Victoria Menéndez , José L. Solórzano , Mónica García-Cosío , Laura Cereceda , Eva Díaz , Mónica Estévez , Giovanna Roncador , Zaira Vega , Carlos Montalbán , Arutha Kulasinghe , Juan F. García
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引用次数: 0
Abstract
As around 25% to 30% of classical Hodgkin lymphoma (cHL) patients with advanced stages do not respond to standard therapies, the tumor microenvironment of cHL is one avenue that may be explored with the aim of improving risk stratification. CD4+ T cells are thought to be one of the main cell types in the tumor microenvironment. However, few immune signatures have been studied, and many of these lack related spatial data. Thus, our aim is to spatially resolve the CD4+ T cell subtypes that influence cHL outcome, depicting new immune signatures or transcriptional patterns that are in crosstalk with the tumor cells. This study was conducted using the NanoString GeoMx digital spatial profiling technology, based on the selection of distinct functional areas of patients’ tissues followed by gene-expression profiling. The goals were to assess the differences in CD4+ T cell populations between tumor-rich and immune-predominant areas defined by different CD30 and PD-L1 expression levels and seek correlations with clinical metadata. Our results depict a complex map of CD4+ T cells with different functions and differentiation states that are enriched at distinct locations, the flux of cytokines and chemokines that could be related to these, and the specific relationships with the clinical outcome.
期刊介绍:
Modern Pathology, an international journal under the ownership of The United States & Canadian Academy of Pathology (USCAP), serves as an authoritative platform for publishing top-tier clinical and translational research studies in pathology.
Original manuscripts are the primary focus of Modern Pathology, complemented by impactful editorials, reviews, and practice guidelines covering all facets of precision diagnostics in human pathology. The journal's scope includes advancements in molecular diagnostics and genomic classifications of diseases, breakthroughs in immune-oncology, computational science, applied bioinformatics, and digital pathology.