RESUMO
Colorectal cancer (CRC) is a major cause of cancer-related deaths globally. While treatment advancements have improved survival rates, primarily through targeted therapies based on KRAS, NRAS, and BRAF mutations, personalized treatment strategies for CRC remain limited. Immunotherapy, mainly immune checkpoint blockade, has shown efficacy in various cancers but is effective in only a small subset of patients with CRC with deficient mismatch repair (dMMR) proteins or high microsatellite instability (MSI). Recent research has challenged the notion that CRC is immunologically inert, revealing subsets with high immunogenicity and diverse lymphocytic infiltration. Identifying precise biomarkers beyond dMMR and MSI is crucial to expanding immunotherapy benefits. Hence, exploration has extended to various biomarker sources, such as the tumor microenvironment, genomic markers, and gut microbiota. Recent studies have introduced a novel classification system, consensus molecular subtypes, that aids in identifying patients with CRC with an immunogenic profile. These findings underscore the necessity of moving beyond single biomarkers and toward a comprehensive understanding of the immunological landscape in CRC, facilitating the development of more effective, personalized therapies.
Assuntos
Neoplasias Colorretais , Imunoterapia , Humanos , Neoplasias Colorretais/imunologia , Neoplasias Colorretais/terapia , Neoplasias Colorretais/genética , Imunoterapia/métodos , Biomarcadores Tumorais/genética , Microambiente Tumoral/imunologia , Instabilidade de MicrossatélitesRESUMO
PURPOSE: Immunoscore can effectively predict prognosis in patients with colon cancer; however, its clinical application is limited. We modified the Immunoscore and created a tumor immune microenvironment (TIM) classification system for gastric carcinoma. Unlike previous studies that used small sample sizes or focused on particular immune-cell subtypes, our simplified system enables pathologists to classify gastric carcinomas intuitively using H&E-stained sections. METHODS: Samples from 326 patients with advanced gastric carcinoma were reviewed and analyzed by pathologists using simple determination and digital image analysis. Comprehensive results of cancer-panel sequencing, Epstein-Barrâvirus (EBV) status, and PD-L1, HER2, ATM, PTEN, MET, FGFR2, and EGFR immunohistochemistry were evaluated with respect to the TIM class. RESULTS: The TIM was classified as "hot" (n = 22), "immunosuppressed" (n = 178), "excluded" (n = 83), or "cold" (n = 43). TIM category was significantly associated with numbers of frameshift mutations (P < 0.001) and high tumor mutational burden (P < 0.004), and predicted overall survival. It was also significantly associated with age, histological type, degree of fibrosis, PD-L1 expression, loss of ATM and PTEN expression (P < 0.001), sex, EBV positivity, and HER2 overexpression (P < 0.04). "Hot" tumors were frequent in PD-L1 expressing and EBV-positive samples, and in those with ATM and PTEN loss. "Excluded" tumors were frequent in HER2-positive cases, whereas "cold" tumors were more frequent in younger patients with poorly cohesive histology and high fibrosis levels. CONCLUSIONS: TIM classification system for gastric carcinoma has prognostic significance and results in classes that are associated with molecular characteristics.
Assuntos
Mutação da Fase de Leitura , Neoplasias Gástricas/genética , Neoplasias Gástricas/imunologia , Microambiente Tumoral/genética , Microambiente Tumoral/imunologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Neoplasias Gástricas/patologiaRESUMO
The success of immunotherapies brings hope for the future of cancer treatment. Even so, we are faced with a new challenge, that of understanding which patients will respond initially and, possibly, develop resistance. The examination of the immune profile, especially approaches related to the immunoscore, may foretell which tumors will have a positive initial response. Ideally, the mutation load would also be analyzed, helping to reveal tumor associated antigens that are predictive of an effective cytolytic attack. However, the response may be hindered by changes induced in the tumor and its microenvironment during treatment, perhaps stemming from the therapy itself. To monitor such alterations, we suggest that minimally invasive approaches should be explored, such as the analysis of circulating tumor DNA. When testing new drugs, the data collected from each patient would initially represent an N of 1 clinical trial that could then be deposited in large databases and mined retrospectively for trends and correlations between genetic alterations and response to therapy. We expect that the investment in personalized approaches that couple molecular analysis during clinical trials will yield critical data that, in the future, may be used to predict the outcome of novel immunotherapies.