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Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
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Precision Oncology: The Road Ahead

Daniela Senft1, Mark D M Leiserson2, Eytan Ruppin3

  • 1Tumor Initiation and Maintenance Program, NCI designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA.

Trends in Molecular Medicine
|September 10, 2017
PubMed

Insights

Integrating genomic and transcriptomic analyses offers advanced precision oncology insights. This approach identifies novel cancer drivers and vulnerabilities, paving the way for next-generation therapies to overcome tumor heterogeneity.

Area of Science:

  • Oncology
  • Genomics
  • Transcriptomics
  • Cancer Biology

Background:

  • Precision oncology currently relies heavily on genomics-guided therapy.
  • Tumor genetic and nongenetic heterogeneity presents a significant challenge.
  • Advances in sequencing reveal complex intra-tumor variations.

Purpose of the Study:

  • To outline the benefits of integrating genomic and transcriptomic analyses in precision oncology.
  • To review computational methods for identifying novel cancer drivers and vulnerabilities.
  • To discuss platforms for functional drug testing and highlight single-cell analysis advancements.

Main Methods:

  • Integration of genomic and transcriptomic data analysis.
  • Application of computational approaches for driver and vulnerability detection.
  • Review of clinically relevant functional testing platforms and single-cell technologies.

Main Results:

  • Genomic and transcriptomic integration provides a comprehensive view of tumor biology.
  • Novel therapeutic targets and vulnerabilities can be identified through integrated analyses.
  • Technological advancements facilitate personalized drug testing and development.

Conclusions:

  • Integrated genomic and transcriptomic analyses are crucial for advanced precision oncology.
  • These approaches enable the discovery of new therapeutic strategies to combat cancer heterogeneity.
  • Future cancer drug development will leverage multi-omic and single-cell insights to overcome treatment resistance.

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