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Identification of Prognostic Genes for Colon Cancer through Gene Co-expression Network Analysis

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Abstract

Objective

The present study was aimed to identify novel key genes, prognostic biomarkers and molecular pathways implicated in tumorigenesis of colon cancer.

Methods

The microarray data GSE41328 containing 10 colon cancer samples and 10 adjacent normal tissues was analyzed to identify 4763 differentially expressed genes. Meanwhile, another microarray data GSE17536 was performed for weighted gene co-expression network analysis (WGCNA).

Results

In present study, 12 co-expressed gene modules associated with tumor progression were identified for further studies. The red module showed the highest association with pathological stage by Pearson’s correlation analysis. Functional enrichment analysis revealed that genes in red module focused on cell division, cell proliferation, cell cycle and metabolic related pathway. Then, a total of 26 key hub genes were identified, and GEPIA database was subsequently selected for validation. Holliday junction-recognizing protein (HJURP) and cell division cycle 25 homolog C (CDC25C) were identified as effective prognosis biomarkers, which were all detrimental to prognosis. Gene set enrichment analyses (GSEA) found the two hub genes were enriched in “oocyte meiosis”, “oocyte maturation that are progesterone-mediated”, “p53 signaling pathway”, and “cell cycle”. Furthermore, the immunohistochemistry and western blotting showed that HJURP was highly expressed in colon cancer tissue.

Conclusion

HJURP was identified as a key gene associated with colon cancer progression and prognosis by WGCNA, which might influence the prognosis by regulating cell cycle pathways.

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Author information

Author notes

  1. Dan-wen WANG, Zhang-shuo YANG and Jian XU contributed equally to this work.

Authors and Affiliations

  1. Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China

    Dan-wen Wang, Li-jie Yang, Tie-cheng Yang, Hua-qiao Wang & Mao-hui Feng

  2. Key Laboratory of Tumor Biological Behavior of Hubei Province, Wuhan, 430071, China

    Dan-wen Wang, Zhang-shuo Yang, Li-jie Yang, Tie-cheng Yang, Hua-qiao Wang & Mao-hui Feng

  3. Center for Clinical Medicine of Peritoneal Cancer of Wuhan, Wuhan, 430071, China

    Dan-wen Wang, Li-jie Yang, Tie-cheng Yang, Hua-qiao Wang & Mao-hui Feng

  4. Clinical Cancer Study Center of Hubei Province, Wuhan, 430071, China

    Dan-wen Wang, Zhang-shuo Yang, Li-jie Yang, Tie-cheng Yang, Hua-qiao Wang & Mao-hui Feng

  5. Department of Pathology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China

    Jian Xu

  6. Department of Oncology, the First Hospital of Lanzhou University, Lanzhou, 730000, China

    Fei Su

Authors
  1. Dan-wen Wang
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  2. Zhang-shuo Yang
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  3. Jian Xu
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  4. Li-jie Yang
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  5. Tie-cheng Yang
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  6. Hua-qiao Wang
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  7. Mao-hui Feng
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  8. Fei Su
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Corresponding authors

Correspondence to Mao-hui Feng or Fei Su.

Additional information

This project was supported in part by grants from the National Natural Science Foundation of China (No. 81072152 and No. 81770283), Natural Science Foundation of Hubei Province (No. 2015CFA027), Research Foundation of Health and Family Planning Commission of Hubei Province (No. WJ2015MA010 and No. WJ2017M249), Clinical Medical Research Center of Peritoneal Cancer of Wuhan (No. 2015060911020462) and Subsidy Project of No. 1 Hospital of Lanzhou University (No. ldyyyn2018-13) and Innovation fund of universities in Gansu Province (No. 2020B-009).

Conflict of Interest Statement

The authors have no conflicts of interest to disclose.

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Wang, Dw., Yang, Zs., Xu, J. et al. Identification of Prognostic Genes for Colon Cancer through Gene Co-expression Network Analysis. CURR MED SCI 41, 1012–1022 (2021). https://doi.org/10.1007/s11596-021-2386-2

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  • DOI: https://doi.org/10.1007/s11596-021-2386-2

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