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A recent study has shed light on the complex dynamics influencing the efficacy of immunotherapy in patients suffering from advanced bladder cancer. Conducted by the Biomedical Informatics Research Programme (GRIB) and the Cancer Programme at the Hospital del Mar Research Institute, in collaboration with Pompeu Fabra University, this research seeks to address the puzzling reality that only 20% of advanced bladder cancer cases show a positive response to immunotherapeutic interventions. This investigation, published in Nature Communications, was spearheaded by a team including Mar Albà , Júlia Perera, and Joaquim Bellmunt, with contributions from Robert Castelo of the Department of Medicine and Life Sciences at UPF. By analyzing extensive datasets from over 700 individuals through six distinct cohorts, the researchers aimed to pinpoint characteristics that differentiate those who benefit from the treatment from those who do not.
Findings suggest that among five identified tumor subtypes in advanced bladder cancer, the neuronal subtype demonstrates the most favorable response to immunotherapy. In contrast, the remaining subtypes show lower response rates. According to Lilian Marie Boll, a researcher at GRIB, “We discovered that, for a certain group of patients, existing markers reliably predict the response to treatment. For others, however, the determinants of response appear to be influenced by additional biological factors that warrant further exploration.”
Key Types of Markers
The research team engineered a machine-learning algorithm to enhance prediction accuracy regarding treatment responses across different tumor subtypes. The most effective markers identified for predicting treatment outcomes include tumor mutational burden—indicative of the mutations present within the tumor—mutations associated with APOBEC enzymes that contribute to tumor diversity, and the prevalence of pro-inflammatory macrophages. Furthermore, the study uncovered markers within the tumor microenvironment that may limit the effectiveness of treatments. Notably, the robust sample size facilitated the detection of infrequent mutations that could present novel protein fragments to the immune system.
Dr. Júlia Perera Bel emphasized that while immune cell infiltration plays a significant role in treatment response, it is not the sole predictor nor does it apply uniformly across all patients. The team found that categorizing patients based on the presence or absence of immune infiltration enhanced the precision of their predictive algorithm, enabling the identification of distinct markers relevant to each group. “Our key insight is in deciphering the response mechanisms within these patient subgroups, rather than treating all advanced bladder cancer cases as the same,” remarked Boll.
According to Dr. Joaquim Bellmunt, who leads the Urologic Cancer Research Group at the Hospital del Mar Research Institute and the Dana-Farber Cancer Institute, this research broadens our understanding of tumor heterogeneity—a crucial limitation in the effectiveness of immunotherapy. He noted the importance of recognizing immune cell populations that either support or inhibit treatment responses.
The study’s outcomes emphasize the intricate interplay between tumor biology and the surrounding immunological environment, which crucially influences treatment responses. Furthermore, it advocates for the consideration of specific tumor subtypes when selecting treatment strategies. The research team asserts that assembling large datasets is crucial for developing predictive computational models that integrate diverse data sets to accurately distinguish among patient subgroups, paving the way for advancements in precision medicine.
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