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Prostate Cancer Lab #12: Hacking the Proteome for Cancer Treatment (Karin Rodland)

Meeting Summary

“You have to study the proteins to really understand the state of the biological system.”

Karin Rodland, Director, Precision Medicine Innovation CoLaboratory at Pacific Northwest National Laboratory, led a discussion about the potential of proteomic analysis to guide treatment decisions in advanced cancer. She is involved in efforts to apply a proteomics-based approach to identify biomarkers for early diagnosis of cancer and other chronic diseases, and in the use of systems biology to identify potential therapeutic targets. Her current research focuses on improving the ability to identify and validate biomarkers of disease by combining expert knowledge of cellular pathways with statistical approaches.

A lot of people have either a genome or transcriptome bias in understanding cancer dynamics. Karin has a protein bias. The way we tend to do precision medicine is on actionable mutations, but it’s really the proteins that execute the signals that are in the genome and messaged in the RNA. “You have to study the proteins to really understand the state of the biological system, and to understand what is going on in multiple dimensions within the cell at the same time, because it’s usually never a single mutation. We don’t know a lot about how multiple mutations in the same tumor interact with each other and change the response to a drug, for example.”

In the field of biomarkers, proteins are the “go to molecule” because they’re stable and easy to measure. Protein-based biomarkers, such as PSA for prostate cancer, have become standard reference points, but they are normal function proteins that are specific to the tissue of the prostate – statistically correlated because you have a bigger prostate if you have prostate cancer – but these proteins are not mechanistically driving the cancer, so there are a lot of false negatives. We are still looking for better biomarkers that say something about the state of the cancer, particularly about the immune response to the cancer, that can change the treatment decision.

Examples of Karin’s experience in using protein analysis to guide cancer treatment

  • Prostate cancer: A prostate cancer diagnostics project found biomarkers that can be used from the first prostate biopsy to accurately predict whether patients will need a prostatectomy without needing a second biopsy sample.
  • Ovarian cancer: A study of proteins in ovarian cancer patients found that proteins could provide better treatment information than DNA or RNA. The proteomic analysis focused on “phosphorylation”, identifying a distinctive signature from a map of the handoffs of phosphorus in communication pathways from the membrane of the cancer cell to the nucleus, which correlated with patients’ long- or short-term survival. Karin said that Brian could develop a similar map, including his BRAF overexpression, if he sent his fresh frozen tumor tissue to a lab like Olink, and then worked with experts with a systems biology background.
  • Acute myeloid leukemia: Using protein and phospho protein analysis, they found they could predict drug response better than genomics or mRNA, particularly in understanding resistance in late phase AML, and they developed a drug combination to apply in the early phase to reduce late phase resistance.


Discussion of Testing and Treatment Improvements

  • Drug Combinations: Drugs are given in sequence. You’re given a drug, you respond, you develop resistance, the disease comes back, then they put you on the next drug. Every time you do that, you are selecting new clones with new survival mechanisms. If we knew what combinations to use early on, could we kill every tumor cell, and there would be nothing left to recur? The FDA slows adoption of new approaches because they are very conservative. They do not want to approve something that kills 10,000 people, even if it saves 10 million, because the 10,000 that died will be blasted all over the media.
  • Combination Testing: Payment is the big issue. As long as payers will only authorize payment for the second test after the first one has failed, you’re not going to have physicians ordering multiple tests at the same time. We have a federal agency that makes recommendations against tests, the U.S. Preventive Services Task Force.
  • Proteomics Adoption: These proteomics tests are available now, or soon, if you find the right academic medical center which is doing the right clinical trial. It’s a very hot area of research. To make it standard of care, the most optimistic estimate is three years. You should work with your friendly doctor who is willing to go outside the standard of care to write up a case report on your success.



  • Do you or anyone you know have the skills to take the results of a proteomic analysis to build a pathway map?
  • Given the potential of protein analysis to guide clinical decisions for advanced cancer, what can be done to accelerate its use?


Upcoming Meetings – Wednesdays at noon Eastern

  • June 15: Payel Chatterjee, Chief Scientist, and Carla Grandori, CEO, SEngine Precision Medicine, on “Organoids”
  • June 22: Selin Kurnaz, PhD, Co-founder and CEO, Massive Bio, on “Finding the Best Clinical Trial”
  • June 29: Peter Kuhn, PhD, Dean’s Professor of Biological Sciences and Professor of Medicine, Biomedical Engineering, Aerospace & Mechanical Engineering, and Urology; Founder and Chief Scientific Advisor, Epic Sciences, on “Liquid Biopsies”
  • July 13, Wendy Fantl, PhD, Assistant Professor, Urology, Stanford Medicine, on “Single cell and cancer heterogeneity analysis”
  • July 27: Panel Discussion: Proteomics and Clinical Decisions – Karin Rodland (OHSU), Kristina Beeler (Biognosys), Marlon Ruiz (Olink)
  • August 3: Alex Feltus, Professor, Department of Genetics and Biochemistry, and Marc Birtwistle, Associate Professor of Chemical and Biomolecular Engineering and Bioengineering, Clemson, on “Simulation Models to Guide Clinical Decisions”


Meeting Recording

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