Radiogenomic Analysis of F-18-Fluorodeoxyglucose Positron Emission Tomography and Gene Expression Data Elucidates the Epidemiological Complexity of Colorectal Cancer Landscape

Vlachavas, Efstathios–Iason; Pilalis, Eleftherios; Papadodima, Olga; Koczan, Dirk; Willis, S.; Klippel, Sven; Chen, Cheng; Pan, Leyun; Sachpekidis, Christos; Pintzas, Alexander; Gregoriou, Vasilis G.; Dimitrakopoulou-Strauß, Antonia; Chatziioannou, Aristotelis

doi:10.1016/j.csbj.2019.01.007

Cited by 74 publications

(63 citation statements)

References 31 publications

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“…Other datasets that satisfied the following criteria were downloaded from GEO ( ): 1) Gene expression data in the microarray datasets included data for both control tissues and CRC tissues, and 2) each microarray contained a minimum of 5 tumor and control tissues. According to the above criteria, 10 GEO datasets were incorporated in this study: GSE9348 ( 10 ), GSE44076 ( 11 ), GSE4183 ( 12 ), GSE20916 ( 13 ), GSE37364 ( 14 ), GSE44861 ( 15 ), GSE81558 ( 16 ), GSE22598 ( 17 ), GSE113513, and GSE110224 ( 18 ).…”

Section: Methodsmentioning

confidence: 99%

Differential Expression Analysis Revealing CLCA1 to Be a Prognostic and Diagnostic Biomarker for Colorectal Cancer

et al. 2020

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Colorectal cancer (CRC) is a common malignant tumor of the digestive tract and lacks specific diagnostic markers. In this study, we utilized 10 public datasets from the NCBI Gene Expression Omnibus (NCBI-GEO) database to identify a set of significantly differentially expressed genes (DEGs) between tumor and control samples and WGCNA (Weighted Gene Co-Expression Network Analysis) to construct gene co-expression networks incorporating the DEGs from The Cancer Genome Atlas (TCGA) and then identify genes shared between the GEO datasets and key modules. Then, these genes were screened via MCC to identify 20 hub genes. We utilized regression analyses to develop a prognostic model and utilized the random forest method to validate. All hub genes had good diagnostic value for CRC, but only CLCA1 was related to prognosis. Thus, we explored the potential biological value of CLCA1. The results of gene set enrichment analysis (GSEA) and immune infiltration analysis showed that CLCA1 was closely related to tumor metabolism and immune invasion of CRC. These analysis results revealed that CLCA1 may be a candidate diagnostic and prognostic biomarker for CRC.

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Section: Methodsmentioning

confidence: 99%

Differential Expression Analysis Revealing CLCA1 to Be a Prognostic and Diagnostic Biomarker for Colorectal Cancer

et al. 2020

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“…DEG Identification by GEO. The gene expression profile data (GSE21510, GSE24514, GSE32323, GSE89076, GSE110225, and GSE113513) for colorectal cancer were extracted from the GEO database [20][21][22][23][24]. All included datasets contained at least 10 samples.…”

Section: Methodsmentioning

confidence: 99%

Identification of Hub Genes Related to Carcinogenesis and Prognosis in Colorectal Cancer Based on Integrated Bioinformatics

Gong

Kao

Zhang

et al. 2020

Mediators of Inflammation

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The high mortality of colorectal cancer (CRC) patients and the limitations of conventional tumor-node-metastasis (TNM) stage emphasized the necessity of exploring hub genes closely related to carcinogenesis and prognosis in CRC. The study is aimed at identifying hub genes associated with carcinogenesis and prognosis for CRC. We identified and validated 212 differentially expressed genes (DEGs) from six Gene Expression Omnibus (GEO) datasets and the Cancer Genome Atlas (TCGA) database. We investigated functional enrichment analysis for DEGs. The protein-protein interaction (PPI) network was constructed, and hub modules and genes in CRC carcinogenesis were extracted. A prognostic signature was developed and validated based on Cox proportional hazards regression analysis. The DEGs mainly regulated biological processes covering response to stimulus, metabolic process, and affected molecular functions containing protein binding and catalytic activity. The DEGs played important roles in CRC-related pathways involving in preneoplastic lesions, carcinogenesis, metastasis, and poor prognosis. Hub genes closely related to CRC carcinogenesis were extracted including six genes in model 1 (CXCL1, CXCL3, CXCL8, CXCL11, NMU, and PPBP) and two genes and Metallothioneins (MTs) in model 2 (SLC26A3 and SLC30A10). Among them, CXCL8 was also related to prognosis. An eight-gene signature was proposed comprising AMH, WBSCR28, SFTA2, MYH2, POU4F1, SIX4, PGPEP1L, and PAX5. The study identified hub genes in CRC carcinogenesis and proposed an eight-gene signature with good reproducibility and robustness at the molecular level for CRC, which might provide directive significance for treatment selection and survival prediction.

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“…In GSE110224 dataset, 17 patients with no significant age difference had been histologically confirmed with CRC [15], and tissue specimens of tumor and adjacent non-tumor tissues were collected during surgery. The isolated RNA was previously profiled by Affymetrix Human Genome U133 Plus 2.0 array.…”

Section: Gene Expression In Human Crc Microarray Datasetmentioning

confidence: 99%

Elastin is a key factor of tumor development in colorectal cancer

Jiang

et al. 2020

BMC Cancer

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Background: Colorectal cancer (CRC) is the most common cancer and a leading cause of death worldwide. Extracellular matrix (ECM) proteins regulate tumor growth and development in CRC. Elastin (ELN) is a component of ECM proteins involved in the tumor microenvironment. However, the role of ELN in CRC remains unclear. Methods: In this study, we analyzed ELN gene expression in tumors from CRC patients and adjacent non-tumor colon tissues and healthy controls from two existing microarray datasets. ELN protein was measured in human normal colon cells and colon cancer epithelial cells and tumor development was assessed in colon epithelial cells cultured in medium with or without ELN peptide on plates coated with ELN recombinant protein. Control plates were coated with PBS only. Results: We found ELN gene expression was increased in tumors from CRC patients compared to adjacent nontumor tissues and healthy controls. ELN protein was increased in cancer cells compared to normal colon epithelial cells. Transforming growth factor beta (TGF-β) was a key cytokine to induce production of ECM proteins, but it did not induce ELN expression in colon cancer cells. Matrix metalloproteinase 9 (MMP9) gene expression was increased, but that of MMP12 (elastase) did not change between CRC patients and control. Tissue inhibitor of metalloproteinases 3 (TIMP3) gene expression was decreased in colon tissues from CRC patients compared to healthy controls. However, MMP9, MMP12 and TIMP3 proteins were increased in colon cancer cells. ELN recombinant protein increased proliferation and wound healing in colon cancer epithelial cells. This had further increased in cancer cells incubated in plates coated with recombinant ELN coated plate and in culture media containing ELN peptide. A potential mechanism was that ELN induced epithelial mesenchymal transition with increased alpha-smooth muscle actin and vimentin proteins but decreased E-cadherin protein. Tumor necrosis factor alpha (TNF) mRNA was also increased in CRC patients compared to controls. ELN recombinant protein induced further increases in TNF protein in mouse bone marrow derived macrophages after lipopolysaccharide stimulation. Conclusions: These data suggest ELN regulates tumor development and the microenvironment in CRC.

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Radiogenomic Analysis of F-18-Fluorodeoxyglucose Positron Emission Tomography and Gene Expression Data Elucidates the Epidemiological Complexity of Colorectal Cancer Landscape

Cited by 74 publications

References 31 publications

Differential Expression Analysis Revealing CLCA1 to Be a Prognostic and Diagnostic Biomarker for Colorectal Cancer

Differential Expression Analysis Revealing CLCA1 to Be a Prognostic and Diagnostic Biomarker for Colorectal Cancer

Identification of Hub Genes Related to Carcinogenesis and Prognosis in Colorectal Cancer Based on Integrated Bioinformatics

Elastin is a key factor of tumor development in colorectal cancer

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