Literature DB >> 33501609

Screening and identification of potential biomarkers and therapeutic drugs in melanoma via integrated bioinformatics analysis.

Bo Chen1,2, Donghong Sun3, Xiuni Qin1,2, Xing-Hua Gao4.   

Abstract

Melanoma is a highly aggressive malignant skin tumor with a high rate of metastasis and mortality. In this study, a comprehensive bioinformatics analysis was used to clarify the hub genes and potential drugs. Download the GSE3189, GSE22301, and GSE35388 microarray datasets from the Gene Expression Omnibus (GEO), which contains a total of 33 normal samples and 67 melanoma samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) approach analyze DEGs based on the DAVID. Use STRING to construct protein-protein interaction network, and use MCODE and cytoHubba plug-ins in Cytoscape to perform module analysis and identified hub genes. Use Gene Expression Profile Interactive Analysis (GEPIA) to assess the prognosis of genes in tumors. Finally, use the Drug-Gene Interaction Database (DGIdb) to screen targeted drugs related to hub genes. A total of 140 overlapping DEGs were identified from the three microarray datasets, including 59 up-regulated DEGs and 81 down-regulated DEGs. GO enrichment analysis showed that these DEGs are mainly involved in the biological process such as positive regulation of gene expression, positive regulation of cell proliferation, positive regulation of MAP kinase activity, cell migration, and negative regulation of the apoptotic process. The cellular components are concentrated in the membrane, dendritic spine, the perinuclear region of cytoplasm, extracellular exosome, and membrane raft. Molecular functions include protein homodimerization activity, calmodulin-binding, transcription factor binding, protein binding, and cytoskeletal protein binding. KEGG pathway analysis shows that these DEGs are mainly related to protein digestion and absorption, PPAR signaling pathway, signaling pathways regulating stem cells' pluripotency, and Retinol metabolism. The 23 most closely related DEGs were identified from the PPI network and combined with the GEPIA prognostic analysis, CDH3, ESRP1, FGF2, GBP2, KCNN4, KIT, SEMA4D, and ZEB1 were selected as hub genes, which are considered to be associated with poor prognosis of melanoma closely related. Besides, ten related drugs that may have therapeutic effects on melanoma were also screened. These newly discovered genes and drugs provide new ideas for further research on melanoma.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.

Entities:  

Keywords:  Bioinformatics analysis; Biomarkers; Drugs; Melanoma; Prognostic

Mesh:

Substances:

Year:  2021        PMID: 33501609     DOI: 10.1007/s10637-021-01072-y

Source DB:  PubMed          Journal:  Invest New Drugs        ISSN: 0167-6997            Impact factor:   3.850


  110 in total

Review 1.  Chinese Guidelines on the Diagnosis and Treatment of Melanoma (2015 Edition).

Authors:  Jun Guo; Shukui Qin; Jun Liang; Tongyu Lin; Lu Si; Xiaohong Chen; Zhihong Chi; Chuanliang Cui; Nan Du; Yun Fan; Kangsheng Gu; Fang Li; Junling Li; Yongheng Li; Houjie Liang; Jiwei Liu; Man Lu; Aiping Lu; Kejun Nan; Xiaohui Niu; Hongming Pan; Guoxin Ren; Xiubao Ren; Yongqian Shu; Xin Song; Min Tao; Baocheng Wang; Wenbin Wei; Di Wu; Lingying Wu; Aiwen Wu; Xiaolin Xu; Junyi Zhang; Xiaoshi Zhang; Yiping Zhang; Huiyan Zhu
Journal:  Ann Transl Med       Date:  2015-12

2.  Integrative genomics identifies molecular alterations that challenge the linear model of melanoma progression.

Authors:  Amy E Rose; Laura Poliseno; Jinhua Wang; Michael Clark; Alexander Pearlman; Guimin Wang; Eleazar C Vega Y Saenz de Miera; Ratna Medicherla; Paul J Christos; Richard Shapiro; Anna Pavlick; Farbod Darvishian; Jiri Zavadil; David Polsky; Eva Hernando; Harry Ostrer; Iman Osman
Journal:  Cancer Res       Date:  2011-02-22       Impact factor: 12.701

3.  Bioinformatics, Sequencing Accuracy, and the Credibility of Clinical Genomics.

Authors:  W Gregory Feero
Journal:  JAMA       Date:  2020-11-17       Impact factor: 56.272

4.  Novel genes associated with malignant melanoma but not benign melanocytic lesions.

Authors:  Dmitri Talantov; Abhijit Mazumder; Jack X Yu; Thomas Briggs; Yuqiu Jiang; John Backus; David Atkins; Yixin Wang
Journal:  Clin Cancer Res       Date:  2005-10-15       Impact factor: 12.531

5.  Cancer statistics, 2020.

Authors:  Rebecca L Siegel; Kimberly D Miller; Ahmedin Jemal
Journal:  CA Cancer J Clin       Date:  2020-01-08       Impact factor: 508.702

Review 6.  Expanding the understanding of the heterogeneous nature of melanoma with bioinformatics and disorder-based proteomics.

Authors:  Mak B Djulbegovic; Vladimir N Uversky
Journal:  Int J Biol Macromol       Date:  2019-11-16       Impact factor: 6.953

Review 7.  The Melanoma and Breast Cancer Association: An Overview of their 'Second Primary Cancers' and the Epidemiological, Genetic and Biological correlations.

Authors:  Arunan Jeyakumar; Terence Chua; Alfred King-Yin Lam; Vinod Gopalan
Journal:  Crit Rev Oncol Hematol       Date:  2020-05-22       Impact factor: 6.312

8.  Final version of 2009 AJCC melanoma staging and classification.

Authors:  Charles M Balch; Jeffrey E Gershenwald; Seng-Jaw Soong; John F Thompson; Michael B Atkins; David R Byrd; Antonio C Buzaid; Alistair J Cochran; Daniel G Coit; Shouluan Ding; Alexander M Eggermont; Keith T Flaherty; Phyllis A Gimotty; John M Kirkwood; Kelly M McMasters; Martin C Mihm; Donald L Morton; Merrick I Ross; Arthur J Sober; Vernon K Sondak
Journal:  J Clin Oncol       Date:  2009-11-16       Impact factor: 44.544

9.  Identifying mRNA, microRNA and protein profiles of melanoma exosomes.

Authors:  Deyi Xiao; Joanna Ohlendorf; Yinlu Chen; Douglas D Taylor; Shesh N Rai; Sabine Waigel; Wolfgang Zacharias; Hongying Hao; Kelly M McMasters
Journal:  PLoS One       Date:  2012-10-09       Impact factor: 3.240

10.  NCBI GEO: mining tens of millions of expression profiles--database and tools update.

Authors:  Tanya Barrett; Dennis B Troup; Stephen E Wilhite; Pierre Ledoux; Dmitry Rudnev; Carlos Evangelista; Irene F Kim; Alexandra Soboleva; Maxim Tomashevsky; Ron Edgar
Journal:  Nucleic Acids Res       Date:  2006-11-11       Impact factor: 16.971

View more
  1 in total

Review 1.  Tissue-derived extracellular vesicles in cancers and non-cancer diseases: Present and future.

Authors:  Su-Ran Li; Qi-Wen Man; Xin Gao; Hao Lin; Jing Wang; Fu-Chuan Su; Han-Qi Wang; Lin-Lin Bu; Bing Liu; Gang Chen
Journal:  J Extracell Vesicles       Date:  2021-12
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.