Literature DB >> 27930095

Multi-Omics Data Integration and Mapping of Altered Kinases to Pathways Reveal Gonadotropin Hormone Signaling in Glioblastoma.

Savita Jayaram1,2, Manoj Kumar Gupta1,2, Rajesh Raju3, Poonam Gautam4, Ravi Sirdeshmukh1,5.   

Abstract

Glioblastoma multiforme (GBM) is one of the most lethal brain tumors with an inadequately understood pathophysiology. Biomarkers that guide accurate diagnosis and treatment decisions would greatly support precision medicine for GBM. Previous studies of GBM have focused on signaling pathways such as epidermal growth factor receptor (EGFR), platelet-derived growth factor receptors (PDGFRs), notch, wnt, and others, identified with single omics technology platforms (genomics, transcriptomics, or proteomics), but not with their integrated use. In this context, we report here a multi-omics pathway view, expanded through integration of the expression data at transcriptomic and proteomic levels, followed by selection of a functionally related group of proteins such as kinases deregulated in GBM. By using this strategy, we observed a highly significant enrichment of the gonadotropin-releasing hormone (GnRH) signaling pathway that was not deciphered with single omics datasets. The curation of the GnRH pathway with extensive literature analysis brought about a comprehensive annotation of the pathway, which included several additional pathway members that were not previously annotated. A targeted search resulted in identification of additional nonkinase members of the pathway in the GBM multi-omics datasets. We found evidence of GnRH receptor expression in GBM and other cancers. We offer here an updated generic pathway map of GnRH signaling, show its enrichment in the context of GBM, and discuss its plausible cross-connectivity with EGFR, wnt, calcium, and focal adhesion kinase signaling pathways that were earlier shown to be the top deregulated pathways in GBM. In conclusion, this study demonstrates the promise of multi-omics research and analyses to better understand complex cancers and suggests continued efforts and research in this direction in the field of integrative biology.

Entities:  

Keywords:  GnRH; glioblastoma; kinases; multi-omic data integration; multi-omics; proteomics; signaling; systems biology; transcriptomics

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Substances:

Year:  2016        PMID: 27930095     DOI: 10.1089/omi.2016.0142

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  5 in total

1.  Potentially functional variants of HBEGF and ITPR3 in GnRH signaling pathway genes predict survival of non-small cell lung cancer patients.

Authors:  Yufeng Wu; Zhensheng Liu; Dongfang Tang; Hongliang Liu; Sheng Luo; Thomas E Stinchcombe; Carolyn Glass; Li Su; Lijuan Lin; David C Christiani; Qiming Wang; Qingyi Wei
Journal:  Transl Res       Date:  2021-01-02       Impact factor: 7.012

Review 2.  Artificial intelligence and machine learning in precision and genomic medicine.

Authors:  Sameer Quazi
Journal:  Med Oncol       Date:  2022-06-15       Impact factor: 3.738

Review 3.  The crucial role of multiomic approach in cancer research and clinically relevant outcomes.

Authors:  Miaolong Lu; Xianquan Zhan
Journal:  EPMA J       Date:  2018-02-21       Impact factor: 6.543

4.  Bacoside A Induces Tumor Cell Death in Human Glioblastoma Cell Lines through Catastrophic Macropinocytosis.

Authors:  Sebastian John; K C Sivakumar; Rashmi Mishra
Journal:  Front Mol Neurosci       Date:  2017-06-15       Impact factor: 5.639

5.  Quantitative proteomic analysis of GnRH agonist treated GBM cell line LN229 revealed regulatory proteins inhibiting cancer cell proliferation.

Authors:  Priyanka H Tripathi; Javed Akhtar; Jyoti Arora; Ravindra Kumar Saran; Neetu Mishra; Ravindra Varma Polisetty; Ravi Sirdeshmukh; Poonam Gautam
Journal:  BMC Cancer       Date:  2022-02-02       Impact factor: 4.430

  5 in total

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