Immunotherapy uses the immune system to target tumor cells, revolutionizing cancer treatment. However, only 20%-40% of patients experience a positive response, and these rates vary depending on the type of cancer. Determining which patients will benefit from immunotherapy is a current focus of research.
Many studies have explored the unique characteristics of tumors, the surrounding microenvironment, and the patient's immune system. Despite these advances, it remains unclear which proposed biomarkers reflect the same underlying factors or how many different factors independently influence the success of this therapy.
Researchers at the International Cancer Institute in Barcelona have discovered five key independent factors that determine patient response and survival after receiving checkpoint inhibitors (CPIs), a type of immunotherapy widely used in cancer treatment. The findings, published in the journal Nature Genetics, provide a reference framework for current and future biomarkers of response to immunotherapy. In the future, they may also provide an important way to personalize cancer treatment, helping to more accurately identify those patients who may benefit from immunotherapy. The findings suggest that patients with certain types of tumors not currently considered candidates for immunotherapy, such as those with liver or kidney cancer, may benefit from this treatment.
A team led by Dr. Núria López-Bigas and Dr. Abel González-Perez from the Laboratory of Biomedical Genomics of the International Research Council in Barcelona, in collaboration with researchers from multiple international research centers, addressed this question by conducting a comprehensive analysis of genomic, transcriptomic and clinical data from 479 patients with metastatic tumors treated with CPI. The data comes from a public database established by the Dutch Hartwig Medical Foundation.
"We used an unbiased approach to analyze thousands of molecular and clinical features and identified five independent factors that influence immunotherapy response and patient survival," explained ICREA researcher Dr. López-Bigas at IRB Barcelona.
Five factors, five keys to immunotherapy
The five factors identified were: tumor mutation load; effective T-cell infiltration; transforming growth factor beta (TGF-β) activity in the tumor microenvironment; the patient's previous treatments; and tumor proliferation potential. These factors in different types of cancer are associated with response to CPIs and the authors have validated these factors in six independent cohorts involving a total of 1,491 patients.
Tumor mutation burden (TMB): Tumors with a large number of mutations tend to produce more neoantigens, making it easier for the immune system to recognize and attack them. TMB is one of the most studied biomarkers for predicting CPI response.
Effective T cell infiltration: The presence of cytotoxic T cells in tumors is critical to the effectiveness of CPI. This study confirms that the greater the infiltration of these cells, the better the response to treatment.
TGF-β activity in the tumor microenvironment: This factor affects the behavior of certain cells in the tumor microenvironment. High TGF-β activity can suppress immune responses, which is reflected in the fact that patients tend to have lower survival rates after immunotherapy treatment.
Previous treatment: Patients who have been previously treated tend to have a poorer response to immunotherapy.
Tumor proliferation potential: Patients with high tumor proliferation index tend to be more aggressive and generally have lower survival rates after treatment.
Enabling personalized cancer treatment
These five factors provide a framework for organizing the vast body of current knowledge on biomarkers of response to immunotherapy. "Many studies to date have focused on identifying and reporting a single biomarker, but our findings suggest that many of these biomarkers may be different versions of the same underlying factor," said Dr. Gonzalez-Perez.
In addition, the researchers demonstrated that a multivariable model that combined these five factors more accurately classified patients and predicted their probability of responding to immunotherapy than using tumor mutation load alone, a method frequently used in clinical practice. This advance could have significant clinical impact in the future, as it could prevent patients with a lower likelihood of response from suffering the side effects of CPIs that can lead to autoimmune disease and also help reduce treatment costs.
International group verification
One of the highlights of the study was the validation of these five factors in six independent cohorts of patients with cancers including lung, colon and melanoma. "We have demonstrated that these factors are associated with different types of cancer and different patient groups, thus strengthening their clinical value. As research continues, new latent factors may be discovered in other types of cancer or in larger groups," explains Dr. Joseph Usset, who worked as a postdoctoral researcher at the International Cancer Research Institute of Barcelona (IRB Barcelona) and is now at the Valld'Hebrón Institute of Oncology.
The team hopes to obtain more patient data in the future to create more accurate models. The accuracy of these models for possible future clinical applications should be verified through prospective clinical trials. However, this progress faces significant challenges in that it is difficult to obtain data as comprehensive and detailed as those used in this study.
"This study is an important step toward understanding how different tumor characteristics influence treatment response," concluded Dr. Lopez-Bigas. "In the future, we hope to incorporate these five factors into clinical practice to guide treatment decisions."
Compiled from /scitechdaily
DOI:10.1038/s41588-024-01899-0