Integrative Bioinformatics approaches to therapeutic gene target selection in various cancers for Nitroglycerin

Jayaprakash Chinnappan1, Akilandeswari Ramu2, Vidhya Rajalakshmi V2

  • 1Anthropology and Health Informatics Lab, Department of Bioinformatics, Bharathiar University, Coimbatore, Tamil Nadu, India. japee.bioinfo@gmail.com.

Scientific Reports
|November 12, 2021
PubMed

Insights

This study used integrative bioinformatics to identify Nitroglycerin

Area of Science:

  • Bioinformatics
  • Genomics
  • Cancer Research

Background:

  • Nitroglycerin's anticancer mechanisms are not fully understood.
  • Identifying target genes and pathways is crucial for understanding its effects on cancer.

Purpose of the Study:

  • To explore Nitroglycerin's mechanisms in various cancers using integrative bioinformatics.
  • To predict target genes, identify mutated and co-expressed genes, and discover biomarkers.

Main Methods:

  • Utilized public databases (PubChem, SwissTargetPrediction, GEO) and tools (STRING, CluePedia, Survexpress).
  • Performed direct target gene identification, PPI network construction, mutation analysis, DEG analysis, and survival analysis.

Main Results:

  • Identified 12 direct target genes of Nitroglycerin.
  • Discovered interconnected, mutated, upregulated, downregulated, and co-expressed genes.
  • Pinpointed four cancer types: bladder, endometrial, melanoma, and non-small cell lung cancer.
  • Identified novel biomarkers for Nitroglycerin in these cancers.

Conclusions:

  • Integrative bioinformatics effectively elucidated Nitroglycerin's complex mechanisms in cancer.
  • The identified biomarkers hold potential for targeted cancer therapies.

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