Prediction and Validation of Hub Genes Associated with Colorectal Cancer by Integrating PPI Network and Gene Expression Data

Abstract

Although hundreds of colorectal cancer- (CRC-) related genes have been screened, the significant hub genes still need to be further identified. The aim of this study was to identify the hub genes based on protein-protein interaction network and uncover their clinical value. Firstly, 645 CRC patients' data from the Tumor Cancer Genome Atlas were downloaded and analyzed to screen the differential expression genes (DEGs). And then, the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed, and PPI network of the DEGs was constructed by Cytoscape software. Finally, four hub genes (CXCL3, ELF5, TIMP1, and PHLPP2) were obtained from four subnets and further validated in our clinical setting and TCGA dataset. The results showed that mRNA expression of CXCL3, ELF5, and TIMP1 was increased in CRC tissues, whereas PHLPP2 mRNA expression was decreased. More importantly, high expression of CXCL3, ELF5, and TIMP1 was significantly associated with lymphatic invasion, distance metastasis, and advanced tumor stage. In addition, a shorter overall survival was observed in patients with increased CXCL3, TIMP1, and ELF5 expression and decreased PHLPP2 expression. In conclusion, the four hub genes screened by our strategy could serve as novel biomarkers for prognosis prediction of CRC patients.

Profiles of alternative splicing in colorectal cancer and their clinical significance: A study based on large-scale sequencing data

“…Then, downloaded samples and corresponding clinical data were cross-referenced by TCGA barcodes. Some patients do not meet the following criteria were eliminated: [ 1 ] a histological diagnosis of CRC [ 2 ] patients with complete clinical features including sex, age, tumor location, local invasion, lymph node metastasis, distal metastasis, differentiation grade, pathologic stage, survival information; [ 3 ] patients were still alive at least 1 month after initial pathologic diagnosis; [ 4 ] patients with corresponding RNA-Seq data. To generate the AS profiles for each CRC patient, SpliceSeq, a java application that unambiguously quantify the inclusion level of each exon and splice junction, was used to evaluate the RNA splicing patterns as previous described [ 26 , 27 ].…”

“…Despite advances in screening, diagnosis, and curative resection, colorectal cancer (CRC) is still one of the leading causes of cancer-related death worldwide [ 1 ]. In addition, it's clinical outcome for individual cases remains unsatisfactory because optimal management and individual therapy strategies still present great challenges [ 2 ]. At present, surgical resection is the only potentially curative therapy for CRC.…”

“…By applying RNA sequencing(RNA Seq) and microarrays in recent year, gene expression and genomic profiling of CRC have been sufficiently evaluated [ [6] , [7] , [8] ], and the arm these studies are mainly focusing on differential gene expression for CRC phenotype classification, but also on gene expression variability according to clinical staging [ [9] , [10] , [11] ]. For example, a genome-wide CRC-related genes identification was conducted in our recently published study, which combining sequence data of paired tissue samples(e.g., neoplastic vs normal tissue) and corresponding clinical information to insight into the potential biological and clinical value of transcriptome variation [ 2 ]. Additionally, studies involved ncRNA expression, copy number variation, DNA methylation and nucleotide polymorphisms have been widely performed, especially in CRC [ 12 , 13 ].…”

Identification of prognostic-associated genes in colorectal cancer based on genome-wide expression profiles

“…C-X-C motif chemokine ligand 3 (CXCL3) is a member of the CXC chemokine family, and its expression is associated with various cancers, such as liver cancer [19], gastric cancer [20], breast cancer [21], prostate cancer [22], and non-small cell cancer [23]. Meanwhile, some scholars have explored CXCL3 in the CRC, and their ndings consistently reveal that the expression of CXCL3 in cancer tissues is signi cantly higher than that in normal tissues [24,25]. The research indicated that there was no signi cant difference in CXCL3 expression between non-metastatic and low metastatic colon cancer cells compared with highly metastatic colon cancer cells [26].…”

Genome-Wide Transcriptional Analysis Reveals Alternative Splicing Event Profiles in Hepatocellular Carcinoma and Their Prognostic Significance

“…RNA sequencing (RNA-Seq) and microarrays, the most representative methods of this technology, are mature enough for use in commercial applications ( Mantione et al, 2014 ; Zhang et al, 2015 ). During the past decades, the genome-wide transcriptional analysis of gene expression has become critically important to gain better insight into the biological processes of HCC and other types of cancer ( Jin et al, 2015 ; Xiong et al, 2017 ). In addition to the aberrant expression of transcripts, studies have focused on different molecular levels (multi-level omics), including copy number variation, epigenetic modifications, nucleotide polymorphisms, and DNA methylation, especially in HCC ( Lee et al, 2016 ; Lin et al, 2017 ).…”