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2000
Volume 16, Issue 4
  • ISSN: 1570-1786
  • E-ISSN: 1875-6255

Abstract

Colorectal cancer (CRC) is a common malignant tumor of the digestive tract occurring in the colon, which mainly divided into adenocarcinoma, mucinous adenocarcinoma, and undifferentiated carcinoma. However, autophagy is related to the occurrence and development of various kinds of human diseases such as cancer. There is little research on the relationship between CRC and autophagy. Hence, we performed multidimensional integration analysis to systematically explore potential relationship between autophagy and CRC. Based on gene expression datasets of colon adenocarcinoma (COAD) and protein-protein interactions (PPIs), we first identified 12 autophagy-related modules in COAD using WGCNA. Then, 9 module pairs which with significantly crosstalk were deciphered, a total of 6 functional modules. Autophagy-related genes in these modules were closely related with CRC, emphasizing that the important role of autophagy-related genes in CRC, including PPP2CA and EIF4E, etc. In addition to, by integrating transcription factor (TF)-target and RNA-associated interactions, a regulation network was constructed, in which 42 TFs (including SMAD3 and TP53, etc.) and 20 miRNAs (including miR-20 and miR-30a, etc.) were identified as pivot regulators. Pivot TFs were mainly involved in cell cycle, cell proliferation and pathways in cancer. And pivot miRNAs were demonstrated associated with CRC. It suggests that these pivot regulators might be have an effect on the development of CRC by regulating autophagy. In a word, our results suggested that multidimensional integration strategy provides a novel approach to discover potential relationships between autophagy and CRC, and further improves our understanding of autophagy and tumor in human.

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/content/journals/loc/10.2174/1570178615666180914113224
2019-04-01
2025-09-23
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/content/journals/loc/10.2174/1570178615666180914113224
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  • Article Type:
    Research Article
Keyword(s): autophagy; co-expression modules; COAD; Colorectal cancer; multidimensional analysis; WGCNA
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