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Pathway analysis of genome-wide association study and transcriptome data highlights new biological pathways in colorectal cancer

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Abstract

Colorectal cancer (CRC) is a common malignancy that meets the definition of a complex disease. Genome-wide association study (GWAS) has identified several loci of weak predictive value in CRC, however, these do not fully explain the occurrence risk. Recently, gene set analysis has allowed enhanced interpretation of GWAS data in CRC, identifying a number of metabolic pathways as important for disease pathogenesis. Whether there are other important pathways involved in CRC, however, remains unclear. We present a systems analysis of KEGG pathways in CRC using (1) a human CRC GWAS dataset and (2) a human whole transcriptome CRC case–control expression dataset. Analysis of the GWAS dataset revealed significantly enriched KEGG pathways related to metabolism, immune system and diseases, cellular processes, environmental information processing, genetic information processing, and neurodegenerative diseases. Altered gene expression was confirmed in these pathways using the transcriptome dataset. Taken together, these findings not only confirm previous work in this area, but also highlight new biological pathways whose deregulation is critical for CRC. These results contribute to our understanding of disease-causing mechanisms and will prove useful for future genetic and functional studies in CRC.

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Acknowledgments

We thank the CoRGI consortium and Lascorz for the CRC GWAS and expression datasets, respectively. This research is supported by the grants from the National Nature Science Foundation of China (Grant No: 81300945, 31200934, 31301040 and 31301938).

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Department of General Surgery, The First Hospital of Harbin, Harbin, China

    Baoku Quan

  2. Department of Gastroenterology, The First Hospital of Harbin, Harbin, China

    Xingsi Qi

  3. Department of Gastroenterology, General Hospital of Heilongjiang Land Reclamation Bureau, Harbin, China

    Zhihui Yu

  4. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China

    Yongshuai Jiang

  5. College of Life Science, Northwest A and F University, Yangling, Shaanxi, China

    Mingzhi Liao

  6. Department of Gastrointestinal Medical Oncology, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China

    Guangyu Wang

  7. Department of Oncology, The First Hospital of Harbin, Harbin, China

    Guangyu Wang

  8. Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China

    Rennan Feng

  9. Department of Statistics, Rice University, Houston, TX, USA

    Liangcai Zhang

  10. Department of Human Genetics, University of California at Los Angeles, Los Angeles, CA, USA

    Zugen Chen

  11. School of Life Science and Technology, Harbin Institute of Technology, Heilongjiang, 150001, Harbin, China

    Qinghua Jiang

  12. Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Xiqi Dao 32, Tianjin Airport Economic Area, 300308, Tianjin, China

    Baoku Quan, Xingsi Qi & Guiyou Liu

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  1. Baoku Quan
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  3. Zhihui Yu
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  10. Qinghua Jiang
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Corresponding authors

Correspondence to Qinghua Jiang or Guiyou Liu.

Additional information

Communicated by S. Hohmann.

Baoku Quan and Xingsi Qi contributed equally to this work.

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Quan, B., Qi, X., Yu, Z. et al. Pathway analysis of genome-wide association study and transcriptome data highlights new biological pathways in colorectal cancer. Mol Genet Genomics 290, 603–610 (2015). https://doi.org/10.1007/s00438-014-0945-y

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  • DOI: https://doi.org/10.1007/s00438-014-0945-y

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