Five key factors predict response to immunotherapy in cancer patients

by Laura Richards – Editor-in-Chief

In recent years, immunotherapy has revolutionized cancer treatment by relying on the immune system itself to attack tumor cells.​ However, immunotherapy is only able to do its job in⁢ 20 to 40 percent of patients, ‍and these percentages vary between different types of cancer.

Predicting which patients​ immunotherapy will work well in and which patients it won’t is currently a ⁤very active area of ​​research. The numerous studies carried out to date​ have focused on some specific characteristics of tumors, their microenvironment or‌ the patient’s immune system. Consequently, ⁢it‍ is unclear which of‌ the biomarkers proposed so far represent the same‌ factors, and how many independent factors influence the ​effectiveness of ​this type of therapy.

Researchers at the Institute for Biomedical Research in‌ Barcelona (IRB Barcelona) have revealed five key factors that are totally independent of each other and determine how patients respond to⁣ immune checkpoint inhibitors (CPIs), a type of immunotherapy widely used in cancer treatment.⁣ These results constitute a​ framework for ⁤the biomarkers of response to immunotherapy identified so far and for those that will be identified from now on. In the future, they could also represent a significant ‌advance in personalizing cancer treatments, helping to ‌more precisely identify which‌ patients will respond favorably to immunotherapy. The findings suggest that patients with certain tumor types who are not currently considered candidates for immunotherapy treatment (for example, ⁣with liver or kidney cancers) may benefit from this type of therapy.

The international team led ⁢by Dr. Núria López-Bigas and Dr. Abel González-Perez, from the Biomedical Genomics group of IRB ‍Barcelona, ​​in collaboration with researchers from different centers, addressed this question​ through‌ an exhaustive analysis of genomic data, transcriptomic data and clinical data from 479 patients with metastatic tumors​ treated with CPI. This data comes from a public⁢ database of the Hartwig Medical Foundation in the Netherlands.

“We used an unbiased ⁢approach to analyze thousands of ‍molecular and clinical characteristics and identified five independent factors that influence immunotherapy response and patient survival,” explains Dr. López-Bigas, ICREA researcher ‍at IRB ⁤Barcelona .

Five factors, five ⁢keys⁢ to immunotherapy

The five‌ factors ⁣identified are: the mutational load of the ​tumor, the effective⁢ infiltration of T cells, the activity of transforming growth factor beta (TGF-beta) ⁢in the tumor microenvironment, the previous treatment received by the patient and​ the proliferative potential of the tumor . tumor. These factors are associated with response to CPIs in several cancer types ⁣and have been validated in six independent cohorts, totaling ⁣1,491 patients.

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

Effective T-cell infiltration: The presence of cytotoxic ‍T cells in the tumor is ⁣essential for CPIs‍ to be effective. This study confirmed that a greater infiltration of‍ these cells is directly related to⁤ a better response to therapy.

Activity of TGF-beta in‌ the tumor microenvironment:⁣ this factor influences the behavior of some cells in the tumor microenvironment. High TGF-beta activity can ⁢suppress the immune‍ response, which is reflected in a tendency for patients to have worse survival after treatment with⁣ immunotherapy.

Previous treatment: Patients who have received previous⁣ treatments have ‍a tendency to⁤ respond worse to immunotherapy.

Proliferative potential of the tumor: Patients with​ tumors with a high proliferative index, which tend to be more aggressive, tend to have worse survival after treatment.

Towards personalized medicine in oncology

These five factors provide ⁢a framework for organizing the vast current ‍knowledge on biomarkers of response to immunotherapy. “Until ‌now, many⁤ studies have focused on identifying single biomarkers, ⁣but our findings ​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 patients to be classified more accurately than tumor mutational‍ burden alone (which is currently used in clinical practice), predicting who will respond best​ to immunotherapy. This‌ advance could have important clinical implications in the future, as it could prevent patients ‌with a low likelihood of responding from ⁤suffering the side effects of PCIs, which can lead to autoimmune diseases.

Artistic recreation of tumor cells. (Image: Amazings/NCYT)

Validation in international⁣ cohorts

One of the highlights 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 confirmed that ⁤these factors​ are relevant across ⁤different cancer types and patient populations, which strengthens their clinical value. As research continues, it is possible that⁢ new latent factors may be discovered in other cancer types or ‌cohorts broader,” explains Dr. Joseph Usset, formerly a postdoctoral researcher at the IRB in Barcelona and now at the Vall d’Hebron Institute of Oncology in Barcelona.

In the future, the team hopes to have ⁣a larger volume of patient data to generate more accurate models. The accuracy ‍of these models for possible future application ⁢in clinical ‌practice ⁢should⁣ be validated through ‌prospective clinical studies. However, this progress faces a significant challenge: the difficulty of accessing data as complete and comprehensive as that used in this study.

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

The study was possible thanks to the collaboration of the⁣ Vall ‍d’Hebron Institute of Oncology (VHIO), the⁤ Pompeu Fabra University of Barcelona, ​​​​the Cancer ​Network Biomedical Research Center (CIBERONC), in Spain, as well as the Hartwig Medical Foundation in Amsterdam, the Center​ for ⁣Molecular Medicine at the University Medical Center in​ Utrecht (the Netherlands)‍ and the⁤ Princess Margaret Cancer Center ‍at the University ⁢of Toronto in Canada.

The study is titled “Five latent ‌factors underlying response to immunotherapy.” And it was published in the academic journal Nature Genetics. (Source: IRB Barcelona)

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How can personalized approaches in immunotherapy improve⁣ patient outcomes in oncology?

Interview between Time.news Editor and Dr. Núria López-Bigas on Advances in Immunotherapy

Editor: Welcome, Dr. López-Bigas! It’s a pleasure to have you on Time.news. Your recent research at IRB Barcelona on immunotherapy and its efficacy is fascinating. To start, can you explain what immunotherapy is and its​ importance in cancer treatment?

Dr. López-Bigas: Thank you for​ having ⁢me! Immunotherapy harnesses the body’s own immune system to target and attack cancer cells. Unlike traditional⁢ therapies like chemotherapy and ‌radiation, which indiscriminately affect both cancerous and healthy cells, immunotherapy aims to enhance ​the immune response ⁣specifically against tumors. It represents a⁤ significant shift in cancer ⁤treatment, but currently only 20 to 40 percent of patients respond effectively, which highlights the need for personalized approaches.

Editor: Those response rates certainly call‍ for a deeper understanding of what characterizes a successful treatment. Your research identified five key factors that influence the response to immune ⁤checkpoint inhibitors (CPIs). Could you elaborate on these factors?

Dr. López-Bigas: Absolutely! ⁣We‌ identified five independent factors: tumor mutational burden, effective ⁢T-cell infiltration, TGF-beta activity in the tumor microenvironment, previous treatments, and the proliferative potential of the tumor.

  1. Tumor Mutational Burden (TMB): Tumors with a high number of mutations are more likely to produce neoantigens, which can make it easier for the immune system to recognize and target them.
  1. Effective T-cell Infiltration: The presence of cytotoxic T cells in the tumor is crucial. Greater infiltration correlates with a better response to CPIs.
  1. TGF-beta Activity: This factor can ​suppress immune responses within the tumor microenvironment. High TGF-beta activity may lead to poorer outcomes.
  1. Previous Treatment: Patients who have undergone ​prior treatments often exhibit lower responsiveness to immunotherapy.
  1. Proliferative Potential: Tumors that grow aggressively (indicated by a high proliferative index) ⁣tend to be associated with worse survival rates after treatment.

Editor: These insights truly‍ provide a more nuanced understanding of ​patient responses. With these five ‍factors established from your analysis, how do they ​inform ⁣future clinical practices‌ in oncology?

Dr. López-Bigas: Our findings can ‍significantly⁤ enhance the personalization‌ of cancer treatments. Currently, TMB​ is one of⁢ the primary biomarkers used, but our multivariate model, ⁣which combines all five​ factors, can more accurately predict which patients are likely to benefit from CPIs. This could ⁤prevent ‍unnecessary side effects in patients unlikely to ⁣respond, ultimately improving treatment outcomes and quality‍ of life.

Editor: That sounds promising! You mentioned that your research was validated across⁣ six independent cohorts. Can you tell us more about this validation and its implications?

Dr. López-Bigas: ⁢ Yes, we validated our​ findings⁤ in ⁤cohorts totalling 1,491 patients with various cancers, including lung, colon, and melanoma. This cross-cancer validation strengthens the clinical relevance of ​these factors, suggesting they could⁤ be applicable⁤ across a broad range of tumor ⁤types. As research progresses, we anticipate identifying additional ​factors that could enhance our understanding and treatment of other malignancies.

Editor: This research could be a game changer in oncology. Do you think there is potential for new biomarkers ‌to be discovered that might further influence immunotherapy effectiveness?

Dr. López-Bigas: Absolutely. The field is evolving, and as we gather⁣ more data and advance ​our methodologies, there​ is ⁣significant potential for discovering new biomarkers.⁤ Each finding contributes⁤ to a‍ more detailed map of how individual tumor characteristics interact with the immune system, ultimately leading us closer to truly personalized cancer therapies.

Editor: Thank you, Dr.‍ López-Bigas, for sharing your insights and the exciting potential that lies ahead in ⁤the realm of ⁣cancer immunotherapy.

Dr. López-Bigas: It was a pleasure to⁤ share our work! Thank you for ⁢shedding ⁢light on this important topic.

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