Proteomic Cancer Testing: How Protein Analysis Reveals Treatment Targets

“Hacking the Proteome for Cancer Treatment” (Karin Rodland) [#12] June 8, 2022 Brad Power “You have to study the proteins to really understand the state of the biological system.

” – Karin Rodland Meeting Summary 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.

ntifying 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

“Hacking the Proteome for Cancer Treatment” (Karin Rodland) [#12] 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. Requests ●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?

The information and opinions expressed on this website or platform, or during discussions and presentations (both verbal and written) are not intended as health care recommendations or medical advice by Cancer Patient Lab/Prostate Cancer Lab, its principals, presenters, participants, or representatives for any medical treatment, product, or course of action.

ancer Lab, its principals, presenters, participants, or representatives for any medical treatment, product, or course of action. You should always consult a doctor about your specific situation before pursuing any health care program, treatment, product or other course of action that might affect your health.

“Hacking the Proteome for Cancer Treatment” (Karin Rodland) [#12] — Meeting Notes Brad Power: We're happy to have with us Karin Rodland, a friend who is based in the Portland, Oregon, area, and southern Washington state, and is an expert in proteomics.

I saw Karin speak at an online conference on the potential of proteomics, and since we're very interested in novel testing and how it might inform patients' decisions, Karin graciously agreed to give us a tutorial and introduce us to the potential of proteomics to inform clinical decision-making.

Karin Rodland: A lot of you are in the biotech industry and are familiar with the technology, and all of you are self-educated and have learned a lot about this. Cancer is personal for almost everyone. I used to give talks to encourage community support for Oregon Health Sciences University, and I would ask the audience to raise their hand if anyone in their family had ever had cancer.

And every hand in the audience went up routinely. That's my motivation here. Hacking the Proteome for Cancer Treatment is something that I'm very passionate about.

The object of the game – and I know that this is why you have the Prostate Cancer Lab and hackathon – is improving cancer survival, and the way we have tackled the problem at PNNL (the Pacific Northwest National Laboratory) is early detection and targeted therapeutics. I recognize that this group is past the stage of early detection.

Your motivation is that you have been diagnosed with prostate cancer, and it has metastasized or recurred, and you're wondering what your treatment options are, and that's where the targeted therapy comes in.

But one of the great strengths of proteomics is in the quest for biomarkers, for early detection and for accurate prognosis and guidance of initial therapy, as well as guidance of later therapy.

“Hacking the Proteome for Cancer Treatment” (Karin Rodland) [#12] I probably don't have to tell you folks that if you find almost any cancer in stage one, while it is localized and can be removed, surgery is pretty darn curative for almost all cancers. But the later the stage of the cancer, the worse the prognosis. How can we use proteomics to improve cancer survival?

“Hacking the Proteome for Cancer Treatment” (Karin Rodland) [#12] I have a protein bias. I know that a lot of the biotech people from San Diego have either a genome or transcriptome bias. There's a plethora of RNA signatures for prognosis of cancer. 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

ave either a genome or transcriptome bias. There's a plethora of RNA signatures for prognosis of cancer. 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.

When it comes to the field of biomarkers, proteins are kind of the “go to molecule'' because they're stable, and they're easy to measure. RNA is more labile (likely to change, easily broken down or displaced). We are now tending towards cell-free DNA or circulating tumor DNA. That's relatively new technology, but over time, protein-based biomarkers have really established themselves.

For example, there are the early detection biomarkers of PSA for prostate cancer and CA125 for ovarian cancer. The big problem with these biomarkers is that they're normal function proteins that are specific to the tissue of the prostate or the ovary. So there are a lot of false negatives.

They're statistically correlated because you have a bigger prostate if you have prostate cancer, but they're not mechanistically driving the cancer. So we are still looking for better biomarkers that say something about the state of cancer and particularly about the immune response of the body to the cancer.

There's a lot of potential that I want to focus on in therapeutic biomarkers that actually change the treatment decision. The two that have been around the longest are the HER2 gene in breast cancer and the BCR-ABL chimeric gene in leukemia. Because BCR-ABL activates the ABL kinase, you can use ABL kinase inhibitors to treat Philadelphia chromosome positive leukemias .

Because HER2 drives proliferation in breast cancer, you can use anti-HER2 strategies to treat breast cancer. I just saw a new trial that's using HER2-targeted antibodies to deliver doxorubicin specifically to breast cancer cells and allow a higher local dose, another example of a protein- driven therapeutic option that is emerging.

“Hacking the Proteome for Cancer Treatment” (Karin Rodland) [#12] You guys know this story. You have been through this. The way we treat cancer patients these days is population science. The way it's always been done. The gold standard for physicians is what treatment works the best in the greatest number of patients.

And even five years ago, there was a feeling that if you did anything that was outside of the gold standard of treatment, you were letting your patients down. The interview would go something like this: “Your PSA is really high. What should we do now? (I know you've been through this.