Ping Gao1, Miao He2, Chunling Zhang3, Changhui Geng4. 1. Department of Gastroenterology, Daqing Oil Field General Hospital, Daqing 163000, Heilongjiang Province, China. 2. Department of Pathology, Daqing Oil Field General Hospital, Daqing 163000, Heilongjiang Province, China. 3. Department of Ultrasound, Daqing Oil Field General Hospital, Daqing 163000, Heilongjiang Province, China. 4. Department of General Surgery, The Fifth Affiliated Hospital of Harbin Medical University, Daqing 163316, Heilongjiang Province, China. Electronic address: Cahhy_G610@126.com.
Abstract
PURPOSE: The present study aimed to elucidate the pathogenesis of colon cancer and identify genes associated with tumor development. METHODS: Three datasets, two (GSE74602 and GSE44861) from the Gene Expression Omnibus database and RNA-Seq colon cancer data from The Cancer Genome Atlas data portal, were downloaded. These three datasets were grouped using a meta-analysis approach, and differentially expressed genes (DEGs) were identified between colon tumor samples and adjacent normal samples. Functional enrichment analysis and regulatory factor predication were performed for significant genes. Additionally, small-molecule drugs associated with colon cancer were predicted, and a prognostic risk model was constructed. RESULTS: There were 251 overlapping DEGs (135 up- and 116 downregulated) between cancer samples and control samples in the three datasets. The DEGs were mainly involved in protein transport and apoptotic and neurotrophin signaling pathways. A total of 70 small-molecule drugs were predicated to be associated with colon cancer. Additionally, in the miRNA-target regulatory network, we found that SLC44A1 can be targeted by hsa-miR-183, hsa-miR-206, and hsa-miR-147, while KLF13 can be regulated by hsa-miR-182, hsa-miR-206, and hsa-miR-153. Moreover, the results of the prognostic risk model showed that four genes (VAMP1, P2RX5, CACNB1, and CRY2) could divide the samples into high and low risk groups. CONCLUSION: SLC44A1 and KLF13 may be involved in tumorigenesis and the metastasis of colon cancer by miRNA regulation. In addition, a four-gene (VAMP1, P2RX5, CACNB1, and CRY2) expression signature may have prognostic and predictive value in colon cancer.
PURPOSE: The present study aimed to elucidate the pathogenesis of colon cancer and identify genes associated with tumor development. METHODS: Three datasets, two (GSE74602 and GSE44861) from the Gene Expression Omnibus database and RNA-Seq colon cancer data from The Cancer Genome Atlas data portal, were downloaded. These three datasets were grouped using a meta-analysis approach, and differentially expressed genes (DEGs) were identified between colon tumor samples and adjacent normal samples. Functional enrichment analysis and regulatory factor predication were performed for significant genes. Additionally, small-molecule drugs associated with colon cancer were predicted, and a prognostic risk model was constructed. RESULTS: There were 251 overlapping DEGs (135 up- and 116 downregulated) between cancer samples and control samples in the three datasets. The DEGs were mainly involved in protein transport and apoptotic and neurotrophin signaling pathways. A total of 70 small-molecule drugs were predicated to be associated with colon cancer. Additionally, in the miRNA-target regulatory network, we found that SLC44A1 can be targeted by hsa-miR-183, hsa-miR-206, and hsa-miR-147, while KLF13 can be regulated by hsa-miR-182, hsa-miR-206, and hsa-miR-153. Moreover, the results of the prognostic risk model showed that four genes (VAMP1, P2RX5, CACNB1, and CRY2) could divide the samples into high and low risk groups. CONCLUSION:SLC44A1 and KLF13 may be involved in tumorigenesis and the metastasis of colon cancer by miRNA regulation. In addition, a four-gene (VAMP1, P2RX5, CACNB1, and CRY2) expression signature may have prognostic and predictive value in colon cancer.
Authors: Marta Sarquis; Debora C Moraes; Luciana Bastos-Rodrigues; Pedro G Azevedo; Adauto V Ramos; Fabiana Versiani Reis; Paula V Dande; Isabela Paim; Eitan Friedman; Luiz De Marco Journal: Endocr Pathol Date: 2020-03 Impact factor: 3.943
Authors: María Sánchez-Ares; Soledad Cameselle-García; Ihab Abdulkader-Nallib; Gemma Rodríguez-Carnero; Carolina Beiras-Sarasquete; José Antonio Puñal-Rodríguez; José Manuel Cameselle-Teijeiro Journal: Front Endocrinol (Lausanne) Date: 2022-02-28 Impact factor: 5.555
Authors: Hirotaka Iwaki; Cornelis Blauwendraat; Hampton L Leonard; Jonggeol J Kim; Ganqiang Liu; Jodi Maple-Grødem; Jean-Christophe Corvol; Lasse Pihlstrøm; Marlies van Nimwegen; Samantha J Hutten; Khanh-Dung H Nguyen; Jacqueline Rick; Shirley Eberly; Faraz Faghri; Peggy Auinger; Kirsten M Scott; Ruwani Wijeyekoon; Vivianna M Van Deerlin; Dena G Hernandez; J Raphael Gibbs; Kumaraswamy Naidu Chitrala; Aaron G Day-Williams; Alexis Brice; Guido Alves; Alastair J Noyce; Ole-Bjørn Tysnes; Jonathan R Evans; David P Breen; Karol Estrada; Claire E Wegel; Fabrice Danjou; David K Simon; Ole Andreassen; Bernard Ravina; Mathias Toft; Peter Heutink; Bastiaan R Bloem; Daniel Weintraub; Roger A Barker; Caroline H Williams-Gray; Bart P van de Warrenburg; Jacobus J Van Hilten; Clemens R Scherzer; Andrew B Singleton; Mike A Nalls Journal: Mov Disord Date: 2019-09-10 Impact factor: 9.698