Microbiome Helps Identify Who Benefits from Combination Immunotherapy

A new study by researchers from the Wellcome Sanger Institute, the Olivia Newton-John Cancer Research Institute in Australia, and collaborators, have identified specific strains of bacteria that are linked with a positive response to combination immunotherapy in the largest study of its kind.

The study is published in Nature Medicine in an article titled, “A gut microbial signature for combination immune checkpoint blockade across cancer types,” and details a signature collection of microorganisms in an individual’s gut bacteria that may help identify those who would benefit from combination immunotherapy and help explain why the efficacy of this treatment is otherwise hard to predict.

“Immune checkpoint blockade (ICB) targeting programmed cell death protein 1 (PD-1) and cytotoxic T lymphocyte protein 4 (CTLA-4) can induce remarkable, yet unpredictable, responses across a variety of cancers,” wrote the researchers. “Studies suggest that there is a relationship between a cancer patient’s gut microbiota composition and clinical response to ICB; however, defining microbiome-based biomarkers that generalize across cohorts has been challenging.”

While immunotherapy can be very effective, it only works in a proportion of recipients across a wide range of cancers. Being able to predict who is most likely to respond to treatment helps ensure that patients do not endure these unnecessary side effects for no medical benefits.

The study used samples collected in a large, multi-center Australian clinical trial where combination immunotherapy was effective in 25% of people with a broad range of advanced rare cancers, including rare gynecological cancers, neuro-endocrine neoplasms, and upper gastrointestinal and biliary cancers.

The clinical trial focused on checkpoint inhibitors. These anticancer agents block the body’s immune checkpoint proteins, allowing the immune cells to destroy cancer cells. In this case, the immunotherapy blocked the PD-1 and CTLA-4 checkpoints.

Researchers used stool samples from clinical trial patients and performed deep shotgun metagenomic sequencing to map all the organisms within the participants’ microbiomes, down to the strain level.

They discovered multiple strains of bacteria in those who responded well to treatment, many of which had not been cultivated before. This allowed them to identify a microbiome signature that was found in patients who responded well to treatment.

The researchers conducted a meta-analysis of previous studies and found that their signature can be applied to different cancers, such as melanoma, and across countries, to predict individuals whose cancer will likely respond to combination immunotherapy.

However, when applied to patients who received just one of the immunotherapy drugs, targeting the immune checkpoint receptor PD-1 only, the machine-learning model could not identify those who would respond to treatment.

This suggests that the relationship between gut microbiota and treatment response is specific for particular therapeutic combinations.

Ashray Gunjur, PhD, first author from the Wellcome Sanger Institute and the Olivia Newton-John Cancer Research Institute, Australia, said: “Our study shows that understanding the microbiome at strain-level, not just species-level, can open up a new level of personalized medicine. Having that extra resolution is crucial if we are to understand what is happening in the human body and the interplay between cancer treatment and the microbiome. Being able to test the specific mechanisms of this relationship between specific strains and response is the next horizon in this research, and one that could benefit human health in a multitude of ways.”