Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups

Identification of new targets for glioblastoma therapy based on a DNA expression microarray

This study provides a comprehensive perspective on the deregulated pathways and impaired biological functions prevalent in human glioblastoma (GBM). In order to characterize differences in gene expression between individuals diagnosed with GBM and healthy brain tissue, we have designed and manufactured a specific, custom DNA microarray. The results obtained from differential gene expression analysis were validated by RT-qPCR. The datasets obtained from the analysis of common differential expressed genes in our cohort of patients were used to generate protein-protein interaction networks of functionally enriched genes and their biological functions. This network analysis, let us to identify 16 genes that exhibited either up-regulation (CDK4, MYC, FOXM1, FN1, E2F7, HDAC1, TNC, LAMC1, EIF4EBP1 and ITGB3) or down-regulation (PRKACB, MEF2C, CAMK2B, MAPK3, MAP2K1 and PENK) in all GBM patients. Further investigation of these genes and enriched pathways uncovered in this investigation promises to serve as a foundational step in advancing our comprehension of the molecular mechanisms underpinning GBM pathogenesis. Consequently, the present work emphasizes the critical role that the unveiled molecular pathways likely play in shaping innovative therapeutic approaches for GBM management. We finally proposed in this study a list of compounds that target hub of GBM-related genes, some of which are already in clinical use, underscoring the potential of those genes as targets for GBM treatment.

Genomic Alterations in Molecularly Defined Oligodendrogliomas

BACKGROUND AND OBJECTIVES

Oligodendrogliomas are defined by IDH1/2 mutation and codeletion of chromosome arms 1p/19q. Although previous studies identified CIC, FUBP1, and TERTp as frequently altered in oligodendrogliomas, the clinical relevance of these molecular signatures is unclear. Moreover, previous studies predominantly used research panels that are not readily available to providers and patients. Accordingly, we explore genomic alterations in molecularly defined oligodendrogliomas using clinically standardized next-generation sequencing (NGS) panels.

METHODS

A retrospective single-center study evaluated adults with pathologically confirmed IDH-mutant, 1p/19q-codeleted oligodendrogliomas diagnosed between 2005 and 2021. Genetic data from formalin-fixed, paraffin-embedded specimens were analyzed with the NGS Solid Tumor Panel at the Johns Hopkins Medical Laboratories, which tests more than 400 cancer-related genes. Kaplan-Meier plots and log-rank tests compared progression-free survival (PFS) and overall survival by variant status. χ2 tests, t-tests, and Wilcoxon rank-sum tests were used to compare clinical characteristics between genomic variant status in the 10 most frequently altered genes.

RESULTS

Two hundred and seventy-seven patients with molecularly defined oligodendrogliomas were identified, of which 95 patients had available NGS reports. Ten genes had 9 or more patients with a genomic alteration, with CIC, FUBP1, and TERTp being the most frequently altered genes (n = 60, 23, and 22, respectively). Kaplan-Meier curves showed that most genes were not associated with differences in PFS or overall survival. At earlier time points (PFS <100 months), CIC alterations conferred a reduction in PFS in patients (P = .038).

CONCLUSION

Our study confirms the elevated frequency of CIC, FUBP1, and TERTp alterations in molecularly defined oligodendrogliomas and suggests a potential relationship of CIC alteration to PFS at earlier time points. Understanding these genomic variants may inform prognosis or therapeutic recommendations as NGS becomes routine.

Epigenome-wide DNA methylation analysis of whole blood cells derived from patients with GAD and OCD in the Chinese Han population

Generalized anxiety disorder (GAD) and obsessive-compulsive disorder (OCD) had high comorbidity and affected more than 44 million people around the world leading to a huge burden on health and economy. Here, we conducted an epigenome-wide DNA methylation study employing 93 patients with GAD, 65 patients with OCD, and 302 health controls, to explore epigenetic alterations associated with the onset and differences of GAD and OCD. We identified multiple differentially methylated positions (DMPs) and regions (DMRs): three DMP genes included RIOK3 (cg21515243, p = 8.00 × 10^-10), DNASE2 (cg09379601, p = 1.10 × 10^-9), and PSMB4 (cg01334186, p = 3.70 × 10^-7) and two DMR genes USP6NL (p = 4.50 × 10^-4) and CPLX1 (p = 6.95 × 10^-4) were associated with the onset of GAD and OCD; three DMPs genes included LDLRAP1 (cg21400344, p = 4.40 × 10^-12), ACIN1 (cg23712970, p = 2.98×10^-11), and SCRT1 (cg25472897, p = 5.60 × 10^-11) and three DMR genes WDR19 (p = 3.39 × 10^-3), SYCP1 (p = 6.41 × 10^-3), and FAM172A (p = 5.74 × 10^-3) were associated with the differences between GAD and OCD. Investigation of epigenetic age and chronological age revealed a different epigenetic development trajectory of GAD and OCD. Conclusively, our findings which yielded robust models may aid in distinguishing patients from healthy controls (AUC = 0.90-0.99) or classifying patients with GAD and OCD (AUC = 0.89-0.99), and may power the precision medicine for them.

Computational gene expression analysis reveals distinct molecular subgroups of T-cell prolymphocytic leukemia

T-cell prolymphocytic leukemia (T-PLL) is a rare blood cancer with poor prognosis. Overexpression of the proto-oncogene TCL1A and missense mutations of the tumor suppressor ATM are putative main drivers of T-PLL development, but so far only little is known about the existence of T-PLL gene expression subtypes. We performed an in-depth computational reanalysis of 68 gene expression profiles of one of the largest currently existing T-PLL patient cohorts. Hierarchical clustering combined with bootstrapping revealed three robust T-PLL gene expression subgroups. Additional comparative analyses revealed similarities and differences of these subgroups at the level of individual genes, signaling and metabolic pathways, and associated gene regulatory networks. Differences were mainly reflected at the transcriptomic level, whereas gene copy number profiles of the three subgroups were much more similar to each other, except for few characteristic differences like duplications of parts of the chromosomes 7, 8, 14, and 22. At the network level, most of the 41 predicted potential major regulators showed subgroup-specific expression levels that differed at least in comparison to one other subgroup. Functional annotations suggest that these regulators contribute to differences between the subgroups by altering processes like immune responses, angiogenesis, cellular respiration, cell proliferation, apoptosis, or migration. Most of these regulators are known from other cancers and several of them have been reported in relation to leukemia (e.g. AHSP, CXCL8, CXCR2, ELANE, FFAR2, G0S2, GIMAP2, IL1RN, LCN2, MBTD1, PPP1R15A). The existence of the three revealed T-PLL subgroups was further validated by a classification of T-PLL patients from two other smaller cohorts. Overall, our study contributes to an improved stratification of T-PLL and the observed subgroup-specific molecular characteristics could help to develop urgently needed targeted treatment strategies.

m6A Regulatory Gene-Mediated Methylation Modification in Glioma Survival Prediction

The median survival of patients with gliomas is relatively short. To investigate the epigenetic mechanisms associated with poor survival, we analyzed publicly available datasets from patients with glioma. This analysis revealed 12 prognosis-related m6A regulatory genes that may be responsible for poor prognosis. These genes may be involved in genomic changes inherent to oxidative phosphorylation, adipogenesis, hedgehog signaling, and Myc signaling. We reconstructed a risk model with univariate and multivariate Cox analyses and identified older age and the m6A risk score as independent risk factors for predicting the prognosis of glioma patients, which is associated with glioma immune infiltration. In conclusion, m6A regulatory genes may serve as both reliable biomarkers and potential targets to increase the chance of survival of patients with glioma.

Bioinformatics analysis of an animal model of diet-induced nonalcoholic fatty liver disease with rapid progression

Nonalcoholic fatty liver disease (NAFLD) develops rapidly in high-fat diet (HFD) fed Mongolian gerbil (Meriones unguiculatus). Here, we aim to explore the gene expression characteristics of Mongolian gerbil to better understand the underlying mechanism in this animal model. Mongolian gerbils were fed with normal diet or HFD for different periods. High-throughput sequencing was carried out on the hepatic mRNA and bioinformatics analysis was further performed. Eight hub genes Cd44, App, Cdc42, Cd68, Cxcr4, Csf1r, Adgre1, and Fermt3, which were involved in inflammation, fibrosis, and HCC were obtained. Four significant independent poor prognostic factors for HCC (GPC1, ARPC1B, DAB2, and CFL1) were screened out. qRT-PCR result showed that the above genes expressed high levels in different periods of modeling process. The findings of this study provide useful information for further studies on Mongolian gerbil NAFLD model.

Single-Cell Proteomic Analysis Dissects the Complexity of Tumor Microenvironment in Muscle Invasive Bladder Cancer

Simple Summary

The tumor microenvironment (TME) is considered to play a key role in the development of many types of tumors. Muscle invasive bladder cancer (MIBC), which is well known for its heterogeneity, has a highly complex TME. Herein, we integrated mass cytometry and imaging mass cytometry to systematically investigate the complexity of the MIBC TME. Our investigation revealed tumor and immune cells with diverse phenotypes. We identified a specific cancer stem-like cell cluster (ALDH⁺PD-L1⁺ER-β⁻), which is associated with poor prognosis and highlighted the importance of the spatial distribution patterns of MIBC TME components. The present study comprehensively elucidated the complexity of the MIBC TME and provides potentially valuable information for future research.

Abstract

Muscle invasive bladder cancer (MIBC) is a malignancy with considerable heterogeneity. The MIBC tumor microenvironment (TME) is highly complex, comprising diverse phenotypes and spatial architectures. The complexity of the MIBC TME must be characterized to provide potential targets for precision therapy. Herein, an integrated combination of mass cytometry and imaging mass cytometry was used to analyze tumor cells, immune cells, and TME spatial characteristics of 44 MIBC patients. We detected tumor and immune cell clusters with abnormal phenotypes. In particular, we identified a previously overlooked cancer stem-like cell cluster (ALDH⁺PD-L1⁺ER-β⁻) that was strongly associated with poor prognosis. We elucidated the different spatial architectures of immune cells (excluded, infiltrated, and deserted) and tumor-associated collagens (curved, stretched, directionally distributed, and chaotic) in the MIBC TME. The present study is the first to provide in-depth insight into the complexity of the MIBC TME at the single-cell level. Our results will improve the general understanding of the heterogeneous characteristics of MIBC, potentially facilitating patient stratification and personalized therapy.

Association of IDH mutation and 1p19q co-deletion with tumor immune microenvironment in lower-grade glioma

Although the successful clinical trials of immunotherapy show promising strategies for many cancers, its application in glioma has lagged in comparison with the progress seen in other cancers. Both isocitrate dehydrogenase (IDH) mutations and 1p/19q codeletions are critical molecular alterations affecting therapeutic response in lower-grade glioma (LGG). The systematic and comprehensive characterization of the immunological phenotypes with different molecular subtypes is key to improving our understanding and application of immunotherapies in LGG. Here, we collected the RNA-sequencing, somatic mutation, and clinical data from 1,052 patients from The Cancer Genome Atlas and Chinese Glioma Genome Atlas and stratified patients into three genetic subgroups: IDH mutations with 1p/19q codeletions (IDH mut-codel), IDH mutations without 1p/19q codeletions (IDH mut-noncodel), and IDH wild-type. Our evaluations revealed that IDH mutations and 1p/19q codeletions were associated with distinct immunological tumor microenvironments in LGG. In addition, immune cell infiltration, the expression of immune checkpoint and human leukocyte antigen (HLA) gene, and the activity of immune signaling pathways shared gradual increase from IDH mut-codel to IDH wild-type. We further constructed and validated an immune-related prognostic signature that presented high value in predicting the overall survival time in LGG. In conclusion, our study may provide valuable information for immunotherapy strategies in LGG patients.

Multifaceted microglia - key players in primary brain tumour heterogeneity

Microglia are the resident innate immune cells of the immune-privileged CNS and, as such, represent the first line of defence against tissue injury and infection. Given their location, microglia are undoubtedly the first immune cells to encounter a developing primary brain tumour. Our knowledge of these cells is therefore important to consider in the context of such neoplasms. As the heterogeneous nature of the most aggressive primary brain tumours is thought to underlie their poor prognosis, this Review places a special emphasis on the heterogeneity of the tumour-associated microglia and macrophage populations present in primary brain tumours. Where available, specific information on microglial heterogeneity in various types and subtypes of brain tumour is included. Emerging evidence that highlights the importance of considering the heterogeneity of both the tumour and of microglial populations in providing improved treatment outcomes for patients is also discussed.

NPC2 as a Prognostic Biomarker for Glioblastoma Based on Integrated Bioinformatics Analysis and Cytological Experiments

Glioblastoma (GBM) is one of the most common and fatal malignancies worldwide, while its prognostic biomarkers are still being explored. This study aims to identify potential genes with clinical and prognostic significance by integrating bioinformatics analysis and investigating their function in HNSCC. Based on the Single-cell RNA sequencing (scRNA-seq) results of H3K27M-glioma cells, computational bioinformatics methods were employed for selecting prognostic biomarker for GBM. The protein NPC2 (NPC Intracellular Cholesterol Transporter 2), which has been shown to be related to lipoprotein metabolism and innate immune system, was identified to be upregulated in GBM. NPC2 showed a relatively higher expression in GBM samples, and a negative correlation with tumor purity and tumor infiltrating immune cells. Additionally, NPC2 was knocked down in U87-MG and U251 cells line, and cell proliferation and migration capability were evaluated with CCK-8, scratch and transwell assay, respectively. Cytological experiments has shown that NPC2 overexpression inhibited GBM cells proliferation and migration, indicating its important role in GBM progression. This is the first investigation into the prognostic value of NPC2 interact with GBM. The potential molecular factor NPC2 have been identified as a prognostic biomarker for GBM.

Personalized cancer therapy prioritization based on driver alteration co-occurrence patterns

Identification of actionable genomic vulnerabilities is key to precision oncology. Utilizing a large-scale drug screening in patient-derived xenografts, we uncover driver gene alteration connections, derive driver co-occurrence (DCO) networks, and relate these to drug sensitivity. Our collection of 53 drug-response predictors attains an average balanced accuracy of 58% in a cross-validation setting, rising to 66% for a subset of high-confidence predictions. We experimentally validated 12 out of 14 predictions in mice and adapted our strategy to obtain drug-response models from patients’ progression-free survival data. Our strategy reveals links between oncogenic alterations, increasing the clinical impact of genomic profiling.

Survival differences and associated molecular signatures of DNMT3A-mutant acute myeloid leukemia patients

Acute myeloid leukemia (AML) is a very heterogeneous and highly malignant blood cancer. Mutations of the DNA methyltransferase DNMT3A are among the most frequent recurrent genetic lesions in AML. The majority of DNMT3A-mutant AML patients shows fast relapse and poor survival, but also patients with long survival or long-term remission have been reported. Underlying molecular signatures and mechanisms that contribute to these survival differences are only poorly understood and have not been studied in detail so far. We applied hierarchical clustering to somatic gene mutation profiles of 51 DNMT3A-mutant patients from The Cancer Genome Atlas (TCGA) AML cohort revealing two robust patient subgroups with profound differences in survival. We further determined molecular signatures that distinguish both subgroups. Our results suggest that FLT3 and/or NPM1 mutations contribute to survival differences of DNMT3A-mutant patients. We observed an upregulation of genes of the p53, VEGF and DNA replication pathway and a downregulation of genes of the PI3K-Akt pathway in short- compared to long-lived patients. We identified that the majority of measured miRNAs was downregulated in the short-lived group and we found differentially expressed microRNAs between both subgroups that have not been reported for AML so far (miR-153-2, miR-3065, miR-95, miR-6718) suggesting that miRNAs could be important for prognosis. In addition, we learned gene regulatory networks to predict potential major regulators and found several genes and miRNAs with known roles in AML pathogenesis, but also interesting novel candidates involved in the regulation of hematopoiesis, cell cycle, cell differentiation, and immunity that may contribute to the observed survival differences of both subgroups and could therefore be important for prognosis. Moreover, the characteristic gene mutation and expression signatures that distinguished short- from long-lived patients were also predictive for independent DNMT3A-mutant AML patients from other cohorts and could also contribute to further improve the European LeukemiaNet (ELN) prognostic scoring system. Our study represents the first in-depth computational approach to identify molecular factors associated with survival differences of DNMT3A-mutant AML patients and could trigger additional studies to develop robust molecular markers for a better stratification of AML patients with DNMT3A mutations.

Molecular Characterization of Astrocytoma Progression Towards Secondary Glioblastomas Utilizing Patient-Matched Tumor Pairs

Astrocytomas are primary human brain tumors including diffuse or anaplastic astrocytomas that develop towards secondary glioblastomas over time. However, only little is known about molecular alterations that drive this progression. We measured multi-omics profiles of patient-matched astrocytoma pairs of initial and recurrent tumors from 22 patients to identify molecular alterations associated with tumor progression. Gene copy number profiles formed three major subcluters, but more than half of the patient-matched astrocytoma pairs differed in their gene copy number profiles like astrocytomas from different patients. Chromosome 10 deletions were not observed for diffuse astrocytomas, but occurred in corresponding recurrent tumors. Gene expression profiles formed three other major subclusters and patient-matched expression profiles were much more heterogeneous than their copy number profiles. Still, recurrent tumors showed a strong tendency to switch to the mesenchymal subtype. The direct progression of diffuse astrocytomas to secondary glioblastomas showed the largest number of transcriptional changes. Astrocytoma progression groups were further distinguished by signaling pathway expression signatures affecting cell division, interaction and differentiation. As expected, IDH1 was most frequently mutated closely followed by TP53, but also MUC4 involved in the regulation of apoptosis and proliferation was frequently mutated. Astrocytoma progression groups differed in their mutation frequencies of these three genes. Overall, patient-matched astrocytomas can differ substantially within and between patients, but still molecular signatures associated with the progression to secondary glioblastomas exist and should be analyzed for their potential clinical relevance in future studies.

Genome-wide expression profiling of glioblastoma using a large combined cohort

Glioblastomas (GBMs), are the most common intrinsic brain tumors in adults and are almost universally fatal. Despite the progresses made in surgery, chemotherapy, and radiation over the past decades, the prognosis of patients with GBM remained poor and the average survival time of patients suffering from GBM was still short. Discovering robust gene signatures toward better understanding of the complex molecular mechanisms leading to GBM is an important prerequisite to the identification of novel and more effective therapeutic strategies. Herein, a comprehensive study of genome-scale mRNA expression data by combining GBM and normal tissue samples from 48 studies was performed. The 147 robust gene signatures were identified to be significantly differential expression between GBM and normal samples, among which 100 (68%) genes were reported to be closely associated with GBM in previous publications. Moreover, function annotation analysis based on these 147 robust DEGs showed certain deregulated gene expression programs (e.g., cell cycle, immune response and p53 signaling pathway) were associated with GBM development, and PPI network analysis revealed three novel hub genes (RFC4, ZWINT and TYMS) play important role in GBM development. Furthermore, survival analysis based on the TCGA GBM data demonstrated 38 robust DEGs significantly affect the prognosis of GBM in OS (p < 0.05). These findings provided new insights into molecular mechanisms underlying GBM and suggested the 38 robust DEGs could be potential targets for the diagnosis and treatment.

Network-based analysis of oligodendrogliomas predicts novel cancer gene candidates within the region of the 1p/19q co-deletion

Oligodendrogliomas are primary human brain tumors with a characteristic 1p/19q co-deletion of important prognostic relevance, but little is known about the pathology of this chromosomal mutation. We developed a network-based approach to identify novel cancer gene candidates in the region of the 1p/19q co-deletion. Gene regulatory networks were learned from gene expression and copy number data of 178 oligodendrogliomas and further used to quantify putative impacts of differentially expressed genes of the 1p/19q region on cancer-relevant pathways. We predicted 8 genes with strong impact on signaling pathways and 14 genes with strong impact on metabolic pathways widespread across the region of the 1p/19 co-deletion. Many of these candidates (e.g. ELTD1, SDHB, SEPW1, SLC17A7, SZRD1, THAP3, ZBTB17) are likely to push, whereas others (e.g. CAP1, HBXIP, KLK6, PARK7, PTAFR) might counteract oligodendroglioma development. For example, ELTD1, a functionally validated glioblastoma oncogene located on 1p, was overexpressed. Further, the known glioblastoma tumor suppressor SLC17A7 located on 19q was underexpressed. Moreover, known epigenetic alterations triggered by mutated SDHB in paragangliomas suggest that underexpressed SDHB in oligodendrogliomas may support and possibly enhance the epigenetic reprogramming induced by the IDH-mutation. We further analyzed rarely observed deletions and duplications of chromosomal arms within oligodendroglioma subcohorts identifying putative oncogenes and tumor suppressors that possibly influence the development of oligodendroglioma subgroups. Our in-depth computational study contributes to a better understanding of the pathology of the 1p/19q co-deletion and other chromosomal arm mutations. This might open opportunities for functional validations and new therapeutic strategies.