A Multiplexed Approach for Predicting Responses to Cancer Immunotherapy: Implementation and Challenges

Mana Chandhok:
Hi everyone. Welcome to this podcast from Cambridge Health Tech Institute for the Next Generation Diagnostic Summit, which runs August 15th to the 18th in Washington, DC. I'm Mana Chandhok, an associate producer. We have with us today one of our speakers from the Biomarkers for Cancer Immunotherapy and Combinations Track, Dr. Robert Anders, an associate professor of pathology at Johns Hopkins. Dr. Anders, thank you for joining us.

Robert Anders:
Thank you for inviting me. It's a pleasure to speak with you about the topics of immune therapy.

Mana Chandhok:
You're suggesting a multiplexed approach for predicting responses to cancer immunotherapy using biomarkers that integrate genomic protein and immunological markers. Can you please elaborate on this strategy?

Robert Anders:
There's a lot of interest in predictive biomarkers in medicine and I think it's important to remember that when making medical decisions or therapeutic decisions, rarely is one parameter the decider whether somebody gets a therapy or not. For instance, a patient who has a mass in their stomach that's maybe found on imaging, it's possible that could be a benign or a malignant mass. It's not until you investigate the mass and maybe do a biopsy and look at the results of that biopsy that you may make a therapeutic decision to go ahead with surgery or something like that or to begin chemotherapy.

A patient who's losing weight, that may or may not be alarming. The patient may or may not have cancer. It's only after further investigations, maybe blood work for tumor markers or biopsies, so it's oftentimes that multiple parameters are used to make medical decisions and that's just how the practice of medicine is carried out. When it comes to immune therapy I think there has been a lot of pressure on trying to find the one predictive biomarker that will determine whether a patient will benefit from a given therapy.

What I plan to do in the lecture that I'm going to give is explain how when it comes to colon cancer, specifically mismatch repair deficient types of colon cancer that selecting patients for treatment or for successful treatment often is possible if people consider the genomic landscape. In other words, do these patients have a lot of mutations. If they have a lot of mutations that means they're more likely to have a neoepitope and an neoepitope is something that the patient's own immune system can use to attack that cancer so mutations would be one additional parameter.

The second would be if the cancers express the target, the checkpoint inhibitor. For instance obviously the best target right now would be PD-L1 expression. We know that patients who have mismatch repair deficient tumors are more likely to have PD-L1 expression so that would be a second parameter. The first would be do patients have a lot of mutations, second would be do patients have expression of the checkpoint inhibitor. The third would be using some type of staining technique, whether it's immunofluorescence staining or immunohistochemical staining to look to see if patients have a high density of lymphocytes in their tumor.

Patients who have more lymphocytes are more likely to have a beneficial immune response in eliminating their tumor. If we take all three parameters together, genomics, PD-L1 expression and lymphocyte density and apply that to colon cancer it makes it obvious that mismatch repair deficient cancers would benefit from anti-PD-L1 therapy. I'm hypothesizing that maybe a similar type of thinking could be applied to other tumor types. I'm not convinced that these three parameters, the genomics, checkpoint inhibitor expression and lymphocyte density are going to work for every cancer. In fact, I think we need to investigate things like RNA expression and cytokine expression if possible.

The emphasis here is that making better predictive immune therapy biomarkers means using multiple parameters and not just one.

Mana Chandhok:
What are some of the bottlenecks to implement a strategy like this?

Robert Anders:
I think here, our ability to interrogate mutations, lymphocyte density, PD-L1 expression at the research level is actually very good but getting these tests validated for clinical use is not trivial. Certainly pharmaceutical companies have sought and obtained FDA approval for PD-L1 expression as a predictive biomarker but it's not clear to me how determining lymphocyte density is going to easily translate in the clinical practice. One, I'm not sure that there is an intellectual property piece that can be patented there and two is it's extremely time consuming. Most cancer diagnoses are made within a few minutes of a pathologist looking at a piece of tissue.

If the pathologist now needs to go in and figure out how to measure lymphocyte density, you're adding a significant amount of time that those practicing pathology really don't have so it's not clear to me how that type of information could be readily obtained so that the flow of care is smooth. Then when it comes to mutations, if you're requiring sequencing to determine mutational density, this is something that takes months and quite frankly I don't think we have the infrastructure as a nation to necessarily be sequencing everybody's tumor.

So I think there are a couple of hurdles here. One is the time that it takes to perform these analyses and then two is the reimbursement strategy. I don't see a clear way forward of how to bill for these services. Then third is really integrating all of that data into one report. The diagnosis may be made and then several weeks to months of followup work to determine the density of the cells or the mutational density. That could take a significant amount of time and it's not clear how with current laboratory information systems we could integrate all that data into one report for the patient or the treating physician.

Mana Chandhok:
We're looking forward to the summit and hope it to be productive for each participant. What do you expect to gain from the meeting as a speaker and an attendee?

Robert Anders:
These types of meetings are always very exciting because it's very focused and nearly everybody who's attending is speaking the same language, if you will. We're all excited about topics that we're looking at, immune therapy or predictive biomarkers and to be able to directly relate to someone. They're giving a lecture and you know exactly what they're talking about and how they see a topic perhaps in a different light. That's just very illuminating for our own research and moving forward. Then there's usually a good enthusiasm around each of the topics because there are highly specialized people who are in attendance recognize exactly what's going to be discussed and there's often a nice discussion either after the lectures or after the session is over when everybody collects together and sort of says, "Hey I understand what you're talking about. I've never thought of it that way," or, "Have you ever thought of this idea?"

Then invariably people want to help or they want to apply their thinking to maybe the set of samples that we have or we want to take our set of samples and interrogate them with the new methodologies. Perhaps something that we didn't even know existed. So these meetings are very important because oftentimes what's discussed or what the lectures cover is several months ahead of what's in publications so if you just want to rely on what's in publication, oftentimes you're at least six months if not even further back, a year behind. If you really want to know what's happening in a particular topic, meetings are always the best forum for that.

Mana Chandhok:
Dr. Anders, thank you for your time and insights today.

Robert Anders:
You're welcome and thank you.

Mana Chandhok:
That was Dr. Robert Anders an associate professor of pathology at Johns Hopkins. He'll be speaking at the Biomarkers for Cancer Immunotherapy and Combinations Conference at the upcoming Next Generation Diagnostic Summit which runs August 15th to the 18th in Washington, DC. I'm Mana Chandhok. Thank you for listening.