4.6

CiteScore

2.2

Impact Factor
  • ISSN 1674-8301
  • CN 32-1810/R
Volume 29 Issue 5
Aug.  2015
Turn off MathJax
Article Contents
Abstract
Related Articles
Liangyu Ge, Siyu Liu, Long Xie, Lei Sang, Changyan Ma, Hongwei Li. Differential mRNA expression profiling of oral squamous cell carcinoma by high-throughput RNA sequencing[J]. The Journal of Biomedical Research, 2015, 29(5): 397-404. DOI: 10.7555/JBR.29.20140088
Citation: Liangyu Ge, Siyu Liu, Long Xie, Lei Sang, Changyan Ma, Hongwei Li. Differential mRNA expression profiling of oral squamous cell carcinoma by high-throughput RNA sequencing[J]. The Journal of Biomedical Research, 2015, 29(5): 397-404. DOI: 10.7555/JBR.29.20140088
shu

Differential mRNA expression profiling of oral squamous cell carcinoma by high-throughput RNA sequencing

  • 1.

    Jiangsu Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, Jiangsu 210029, China

  • 2.

    Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Stomatology, Nanjing Medical University, Nanjing, Jiangsu 210029, China

  • 3.

    Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Stomatology, Nanjing Medical University, Nanjing, Jiangsu 210029, China

  • 4.

    Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Stomatology, Nanjing Medical University, Nanjing, Jiangsu 210029, China

  • 5.

    Department of Oral and Maxillofacial Surgery, Suzhou Huaxia Stomatological Hospital, Suzhou, Jiangsu 215002, China

  • 6.

    Department of Developmental Genetics, Nanjing Medical University, Nanjing, Jiangsu 210029, China

Funds: 

the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD, 2014-37)

More Information
  • Received Date: June 21, 2014
  • Revised Date: August 11, 2014
    Graphical Abstract
    • Abstract
  • Differentially expressed genes are thought to regulate the development and progression of oral squamous cell carcinomas (OSCC). The purpose of this study was to screen differentially expressed mRNAs in OSCC and matched paraneoplastic normal tissues, and to explore the intrinsic mechanism of OSCC development and progression. We obtained the differentially expressed mRNA expression profiles in 10 pairs of fresh-frozen OSCC tissue specimens and matched paraneoplastic normal tissue specimens by high-throughput RNA sequencing. By using Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, the functional significance of the differentially expressed genes were analyzed. We identified 1,120 significantly up-regulated mRNAs and 178 significantly down-regulated mRNAs in OSCC, compared to normal tissue. The differentially expressed mRNAs were involved in 20 biological processes and 68 signal pathways. Compared to adjacent normal tissue, the expression of MAGEA11 was up-regulated; TCHH was down-regulated. These findings were verified by real-time PCR. These differentially expressed mRNAs may function as oncogenes or tumor suppressors in the development and progression of OSCC. This study provides novel insights into OSCC. However, further work is needed to determine if these differentially expressed mRNAs have potential roles as diagnostic biomarkers and candidate therapeutic targets for OSCC.
    • FullText(HTML)
    • References (0)
    • Related Articles

  • Related Articles

    [1]Xu Han, Wen Li, Changying Chen, Jiahui Liu, Junxiang Sun, Feifan Wang, Chao Wang, Jialing Mu, Xincheng Gu, Fangyuan Liu, Hankun Xie, Song Yang, Chong Shen. Genetic variants and mRNA expression levels of KLF4 and KLF5 with hypertension: A combination of case-control study and cohort study[J]. The Journal of Biomedical Research, 2025, 39(1): 103-113. DOI: 10.7555/JBR.38.20240208
    [2]Miao Xu, Yan Gao, Wenjie Yin, Qinghuai Liu, Songtao Yuan. RNA-sequencing expression profile and functional analysis of retinal pigment epithelium in atrophic age-related macular degeneration[J]. The Journal of Biomedical Research, 2024, 38(5): 500-511. DOI: 10.7555/JBR.37.20230320
    [3]Yujuan Zhang, Kai Lu, Xu Wu, Hanting Liu, Junyi Xin, Xiaowei Wang, Weida Gong, Qinghong Zhao, Meilin Wang, Haiyan Chu, Mulong Du, Guoquan Tao, Zhengdong Zhang. Genetic variants in the Hedgehog signaling pathway genes are associated with gastric cancer risk in a Chinese Han population[J]. The Journal of Biomedical Research, 2022, 36(1): 22-31. DOI: 10.7555/JBR.35.20210091
    [4]Kai Wang, Zhongming Li, Wenjie Ma, Yan Sun, Xianling Liu, Lijun Qian, Jian Hong, Dasheng Lu, Jing Zhang, Di Xu. Construction of miRNA-mRNA network reveals crucial miRNAs and genes in acute myocardial infarction[J]. The Journal of Biomedical Research, 2021, 35(6): 425-435. DOI: 10.7555/JBR.35.20210088
    [5]Tiwari-Heckler Shilpa, Jiang Z. Gordon, Popov Yury, J. Mukamal Kenneth. Daily high-dose aspirin does not lower APRI in the Aspirin-Myocardial Infarction Study[J]. The Journal of Biomedical Research, 2020, 34(2): 139-142. DOI: 10.7555/JBR.33.20190041
    [6]Sun Meiqing, Ding Zhanlin, Wang Hong, Yu Guangping, Feng Zhe, Li Bingzhi, Li Penghui. Gelatin filter capture-based high-throughput sequencing analysis of microbial diversity in haze particulate matter[J]. The Journal of Biomedical Research, 2019, 33(6): 414-421. DOI: 10.7555/JBR.33.20180121
    [7]Minbo Zang, Qiao Zhou, Yunfei Zhu, Mingxi Liu, Zuomin Zhou. Effects of chemotherapeutic agent bendamustine for nonhodgkin lymphoma on spermatogenesis in mice[J]. The Journal of Biomedical Research, 2018, 32(6): 442-453. DOI: 10.7555/JBR.31.20170023
    [8]Kaibo Lin, Shikun Zhang, Jieli Chen, Ding Yang, Mengyi Zhu, Eugene Yujun Xu. Generation and functional characterization of a conditional Pumilio2 null allele[J]. The Journal of Biomedical Research, 2018, 32(6): 434-441. DOI: 10.7555/JBR.32.20170117
    [9]Huanqiang Wang, Congying Yang, Siyuan Wang, Tian Wang, Jingling Han, Kai Wei, Fucun Liu, Jida Xu, Xianzhen Peng, Jianming Wang. Cell-free plasma hypermethylated CASZ1, CDH13 and ING2 are promising biomarkers of esophageal cancer[J]. The Journal of Biomedical Research, 2018, 32(6): 424-433. DOI: 10.7555/JBR.32.20170065
    [10]Sundeep?S.?Tumber, Hong?Liu. Epidural abscess after multiple lumbar punctures for labour epidural catheter placement[J]. The Journal of Biomedical Research, 2010, 24(4): 332-335. DOI: 10.1016/S1674-8301(10)60046-2

  • Cited by

    Periodical cited type(11)

    1. Yu F, Zhao LX, Chu S. TCHH as a Novel Prognostic Biomarker for Patients with Gastric Cancer by Bioinformatics Analysis. Clin Exp Gastroenterol, 2024, 17: 61-74. DOI:10.2147/CEG.S451676
    2. Li K, Qiu Y, Liu X, et al. Biomimetic Nanosystems for the Synergistic Delivery of miR-144/451a for Oral Squamous Cell Carcinoma. Balkan Med J, 2022, 39(3): 178-186. DOI:10.4274/balkanmedj.galenos.2022.2021-11-1
    3. Yu CC, Chan MWY, Lin HY, et al. IRAK2, an IL1R/TLR Immune Mediator, Enhances Radiosensitivity via Modulating Caspase 8/3-Mediated Apoptosis in Oral Squamous Cell Carcinoma. Front Oncol, 2021, 11: 647175. DOI:10.3389/fonc.2021.647175
    4. Amiri-Dashatan N, Koushki M, Jalilian A, et al. Integrated Bioinformatics Analysis of mRNAs and miRNAs Identified Potential Biomarkers of Oral Squamous Cell Carcinoma. Asian Pac J Cancer Prev, 2020, 21(6): 1841-1848. DOI:10.31557/APJCP.2020.21.6.1841
    5. Xu GQ, Li LH, Wei JN, et al. Identification and profiling of microRNAs expressed in oral buccal mucosa squamous cell carcinoma of Chinese hamster. Sci Rep, 2019, 9(1): 15616. DOI:10.1038/s41598-019-52197-3
    6. Li CY, Zhang WW, Xiang JL, et al. Integrated analysis highlights multiple long non‑coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma. Oncol Rep, 2019, 42(6): 2583-2599. DOI:10.3892/or.2019.7377
    7. Zhong L, Liu Y, Wang K, et al. Biomarkers: paving stones on the road towards the personalized precision medicine for oral squamous cell carcinoma. BMC Cancer, 2018, 18(1): 911. DOI:10.1186/s12885-018-4806-7
    8. Willett CS, Wilson EM. Evolution of Melanoma Antigen-A11 (MAGEA11) During Primate Phylogeny. J Mol Evol, 2018, 86(3-4): 240-253. DOI:10.1007/s00239-018-9838-8
    9. Li J, Zhou D, Qiu W, et al. Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design. Sci Rep, 2018, 8(1): 622. DOI:10.1038/s41598-017-18705-z
    10. Mallik S, Zhao Z. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis. Genes (Basel), 2017, 9(1): 7. DOI:10.3390/genes9010007
    11. Irimie AI, Braicu C, Pileczki V, et al. Knocking down of p53 triggers apoptosis and autophagy, concomitantly with inhibition of migration on SSC-4 oral squamous carcinoma cells. Mol Cell Biochem, 2016, 419(1-2): 75-82. DOI:10.1007/s11010-016-2751-9

    Other cited types(0)

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article has an altmetric score of 2
    Article has an altmetric score of 2
    Article views (3387) PDF downloads (621) Cited by(11)
    Related

    ©2023 by the Editorial Department of the Journals of Nanjing Medical University. All rights reserved.   苏ICP备05071376号-5

    Supported by: Beijing Renhe Information Technology Co., Ltd. E-mail: info@rhhz.net  Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return