Advances in the classification of round cell sarcomas

Round cell sarcomas represent a diagnostic challenge for pathologists, owing to the poorly differentiated features of these high-grade tumours. The diagnosis of round cell sarcoma requires large immunohistochemical panels and molecular testing in many cases. This spectrum of malignancies is largely dominated by Ewing sarcomas (ESs), which represent the most common family of these tumours. Nonetheless, new families have been delineated in the past few years, with the addition of two additional families in the 2020 World Health Organization classification of bone and soft tissue tumours, namely sarcomas with CIC rearrangements and sarcomas with BCOR alterations. EWSR1, one of the genes involved in the driver fusion of ESs, is also implicated in the translocation of many other tumours with heterogeneous lineages and variable levels of aggressiveness. Round cell sarcomas associated with fusions inwhichEWSR1is partnered with genes encoding transcription factors distinct from those of the 'Ewing family' represent a heterogeneous group of rare tumours that require further study to determine whether their fusions may or not define a specific subgroup. They include mainly sarcomas with NFATc2 rearrangements and sarcomas with PATZ1 rearrangements. At this point, PATZ1 fusions seem to be associated with tumours of high clinical and morphological heterogeneity. Molecular studies have also helped in the identification of more consistent biomarkers that give tremendous help to pathologists in triaging, if not diagnosing, these tumours in practice. This review compiles the latest accumulated evidence regarding round cell sarcomas, and discusses the areas that are still under investigation.

Mutational profiling of low-grade gliomas identifies prognosis and immunotherapy-related biomarkers and tumour immune microenvironment characteristics

Low-grade glioma (LGG) is a heterogeneous tumour with the median survival rate less than 10 years. Therefore, it is urgent to develop efficient immunotherapy strategies of LGG. In this study, we analysed mutation profiles based on the data of 510 LGG patients from the Cancer Genome Atlas (TCGA) database and investigated the prognostic value of mutated genes and evaluate their immune infiltration. Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to indicate the characteristics of gliomas that respond to immune checkpoint blockade (ICB) therapy. Univariate and multivariate cox regression analysis was performed to identify indicators to construct the nomogram model. 485 (95.47%) of 508 LGG samples showed gene mutation, and 9 mutated genes were significantly related to overall survival (OS), among which 6 mutated genes were significantly correlated with OS between mutation and wildtypes. Immune infiltration and immune score analyses revealed that these six mutated genes were significantly associated with tumour immune microenvironment in LGG. The response of LGG with different characteristics to ICB was evaluated by TIDE algorithm. Finally, CIC gene was screened through both univariate and multivariate Cox regression analyses, and the nomogram model was established to determine the potential prognostic value of CIC in LGG. Our study provides comprehensive analysis of mutated genes in LGG, supporting modulation of mutated genes in the management of LGG.