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Study identifies biomarker that may help predict benefits of immunotherapy

Scanning electron micrographs of human T lymphocytes (also called T cells) from the immune system of a healthy donor. Credit: NIAID

In recent years, immune-based treatment of cancer has boosted the hopes of both doctors and patients. Drugs called immune checkpoint inhibitors have provided life-saving benefits to the growing list of people with several types of cancer, including melanoma, lung cancer, and bladder cancer.

Despite the excitement surrounding these drugs, the frustrating problem was that doctors couldn’t predict who would benefit from them and who wouldn’t.

On August 25, 2021, a group of researchers at the Memorial Sloan Kettering Cancer Center reported to the journal. Scientific translation medicine Specific pattern of markers above, or “signature” Immune cells Blood may be a biomarker of the response to checkpoint immunotherapy.Within this immune signature, the molecule LAG-3 provided important information to identify. Patience With bad results.

This link was found in a group of patients with metastatic melanoma and validated in a second group of patients with metastatic bladder cancer. This suggests that this potential biomarker may be widely applicable to patients with a variety of cancers.

According to Margaret Callahan, a researcher and leading physician researcher at MSK’s Parker Institute for Cancer Immunotherapy, she has a large patient cohort, strong clinical follow-up, and a rigorous statistical approach to the study. “Immunity signatures tell us important things about who responds to immunotherapy and why.”

The findings are for prospective clinical trials designed to test whether incorporating this biomarker into patient care can improve outcomes in people who are unlikely to benefit from existing therapies. Open the way.

Big data, big conclusions

In making their discoveries, the researchers had the data on their side. As one of the first cancer centers in the world to begin treating large numbers of patients with immunotherapy, MSK has a cache of stored blood from hundreds of patients treated over the years. About research. Researchers in this study made their findings using pretreatment blood samples collected from patients enrolled in seven different clinical trials held at MSK between 2011 and 2017.

To mine blood for clues, researchers used a technique called flow cytometry. Flow cytometry is a tool that quickly analyzes the attributes of a single cell as it passes through the laser. The researcher’s goal was to identify markers found in the patient’s immune cells that correlate with the response to immunotherapy, primarily PD-1 targeting drugs such as nivolumab (Opdivo) and pembrolizumab (Keitruda). But this was not a normal human eye job.

“Given the fact that there are hundreds of thousands of blood cells in a patient’s blood sample, mapping the composition of nearly 100 different immune cell subsets, effectively extracting clinically relevant information. Is very difficult, “says Ronglai Shen, a statistician at MSK’s Faculty of Epidemiology and Biostatistics, who has developed some of the statistical tools used in this study. “There, as data scientists, we were able to help Dr. Callahan and other physician researchers in their research. It was a perfect blend of skills.”

A statistical tool developed by Dr. Shen and fellow data scientist Catherine Nageas allows the team to classify patients into three distinctive immune signatures or types based on a unique pattern of blood markers. I was able to do it.

The populated immune form was a group of patients expressing high levels of a protein called LAG-3 in various T cell subsets. The team found this LAG + immune patient had a much shorter survival time compared to the LAG-immune patient: median survival was more than 4 years different for patients with melanoma. (22.2 months compared to 75.8 months). The difference was statistically significant.

LAG-3 as a target

LAG-3 (short for lymphocyte activation gene 3) belongs to a family of molecules called immune checkpoints. Like the better known checkpoints CTLA-4 and PD-1, LAG-3 has an inhibitory effect on the immune response and suppresses the immune response. Some drugs targeting LAG-3 are currently in clinical development, but it is difficult to define who is most likely to benefit from them.

When Dr. Callahan and her colleagues began this study, they did not intend to focus specifically on LAG-3. “We guided us to the data and the LAG-3 shocked us,” she says.

One of the strengths of this study is that it uses both a “detection set” and a “verification set”. What this means is that the researchers performed the first analysis on a set of blood samples from a large group of patients (in this case, 188 patients with melanoma). They then asked if the immune signatures identified in the discovery set could predict the outcome of a completely different batch of patients, 94 patients with bladder cancer.

It was possible and worked very well.

“We examined a validation cohort of patients with bladder cancer who underwent checkpoint blockage and found that patients with the LAG + immune system had a response rate of 0%,” said Dr. Callahan. “Zero. No one responded. This is compared to the 49% response rate of people with the LAG immune type.”

Due to the large data set, scientists could also ask how the LAG + immune type is compared to other known response biomarkers, specifically PD-L1 status and tumor mutation loading. .. What they found was that the immune system provided new, independent information about patient outcomes rather than simply echoing these other biomarkers.

Why you need good biomarkers

Biomarkers are important in cancer for several reasons. They may help clinicians and patients choose the best treatments and avoid unnecessary or unsuccessful treatments.

“Immunotherapeutic drugs are not without potential toxicity,” says Dr. Panageas. “So it’s a big step forward if someone can avoid the potential risk of treatment because they know they’re unlikely to react.”

The second reason is cost. Because immunotherapeutic drugs are expensive, it is essential to have a means to better match the available drugs with the patient.

Researchers have also used patient blood samples to identify this biomarker, which gives a satisfactory prospect that patients can be evaluated for this marker using simple blood draws. Other biomarkers currently in use usually depend on the tumor tissue obtained by biopsy.

“If you say that you can get a simple blood draw and get the information to decide which treatment to choose within a few days, I don’t think it’s going to be any better,” says Dr. Callahan. .. .. “Of course, there’s still a lot to do before applying these findings to patients in the clinic, but we’re really keen on the possibility of applying these findings.”

What’s next?

The limitation of research is that it is retroactive. That is, the data analyzed was from blood samples that were collected many years ago and stored in the freezer. Researchers need to test their hypotheses in prospective studies to ensure that the findings may benefit patients. That is, patients are enrolled in clinical trials specially designed to test the idea that using this immune type in treatment decisions can improve patients. result.

“I’m most excited about the idea that not only can we identify patients who do not work with conventional treatments, but based on our knowledge, we can offer other treatments that may help these patients. Is a positive evaluation of what LAG-3 is doing biologically. ”


The scoring system predicts the response of patients with head and neck cancer to immunotherapy


For more information:
Ronglai Shen et al, LAG-3 expression in peripheral blood cells, identifies patients with poor outcomes after immune checkpoint inhibition. Scientific translation medicine (2021). DOI: 10.1126 / scitranslmed.abf5107

Quote: The study predicts the benefits of immunotherapy (August 25, 2021) obtained from https://medicalxpress.com/news/2021-08-biomarker-benefits-immunotherapy.html on August 25, 2021. Identify biomarkers that may help you

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