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Related Experiment Video

Updated: Jan 2, 2026

The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
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Using Reverse Phase Protein Array (RPPA) to Identify and Target Adaptive Resistance.

Marilyne Labrie1, Yong Fang2, Nicholas D Kendsersky2

  • 1Knight Cancer Institute, Oregon Health and Sciences University, Portland, OR, USA. labriem@ohsu.edu.

Advances in Experimental Medicine and Biology
|December 11, 2019
PubMed
Summary
This summary is machine-generated.

Tumor cells adapt to therapy by rewiring protein networks, leading to drug resistance. Understanding this adaptive evolution using Reverse Phase Protein Array (RPPA) can reveal new therapeutic strategies and improve patient outcomes.

Keywords:
Adaptive resistanceCombination therapyReverse phase protein arrayTargeted therapyTumor evolution

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Area of Science:

  • Oncology
  • Molecular Biology
  • Cancer Therapeutics

Background:

  • Cancer cells and their environment rapidly evolve under therapeutic pressure.
  • This evolution leads to acquired drug resistance, limiting treatment efficacy across chemotherapy, targeted therapy, and immunotherapy.
  • Understanding and interrupting tumor evolution is critical for enhancing patient response to cancer treatments.

Purpose of the Study:

  • To review the concepts of adaptive resistance in tumors.
  • To highlight the utility of Reverse Phase Protein Array (RPPA) in dissecting tumor evolution and resistance mechanisms.
  • To demonstrate how RPPA-driven insights can inform the development of novel therapeutic strategies and combination therapies.

Main Methods:

  • Review of existing literature on tumor adaptive resistance.
  • Discussion of Reverse Phase Protein Array (RPPA) as a technology for analyzing protein network alterations.
  • Analysis of how RPPA data can identify resistance mechanisms and guide drug combination strategies.

Main Results:

  • Adaptive resistance arises from rapid rewiring of protein networks within tumor cells and the microenvironment.
  • RPPA is a powerful tool for evaluating these adaptive changes and identifying key nodes in resistance pathways.
  • Insights from RPPA can uncover effective drug combinations to overcome adaptive resistance.

Conclusions:

  • Targeting adaptive resistance is a crucial strategy to improve patient benefit from cancer therapies.
  • RPPA provides valuable data for understanding resistance mechanisms and developing biomarker-driven clinical trials.
  • Future research should focus on leveraging RPPA-derived information to design trials that specifically target adaptive resistance, ultimately improving patient outcomes.