Dataset Information

Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression.

ABSTRACT: Recurrence and poorly differentiated (grade 3 and above) and atypical cell type endometrial cancer (EC) have poor prognosis outcome. The mechanisms and characteristics of recurrence and distal metastasis of EC remain unclear. The extracellular matrix (ECM) of the reproductive tract in women undergoes extensive structural remodelling changes every month. Altered ECMs surrounding cells were believed to play crucial roles in a cancer progression. To decipher the associations between ECM and EC development, we generated a PAN-ECM Data list of 1516 genes including ECM molecules (ECMs), synthetic and degradation enzymes for ECMs, ECM receptors, and soluble molecules that regulate ECM and used RNA-Seq data from The Cancer Genome Atlas (TCGA) for the studies. The alterations of PAN-ECM genes by comparing the RNA-Seq expressions profiles of EC samples which have been grouped as tumorigenesis and metastasis group based on their pathological grading were identified. Differential analyses including functional enrichment, co-expression network, and molecular network analysis were carried out to identify the specific PAN-ECM genes that may involve in the progression of EC. Eight hundred and thirty-one and 241 PAN-ECM genes were significantly involved in tumorigenesis (p-value <1.571e-15) and metastasis (p-value <2.2e-16), respectively, whereas 140 genes were in the intersection of tumorigenesis and metastasis. Interestingly, 92 of the 140 intersecting PAN-ECM genes showed contrasting fold changes between the tumorigenesis and metastasis datasets. Enrichment analysis for the contrast PAN-ECM genes indicated pathways such as GP6 signaling, ILK signaling, and interleukin (IL)-8 signaling pathways were activated in metastasis but inhibited in tumorigenesis. The significantly activated ECM and ECM associated genes in GP6 signaling, ILK signaling, and interleukin (IL)-8 signaling pathways may play crucial roles in metastasis of EC. Our study provides a better understanding of the etiology and the progression of EC.

SUBMITTER: Yadav VK

PROVIDER: S-EPMC7173926 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression.

Yadav Vijesh Kumar VK Lee Tzong-Yi TY Hsu Justin Bo-Kai JB Huang Hsien-Da HD Yang Wei-Chung Vivian WV Chang Tzu-Hao TH

PloS one 20200421 4

Recurrence and poorly differentiated (grade 3 and above) and atypical cell type endometrial cancer (EC) have poor prognosis outcome. The mechanisms and characteristics of recurrence and distal metastasis of EC remain unclear. The extracellular matrix (ECM) of the reproductive tract in women undergoes extensive structural remodelling changes every month. Altered ECMs surrounding cells were believed to play crucial roles in a cancer progression. To decipher the associations between ECM and EC deve ...[more]

PMID: 32315343

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Project description:Cell adhesion molecules (CAMs) determine the behavior of cancer cells during metastasis. Although some CAMs are dysregulated in certain types of cancer and are associated with cancer progression, to the best of our knowledge, a comprehensive study of CAMs has not been undertaken, particularly in endometrial cancer (EC). In the present study the expression of 225 CAMs in EC patients with various clinicopathological phenotypes were evaluated by statistical analysis using publicly available data from The Cancer Genome Atlas database. The Kaplan-Meier method, and univariate and multivariate Cox proportional hazards regression models were used for survival analyses. Among the differentially expressed CAMs that were associated with aggressive clinicopathological phenotypes, 10 CAM genes were independent prognostic factors compared with other clinicopathological prognostic factors, including stage, grade, age, lymph node status, peritoneal cytology and histological subtype. A total of six genes (L1 cell adhesion molecule, mucin 15, cell surface associated, cell adhesion associated, oncogene regulated, immunoglobulin superfamily member 9B, protocadherin 9 and protocadherin β1) were selected for integrative analysis. The six-gene signature was demonstrated to be an independent prognostic factor and could effectively stratify patients with different risks. Patients with more high-expression CAMs had a higher risk of poor overall survival (OS) rate. The mortality risk for patients with elevation of >4 CAMs was 11 times of that in those without elevation of these 6 CAMs. Similar results were obtained when relapse-free survival (RFS) time was used during the analysis. Prognostic reliability of the six-gene model was validated using data of an independent cohort from the International Cancer Genome Consortium. In conclusion, a combination of CAM alterations contributed to progression and aggressiveness of EC. The six-gene signature was effective for predicting worse OS and RFS in patients with EC and could be complementary to the present clinical prognostic criteria.

Dataset Information

Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression.

Publications

Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression.

Similar Datasets

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