Application of weighted gene co‑expression network analysis to explore the potential diagnostic biomarkers for colorectal cancer

Qin,Liping; Zeng,Jianping; Shi,Nannan; Chen,Liu; Wang,Li

doi:10.3892/mmr.2020.11047

Application of weighted gene co‑expression network analysis to explore the potential diagnostic biomarkers for colorectal cancer

Authors:
- Liping Qin
- Jianping Zeng
- Nannan Shi
- Liu Chen
- Li Wang
View Affiliations

Affiliations: Molecular Laboratory, Institute of Aging Research, School of Medicine, Hangzhou Normal University, Hangzhou, Zhejiang 311121, P.R. China, Department of Neurosurgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 311121, P.R. China
Published online on: April 1, 2020 https://doi.org/10.3892/mmr.2020.11047
Pages: 2533-2543
Copyright: © Qin et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

Colorectal cancer (CRC) is one of the most common malignant diseases in the world. Although mechanistic studies have been conducted on the pathogenesis of CRC, the molecular mechanism of CRC tumorigenesis remains unclear. In the present study, the weighted gene co‑expression network analysis was performed for the Gene Expression Omnibus (GEO) dataset GSE87211, in order to analyze the key modules involved in the pathogenesis of CRC. Next, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on the key module genes to analyze the functional pathways involved. The hub genes were screened using the Cytoscape platform and verified by a second GEO dataset, GSE21510. Finally, 10 hub genes were identified in 2 key modules (the green and brown modules) as the genes most significantly associated with the tumorigenesis of CRC. The 5 hub genes from the green module included collagen type I α1 chain, collagen type XII α1 chain, collagen triple helix repeat containing 1, inhibin subunit βa (INHBA) and chromobox 2 (CBX2), while the 5 hub genes from the brown module included bestrophin 2 (BEST2), carbonic anhydrase 2, glucagon, solute carrier family 4 member 4 and gliomedin. The 2 key modules with the 10 hub genes identified may regulate the occurrence and development of CRC through the extracellular matrix pathway, PI3K‑Akt and chemokine signaling pathways, thus providing a reference for understanding the complex mechanism of tumorigenesis in CRC. Of note, few studies have reported the pathogenesis of CRC with the 3 identified hub genes, INHBA, CBX2 and BEST2. Further investigation of the molecular mechanism of these genes in CRC is recommended.

View Figures

View References

1	Dekker E, Tanis PJ, Vleugels JLA, Kasi PM and Wallace MB: Colorectal cancer. Lancet. 394:1467–1480. 2019. View Article : Google Scholar : PubMed/NCBI
2	Janz T, Lu K, Povlow MR and Urso B: A review of colorectal cancer detection modalities, stool DNA, and fecal immunochemistry testing in adults over the age of 50. Cureus. 8:e9312016.PubMed/NCBI
3	Advani S and Kopetz S: Ongoing and future directions in the management of metastatic colorectal cancer: Update on clinical trials. J Surg Oncol. 119:642–652. 2019. View Article : Google Scholar : PubMed/NCBI
4	Muller MF, Ibrahim AE and Arends MJ: Molecular pathological classification of colorectal cancer. Virchows Arch. 469:125–134. 2016. View Article : Google Scholar : PubMed/NCBI
5	Marmol I, Sanchez-de-Diego C, Pradilla Dieste A, Cerrada E and Rodriguez Yoldi MJ: Colorectal carcinoma: A general overview and future perspectives in colorectal cancer. Int J Mol Sci. 18:E1972017. View Article : Google Scholar : PubMed/NCBI
6	Pino MS and Chung DC: The chromosomal instability pathway in colon cancer. Gastroenterology. 138:2059–2072. 2010. View Article : Google Scholar : PubMed/NCBI
7	Cheng X, Xu X, Chen D, Zhao F and Wang W: Therapeutic potential of targeting the Wnt/β-catenin signaling pathway in colorectal cancer. Biomed Pharmacother. 110:473–481. 2019. View Article : Google Scholar : PubMed/NCBI
8	Aghabozorgi AS, Bahreyni A, Soleimani A, Bahrami A, Khazaei M, Ferns GA, Avan A and Hassanian SM: Role of adenomatous polyposis coli (APC) gene mutations in the pathogenesis of colorectal cancer; current status and perspectives. Biochimie. 157:64–71. 2019. View Article : Google Scholar : PubMed/NCBI
9	Wang J, Shibayama Y, Zhang A, Ohsaki H, Asano E, Suzuki Y, Kushida Y, Kobara H, Masaki T, Wang Z and Nishiyama A: (Pro)renin receptor promotes colorectal cancer through the Wnt/beta-catenin signalling pathway despite constitutive pathway component mutations. Br J Cancer. 120:229–237. 2019. View Article : Google Scholar : PubMed/NCBI
10	Xu M, Liu X, Xu Y, Zhu S and Gao Y: Co-expression of Axin and APC gene fragments inhibits colorectal cancer cell growth via regulation of the Wnt signaling pathway. Mol Med Rep. 16:3783–3790. 2017. View Article : Google Scholar : PubMed/NCBI
11	Su YH, Tang WC, Cheng YW, Sia P, Huang CC, Lee YC, Jiang HY, Wu MH, Lai IL, Lee JW and Lee KH: Targeting of multiple oncogenic signaling pathways by Hsp90 inhibitor alone or in combination with berberine for treatment of colorectal cancer. Biochim Biophys Acta. 1853:2261–2272. 2015. View Article : Google Scholar : PubMed/NCBI
12	Hu Y, Gaedcke J, Emons G, Beissbarth T, Grade M, Jo P, Yeager M, Chanock SJ, Wolff H, Camps J, et al: Colorectal cancer susceptibility loci as predictive markers of rectal cancer prognosis after surgery. Genes Chromosomes Cancer. 57:140–149. 2018. View Article : Google Scholar : PubMed/NCBI
13	Tsukamoto S, Ishikawa T, Iida S, Ishiguro M, Mogushi K, Mizushima H, Uetake H, Tanaka H and Sugihara K: Clinical significance of osteoprotegerin expression in human colorectal cancer. Clin Cancer Res. 17:2444–2450. 2011. View Article : Google Scholar : PubMed/NCBI
14	Langfelder P and Horvath S: WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics. 9:5592008. View Article : Google Scholar : PubMed/NCBI
15	Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al: Gene ontology: Tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 25:25–29. 2000. View Article : Google Scholar : PubMed/NCBI
16	Kanehisa M and Goto S: KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28:27–30. 2000. View Article : Google Scholar : PubMed/NCBI
17	The Gene Ontology Consortium, . The gene ontology resource: 20 years and still GOing strong. Nucleic Acids Res. 47:D330–D338. 2019. View Article : Google Scholar : PubMed/NCBI
18	Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B and Ideker T: Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 13:2498–2504. 2003. View Article : Google Scholar : PubMed/NCBI
19	Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W and Smyth GK: Lim ma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43:e472015. View Article : Google Scholar : PubMed/NCBI
20	Wickham H: ggplot2: Elegant Graphics for Data Analysis. Springer International Publishing. (New York, NY). 2016.ISBN 978-3-319-24277-4.
21	Tang Z, Li C, Kang B, Gao G, Li C and Zhang Z: GEPIA: A web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 45:W98–W102. 2017. View Article : Google Scholar : PubMed/NCBI
22	Fischer J, Walker LC, Robinson BA, Frizelle FA, Church JM and Eglinton TW: Clinical implications of the genetics of sporadic colorectal cancer. ANZ J Surg. 89:1224–1229. 2019. View Article : Google Scholar : PubMed/NCBI
23	Maida M, Macaluso FS, Ianiro G, Mangiola F, Sinagra E, Hold G, Maida C, Cammarota G, Gasbarrini A and Scarpulla G: Screening of colorectal cancer: Present and future. Expert Rev Anticancer Ther. 17:1131–1146. 2017. View Article : Google Scholar : PubMed/NCBI
24	Willauer AN, Liu Y, Pereira AAL, Lam M, Morris JS, Raghav KPS, Morris VK, Menter D, Broaddus R, Meric-Bernstam F, et al: Clinical and molecular characterization of early-onset colorectal cancer. Cancer. 125:2002–2010. 2019. View Article : Google Scholar : PubMed/NCBI
25	Pancione M, Remo A and Colantuoni V: Genetic and epigenetic events generate multiple pathways in colorectal cancer progression. Patholog Res Int. 2012:5093482012.PubMed/NCBI
26	Hagland HR, Berg M, Jolma IW, Carlsen A and Soreide K: Molecular pathways and cellular metabolism in colorectal cancer. Dig Surg. 30:12–25. 2013. View Article : Google Scholar : PubMed/NCBI
27	Wang W, Kandimalla R, Huang H, Zhu L, Li Y, Gao F, Goel A and Wang X: Molecular subtyping of colorectal cancer: Recent progress, new challenges and emerging opportunities. Semin Cancer Biol. 55:37–52. 2019. View Article : Google Scholar : PubMed/NCBI
28	Liu W, Li L, Ye H and Tu W: Weighted gene co-expression network analysis in biomedicine research. Sheng Wu Gong Cheng Xue Bao. 33:1791–1801. 2017.(In Chinese). PubMed/NCBI
29	Roy I, Veldkamp CT, Volkman BF and Dwinell MB: Chemokines in colitis: MicroRNA control. Gut. 63:1202–1204. 2014. View Article : Google Scholar : PubMed/NCBI
30	Wu JS, Sheng SR, Liang XH and Tang YL: The role of tumor microenvironment in collective tumor cell invasion. Future Oncol. 13:991–1002. 2017. View Article : Google Scholar : PubMed/NCBI
31	Mandal P: Insight of nitric oxide signaling: A potential biomarker with multifaceted complex mechanism in colorectal carcinogenesis. Biochem Biophys Res Commun. 495:1766–1768. 2018. View Article : Google Scholar : PubMed/NCBI
32	Wu X, Cai J, Zuo Z and Li J: Collagen facilitates the colorectal cancer stemness and metastasis through an integrin/PI3K/AKT/Snail signaling pathway. Biomed Pharmacother. 114:1087082019. View Article : Google Scholar : PubMed/NCBI
33	Qi L and Ding Y: Construction of key signal regulatory network in metastatic colorectal cancer. Oncotarget. 9:6086–6094. 2018. View Article : Google Scholar : PubMed/NCBI
34	Viikila P, Kivela AJ, Mustonen H, Koskensalo S, Waheed A, Sly WS, Pastorek J, Pastorekova S, Parkkila S and Haglund C: Carbonic anhydrase enzymes II, VII, IX and XII in colorectal carcinomas. World J Gastroenterol. 22:8168–8177. 2016. View Article : Google Scholar : PubMed/NCBI
35	McDonald PC, Winum JY, Supuran CT and Dedhar S: Recent developments in targeting carbonic anhydrase IX for cancer therapeutics. Oncotarget. 3:84–97. 2012. View Article : Google Scholar : PubMed/NCBI
36	Qi C, Hong L, Cheng Z and Yin Q: Identification of metastasis-associated genes in colorectal cancer using metaDE and survival analysis. Oncol Lett. 11:568–574. 2016. View Article : Google Scholar : PubMed/NCBI
37	Zou X, Feng B, Dong T, Yan G, Tan B, Shen H, Huang A, Zhang X, Zhang M, Yang P, et al: Up-regulation of type I collagen during tumorigenesis of colorectal cancer revealed by quantitative proteomic analysis. J Proteomics. 94:473–485. 2013. View Article : Google Scholar : PubMed/NCBI
38	Mikula M, Rubel T, Karczmarski J, Goryca K, Dadlez M and Ostrowski J: Integrating proteomic and transcriptomic high-throughput surveys for search of new biomarkers of colon tumors. Funct Integr Genomics. 11:215–224. 2011. View Article : Google Scholar : PubMed/NCBI
39	Yang XM, You HY, Li Q, Ma H, Wang YH, Zhang YL, Zhu L, Nie HZ, Qin WX, Zhang ZG and Li J: CTHRC1 promotes human colorectal cancer cell proliferation and invasiveness by activating Wnt/PCP signaling. Int J Clin Exp Pathol. 8:12793–12801. 2015.PubMed/NCBI
40	Parks SK and Pouyssegur J: The Na(+)/HCO3(−) co-transporter SLC4A4 plays a role in growth and migration of colon and breast cancer cells. J Cell Physiol. 230:1954–1963. 2015. View Article : Google Scholar : PubMed/NCBI
41	Chen L, Lu D, Sun K, Xu Y, Hu P, Li X and Xu F: Identification of biomarkers associated with diagnosis and prognosis of colorectal cancer patients based on integrated bioinformatics analysis. Gene. 692:119–125. 2019. View Article : Google Scholar : PubMed/NCBI
42	Spisak S, Kalmar A, Galamb O, Wichmann B, Sipos F, Peterfia B, Csabai I, Kovalszky I, Semsey S, Tulassay Z and Molnár B: Genome-wide screening of genes regulated by DNA methylation in colon cancer development. PLoS One. 7:e462152012. View Article : Google Scholar : PubMed/NCBI
43	Wu Z, Liu Z, Ge W, Shou J, You L, Pan H and Han W: Analysis of potential genes and pathways associated with the colorectal normal mucosa-adenoma-carcinoma sequence. Cancer Med. 7:2555–2566. 2018. View Article : Google Scholar : PubMed/NCBI
44	Okano M, Yamamoto H, Ohkuma H, Kano Y, Kim H, Nishikawa S, Konno M, Kawamoto K, Haraguchi N, Takemasa I, et al: Significance of INHBA expression in human colorectal cancer. Oncol Rep. 30:2903–2908. 2013. View Article : Google Scholar : PubMed/NCBI
45	Yokota M, Kojima M, Higuchi Y, Nishizawa Y, Kobayashi A, Ito M, Saito N and Ochiai A: Gene expression profile in the activation of subperitoneal fibroblasts reflects prognosis of patients with colon cancer. Int J Cancer. 138:1422–1431. 2016. View Article : Google Scholar : PubMed/NCBI
46	Clermont PL, Crea F, Chiang YT, Lin D, Zhang A, Wang JZ, Parolia A, Wu R, Xue H, Wang Y, et al: Identification of the epigenetic reader CBX2 as a potential drug target in advanced prostate cancer. Clin Epigenetics. 8:162016. View Article : Google Scholar : PubMed/NCBI
47	Yu K, Lujan R, Marmorstein A, Gabriel S and Hartzell HC: Bestrophin-2 mediates bicarbonate transport by goblet cells in mouse colon. J Clin Invest. 120:1722–1735. 2010. View Article : Google Scholar : PubMed/NCBI