Hamid Highlights Emerging Biomarkers for Immunotherapy in Melanoma

Several novel markers are under exploration to help guide the optimal use of immunotherapy in patients with melanoma, according to Omid Hamid, MD, who added that although they have shown great promise, many are not quite ready for primetime.

Two markers that are currently being examined are tumor mutational burden (TMB), which can be utilized in conjunction with circulating tumor DNA (ctDNA) to predict response, according to Hamid.

Several research efforts have been dedicated to understanding how TMB can be used to understand or predict how patients will respond to immunotherapy; this is evidenced by the June 2020 FDA approval of pembrolizumab (Keytruda) for use in patients with TMB-high tumors. Additionally, ctDNA has been used as a biomarker for relapse as well as an indicator of response, added Hamid; however, it is not quite ready for standard use.

“The question really becomes now: Is [TMB] enough to tell us not to give a patient a treatment? That's not really clear at this time,” said Hamid. “For example, would you remove the ability of a patient with metastatic melanoma to receive immunotherapy with a checkpoint inhibitor based on a low TMB? Probably not, based on the fact that the patient doesn't have many other options. It is something that is helping us to understand how to make decisions and it will come in the future as we understand how to utilize TMB with ctDNA [to understand] response.”

Other markers, such as microRNA (mRNA), at interferon gamma (IFNγ) gene expression profile in the adjuvant setting, and biomarkers for toxicity are also under exploration.

In an interview with OncLive, Hamid, director of the melanoma program and Phase I Immuno-Oncology Program at The Angeles Clinic and Research Institute, discussed emerging biomarkers in melanoma, data supporting their efficacy and their potential for use in clinical practice, and future directions for research.

OncLive: Could you start off by discussing the benefits of biomarkers in melanoma?

Hamid: When you talk about biomarkers, you're looking at any evidence that can help you monitor disease status, whether it's recurrence in the adjuvant setting or the presence of progressive disease in the metastatic setting. They can also be predictive [and inform treatment] before [a patient] starts their therapy; [there are] predictive biomarkers of response and for toxicities.

It's hoped that they will help us to understand which therapies to choose, where to go, and what to avoid, whether it's giving a therapy that would have a significant risk of a life-threatening toxicity despite response, or indicating no chance of response, or even a high chance of response. If we have a regimen that has a 30% response rate, by using predictive biomarkers to select a better subset of patients [to receive it], then you can offer them a 70% response rate. You can potentially prevent patients from wasting 3 months of their time on a treatment [that won’t work]. You can offer patients the ability to move forward and do better.

How has TMB helped to guide immunotherapy decisions for patients with this disease?

It's not just for melanoma; TMB has done a significant job in understanding patients who would respond to immunotherapy. High TMB has been used to [predict] response to immunotherapy; that has been well-known for CTLA-4 and PD-1 agents. Multiple [studies have indicated] that. For example, one study published in the New England Journal of Medicine examined TMB [as a marker] for CTLA-4 blockade response. We know that TMB for PD-L1 responses is important, ergo the FDA recent of pembrolizumab approval for patients who have high TMB. It is an indicator of a patient who is going to have a higher response rate to treatment.

How is ctDNA being used to predict response in this patient population?

The Melanoma Institute of Australia has done many studies looking at ctDNA. We know that the majority of melanomas have ctDNA, not just for the 50% of patients who have BRAF mutations, but for the other mutations that exist, as well. We know that it's a good marker for risk of relapse in the adjuvant setting. If [a patient] has ctDNA, they get their sentinel node incision and [if their ctDNA] goes down to 0, they will have a lower risk of relapse than someone who has persistent ctDNA.

In addition, [ctDNA] has also been utilized as an indicator for response. One abstract that was recently presented looked at patients who had pseudo-progression [and investigators] utilized ctDNA to help understand what that means. At 12 weeks when you image and it looks like the patient’s disease has grown, you don't know whether it has grown and is shrinking now or it consistently [growing]. Some investigators have correlated that with ctDNA. As you get to week 12, if ctDNA has decreased, that's a greater indication that what you're seeing is a late response; that tells you that you can hold on longer and revaluate in 4-6 weeks.

We know that ctDNA can help [us] to understand what's going on in the body or in the adjuvant setting. However, most recently, investigators from the Melanoma Institute of Australia, looked to see whether we can understand what's going on with patients who have brain metastases [by using ctDNA]. Unfortunately, it does not [help in that instance]. ctDNA is something that is not quite standard, not quite ready for primetime, but it's coming. It's involved in almost every clinical trial right now to understand what's going on.

What is the role of mRNA with regard to immunotherapy?

mRNAs have been reported in multiple cancers; they're regulators of gene expression and can be correlated with certain genes that are invariably expressed in certain malignancies. Their quantification can help us in the same way; they’re potential biomarkers to diagnose early lesions or early metastatic disease, so what's there when you initially see the tumor and whether it recurs. In addition, they can help with understanding therapeutic targets; if these mRNAs are associated with therapeutic pathways that we can target, then you can understand how to utilize them as therapeutic targets.

Getting back to mRNAs and ctDNAs, [these 2 factors] can potentially help you in multiple ways. They can help you initially by understanding whether there is a target. If there is circulating tumor BRAF, with a blood test, you may have an earlier way of knowing whether a tumor has that mutation and [be able to] target it. As we get more and more savvy with understanding mRNAs and what happens with the changes and the evolution of the tumor, then we may be able to understand newer targets and how to introduce either combinatorial therapeutics or even a whole new therapeutic landscape for a patient.

If something shows up as a patient is progressing, if it's a pathway that we know how to target, then we understand the molecular events that are ongoing in that tumor without having to biopsy. In addition, hopefully it can help us to understand prognosis. In situations where we don't know where the tumor is coming from, you can look at gene signatures and ctDNA, and those tumors of unknown primary, and you can potentially adequately treat.

Are any other emerging biomarkers under examination right now that you feel are particularly interesting?

Let's talk about the adjuvant space. Right now, PD-1 is getting more and more of a foothold in adjuvant therapy. Jeffrey Weber, MD, PhD, of NYU Langone Health, [presented] updated data from the CheckMate-238 trial, which examined ipilimumab (Yervoy) versus nivolumab (Opdivo) in the adjuvant setting; this set nivolumab as the standard. With the updated analysis, [they] examined exploratory biomarkers at baseline and median values. This helps us to understand who can benefit more from these therapies. They looked at IFNγ gene expression profile.

What [CheckMate-238 investigators] found was that improved relapse-free survival (RFS) was seen with higher IFNγ expression with both nivolumab and ipilimumab, a higher CD8 T-cell infiltration, high TMB, and lower peripheral myeloid-derived stem cells. When you put those together, the higher TMB and IFNγ, that gave you the best RFS. [This allows us to understand] how those biomarkers can then go forward and help not just with that, but with [understanding] long-term survival.

This [idea] was brought forth in a pembrolizumab study, [in which investigators] showed a high response rate with an IFNγ gene expression profile, CDAT cells in the tumor, TMB, and then also myeloid-derived suppressor cells in the periphery. You can detect those through whole exome sequencing, immunohistochemistry, and flow cytometry.

In the future, we can understand not only how [these markers] can [potentially] help us [choose] the right therapy for a whole group of patients, but it’s also possible that there's a subgroup of patients who do better with [certain agents]. We don't know [the answer to] that yet, but we can [use this to] understand which adjuvant therapy to choose, whether it's looking at the unknown question of whether we should target BRAF or use PD-1 in the adjuvant setting for a patient with BRAF-mutated disease.

Where is future biomarker research going to be focused?

A lot of information on biomarkers of toxicity was presented during the 2020 ASCO Virtual Scientific Program; I believe that is where we are going next. What are these biomarkers that can help us understand toxicity? In 1 study, investigators examined autoantibodies as predictors for survival and immune-related adverse effects (AEs) in checkpoint inhibition therapy.

Investigators examined samples and data analyses, [including] pre-treatment samples from checkpoint inhibitor-treated stage IV melanoma A total of 832 autoantibody antigens were profiled and [examined] patients treated with anything. They looked at these data analyses, associated antigens, and pathways that lead to toxicities. MIF antibodies showed increased disease progression and a lower risk of immune-related AEs. EGFR antibodies were associated with progressive disease, shorter survival, and a lower rate of immune-related AEs. MAGE antibodies were associated with better survival and higher rate of immune-related AEs. MITF antibodies were associated with colitis.

In the future, you can foresee this idea that has been brought forth in many sci-fi novels; with 1 drop of blood, we can look at antibodies, ctDNA, and gene signatures. In a multivariate analysis, this can tell us how [a patient is] going to do [on different treatments]. That's where we're going in the next 3-5 years. Not just understanding initially, but [grasping] dynamic changes within the tumor, tumor microenvironment, and tumor expression through mRNA, changes in ctDNA, etc, to understand what is going on.

It doesn't have to just be pathological, like a biopsy or blood. We're also looking at predictors of response through imaging. There are now PET tracers that target T cells, and we're using that as a dynamic predictive marker for response. There are companies such as ImagiNav Technologies that are doing studies trying to understand what that means. With an initial CD8 T-cell scan, you can tell where your CD8s are. Then, after a couple of doses, you can image and see if you're really trafficking those CD8 T cells into the tumor.

This is an easy read: If you see it getting hot where the tumors are, you're getting your desired effect. If not, you're not getting your desired effect and may need to add something or move onto [a different treatment]. You may need to go directly to targeted therapies. Ultimately, these can help us to understand what is happening with our patients.