A research team has produced a detailed summary of how the immune system changes tumor structure in response to immune checkpoint therapy. This eight-year investigation elaborates on how cancer immunotherapy prompts tumor recognition through neoantigens, altering the tumor environment.
A collaborative research effort led by Cleveland Clinic’s Timothy Chan, MD, PhD, who oversees the Global Center for Immunotherapy, alongside Bristol Myers Squibb, has released the most thorough overview to date regarding how the immune system modifies tumor architecture when faced with immune checkpoint therapy.
The extensive eight-year study, published in Nature Medicine, describes how cancer immunotherapy encourages the recognition of tumors through neoantigens, fundamentally reshaping the tumor ecosystem. Neoantigens are tiny peptides formed when cancer cells mutate, and they serve as key markers allowing the immune system to distinguish cancer cells from normal cells.
“What sets this study apart is that we collected tumor samples before therapy and shortly after immunotherapy began,” states Dr. Chan, who also chairs Cleveland Clinic’s Center for Immunotherapy & Precision Immuno-Oncology, leads the Immune Oncology Program at Case Comprehensive Cancer Center, and holds the Sheikha Fatima bint Mubarak Endowed Chair in Immunotherapy. “We aimed to comprehend how individuals’ tumors are recognized and modified by their immune systems as a result of immunotherapy.”
Throughout the course of cancer, our immune cells and cancer cells continuously interact and influence each other. Immunotherapy must function within this context by enhancing our immune cells to combat cancer. Researchers like Dr. Chan have started to unravel the intricate relationships among treatment, immunity, and cancer over the last 15 years, yet human data remains limited.
The CheckMate-153 trial, managed by Bristol Myers Squibb, included Dr. Chan’s team as a critical analysis site for the trial. In this trial, investigators conducted a biomarker sub-study to evaluate how neoantigens influence responses to nivolumab by obtaining tumor samples from patients prior to treatment and three weeks after starting therapy. Sequencing of these tumor samples enabled the identification of mutations responsible for the formation of neoantigens.
While neoantigens are believed to be the primary means by which the immune system identifies tumors, current prediction tools for neoantigens often lack precision due to insufficient existing data. To address this limitation, the team created the largest neoantigen screening to date, where they validated predictions and tracked the dynamic reactions to neoantigens through sequential blood samples.
After three weeks of treatment, those who responded favorably to nivolumab exhibited a significant drop in clonal neoantigens. In contrast, patients whose cancer did not enter remission showed an immune response, but targeted smaller sub-clonal populations. This finding is significant because it was previously thought that non-responders failed to activate their immune response towards the tumor; instead, the immune system was responding to neoantigens, but this reaction did not suffice to eradicate all tumor clones.
Present neoantigen prediction tools primarily focus on HLA-binding neoantigens, often overlooking the T cell recognition aspect of immunogenicity, explains Tyler Alban, PhD, a co-first author from Cleveland Clinic and research staff in the Chan Lab. Dr. Alban, along with data scientist Prerana Parthasarathy and other team members, developed a machine-learning program leveraging the new screening data to enhance predictions of immunogenic neoantigens. This process revealed novel characteristics associated with these cancer-derived neoantigens.
“We discovered a vast ecosystem of immune cells at play, with each T cell recognizing different neoantigens, thus altering the clonal structure of the tumor,” Dr. Alban remarks. “Our findings provided new insights into neoantigens and the mechanisms of resistance to immunotherapy.”
By tracking neoantigen changes during treatment, the analyses conducted by Dr. Alban challenged the existing notion in immunotherapy that a single fortunate mutation in a tumor is sufficient for immune systems to recognize it as a danger. The results demonstrate that a multitude of different T cells, each recognizing various cancer-causing factors, is essential for a robust treatment response.
Roadmaps produced by such observational studies will be vital for directing future immuno-oncology research, according to Dr. Chan.
“Understanding why our immune systems respond to certain cancer mutations while ignoring others is akin to discovering the holy grail for immunotherapy researchers,” he explains. “Our findings bring us closer to unlocking these mysteries.”
The research group is also collaborating with IBM through the Cleveland Clinic – IBM Discovery Accelerator, utilizing their dataset to develop advanced AI models that can predict new molecules for cancer treatments and vaccine development.
