Researchers have identified five distinct factors that predict how cancer patients will respond to checkpoint inhibitors (CPIs), a form of immunotherapy. This study confirms these factors across more than 1,400 patients and various cancer types, offering a new way to understand biomarkers linked to CPI responses. It also lays the groundwork for enhancing personalized cancer treatment in the future.
In recent years, immunotherapy has revolutionized cancer treatment by allowing the immune system to target and destroy tumor cells. Yet, only about 20-40% of patients see positive results from this treatment, and the effectiveness varies among different cancer types. Determining who will respond well to immunotherapy is an active research focus. Previous studies have looked at a range of factors, including tumor characteristics, the surrounding microenvironment, and the patient’s immune function. However, it remains unclear how many independent factors truly affect treatment success or if the proposed biomarkers signify the same underlying elements.
Researchers at IRB Barcelona have pinpointed five crucial, independent factors that affect how patients respond to checkpoint inhibitors (CPIs) and their overall survival rates. The study, published in Nature Genetics, serves as a foundational reference for current and future biomarkers related to immunotherapy response. Moreover, these findings could pave the way for advancements in personalized cancer therapy, improving the ability to identify patients who might benefit from CPI treatments. Interestingly, it suggests that patients with certain tumors not currently deemed suitable for immunotherapy, like those with liver or kidney cancers, might actually gain from this treatment.
The research team, led by Dr. Núria López-Bigas and Dr. Abel González-Perez from the Biomedical Genomics laboratory at IRB Barcelona, collaborated with various international researchers to analyze comprehensive genomic, transcriptomic, and clinical data from 479 metastatic patients who underwent CPI therapy. This data was sourced from a public database from the Dutch Hartwig Medical Foundation.
“We employed an unbiased method to analyze thousands of molecular and clinical characteristics and identified five independent factors that impact both immunotherapy response and patient survival,” said Dr. López-Bigas, an ICREA researcher at IRB Barcelona.
Five Factors: Keys to Immunotherapy Success
The five identified factors include: tumor mutational burden; effective T cell infiltration; transforming growth factor beta (TGF-β) levels in the tumor microenvironment; previous treatments the patient has received; and tumor proliferation potential. In various cancer types, these elements correlate with CPI response, having been validated across six independent patient cohorts totaling 1,491 participants.
- Tumor Mutational Burden (TMB): Tumors with a high mutation count tend to generate more neoantigens, making them more recognizable targets for the immune system. TMB is one of the most researched biomarkers for predicting CPI response.
- Effective T-cell Infiltration: The presence of cytotoxic T-cells within tumors is crucial for the success of CPIs. This study confirmed a direct correlation between higher T-cell infiltration and improved therapy responses.
- TGF-β Activity in Tumor Microenvironment: This factor affects the behavior of certain cells within the tumor’s microenvironment. Elevated TGF-β levels can hinder immune responses, leading to worse survival rates following immunotherapy.
- Previous Treatments: Patients with prior treatments typically exhibit reduced responses to immunotherapy.
- Tumor Proliferative Potential: Patients with tumors showing high proliferation rates, indicative of aggressive forms of cancer, generally experience lower survival rates post-treatment.
Advancing Personalized Cancer Treatment
The five factors identified serve as a framework to consolidate the extensive knowledge regarding immunotherapy response biomarkers. “Many prior studies concentrated on individual biomarkers, but our findings indicate that several of these may actually represent different manifestations of the same underlying factors,” explained Dr. González-Pérez.
Additionally, the team found that a multivariate model incorporating these five factors provides a more precise classification of patients compared to the common practice of relying only on tumor mutational burden. This progress could have significant clinical implications, as it may help avoid subjecting patients with little chance of benefiting from treatment to the adverse effects of CPIs, which can result in autoimmune disorders, and could also cut treatment costs.
Validation Across International Cohorts
A key aspect of this study is the validation of these five factors across six independent cohorts involving cancers such as lung, colon, and melanoma. “We have demonstrated that these factors are applicable across diverse cancer types and patient groups, reinforcing their clinical importance. As research progresses, more unknown factors may emerge in other cancers or larger populations,” noted Dr. Joseph Usset, a former postdoctoral researcher at IRB Barcelona who currently works at the Vall d’Hebrón Institute of Oncology.
The research team aims to gather more patient data to enhance their models’ accuracy. The clinical applicability of these models will need to be validated through prospective clinical trials, although challenges remain in accessing comprehensive data like that utilized in this study.
“This research marks a vital advancement in understanding how various tumor characteristics impact treatment responses. We hope that these five factors will eventually be integrated into clinical settings to inform treatment decisions,” Dr. López-Bigas concluded.
This study was made possible through collaboration with the Vall d’Hebron Institute of Oncology (VHIO), the Hartwig Medical Foundation in Amsterdam, the Centro de Investigación Biomédica en Red en Cáncer (CIBERONC) from the Instituto de Salud Carlos III, the Center for Molecular Medicine at the University Medical Center of Utrecht, the Princess Margaret Cancer Centre at the University of Toronto, and Pompeu Fabra University in Barcelona.
Funding for this work was provided by the Excellence Programme of the Spanish Association Against Cancer (AECC), the European Research Council, the European Commission’s Horizon Program, the Ministry of Science and Technology, and the Government of Catalonia.
