We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

The somatic genomic landscape of glioblastoma

This review focuses on exosomes derived from various cancer cells. The review discusses the possibility of differentiating macrophages in alternatively activated anti-inflammatory pro-tumorigenic M2 macrophage phenotypes and classically activated pro-inflammatory, anti-tumorigenic M1 macrophage phenotypes in the tumor microenvironment (TME). The review is divided into two main parts, as follows: (1) role of exosomes in alternatively activating M2-like macrophages-breast cancer-derived exosomes, hepatocellular carcinoma (HCC) cell-derived exosomes, lung cancer-derived exosomes, prostate cancer-derived exosomes, Oral squamous cell carcinoma (OSCC)—derived exosomes, epithelial ovarian cancer (EOC)—derived exosomes, Glioblastoma (GBM) cell-derived exosomes, and colorectal cancer-derived exosomes, (2) role of exosomes in classically activating M1-like macrophages, oral squamous cell carcinoma-derived exosomes, breast cancer-derived exosomes, Pancreatic-cancer derived modified exosomes, and colorectal cancer-derived exosomes, and (3) exosomes and antibody-dependent cellular cytotoxicity (ADCC). This review addresses the following subjects: (1) crosstalk between cancer-derived exosomes and recipient macrophages, (2) the role of cancer-derived exosome payload(s) in modulating macrophage fate of differentiation, and (3) intracellular signaling mechanisms in macrophages regarding the exosome’s payload(s) upon its uptake and regulation of the TME. Under the electron microscope, nanoscale exosomes appear as specialized membranous vesicles that emerge from the endocytic cellular compartments. Exosomes harbor proteins, growth factors, cytokines, lipids, miRNA, mRNA, and DNAs. Exosomes are released by many cell types, including reticulocytes, dendritic cells, B-lymphocytes, platelets, mast cells, and tumor cells. It is becoming clear that exosomes can impinge upon signal transduction pathways, serve as a mediator of signaling crosstalk, thereby regulating cell-to-cell wireless communications. Based on the vesicular cargo, the molecular constituents, the exosomes have the potential to change the fate of macrophage phenotypes, either M1, classically activated macrophages, or M2, alternatively activated macrophages. In this review, we discuss and describe the ability of tumor-derived exosomes in the mechanism of macrophage activation and polarization.

Tumor-derived exosomes in the regulation of macrophage polarization

Glioblastoma (GBM) is an extremely aggressive tumor of the central nervous system, with a prognosis of 12–15 months and just 3–5% of survival over 5 years. This is mainly because most patients suffer recurrence after treatment that currently consists in maximal resection followed by radio- and chemotherapy with temozolomide. The recurrent tumor shows a more aggressive behavior due to a phenotypic shift toward the mesenchymal subtype. Proneural-mesenchymal transition (PMT) may represent for GBM the equivalent of epithelial–mesenchymal transition associated with other aggressive cancers. In this review we frame this process in the high degree of phenotypic inter- and intra-tumor heterogeneity of GBM, which exists in different subtypes, each one characterized by further phenotypic variability in its stem-cell compartment. Under the selective pressure of different treatment agents PMT is induced. The mechanisms involved, as well as the significance of such event in the acquisition of a multitherapy resistance phenotype, are taken in consideration for future perspectives in new anti-GBM therapeutic options.

https://www.mdpi.com/1422-0067/20/11/2746/pdf

Proneural-Mesenchymal Transition: Phenotypic Plasticity to Acquire Multitherapy Resistance in Glioblastoma

Gliomas are the most common central nervous system tumors. New technologies, including genetic research and advanced statistical methods, revolutionize the therapeutic approach to the patient and reveal new points of treatment options. Moreover, the 2021 World Health Organization Classification of Tumors of the Central Nervous System has fundamentally changed the classification of gliomas and incorporated many molecular biomarkers. Given the rapid progress in neuro-oncology, here we compile the latest research on prognostic and predictive biomarkers in gliomas. In adult patients, IDH mutations are positive prognostic markers and have the greatest prognostic significance. However, CDKN2A deletion, in IDH-mutant astrocytomas, is a marker of the highest malignancy grade. Moreover, the presence of TERT promoter mutations, EGFR alterations, or a combination of chromosome 7 gain and 10 loss upgrade IDH-wildtype astrocytoma to glioblastoma. In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome. MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. Finally, we discussed liquid biopsies, which are promising diagnostic, prognostic, and predictive techniques, but further work is needed to implement these novel technologies in clinical practice.

Prognostic and Predictive Biomarkers in Gliomas.

Synovial mesenchymal stem cells (SMSCs) have the potential to attenuate osteoarthritis (OA)-induced injury. The role and mechanism of SMSC-derived exosomes (SMSC-Exos), pivotal paracrine factors of stem cells, in OA-associated injury remain unclear. We aimed to confirm the effect of SMSC-Exos with specific modifications on OA-induced damage and to investigate the potential molecular mechanisms. Exosomes derived from miR-155-5p-overexpressing SMSCs (SMSC-155-5p-Exos) and SMSCs (SMSC-Exos) were isolated and characterized. CCK-8, Transwell, and Western blot analyses were used to detect proliferation, migration, extracellular matrix (ECM) secretion, and apoptosis of osteoarthritic chondrocytes. The therapeutic effect of exosomes in a mouse model of OA was examined using immunohistochemical staining and OARSI scores. SPSS 17.0 and GraphPad software were used for all statistical analyses in this study. The SMSC-Exos enhanced the proliferation and migration and inhibited the apoptosis of osteoarthritic chondrocytes but had no effect on ECM secretion. The miR-155-5p-overexpressing exosomes showed common characteristics of exosomes in vitro and further promoted ECM secretion by targeting Runx2. Thus, the SMSC-155-5p-Exos promoted proliferation and migration, suppressed apoptosis and enhanced ECM secretion of osteoarthritic chondrocytes, and effectively prevented OA in a mouse model. In addition, overexpression of Runx2 partially reversed the effect of the SMSC-155-5p-Exos on osteoarthritic chondrocytes. Given the insufficient effect of the SMSC-Exos on the ECM secretion of osteoarthritic chondrocytes, we modified the SMSM-Exos and demonstrated that the SMSC-155-5p-Exos could prevent OA. Exosomes derived from modified SMSCs may be a new treatment strategy to prevent OA. Graphical abstract.

Exosomes derived from miR-155-5p–overexpressing synovial mesenchymal stem cells prevent osteoarthritis via enhancing proliferation and migration, attenuating apoptosis, and modulating extracellular matrix secretion in chondrocytes

Lipid metabolism reprogramming plays important role in cell growth, proliferation, angiogenesis and invasion in cancers. However, the diverse lipid metabolism programmes and prognostic value during glioma progression remain unclear. Here, the lipid metabolism-related genes were profiled using RNA sequencing data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database. Gene ontology (GO) and gene set enrichment analysis (GSEA) found that glioblastoma (GBM) mainly exhibited enrichment of glycosphingolipid metabolic progress, whereas lower grade gliomas (LGGs) showed enrichment of phosphatidylinositol metabolic progress. According to the differential genes of lipid metabolism between LGG and GBM, we developed a nine-gene set using Cox proportional hazards model with elastic net penalty, and the CGGA cohort was used for validation data set. Survival analysis revealed that the obtained gene set could differentiate the outcome of low- and high-risk patients in both cohorts. Meanwhile, multivariate Cox regression analysis indicated that this signature was a significantly independent prognostic factor in diffuse gliomas. Gene ontology and GSEA showed that high-risk cases were associated with phenotypes of cell division and immune response. Collectively, our findings provided a new sight on lipid metabolism in diffuse gliomas.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jcmm.14647

Prognostic power of a lipid metabolism gene panel for diffuse gliomas

https://febs.onlinelibrary.wiley.com/doi/pdf/10.1002/1878-0261.12707

Classification of diffuse lower-grade glioma based on immunological profiling.

Isocitrate dehydrogenase (IDH) wild-type diffuse lower-grade glioma (LGG) is usually associated with poor outcome, but there have been disputes over its clinical outcome and classification. We present here a robust gene expression-based molecular classification of IDH wild-type diffuse LGG into two subtypes with distinct biological and clinical features. A discovery cohort of 49 IDH wild-type diffuse LGGs from the Chinese Glioma Genome Atlas (CGGA) was subjected to clustering and function analysis. Seventy-three tumors from The Cancer Genome Atlas (TCGA) were used to validate our findings. Consensus clustering of transcriptional data uncovered concordant classification of two robust and prognostically significant subtypes of IDH wild-type LGG. Subtype 1, associated with poorer outcomes, was characterized by significantly higher immune and cytolytic scores, M2 macrophages, and up-regulation of immune exhaustion markers, while Subtype 2, which had elevated lymphocytes and plasma cells, showed relatively favorable survival. Somatic alteration analysis revealed that Subtype 1 showed more frequently deleted regions, such as the locus of CDKN2A/CDKN2B, DMRTA1, C9orf53, and MTAP. Furthermore, we developed and validated a five-gene signature for better application of this acquired stratification. Our data demonstrate the biological and prognostic heterogeneity within IDH wild-type diffuse LGGs and deepen our molecular understandi-g of this tumor entity. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Molecular subtyping reveals immune alterations in IDH wild-type lower-grade diffuse glioma

Abstract Preoperative MRI is one of the most important clinical results for the diagnosis and treatment of glioma patients. The objective of this study was to construct a stable and validatable preoperative T2-weighted MRI-based radiomics model for predicting the survival of gliomas. A total of 652 glioma patients across three independent cohorts were covered in this study including their preoperative T2-weighted MRI images, RNA-seq and clinical data. Radiomic features (1731) were extracted from preoperative T2-weighted MRI images of 167 gliomas (discovery cohort) collected from Beijing Tiantan Hospital and then used to develop a radiomics prediction model through a machine learning-based method. The performance of the radiomics prediction model was validated in two independent cohorts including 261 gliomas from the The Cancer Genomae Atlas database (external validation cohort) and 224 gliomas collected in the prospective study from Beijing Tiantan Hospital (prospective validation cohort). RNA-seq data of gliomas from discovery and external validation cohorts were applied to establish the relationship between biological function and the key radiomics features, which were further validated by single-cell sequencing and immunohistochemical staining. The 14 radiomic features-based prediction model was constructed from preoperative T2-weighted MRI images in the discovery cohort, and showed highly robust predictive power for overall survival of gliomas in external and prospective validation cohorts. The radiomic features in the prediction model were associated with immune response, especially tumour macrophage infiltration. The preoperative T2-weighted MRI radiomics prediction model can stably predict the survival of glioma patients and assist in preoperatively assessing the extent of macrophage infiltration in glioma tumours.

/pdf/an-mri-radiomics-approach-to-predict-survival-and-tumour-115y58v8.pdf

An MRI radiomics approach to predict survival and tumour-infiltrating macrophages in gliomas

Increasing evidence has shown that long non-coding RNAs (lncRNAs) are important prognostic biomarkers and epigenetic regulators with critical roles in cancer initiation and progression. However, the expression and clinical prognostic value of antisense lncRNAs in diffuse glioma patients remain unknown. Here, we profiled differentially expressed antisense lncRNAs in glioma using RNA sequencing data from Chinese Glioma Genome Atlas database. Cox regression was performed to evaluate the prognostic value. Gene oncology (GO) and gene set enrichment analysis (GSEA) were used for functional analysis of antisense LncRNAs. Expression profiling identified 169 aberrantly expressed antisense lncRNAs between lower grade glioma (LGG) (grade II and III) and glioblastoma multiforme (GBM), 113 antisense lncRNAs between LGG IDH-wt and IDH-mut samples, and 70 antisense lncRNAs between GBM IDH-wt and IDH-mut samples, respectively. Among them, three antisense lncRNAs (WDFY3-AS2, MCM3AP-AS1 and LBX2-AS1) were significantly associated with prognosis and malignant progression of patients. WDFY3-AS2, the top one of downregulated antisense lncRNAs in GBM with fold change of 0.441 (P < 0.001), showed specific decreased expression in classical, mesenchymal, LGG IDH-wt, GBM IDH-wt or MGMT promoter unmethylated stratified patients. Chi square test found that WDFY3-AS2 was significantly associated with the clinical and molecular features of glioma. Univariate and multivariate Cox regression analysis indicated that WDFY3-AS2 was independently correlated with overall survival (OS) of patients. Kaplan–Meier analysis found that patients with high WDFY3-AS2 expression had longer OS than the low expression ones in the stratified cohorts. Additionally, GO and GSEA showed that gene sets correlated with WDFY3-AS2 expression were involved in regulation of synaptic transmission, glutamate receptor and TNF signaling pathway. Our findings provided convincing evidence that WDFY3-AS2 is a novel valuable prognostic biomarker for diffuse glioma.

/pdf/expression-profile-analysis-of-antisense-long-non-coding-rna-16get4m39l.pdf

Haoyu Jiang

Papers

Prognostic power of a lipid metabolism gene panel for diffuse gliomas

Classification of diffuse lower-grade glioma based on immunological profiling.

Molecular subtyping reveals immune alterations in IDH wild-type lower-grade diffuse glioma

An MRI radiomics approach to predict survival and tumour-infiltrating macrophages in gliomas

Expression profile analysis of antisense long non-coding RNA identifies WDFY3-AS2 as a prognostic biomarker in diffuse glioma