Study identifies five key factors that predict cancer patients’ response to immunotherapy

A team of researchers from the IRB in Barcelona has identified five independent factors that predict the response of cancer patients to checkpoint inhibitors (CPIs). The study, which was published in Genetics of naturevalidates these factors in more than 1,400 patients and different cancer types. These results provide a framework for interpreting biomarkers of response to CPIs and suggest a future path to improve personalized cancer medicine.

Immunotherapy has revolutionized cancer treatment in recent years by enabling the immune system to attack tumor cells. However, only 20 to 40% of patients respond positively to immunotherapy, and these rates vary across different types of cancer.

Predicting which patients will respond to immunotherapy and which will not is currently a very active area of ​​research. Many studies conducted so far have focused on specific characteristics of tumors, their microenvironment or the patient’s immune system. Therefore, it is still unclear which proposed biomarkers represent the same underlying factors or how many independent factors influence the effectiveness of this therapy.

Researchers from IRB Barcelona have identified five key and independent factors that determine the response and survival of patients after receiving checkpoint inhibitors (CPIs), a type of immunotherapy widely used in the treatment of cancer. These results provide a framework for current and future biomarkers of response to immunotherapy.

These findings could also pave the way for a significant advance in the personalization of cancer treatments, by making it possible to more accurately identify patients who are likely to benefit from immunotherapy. The findings suggest that patients with certain tumor types that are not currently considered candidates for immunotherapy (such as those with liver or kidney carcinomas) could benefit from this type of treatment.

The team led by doctors Núria López-Bigas and Abel González-Perez, from the Biomedical Genomics Laboratory of the IRB in Barcelona, ​​in collaboration with researchers from several international centers, addressed this question through a comprehensive analysis of genomic, transcriptomic and clinical data from 479 patients with metastatic tumors who received CPI treatment. These data come from a public database generated 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 the response to immunotherapy and patient survival,” explains Dr. López-Bigas, ICREA researcher at IRB Barcelona.

Five factors, five keys to immunotherapy

The five factors identified are tumor mutational burden; effective T cell infiltration; transforming growth factor beta (TGF-β) activity in the tumor microenvironment; previous treatment received by the patient; and tumor proliferative potential. These factors in different cancer types are associated with response to CPIs and were validated by the authors in six independent cohorts, covering a total of 1,491 patients.

• Tumor mutational burden (TMB): Tumors with a high number of mutations tend to produce more neoantigens, making them easier for the immune system to recognize and attack. TMB is one of the most studied biomarkers for predicting response to CPIs.

• Effective T-cell infiltration: The presence of cytotoxic T lymphocytes in the tumor is essential for the efficacy of IPCs. This study confirmed that greater infiltration of these cells is directly linked to a better response to therapy.

• TGF-β activity in the tumor microenvironment: This factor influences the behavior of certain cells in the tumor microenvironment. High TGF-β activity can inhibit the immune response, resulting in a tendency for patients to have poorer survival after immunotherapy treatment.

• Prior treatment: Patients who have received prior treatments tend to have a poorer response to immunotherapy.

• Tumor proliferative potential: Patients with tumors with a high proliferative index, which tend to be more aggressive, generally have poorer survival after treatment.

Towards personalized cancer treatment

These five factors provide a framework for organizing the vast current knowledge about biomarkers of response to immunotherapy.

“So far, many studies have focused on identifying and reporting individual biomarkers, but our results suggest that many of these biomarkers may be different versions of the same underlying factors,” says Dr. González-Pérez.

Furthermore, the researchers demonstrated that a multivariate model combining these five factors allows for a more accurate classification of patients than using tumor mutational burden alone (as is frequently done in clinical practice), thereby predicting the likelihood that patients will respond to immunotherapy.

This advance could have important clinical implications in the future, as it could prevent patients with a low probability of response from experiencing the side effects of CPIs, which can lead to autoimmune diseases, and could also help reduce the cost of treatments.

Validation in international cohorts

One of the strengths of this study is the validation of these five factors in six independent cohorts of patients with cancers such as lung, colon and melanoma.

“We have confirmed that these factors are relevant in different types of cancer and in different patient populations, reinforcing their clinical value. As research continues, new latent factors could be discovered in other types of cancer or in larger cohorts,” explains Dr. Joseph Usset, former postdoctoral fellow at IRB Barcelona, ​​now at the Vall d’Hebrón Institute of Oncology.

The team hopes to have more patient data in the future to create more accurate models. The accuracy of these models for possible future clinical application should be validated through prospective clinical trials. However, this progress faces a major challenge: the difficulty of accessing data as comprehensive and detailed as that used in this study.

“This study represents an important step in understanding how different tumor characteristics influence treatment response. In the future, we hope that these five factors will be integrated into clinical practice to guide treatment decisions,” concludes Dr. Lopez-Bigas.