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Using Pharmacogenomic Databases for Discovering Patient-Target Genes and Small Molecule Candidates to Cancer Therapy

José E Belizário1, Beatriz A Sangiuliano1, Marcela Perez-Sosa1

  • 1Department of Pharmacology, Institute of Biomedical Sciences, University of São Paulo São Paulo, Brazil.

Frontiers in Pharmacology
|October 18, 2016
PubMed

Insights

Researchers can plan targeted cancer therapies by integrating diverse omics data. User-friendly web tools like CBioPortal, CellMiner, and Connectivity Map aid in analyzing cancer genomics and predicting drug responses.

Area of Science:

  • Computational biology and bioinformatics
  • Cancer genomics and pharmacogenomics
  • Integrative omics data analysis

Background:

  • Advancements in omics technologies provide vast cancer genomics datasets.
  • Analyzing these diverse pharmacogenomic datasets is complex, requiring specialized tools and biological expertise.
  • Predicting signaling networks and clinical outcomes necessitates integrative approaches.

Approach:

  • Web-based *in silico* tools are presented for exploring cancer biology and pharmacogenomics.
  • CBioPortal is used for querying cancer genome databases to identify significantly altered genes across cancer types.
  • CellMiner is employed to identify drugs and small molecules for gene targeting.
  • Connectivity Map is utilized for generating gene signatures and comparing expression profiles to understand drug response.

Key Points:

  • User-friendly *in silico* platforms facilitate the exploration of integrative cancer genomics and pharmacogenomics studies.
  • Specific tools enable gene alteration analysis, drug identification, and gene expression profiling for drug response investigation.
  • Patient-Derived Xenografts (PDXs) models are discussed for *in vivo* drug profiling.

Conclusions:

  • These integrative platforms and approaches offer a rational strategy for predicting patient-specific targeted therapy responses.
  • The discussed methods support the development of clinically relevant small molecule drugs.
  • Ongoing challenges and future directions in integrating multi-omics and epidemiological data are highlighted.
Keywords:
CellMinerConnectivity MapcBioPortalcancer genomepharmacogenomics

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