Combined Analysis of RNA Sequence and Microarray Data Reveals a Competing Endogenous RNA Network as Novel Prognostic Markers in Malignant Pleural Mesothelioma

Our plain-English summary of Combined Analysis of RNA Sequence and Microarray Data Reveals a Competing Endogenous RNA Network as Novel Prognostic Markers in Malignant Pleural Mesothelioma, by W. Duan, K. Wang, Y. Duan, et al (Frontiers in Oncology, 2021).

The study

• Authors: W. Duan, K. Wang, Y. Duan, X. Chen, X. Chu, P. Hu, B. Xiong
• Journal: Frontiers in Oncology
• Published: 2021;11:615234
• Cited by: 10 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Malignant pleural mesothelioma (MPM) is a highly aggressive cancer with short survival time. Unbalanced competing endogenous RNAs (ceRNAs) have been shown to participate in the tumor pathogenesis and served as biomarkers for the clinical prognosis. However, the comprehensive analyses of the ceRNA network in the prognosis of MPM are still rarely reported. In this study, we obtained the transcriptome data of the MPM and the normal samples from TCGA, EGA, and GEO databases and identified the differentially expressed (DE) mRNAs, lncRNAs, and miRNAs. The functions of the prognostic genes and the overlapped DEmRNAs were further annotated by the multiple enrichment analyses. Then, the targeting relationships among lncRNA-miRNA and miRNA-mRNA were predicted and calculated, and a prognostic ceRNA regulatory network was established. We included the prognostic 73 mRNAs and 13 miRNAs and 26 lncRNAs into the ceRNA network. Moreover, 33 mRNAs, three miRNAs, and seven lncRNAs were finally associated with prognosis, and a model including seven mRNAs, two lincRNAs, and some clinical factors was finally established and validated by two independent cohorts, where CDK6 and SGMS1-AS1 were significant to be independent prognostic factors. In addition, the identified co-expressed modules associated with the prognosis were overrepresented in the ceRNA network. Multiple enrichment analyses showed the important roles of the extracellular matrix components and cell division dysfunction in the invasion of MPM potentially. In summary, the prognostic ceRNA network of MPM was established and analyzed for the first time and these findings shed light on the function of ceRNAs and revealed the potential prognostic and therapeutic biomarkers of MPM.

Copyright © 2021 Duan, Wang, Duan, Chen, Chu, Hu and Xiong.

In plain English

This was a computer-based analysis of gene-activity data from public databases. It did not study asbestos exposure. The authors used tumour data from 80 patients with malignant pleural mesothelioma in the TCGA database. They compared 9 patients who survived less than 12 months with 21 who survived more than 30 months, then checked the genes they found against two smaller datasets of mesothelioma and normal tissue. They built a network of 26 lncRNAs, 13 miRNAs and 73 mRNAs, which are types of RNA molecules that can regulate one another. Of these, 33 mRNAs, three miRNAs and seven lncRNAs were linked with survival. A risk score combined nine of these RNAs with clinical factors such as age, sex and tumour stage. It separated patients with lower survival from those with higher survival. Its AUC, a measure of predictive accuracy, was 86.9% in the TCGA patients and 77.0% in a separate dataset from the EGA database. CDK6 and SGMS1-AS1 were independent predictors in the TCGA model. The authors concluded that the risk score could predict overall survival, and said further clinical and laboratory research is needed to refine the models.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Bioinformatic (computational) analysis of publicly available RNA sequencing and microarray data, with construction and validation of a survival prediction model
• Who was studied: 80 malignant pleural mesothelioma (MPM) patients from the TCGA database (training group); 211 MPM patients from the EGA database (validation); GEO microarray datasets GSE12345 (4 normal, 9 MPM tissues) and GSE42977 (9 normal, 39 MPM tissues)
• Exposure: No asbestos or other exposure was studied. The study examined RNA expression (mRNAs, lncRNAs, miRNAs) in tumour tissue in relation to overall survival. Asbestos is mentioned only as background in the introduction.
• Main results:
  • Comparing 21 low-risk (overall survival more than 30 months) and 9 high-risk (overall survival less than 12 months) TCGA patients, 1,499 differentially expressed mRNAs, 358 lncRNAs and 29 miRNAs were identified
  • The ceRNA network included 26 lncRNAs, 13 miRNAs and 73 mRNAs
  • In the 80 TCGA patients, 33 mRNAs, three miRNAs and seven lncRNAs from the network were significant in Kaplan–Meier survival analyses
  • Nine RNAs were included in the survival model along with clinical factors (age, gender, T stage, N stage, tumour type)
  • The model's AUC was 86.9%, and patients with high-risk scores had significantly lower overall survival (p less than 0.001)
  • In the TCGA risk model, CDK6 and SGMS1-AS1 were significant independent prognostic factors
  • In the EGA validation data, the model gave P less than 0.001 and an AUC of 77.0%. In multivariate analysis there, CDK6 had marginal significance, and KIF23 and CORO1C were significant.
  • Histological type was associated with the risk score. Biphasic mesothelioma: 5 low-score vs 17 high-score patients. Epithelioid: 33 vs 20. P = 0.003296.
  • Compared with the low-risk group, the high-risk group had higher estimated proportions of neutrophils, activated NK cells and gamma delta T cells, and lower proportions of several other immune cell types
• The authors' conclusion: The authors concluded that a risk score based on two lncRNAs, seven mRNAs and five clinical factors was established and validated to predict overall survival of MPM patients, and that further clinical and experimental research is needed.
• Limitations the authors state:
  • KIF23 was an independent predictor in the EGA data but not in the TCGA data, possibly due to insufficient data
  • SGMS1-AS1 as an independent prognostic factor needs more data to verify
  • The ceRNA mechanisms of the hub genes in MPM were not assessed experimentally
  • Further clinical and experimental research is needed to optimise the models

Topics

Medical terms in this study, explained in our Lexicon: Pleural Mesothelioma, Biomarker, Prognosis.

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