Dataset Information

Construction of a nine DNA repair-related gene prognostic classifier to predict prognosis in patients with endometrial carcinoma.

ABSTRACT:

Background

Endometrial cancer (EC) is one of the most common gynecological malignancies worldwide. However, the molecular mechanisms and the prognostic prediction for EC patients remain unclear.

Methods

In the current study, we performed an in-depth analysis of over 500 patients which were obtained from the Cancer Genome Atlas (TCGA) database. The bioinformatics analysis included gene set enrichment analysis (GSEA) and Cox and lasso regression analyses to ensure overall survival (OS)-related genes, moreover, to construct a prognostic model and a nomogram for EC patients.

Results

GSEA identified 4 gene sets significantly associated with EC, which are DNA repair, unfolded protein response, reactive oxygen species pathway and UV response up. Twenty-five OS-related DNA repair genes were screened out, after that, a 9-mRNA signature was constructed to measure the risk scores of patients with different outcomes. In addition, a nomogram contained the 9-mRNA model and clinical parameters was also presented to assess the prognosis. Patients with low risk were more likely to have sensitivity to paclitaxel, vinblastine, rapamycin, metformin, imatinib, Akt inhibitor and lapatinib.

Conclusions

The identified highly enriched gene sets may offer a novel insight into the tumorigenesis and treatment of EC. Additionally, the constructed 9-mRNA model and the nomogram have prominent clinical implications for prognosis evaluation and specific therapy guidance for EC patients.

SUBMITTER: Liu J

PROVIDER: S-EPMC7789410 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Construction of a nine DNA repair-related gene prognostic classifier to predict prognosis in patients with endometrial carcinoma.

Liu Jinhui J Jiang Pinping P Chen Xucheng X Shen Yujie Y Cui Guoliang G Ma Ziyan Z Zhao Shaojie S Zhang Yan Y

BMC cancer 20210106 1

<h4>Background</h4>Endometrial cancer (EC) is one of the most common gynecological malignancies worldwide. However, the molecular mechanisms and the prognostic prediction for EC patients remain unclear.<h4>Methods</h4>In the current study, we performed an in-depth analysis of over 500 patients which were obtained from the Cancer Genome Atlas (TCGA) database. The bioinformatics analysis included gene set enrichment analysis (GSEA) and Cox and lasso regression analyses to ensure overall survival ( ...[more]

PMID: 33407221

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Project description:Ferroptosis is an iron-dependent cell death process that plays important regulatory roles in the occurrence and development of cancers, including hepatocellular carcinoma (HCC). Moreover, the molecular events surrounding aberrantly expressed long non-coding RNAs (lncRNAs) that drive HCC initiation and progression have attracted increasing attention. However, research on ferroptosis-related lncRNA prognostic signature in patients with HCC is still lacking. In this study, the association between differentially expressed lncRNAs and ferroptosis-related genes, in 374 HCC and 50 normal hepatic samples obtained from The Cancer Genome Atlas (TCGA), was evaluated using Pearson's test, thereby identifying 24 ferroptosis-related differentially expressed lncRNAs. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression model were used to construct and validate a prognostic risk score model from both TCGA training dataset and GEO testing dataset (GSE40144). A nine-lncRNA-based signature (CTD-2033A16.3, CTD-2116N20.1, CTD-2510F5.4, DDX11-AS1, LINC00942, LINC01224, LINC01231, LINC01508, and ZFPM2-AS1) was identified as the ferroptosis-related prognostic model for HCC, independent of multiple clinicopathological parameters. In addition, the HCC patients were divided into high-risk and low-risk groups according to the nine-lncRNA prognostic signature. The gene set enrichment analysis enrichment analysis revealed that the lncRNA-based signature might regulate the HCC immune microenvironment by interfering with tumor necrosis factor α/nuclear factor kappa-B, interleukin 2/signal transducers and activators of transcription 5, and cytokine/cytokine receptor signaling pathways. The infiltrating immune cell subtypes, such as resting memory CD4(+) T cells, follicular helper T cells, regulatory T cells, and M0 macrophages, were all significantly different between the high-risk group and the low-risk group as indicated in Spearman's correlation analysis. Moreover, a substantial increase in the expression of B7H3 immune checkpoint molecule was found in the high-risk group. Our findings provided a promising insight into ferroptosis-related lncRNAs in HCC and a personalized prediction tool for prognosis and immune responses in patients.

Dataset Information

Construction of a nine DNA repair-related gene prognostic classifier to predict prognosis in patients with endometrial carcinoma.

Background

Methods

Results

Conclusions

Publications

Construction of a nine DNA repair-related gene prognostic classifier to predict prognosis in patients with endometrial carcinoma.

Similar Datasets

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