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Meningiomas are, in most cases, low grade intracranial tumors. However, relapses are frequent. To date, only a few prognostic markers are described in the literature. Several studies have discussed the expression of progesterone, estrogen, androgen, and somatostatin receptors. The utility of analyzing these expressions for prognostic, theragnostic, and therapeutic purposes remains unclear. The aim of this study was to report the expression of these receptors, based on immunohistochemistry. Cochrane Collaboration guidelines and PRISMA statements were followed. We did an online search in PubMed using the MeSH database. References were selected if the investigations occurred from 1990 to 2022. 61 references were included (34 descriptive observational studies, 26 analytical observational studies, and one case report). In this review, we describe the expression of these receptors in function of age, sex, hormonal context, localization, histological subtype, grade, and recurrence.

The aim of this study was to evaluate the prognostic value of MCM6, in comparison with Ki-67, in two series of grade 1 and 2 meningiomas, and to evaluate its correlation with methylation classes. The first cohort included 100 benign (grade 1, World Health Organization 2021) meningiomas, and the second 69 atypical meningiomas (grade 2). Immunohistochemical Ki-67 and MCM6 labeling indices (LI) were evaluated independently by two observers. Among the atypical meningiomas, 33 cases were also studied by genome-wide DNA methylation. In grade 2 meningiomas, but not grade 1, both Ki-67 and MCM6 LIs were correlated with PFS ( p = 0.004 and p = 0.005, respectively; Cox univariate analyses). Additionally, MCM6 was correlated with overall survival only in univariate analysis. In a multivariate model, including mitotic index, Ki-67, MCM6, age, sex, and the quality of surgical resection, only MCM6 was correlated with PFS ( p = 0.046). Additionally, we found a significant correlation between PTEN loss and high MCM6 or Ki-67 LIs. Although no correlation was found with the methylation classes and subtypes returned by the meningioma algorithm MNGv2.4., MCM6 LI was significantly correlated with the methylation of 2 MCM6 gene body loci. In conclusion, MCM6 is a relevant prognostic marker in atypical meningiomas. This reproducible and easy-to-use marker allows the identification of a highly aggressive subtype of proliferative meningiomas, characterized notably by frequent PTEN losses, which was previously reported to be sensitive to histone deacetylase inhibitors.

Meningiomas are the most common primary tumors of the central nervous system. Based on the 2021 WHO classification, they are classified into three grades reflecting recurrence risk and aggressiveness. However, the WHO's histopathological criteria defining these grades are somewhat subjective. Together with reliable immunohistochemical proliferation indices, other molecular markers such as those studied with genome-wide epigenetics promise to revamp the current prognostic classification. In this study, 48 meningiomas of various grades were randomly included and explored for DNA methylation with the Infinium MethylationEPIC microarray over 850k CpG sites. We conducted differential and correlative analyses on grade and several proliferation indices and markers, such as mitotic index and Ki-67 or MCM6 immunohistochemistry. We also set up Cox proportional hazard models for extensive associations between CpG methylation and survival. We identified loci highly correlated with cell growth and a targeted methylation signature of regulatory regions persistently associated with proliferation, grade, and survival. Candidate genes under the control of these regions include SMC4 , ESRRG , PAX6 , DOK7 , VAV2 , OTX1 , and PCDHA - PCDHB - PCDHG , i.e., the protocadherin gene clusters. This study highlights the crucial role played by epigenetic mechanisms in shaping dysregulated cellular proliferation and provides potential biomarkers bearing prognostic and therapeutic value for the clinical management of meningioma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and deadliest cancer worldwide with an overall survival rate, all stages combined, of still <10% at 5 years. The poor prognosis is attributed to challenges in early detection, a low opportunity for radical resection, limited response to chemotherapy, radiotherapy, and resistance to immune therapy. Moreover, pancreatic tumoral cells are surrounded by an abundant desmoplastic stroma, which is responsible for creating a mechanical barrier, preventing appropriate vascularization and leading to poor immune cell infiltration. Accumulated evidence suggests that PDAC is impaired with multiple "immune defects", including a lack of high-quality effector cells (CD4, CD8 T cells, dendritic cells), barriers to effector cell infiltration due to that desmoplastic reaction, and a dominance of immune cells such as regulatory T cells, myeloid-derived suppressor cells, and M2 macrophages, resulting in an immunosuppressive tumor microenvironment (TME). Although recent studies have brought new insights into PDAC immune TME, its understanding remains not fully elucidated. Further studies are required for a better understanding of human PDAC immune TME, which might help to develop potent new therapeutic strategies by correcting these immune defects with the hope to unlock the resistance to (immune) therapy. In this review, we describe the main effector immune cells and immunosuppressive actors involved in human PDAC TME, as well as their implications as potential biomarkers and therapeutic targets.

DNA methylation profiling has recently emerged as a powerful tool to help establish diagnosis in neuro-oncology. Here we present our national diagnostic strategy as the French neuropathology network (RENOCLIP-LOC) and our current approach of integrating DNA methylation profiling into our multistep diagnostic process for challenging pediatric CNS tumors. The tumors with diagnostic uncertainty were prospectively selected for DNA methylation after two rounds of review by neuropathology experts. We first integrated the classifier score into the histopathological findings. Subsequent analyses using t-SNE (t-Distributed Stochastic Neighbor Embedding) representation were performed. An additional step consisted of analyzing copy-number variation data (CNV). Finally, we combined all data to establish diagnoses and evaluated the impact of DNA methylation profiling on diagnostic and grading changes that would affect patient management. Over two years, 62 pediatric tumors were profiled. (1) Integrating the classifier score to the histopathological findings impacted the diagnosis in 33 cases (53%). (2) t-SNE analysis provided arguments for diagnosis in 26/35 cases with calibrated scores <0.84 (74.3%). (3) CNV investigations also evidenced alterations used for diagnosis and prognostication. (4) A diagnosis was finally established for 44 tumors (71%). Our results support the use of DNA methylation for challenging pediatric tumors. We demonstrated how additional methylation-based analyses complement the classifier score to support conventional histopathological diagnosis.