Immunol, Vol. 5, no. 5, pp. 22, Feb. 2014.
[10] J. Xiao, X. Lu, X. Chen, Y. Zou, A. Liu, W. Li, B. He, S. He, Q. Chen, “Eight potential biomarkers for distinguishing between lung adenocarcinoma and squamous cell carcinoma” Oncotarget, vol. 3, no. 8, pp. 71759-71771, May. 2017.
[11] J. Liu, L. Liu, L. Cao, Q. Wen, “Keratin 17 Promotes Lung Adenocarcinoma Progression by Enhancing Cell Proliferation and Invasion” Med Sci Monit, vol. 24, pp. 4782-4790, Jul. 2018.
[12] J. Xiao, X. Lu, X. Chen, et al. “Eight potential biomarkers for distinguishing between lung adenocarcinoma and squamous cell carcinoma” Oncotarget, vol. 8, no. 42, pp. 71759-71771, May. 2017.