Researchers Identify Five Tumor Mutation Patterns Impacting Immunotherapy

A recent study from the HUN-REN Szeged Biological Research Centre and HCEMM reveals that specific mutation patterns in tumors can significantly affect how visible they are to the immune system. The research suggests that rather than simply focusing on the quantity of mutations, understanding the type of mutations present is crucial for the effectiveness of immunotherapy. The findings have been published in the journal Molecular Systems Biology.

Five Distinct Mutation Patterns Identified

Cancer cells typically possess thousands of mutations, but not every mutation impacts the immune response in the same way. Researchers have identified five dominant patterns of protein-altering mutations, known as amino acid substitution signatures, that play a vital role in determining how tumors interact with the immune system.

The team analyzed nearly 9,300 cancer genomes across various cancer types. They discovered that, instead of random mutations, tumors tend to exhibit one of these five characteristic substitution signatures. This insight indicates that the type of mutations present can significantly influence how well the immune system recognizes and responds to the tumor.

The Role of Mutation Patterns in Immune Recognition

Crucially, these five mutation signatures not only serve as molecular fingerprints of tumor development but also affect the immune system’s ability to detect tumors. Some patterns produce highly immunogenic protein fragments, known as neoantigens, which alert immune cells, while others create less detectable neoantigens, resulting in “cold” tumors that can evade immune attacks.

Dr. Szilvia Juhász, head of the Cancer Microbiome Research Group at HCEMM and a lead author of the study, noted, “Despite the diversity of mutational processes, their protein-level consequences converge into just five recurring fingerprints, which can strongly influence immune recognition.”

Another significant finding from the study highlights a mutation signature associated with DNA repair defects and environmental chemical exposures. Tumors characterized by this pattern often demonstrate poor responses to immune checkpoint inhibitor therapies, even when the overall mutation burden is high. Dr. Benjamin Papp, a researcher at the HUN-REN Szeged Biological Research Centre and co-first author, stated, “Mutational burden alone is insufficient. Qualitative, protein-level consequences of mutations are critical for understanding why immunotherapy fails in many patients.”

The study also indicates that certain genetic variants in the human immune system, particularly specific HLA class I types common in Europeans, can enhance the presentation of these mutated peptides to T cells. This suggests that a tumor’s visibility to the immune system may vary among patients, depending on their genetic background.

Implications for Personalized Immunotherapy

These findings pave the way for a more sophisticated understanding of immunotherapy responses. Dr. Máté Manczinger, head of the Systems Immunology Research Group at the HUN-REN Szeged Biological Research Centre and senior author of the study, emphasized the importance of these results, stating, “Tumor visibility to the immune system is not determined by mutation numbers alone, but also by the protein-level patterns those mutations create.”

The implications of this research extend beyond scientific understanding. More accurate predictions of therapy responses could lead to reduced unnecessary treatments, fewer side effects, and a more efficient identification of effective therapies tailored to individual patients.

This study was conducted through a collaborative effort between the Systems Immunology Research Group at the HUN-REN Szeged Biological Research Centre, the HCEMM Cancer Microbiome Research Group, and contributions from the Evolutionary Systems Biology Research Group led by Csaba Pál. The research represents a significant step forward in the quest for personalized cancer treatment, integrating tumor genomics with the patient’s immunogenetic background.