Pathological Grade-Associated Transcriptome Profiling of lncRNAs and mRNAs in Gliomas

Junlong Sun; Rui Jiang; Mengruo Song; Junzhong Yao; Shiqiang Hou; Yunhua Zhu; Xiang Ji; Hao Sheng; Zhongyu Tang; Qianqian Liu; Zhongzheng Jia; Wei Shi; Jinlong Shi

doi:10.3389/fonc.2020.00253

Pathological Grade-Associated Transcriptome Profiling of lncRNAs and mRNAs in Gliomas

Front Oncol. 2020 Mar 10:10:253. doi: 10.3389/fonc.2020.00253. eCollection 2020.

Authors

Junlong Sun^{1

2

3}, Rui Jiang^{1

3}, Mengruo Song^{1

3}, Junzhong Yao^{1

3}, Shiqiang Hou⁴, Yunhua Zhu^{1

3}, Xiang Ji^{1

3}, Hao Sheng³, Zhongyu Tang^{1

3}, Qianqian Liu^{1

3}, Zhongzheng Jia⁵, Wei Shi^{1

3}, Jinlong Shi^{1

3}

Affiliations

¹ Jiangsu Clinical Medicine Center of Tissue Engineering and Nerve Injury Repair and Department of Neurosurgery, The Affiliated Hospital of Nantong University, Nantong, China.
² Department of Neurosurgery, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai, China.
³ Department of Clinic Research Center, The Affiliated Hospital of Nantong University, Nantong, China.
⁴ Department of Neurosurgery, Chuzhou Clinical College of Anhui Medical University, The First Peoples Hospital Chuzhou, Chuzhou, China.
⁵ Medical Image Center, The Affiliated Hospital of Nantong University, Nantong, China.

Abstract

The aim of the present study was to explore the expression profiles of lncRNAs and mRNAs in glioma patients and to elucidate any potential relationship between lncRNAs and mRNAs in glioma. High-throughput transcriptome sequencing of mRNAs and lncRNAs from six normal tissues and 16 glioma tissues (grade II, six cases; grade III, four cases; and grade IV, six cases) was performed. Series test of cluster (STC) analysis was used to screen significant trending models associated with glioma. Gene co-expression networks were constructed for the differentially expressed lncRNAs and mRNAs, and gene-ontology (GO) and pathway-enrichment analyses were further performed. Quantitative real-time PCR was performed to validate the five most differentially expressed lncRNAs and mRNAs. After filtering the raw sequencing data, we found 578 lncRNAs and 3,216 mRNAs that were significantly dysregulated in glioma (fold change ≥ 2, p < 0.05). Twenty model profiles of lncRNA and 10 model profiles of mRNA were summarized, and three patterns of lncRNAs and two patterns of mRNAs were of clinical significance. Three gene co-expression networks between mRNAs and lncRNAs were built to clarify the relationship between lncRNAs and mRNAs in glioma. GO and pathway analyses indicated that the differentially expressed lncRNAs and mRNAs were enriched in several biological processes and signaling pathways associated with tumorigenesis. Both lncRNAs and mRNAs exhibited dynamic differential expression profiles that indicated their potential roles in different degrees of glioma malignancy. A series of bioinformatics analyses indicated that most of these lncRNAs and mRNAs are involved in important biological processes and pathways associated with the pathogenesis of glioma. These results provide potential directions and valuable resources for future investigations via the comprehensive integration of these lncRNAs and mRNAs.

Keywords: glioma; high-throughput sequencing; lncRNA; mRNA; transcriptome.