Dataset Information

Identification and Validation of MSX1 as a Key Candidate for Progestin Resistance in Endometrial Cancer.

ABSTRACT: Purpose:Progestin resistance is a critical obstacle for endometrial conservative therapy. Therefore, studies to acquire a more comprehensive understanding of the mechanisms are urgent. However, the pivotal molecules are still unexplored. Materials and Methods:We downloaded GSE121367 from the GEO database. The "limma" R language package was applied to identify differentially expressed genes (DEGs). We conducted Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA). Protein-protein interaction was constructed by STRING and visualized in Cytoscape. The tumor immune microenvironment was explored by the TISIDB database. Methylation validation and overall survival analysis were conducted by the TCGA database. In addition, the upstream modulators of hub genes were predicted by miRTarBase and Network Analyst databases. The expression levels of candidate genes were validated by quantitative real-time PCR (qRT-PCR), Western blot, and immunohistochemical assay (IHC). Cell growth, clone formation, migration, invasion, and wound healing assays were studied to explore the role of MSX1 in progestin resistance in vitro. Results:A total of 3,282 DEGs were identified and they were mostly enriched in the cell adhesion pathway. We screened out ten hub genes whose genomic alteration rates were low based on the current endometrial carcinoma sample sets. Has-miR-335-5p, has-miR-124-3p, MAZ, and TFDP1 were the most prominent upstream regulators. The methylation status of CDH1, JAG1, EPCAM, and MSX1 was decreased, corresponding to their high protein expression, which also predicted better overall survival. The homeobox protein of MSX1 showed significant tissue specificity and better prognostic value and its knockdown inhibited epithelial-mesenchymal transitions (EMT) and enhanced progesterone efficacy. Conclusion:Our study identified that the gene of MSX1 promised to be the specific indicator and therapeutic target for progestin resistance. This would shed new light on the underlying biological mechanism to overcome progestin resistance of endometrial cancer.

SUBMITTER: Yang L

PROVIDER: S-EPMC7679365 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification and Validation of MSX1 as a Key Candidate for Progestin Resistance in Endometrial Cancer.

Yang Linlin L Cui Yunxia Y Huang Ting T Sun Xiao X Wang Yudong Y

OncoTargets and therapy 20201113

<h4>Purpose</h4>Progestin resistance is a critical obstacle for endometrial conservative therapy. Therefore, studies to acquire a more comprehensive understanding of the mechanisms are urgent. However, the pivotal molecules are still unexplored.<h4>Materials and methods</h4>We downloaded GSE121367 from the GEO database. The "limma" R language package was applied to identify differentially expressed genes (DEGs). We conducted Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GS ...[more]

PMID: 33235459

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Project description:Endometrial cancer (EC) is the fourth most common cancer in women worldwide. Although researchers are exploring the biological processes of tumorigenesis and development of EC, the gene interactions and biological pathways of EC are not accurately verified. In the present study, bioinformatics methods were used to screen for key candidate genes and pathways that were associated with EC and to reveal the possible mechanisms at molecular level. Microarray datasets (GSE63678, GSE17025 and GSE3013) from the Gene Expression Omnibus database were downloaded and 118 differentially expressed genes (DEGs) were selected using a Venn diagram. Functional enrichment analyses were performed on the DEGs. A protein-protein interaction network was constructed, including the module analysis. A total of 11 hub genes were identified from the DEGs, and functional enrichment analyses were performed to clarify their possible biological processes. A total of 118 DEGs were selected from three mRNA datasets. Functional enrichment demonstrated 27 downregulated genes that were primarily involved in the positive regulation of transcription from RNA polymerase II promoter, protein binding and the nucleus. A total of 91 upregulated DEGs were mainly associated with cell division, protein binding and the nucleus. Pathway analysis indicated that the downregulated DEGs were mainly enriched in pathways associated with cancer, and the upregulated DEGs were mainly enriched in the cell cycle. The 11 hub genes were primarily enriched in the cell cycle, oocyte meiosis, progesterone-mediated oocyte maturation, the p53 signaling pathway and viral carcinogenesis. The integrated analysis showed that cyclin B1, ubiquitin conjugating enzyme E2 C and cell division cycle 20 may participate in the tumorigenesis, development and invasion of EC. In conclusion, the hub genes and pathways identified in the present study contributed to the understanding of carcinogenesis and progression of EC at the mechanistic and molecular-biological level. As candidate targets for the diagnosis and treatment of EC, these genes deserve further investigation.

Project description:ObjectiveProgestin based therapy is the preferred option for fertility-sparing treatment of reproductive-age women with preserved fertility in endometrial hyperplasia (EH) or early endometrial cancer (EEC). Our objective was to investigate whether metformin could enhance the efficacy of progestin-based therapies by meta-analysis.MethodsWe conducted a meta-analysis of randomized or non-randomized controlled trials by searching of PubMed, Embase, Web of science, and Cochrane database from inception to November 8, 2022. The results of enrolled studies were pooled using meta-analysis to estimate the effect of progestin plus metformin on remission, recurrence, pregnancy rate and live birth rate.ResultsIn the analysis of progestin administered systemically or locally, complete response (CR) was significantly higher in progestin plus metformin versus progestin alone in the EH group (pooled OR 2.08, 95% CI 1.29 to 3.34, P=0.003), in the EEC group (pooled OR 1.86, 95% CI 1.13 to 3.05, P=0.01), but not in EEC and EH group (pooled OR 1.46, 95% CI 0.97 to 2.21, P=0.07). In the analysis of progestin administered systemically, complete response was improved in progestin plus metformin versus progestin alone, in the EH group (pooled OR 2.47, 95% CI 1.45 to 4.21, P=0.0009), in the EEC group (pooled OR 2.09, 95% CI 1.18 to 3.71, P=0.01), and in the EEC and EH group (pooled OR 2.03, 95% CI 1.16 to 3.54, P=0.01). The relapse rates of patients with EEC and EH were not different (pooled OR 0.54, 95% CI 0.24 to 1.20, P=0.13). For obstetric outcomes, the addition of metformin improved pregnancy rate (pooled OR 1.55, 95% CI 0.99 to 2.42, P=0.05), but not live birth rate (pooled OR 0.95, 95% CI 0.45 to 2.01, P=0.89).ConclusionFor fertility-sparing management, compared to progestin alone, the outcomes of patients with endometrial hyperplasia and early endometrial cancer were more improved with progestin plus metformin because progestin plus metformin increases the rate of remission and pregnancy.

Project description:ObjectivesThis review examines how response rates to progestin treatment of low-grade endometrial cancer can be improved. In addition to providing a brief overview of the pathogenesis of low-grade endometrial cancer, we discuss limitations in the current classification of endometrial cancer and how stratification may be refined using molecular markers to reproducibly identify 'low-risk' cancers which may represent the best candidates for progestin therapy. We also discuss constraints in current approaches to progestin treatment of low-grade endometrial cancer and perform a systematic review of predictive biomarkers.MethodsPubMed, ClinicalTrials.gov, and Cochrane Library were searched for studies reporting pre-treatment biomarkers associated with outcome in women with low-grade endometrial cancer or endometrial hyperplasia with an intact uterus who received progestin treatment. Studies of fewer than 50 women were excluded. The study protocol was registered in PROSPERO (ID 152374). A descriptive synthesis of pre-treatment predictive biomarkers reported in the included studies was conducted.ResultsOf 1908 records reviewed, 19 studies were included. Clinical features such as age or body mass index cannot predict progestin response. Lesions defined as 'low-risk' by FIGO criteria (stage 1A, grade 1) can respond well; however, the reproducibility and prognostic ability of the current histopathological classification system is suboptimal. Molecular markers can be reproducibly assessed, have been validated as prognostic biomarkers, and may inform patient selection for progestin treatment. DNA polymerase epsilon (POLE)-ultramutated tumors and a subset of p53 wild-type or DNA mismatch repair (MMR)-deficient tumors with 'low-risk' features (eg, progesterone and estrogen receptor-positive) may have improved response rates, though this needs to be validated.DiscussionMolecular markers can identify cases which may be candidates for progestin treatment. More work is needed to validate these biomarkers and potentially identify new ones. Predictive biomarkers are anticipated to inform future research into progestin treatment of low-grade endometrial cancer and ultimately improve patient outcomes.

Dataset Information

Identification and Validation of MSX1 as a Key Candidate for Progestin Resistance in Endometrial Cancer.

Publications

Identification and Validation of MSX1 as a Key Candidate for Progestin Resistance in Endometrial Cancer.

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