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      COL12A1, a novel potential prognostic factor and therapeutic target in gastric cancer

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          Abstract

          Dysregulation of collagen type XII α1 chain ( COL12A1) has been found in several cancer types and could be involved in tumor progression. However, its clinical significance in gastric cancer (GC) remains under exploration. Online databases (Gene Expression Omnibus and UALCAN), reverse transcription-quantitative PCR and immunohistochemistry were utilized in the present study to evaluate the expression of COL12A1 in GC tissues and cell lines. It was found that COL12A1 expression was notably upregulated in GC. Clinicopathological analysis showed that elevated COL12A1 expression was positively correlated with tumor invasiveness, metastasis and advanced clinical stage. The prognostic analysis suggested that high COL12A1 expression contributed to poor overall survival. Multivariate Cox analysis indicated that COL12A1 overexpression was a powerful independent prognostic indicator in patients with GC (hazard ratio, 1.896; 95% CI, 1.267–2.837; P=0.002). The results highlighted the importance of COL12A1 in GC and suggested its potential role as a candidate for clinical outcome prediction and targeted therapy in patients with GC.

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          The Gene Expression Omnibus Database.

          Emily Clough, Tanya Barrett (2016)
          The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.
          Article 0 comments Cited 431 times – based on 0 reviews     Review now
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            Genome-wide expression profile of sporadic gastric cancers with microsatellite instability.

            Mariarosaria D’Errico, Emanuele Rinaldis, Monica F. Blasi … (2009)
            Gastric cancers with mismatch repair (MMR) inactivation are characterised by microsatellite instability (MSI). In this study, the transcriptional profile of 38 gastric cancers with and without MSI was analysed. Unsupervised analysis showed that the immune and apoptotic gene networks efficiently discriminated these two cancer types. Hierarchical clustering analysis revealed numerous gene expression changes associated with the MSI phenotype. Amongst these, the p53-responsive genes maspin and 14-3-3 sigma were significantly more expressed in tumours with than without MSI. A tight immunosurveillance coupled with a functional p53 gene response is consistent with the better prognosis of MSI cancers. Frequent silencing of MLH1 and downregulation of MMR target genes, such as MRE11 and MBD4, characterised MSI tumours. The downregulation of SMUG1 was also a typical feature of these tumours. The DNA repair gene expression profile of gastric cancer with MSI is of relevance for therapy response.
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              Proteome profiling of cancer-associated fibroblasts identifies novel proinflammatory signatures and prognostic markers for colorectal cancer.

              Marta Mendes, María López, Rodrigo Barderas … (2013)
              Cancer-associated fibroblasts (CAF) are essential components of the stroma that play a critical role in cancer progression. This study aimed to identify novel CAFs markers that might contribute to the invasion and the prognosis of colorectal cancer. The azoxymethane/dextran sodium sulfate mouse model of sporadic colon cancer represents an adequate source for the isolation of CAFs and normal fibroblasts. By using the explants technique, we purified CAFs and normal fibroblasts from colon tissues. Whole-cell extracts and supernatants were subjected to in-depth quantitative proteomic analysis by tandem mass spectrometry. Further validations of upregulated proteins in CAFs were carried out by chemokine microarray and immunohistochemical analyses of mouse and human tissues. Using a fold-change of 1.4 or more, we found 132 and 125 differentially expressed proteins in whole-cell extracts and supernatants, respectively. We found CAFs-associated proinflammatory and desmoplastic signatures. The proinflammatory signature was composed of several cytokines. Among them, CCL2 and CCL8 caused an increase in migration and invasion of colorectal cancer KM12 cells. The desmoplastic signature was composed of 30 secreted proteins. In mouse and human samples, expression of LTBP2, CDH11, OLFML3, and, particularly, FSTL1 was significantly increased in the tumoral stroma, without significant expression in the cancer epithelial cells. The combination of CALU and CDH11 stromal expression showed a significant association with disease-free survival and poor prognosis. We have identified LTBP2, CDH11, OLFML3, and FSTL1 as selective biomarkers of cancer stroma, and CALU and CDH11 as candidate stromal biomarkers of prognostic significance in colon cancer.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Mol Med Rep
                Journal ID (iso-abbrev): Mol Med Rep
                Title: Molecular Medicine Reports
                Publisher: D.A. Spandidos
                ISSN (Print): 1791-2997
                ISSN (Electronic): 1791-3004
                Publication date (Print): October 2019
                Publication date (Electronic): 01 August 2019
                Publication date PMC-release: 01 August 2019
                Volume: 20
                Issue: 4
                Pages: 3103-3112
                Affiliations
                [1 ]Cancer Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, P.R. China
                [2 ]Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou, Zhejiang 310003, P.R. China
                [3 ]Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, P.R. China
                Author notes
                Correspondence to: Professor Lisong Teng, Cancer Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 Qingchun Road, Hangzhou, Zhejiang 310003, P.R. China, E-mail: lsteng@ 123456zju.edu.cn
                Article
                Publisher ID: mmr-20-04-3103
                DOI: 10.3892/mmr.2019.10548
                PMC ID: 6755194
                PubMed ID: 31432110
                SO-VID: be324913-d83b-4e53-8cfc-f172963e012d
                Copyright © Copyright: © Jiang et al.
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

                History
                Date received : 30 January 2019
                Date accepted : 05 July 2019
                Categories
                Subject: Articles

                Keywords: bioinformatics analysis,immunohistochemistry,collagen type xii α1 chain,extracellular matrix,prognosis
                Data availability:
                Keywords: bioinformatics analysis, immunohistochemistry, collagen type xii α1 chain, extracellular matrix, prognosis

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