Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study

Jieting Liu; Hongrui Zhang; Jingyun Zhang; Zhitong Bing; Yingbin Wang; Qiao Li; Kehu Yang

doi:10.7717/peerj.11350

Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study

PeerJ. 2021 May 11:9:e11350. doi: 10.7717/peerj.11350. eCollection 2021.

Authors

Jieting Liu^{1

2

3}, Hongrui Zhang⁴, Jingyun Zhang⁵, Zhitong Bing^{6

7}, Yingbin Wang², Qiao Li⁸, Kehu Yang^{1

3}

Affiliations

¹ The First Clinical Medical College, Lanzhou University, Lanzhou, China.
² Department of Anesthesiology, Lanzhou University Second Hospital, Lanzhou, China.
³ Evidence-based Medicine Center, Lanzhou University, Lanzhou, China.
⁴ College of Pharmacy, Lanzhou University, Lanzhou, China.
⁵ School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
⁶ Department of Computational Physics, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China.
⁷ School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Lanzhou, China.
⁸ Department of Neurosurgery, Lanzhou University Second Hospital, Lanzhou, China.

Abstract

Background: Gliomas are the most common primary tumors of the central nervous system. The complexity and heterogeneity of the tumor makes it difficult to obtain good biomarkers for drug development. In this study, through The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), we analyze the common diagnostic and prognostic moleculer markers in Caucasian and Asian populations, which can be used as drug targets in the future.

Methods: The RNA-seq data from Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) were analyzed to identify signatures. Based on the signatures, the prognosis index (PI) of every patient was constructed to predict the prognostic risk. Also, gene ontology (GO) functional enrichment analysis and KEGG analysis were conducted to investigate the biological functions of these mRNAs. Glioma patients' data in the CGGA database were introduced to validate the effectiveness of the signatures among Chinese populations. Excluding the previously reported prognostic markers of gliomas from this study, the expression of HSPA5 and MTPN were examined by qRT-PCR and immunohistochemical assay.

Results: In total, 20 mRNAs were finally selected to build PI for patients from TCGA, including 16 high-risk genes and four low-risk genes. For Chinese patients, the log-rank test p values of PI were both less than 0.0001 in two independent datasets. And the AUCs were 0.831 and 0.907 for 3 years of two datasets, respectively. Moreover, among these 20 mRNAs, 10 and 15 mRNAs also had a significant predictive effect via univariate COX analysis in CGGA_693 and CGGA_325, respectively. qRT-PCR and Immunohistochemistry assay indicated that HSPA5 and MTPN over-expressed in Glioma samples compared to normal samples.

Conclusion: The 20-gene signature can forecast the risk of Glioma in TCGA effectively, moreover it can also predict the risks of Chinese patients through validation in the CGGA database. HSPA5 and MTPN are possible biomarkers of gliomas suitable for all populations to improve the prognosis of these patients.

Keywords: Bioinformatics; Gene Signatures; Gliomas; LASSO; Prognosis.

Grants and funding

This research is funded by the Fundamental Research Funds for the Central Universities (2019jbkyzy002; lzujbky-2019-ct02; 2020jbkyzx001; lzujbky-2020-kb20). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.