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Collaboration key to identification, incorporation of biomarkers for immuno-oncology
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NEW YORK — Both predictive and prognostic biomarkers can influence immuno-oncology treatment, but further research is still needed to determine the best course of therapy, according to a presenter at HemOnc Today New York.
“As translational researchers or researchers in the laboratory, we need to think about, can we bring what we are measuring into the clinic? Is it easy enough?” Nikhil I. Khushalani, MD, associate member and vice chair of cutaneous oncology at Moffitt Cancer Center and associate professor at USF Morsani College of Medicine, said during his presentation. “Clinical trials routinely require biopsies: biopsies prior to treatment, biopsies 2 weeks into treatment, biopsies 6 weeks into treatment. The question one has to step back and ask is, how practical is that?”
For immuno-oncology, biomarkers can inform clinicians on what to do and when to do it, Khushalani said.
There are many types of biomarkers but, for immuno-oncology, prognostic and predictive biomarkers are among the most important. Prognostic biomarkers define the likelihood of a clinical outcome — for example, testing for BRCA1 or BRCA2 mutations in women with breast cancer to understand risk for developing a second breast cancer. Predictive biomarkers are used to identify individuals who are more likely to have a favorable or unfavorable reaction to a therapy, for example BRAF mutations in melanoma.
The field on immuno-oncology needs biomarkers because response to therapy is not universal, Khushalani said. In anti-PDL1 therapy, for example, response among patients with melanoma was 40%, compared with 20% among patients with non-small cell lung cancer and 22% among patients with renal cell carcinoma.
Adverse events can also vary despite favorable response, and biomarkers may play a role in determining which patients are more likely to develop adverse events. Additionally, biomarkers can help determine who may have an unfavorable response with a therapy and, therefore, allow patients who likely will not derive benefit to avoid potentially ineffective and expensive treatments.
“If we a priori can identity those patients that are destined to develop toxicities, maybe we can alter our therapy accordingly,” Khushalani said.
Predictive biomarkers that have clinical data include tumor mutational load, T-cell mutation, PD-L1 and tumor inflammation. However, more biomarker research is needed, preferably in a prospective trial, Khushalani said.
“Biomarkers are relatively easy to measure, but we need to do it prospectively rather than retrospectively to say, can we truly utilize these biomarkers to make a difference in what treatment we chose for patients,” Khushalani said.
Many challenges come with using biomarkers to determine treatment. These include:
- Lack of uniform methodology for study;
- Tumor heterogeneity;
- Patient diversity;
- Fluctuation in the dynamics of the immune system; and
- Funding constraints.
“One size fits all does not work here,” Khushalani said. “We really have to tailor treatment and hopefully further research will really help us. The immunotherapy renaissance, whether we like it or not, is here to stay and this is the rebirth of immunotherapy. It’s unlikely that a single composite biomarker will satisfy all requirements.
“Collaboration between all stakeholders — investigators, treating physicians, industry, regulatory authorities — is really key if we want to move this field forward,” he added. – by Cassie Homer
Reference:
Khushalani NI. Biomarkers and Immunotherapy. Presented at: HemOnc Today New York; March 8-10, 2018; New York.
Disclosures: Khushalani reports serving on the advisory/data safety monitoring board of AstraZeneca, Bristol-Myers Squibb, Castle Bioscience, EMD Serono, Genentech and Regeneron; and receiving institutional research funding from Amgen, Bristol-Myers Squibb, GlaxoSmithKline, HUYA Bioscience International, Merck and Regeneron.