Epigenetic Activation of WNT5A Drives Glioblastoma Stem Cell Differentiation and Invasive Growth.

Glioblastoma stem cells (GSCs) are implicated in tumor neovascularization, invasiveness, and therapeutic resistance. To illuminate mechanisms governing these hallmark features, we developed a de novo glioblastoma multiforme (GBM) model derived from immortalized human neural stem/progenitor cells (hNSCs) to enable precise system-level comparisons of pre-malignant and oncogene-induced malignant states of NSCs. Integrated transcriptomic and epigenomic analyses uncovered a PAX6/DLX5 transcriptional program driving WNT5A-mediated GSC differentiation into endothelial-like cells (GdECs). GdECs recruit existing endothelial cells to promote peritumoral satellite lesions, which serve as a niche supporting the growth of invasive glioma cells away from the primary tumor. Clinical data reveal higher WNT5A and GdECs expression in peritumoral and recurrent GBMs relative to matched intratumoral and primary GBMs, respectively, supporting WNT5A-mediated GSC differentiation and invasive growth in disease recurrence. Thus, the PAX6/DLX5-WNT5A axis governs the diffuse spread of glioma cells throughout the brain parenchyma, contributing to the lethality of GBM.

A predictive paradigm for COVID-19 prognosis based on the longitudinal measure of biomarkers.

Novel coronavirus disease 2019 (COVID-19) is an emerging, rapidly evolving crisis, and the ability to predict prognosis for individual COVID-19 patient is important for guiding treatment. Laboratory examinations were repeatedly measured during hospitalization for COVID-19 patients, which provide the possibility for the individualized early prediction of prognosis. However, previous studies mainly focused on risk prediction based on laboratory measurements at one time point, ignoring disease progression and changes of biomarkers over time. By using historical regression trees (HTREEs), a novel machine learning method, and joint modeling technique, we modeled the longitudinal trajectories of laboratory biomarkers and made dynamically predictions on individual prognosis for 1997 COVID-19 patients. In the discovery phase, based on 358 COVID-19 patients admitted between 10 January and 18 February 2020 from Tongji Hospital, HTREE model identified a set of important variables including 14 prognostic biomarkers. With the trajectories of those biomarkers through 5-day, 10-day and 15-day, the joint model had a good performance in discriminating the survived and deceased COVID-19 patients (mean AUCs of 88.81, 84.81 and 85.62% for the discovery set). The predictive model was successfully validated in two independent datasets (mean AUCs of 87.61, 87.55 and 87.03% for validation the first dataset including 112 patients, 94.97, 95.78 and 94.63% for the second validation dataset including 1527 patients, respectively). In conclusion, our study identified important biomarkers associated with the prognosis of COVID-19 patients, characterized the time-to-event process and obtained dynamic predictions at the individual level.

A map of the spatial distribution and tumour-associated macrophage states in glioblastoma and grade 4 IDH-mutant astrocytoma.

Tumour-associated macrophages (TAMs) abundantly infiltrate high-grade gliomas and orchestrate immune response, but their diversity in isocitrate dehydrogenase (IDH)-differential grade 4 gliomas remains largely unknown. This study aimed to dissect the transcriptional states, spatial distribution, and clinicopathological significance of distinct monocyte-derived TAM (Mo-TAM) and microglia-derived TAM (Mg-TAM) clusters across glioblastoma-IDH-wild type and astrocytoma-IDH-mutant-grade 4 (Astro-IDH-mut-G4). Single-cell RNA sequencing was performed on four cases of human glioblastoma and three cases of Astro-IDH-mut-G4. Cell clustering, single-cell regulatory network inference, and gene set enrichment analysis were performed to characterize the functional states of myeloid clusters. The spatial distribution of TAM subsets was determined in human glioma tissues using multiplex immunostaining. The prognostic value of different TAM-cluster specific gene sets was evaluated in the TCGA glioma cohort. Profiling and unbiased clustering of 24,227 myeloid cells from glioblastoma and Astro-IDH-mut-G4 identified nine myeloid cell clusters including monocytes, six Mo/Mg-TAM subsets, dendritic cells, and proliferative myeloid clusters. Different Mo/Mg-TAM clusters manifest functional and transcriptional diversity controlled by specific regulons. Multiplex immunostaining of subset-specific markers identified spatial enrichment of distinct TAM clusters at peri-vascular/necrotic areas in tumour parenchyma or at the tumour-brain interface. Glioblastoma harboured a substantially higher number of monocytes and Mo-TAM-inflammatory clusters, whereas Astro-IDH-mut-G4 had a higher proportion of TAM subsets mediating antigen presentation. Glioblastomas with a higher proportion of monocytes exhibited a mesenchymal signature, increased angiogenesis, and worse patient outcome. Our findings provide insight into myeloid cell diversity and its clinical relevance in IDH-differential grade 4 gliomas, and may serve as a resource for immunotherapy development. © 2022 The Pathological Society of Great Britain and Ireland.

Sex-based clinical and immunological differences in COVID-19.

BACKGROUND: Males and females differ in their immunological responses to foreign pathogens. However, most of the current COVID-19 clinical practices and trials do not take the sex factor into consideration. METHODS: We performed a sex-based comparative analysis for the clinical outcomes, peripheral immune cells, and severe acute respiratory syndrome coronavirus (SARS-CoV-2) specific antibody levels of 1558 males and 1499 females COVID-19 patients from a single center. The lymphocyte subgroups were measured by Flow cytometry. The total antibody, Spike protein (S)-, receptor binding domain (RBD)-, and nucleoprotein (N)- specific IgM and IgG levels were measured by chemiluminescence. RESULTS: We found that male patients had approximately two-fold rates of ICU admission (4.7% vs. 2.7% in males and females, respectively, P = 0.005) and mortality (3% vs. 1.4%, in males and females, respectively, P = 0.004) than female patients. Survival analysis revealed that the male sex is an independent risk factor for death from COVID-19 (adjusted hazard ratio [HR] = 2.22, 95% confidence interval [CI]: 1.3-3.6, P = 0.003). The level of inflammatory cytokines in peripheral blood was higher in males during hospitalization. The renal (102/1588 [6.5%] vs. 63/1499 [4.2%], in males and females, respectively, P = 0.002) and hepatic abnormality (650/1588 [40.9%] vs. 475/1499 [31.7%], P = 0.003) were more common in male patients than in female patients. By analyzing dynamic changes of lymphocyte subsets after symptom onset, we found that the percentage of CD19+ B cells and CD4+ T cells was generally higher in female patients during the disease course of COVID-19. Notably, the protective RBD-specific IgG against SARS-CoV-2 sharply increased and reached a peak in the fourth week after symptom onset in female patients, while gradually increased and reached a peak in the seventh week after symptom onset in male patients. CONCLUSIONS: Males had an unfavorable prognosis, higher inflammation, a lower percentage of lymphocytes, and indolent antibody responses during SARS-CoV-2 infection and recovery. Early medical intervention and close monitoring are important, especially for male COVID-19 patients.

Implications of cardiac markers in risk-stratification and management for COVID-19 patients.

BACKGROUND: COVID-19 has resulted in high mortality worldwide. Information regarding cardiac markers for precise risk-stratification is limited. We aim to discover sensitive and reliable early-warning biomarkers for optimizing management and improving the prognosis of COVID-19 patients. METHODS: A total of 2954 consecutive COVID-19 patients who were receiving treatment from the Wuhan Huoshenshan Hospital in China from February 4 to April 10 were included in this retrospective cohort. Serum levels of cardiac markers were collected after admission. Coronary artery disease diagnosis and survival status were recorded. Single-cell RNA-sequencing and bulk RNA-sequencing from different cohorts of non-COVID-19 were performed to analyze SARS-CoV-2 receptor expression. RESULTS: Among 2954 COVID-19 patients in the analysis, the median age was 60 years (50-68 years), 1461 (49.5%) were female, and 1515 (51.3%) were severe/critical. Compared to mild/moderate (1439, 48.7%) patients, severe/critical patients showed significantly higher levels of cardiac markers within the first week after admission. In severe/critical COVID-19 patients, those with abnormal serum levels of BNP (42 [24.6%] vs 7 [1.1%]), hs-TNI (38 [48.1%] vs 6 [1.0%]), α- HBDH (55 [10.4%] vs 2 [0.2%]), CK-MB (45 [36.3%] vs 12 [0.9%]), and LDH (56 [12.5%] vs 1 [0.1%]) had a significantly higher mortality rate compared to patients with normal levels. The same trend was observed in the ICU admission rate. Severe/critical COVID-19 patients with pre-existing coronary artery disease (165/1,155 [10.9%]) had more cases of BNP (52 [46.5%] vs 119 [16.5%]), hs-TNI (24 [26.7%] vs 9.6 [%], α- HBDH (86 [55.5%] vs 443 [34.4%]), CK-MB (27 [17.4%] vs 97 [7.5%]), and LDH (65 [41.9%] vs 382 [29.7%]), when compared with those without coronary artery disease. There was enhanced SARS-CoV-2 receptor expression in coronary artery disease compared with healthy controls. From regression analysis, patients with five elevated cardiac markers were at a higher risk of death (hazards ratio 3.4 [95% CI 2.4-4.8]). CONCLUSIONS: COVID-19 patients with pre-existing coronary artery disease represented a higher abnormal percentage of cardiac markers, accompanied by high mortality and ICU admission rate. BNP together with hs-TNI, α- HBDH, CK-MB and LDH act as a prognostic biomarker in COVID-19 patients with or without pre-existing coronary artery disease.

The androgen receptor expression and association with patient's survival in different cancers.

To understand the androgen receptor (AR) in different human malignancies, we conducted a pan-cancer analysis of AR in different tumor tissues and association with patient survival and obtained AR expression data from The Cancer Genome Atlas. Pan-Cancer Analysis of AR indicated that 12 tumor types had decreased AR expression in the tumor, while glioblastoma multiforme has overexpressed AR. The survival analysis showed that high AR mRNA is associated with poor survival of stomach adenocarcinoma and low-grade glioma, but better survival of adrenocortical carcinoma, kidney renal clear cell carcinoma, acute myeloid leukemia, liver hepatocellular carcinoma, ovarian serous cystadenocarcinoma, and skin cutaneous melanoma based on AR mRNA, protein or AR-score. AR was associated with different clinical characteristics and AR correlated genes enriched in cancer-related pathways. These data indicate that AR signaling may be strongly associated with some cancer development and patients' survival, which is promising for potential treatment using antiandrogen therapies.

TumorFusions: an integrative resource for cancer-associated transcript fusions.

Gene fusion represents a class of molecular aberrations in cancer and has been exploited for therapeutic purposes. In this paper we describe TumorFusions, a data portal that catalogues 20 731 gene fusions detected in 9966 well characterized cancer samples and 648 normal specimens from The Cancer Genome Atlas (TCGA). The portal spans 33 cancer types in TCGA. Fusion transcripts were identified via a uniform pipeline, including filtering against a list of 3838 transcript fusions detected in a panel of 648 non-neoplastic samples. Fusions were mapped to somatic DNA rearrangements identified using whole genome sequencing data from 561 cancer samples as a means of validation. We observed that 65% of transcript fusions were associated with a chromosomal alteration, which is annotated in the portal. Other features of the portal include links to SNP array-based copy number levels and mutational patterns, exon and transcript level expressions of the partner genes, and a network-based centrality score for prioritizing functional fusions. Our portal aims to be a broadly applicable and user friendly resource for cancer gene annotation and is publicly available at http://www.tumorfusions.org.

PAF promotes stemness and radioresistance of glioma stem cells.

An integrated genomic and functional analysis to elucidate DNA damage signaling factors promoting self-renewal of glioma stem cells (GSCs) identified proliferating cell nuclear antigen (PCNA)-associated factor (PAF) up-regulation in glioblastoma. PAF is preferentially overexpressed in GSCs. Its depletion impairs maintenance of self-renewal without promoting differentiation and reduces tumor-initiating cell frequency. Combined transcriptomic and metabolomic analyses revealed that PAF supports GSC maintenance, in part, by influencing DNA replication and pyrimidine metabolism pathways. PAF interacts with PCNA and regulates PCNA-associated DNA translesion synthesis (TLS); consequently, PAF depletion in combination with radiation generated fewer tumorspheres compared with radiation alone. Correspondingly, pharmacological impairment of DNA replication and TLS phenocopied the effect of PAF depletion in compromising GSC self-renewal and radioresistance, providing preclinical proof of principle that combined TLS inhibition and radiation therapy may be a viable therapeutic option in the treatment of glioblastoma multiforme (GBM).

Suppression of RAF/MEK or PI3K synergizes cytotoxicity of receptor tyrosine kinase inhibitors in glioma tumor-initiating cells.

BACKGROUND: The majority of glioblastomas have aberrant receptor tyrosine kinase (RTK)/RAS/phosphoinositide 3 kinase (PI3K) signaling pathways and malignant glioma cells are thought to be addicted to these signaling pathways for their survival and proliferation. However, recent studies suggest that monotherapies or inappropriate combination therapies using the molecular targeted drugs have limited efficacy possibly because of tumor heterogeneities, signaling redundancy and crosstalk in intracellular signaling network, indicating necessity of rationale and methods for efficient personalized combination treatments. Here, we evaluated the growth of colonies obtained from glioma tumor-initiating cells (GICs) derived from glioma sphere culture (GSC) in agarose and examined the effects of combination treatments on GICs using targeted drugs that affect the signaling pathways to which most glioma cells are addicted. METHODS: Human GICs were cultured in agarose and treated with inhibitors of RTKs, non-receptor kinases or transcription factors. The colony number and volume were analyzed using a colony counter, and Chou-Talalay combination indices were evaluated. Autophagy and apoptosis were also analyzed. Phosphorylation of proteins was evaluated by reverse phase protein array and immunoblotting. RESULTS: Increases of colony number and volume in agarose correlated with the Gompertz function. GICs showed diverse drug sensitivity, but inhibitions of RTK and RAF/MEK or PI3K by combinations such as EGFR inhibitor and MEK inhibitor, sorafenib and U0126, erlotinib and BKM120, and EGFR inhibitor and sorafenib showed synergy in different subtypes of GICs. Combination of erlotinib and sorafenib, synergistic in GSC11, induced apoptosis and autophagic cell death associated with suppressed Akt and ERK signaling pathways and decreased nuclear PKM2 and ß-catenin in vitro, and tended to improve survival of nude mice bearing GSC11 brain tumor. Reverse phase protein array analysis of the synergistic treatment indicated involvement of not only MEK and PI3K signaling pathways but also others associated with glucose metabolism, fatty acid metabolism, gene transcription, histone methylation, iron transport, stress response, cell cycle, and apoptosis. CONCLUSION: Inhibiting RTK and RAF/MEK or PI3K could induce synergistic cytotoxicity but personalization is necessary. Examining colonies in agarose initiated by GICs from each patient may be useful for drug sensitivity testing in personalized cancer therapy.

Mesenchymal Stem Cells Isolated From Human Gliomas Increase Proliferation and Maintain Stemness of Glioma Stem Cells Through the IL-6/gp130/STAT3 Pathway.

Although mesenchymal stem cells (MSCs) have been implicated as stromal components of several cancers, their ultimate contribution to tumorigenesis and their potential to drive cancer stem cells, particularly in the unique microenvironment of human brain tumors, remain largely undefined. Consequently, using established criteria, we isolated glioma-associated-human MSCs (GA-hMSCs) from fresh human glioma surgical specimens for the first time. We show that these GA-hMSCs are nontumorigenic stromal cells that are phenotypically similar to prototypical bone marrow-MSCs. Low-passage genomic sequencing analyses comparing GA-hMSCs with matched tumor-initiating glioma stem cells (GSCs) suggest that most GA-hMSCs (60%) are normal cells recruited to the tumor (group 1 GA-hMSCs), although, rarely (10%), GA-hMSCs may differentiate directly from GSCs (group 2 GA-hMSCs) or display genetic patterns intermediate between these groups (group 3 GA-hMSCs). Importantly, GA-hMSCs increase proliferation and self-renewal of GSCs in vitro and enhance GSC tumorigenicity and mesenchymal features in vivo, confirming their functional significance within the GSC niche. These effects are mediated by GA-hMSC-secreted interleukin-6, which activates STAT3 in GSCs. Our results establish GA-hMSCs as a potentially new stromal component of gliomas that drives the aggressiveness of GSCs, and point to GA-hMSCs as a novel therapeutic target within gliomas.

Systematic identification of single amino acid variants in glioma stem-cell-derived chromosome 19 proteins.

Novel proteoforms with single amino acid variations represent proteins that often have altered biological functions but are less explored in the human proteome. We have developed an approach, searching high quality shotgun proteomic data against an extended protein database, to identify expressed mutant proteoforms in glioma stem cell (GSC) lines. The systematic search of MS/MS spectra using PEAKS 7.0 as the search engine has recognized 17 chromosome 19 proteins in GSCs with altered amino acid sequences. The results were further verified by manual spectral examination, validating 19 proteoforms. One of the novel findings, a mutant form of branched-chain aminotransferase 2 (p.Thr186Arg), was verified at the transcript level and by targeted proteomics in several glioma stem cell lines. The structure of this proteoform was examined by molecular modeling in order to estimate conformational changes due to mutation that might lead to functional modifications potentially linked to glioma. Based on our initial findings, we believe that our approach presented could contribute to construct a more complete map of the human functional proteome.

PRADA: pipeline for RNA sequencing data analysis.

SUMMARY: Technological advances in high-throughput sequencing necessitate improved computational tools for processing and analyzing large-scale datasets in a systematic automated manner. For that purpose, we have developed PRADA (Pipeline for RNA-Sequencing Data Analysis), a flexible, modular and highly scalable software platform that provides many different types of information available by multifaceted analysis starting from raw paired-end RNA-seq data: gene expression levels, quality metrics, detection of unsupervised and supervised fusion transcripts, detection of intragenic fusion variants, homology scores and fusion frame classification. PRADA uses a dual-mapping strategy that increases sensitivity and refines the analytical endpoints. PRADA has been used extensively and successfully in the glioblastoma and renal clear cell projects of The Cancer Genome Atlas program. AVAILABILITY AND IMPLEMENTATION: http://sourceforge.net/projects/prada/ CONTACT: gadgetz@broadinstitute.org or rverhaak@mdanderson.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrated chromosome 19 transcriptomic and proteomic data sets derived from glioma cancer stem-cell lines.

One subproject within the global Chromosome 19 Consortium is to define chromosome 19 gene and protein expression in glioma-derived cancer stem cells (GSCs). Chromosome 19 is notoriously linked to glioma by 1p/19q codeletions, and clinical tests are established to detect that specific aberration. GSCs are tumor-initiating cells and are hypothesized to provide a repository of cells in tumors that can self-replicate and be refractory to radiation and chemotherapeutic agents developed for the treatment of tumors. In this pilot study, we performed RNA-Seq, label-free quantitative protein measurements in six GSC lines, and targeted transcriptomic analysis using a chromosome 19-specific microarray in an additional six GSC lines. The data have been deposited to the ProteomeXchange with identifier PXD000563. Here we present insights into differences in GSC gene and protein expression, including the identification of proteins listed as having no or low evidence at the protein level in the Human Protein Atlas, as correlated to chromosome 19 and GSC subtype. Furthermore, the upregulation of proteins downstream of adenovirus-associated viral integration site 1 (AAVS1) in GSC11 in response to oncolytic adenovirus treatment was demonstrated. Taken together, our results may indicate new roles for chromosome 19, beyond the 1p/19q codeletion, in the future of personalized medicine for glioma patients.

Reactivating PTEN to impair glioma stem cells by inhibiting cytosolic iron-sulfur assembly.

Glioblastoma, the most lethal primary brain tumor, harbors glioma stem cells (GSCs) that not only initiate and maintain malignant phenotypes but also enhance therapeutic resistance. Although frequently mutated in glioblastomas, the function and regulation of PTEN in PTEN-intact GSCs are unknown. Here, we found that PTEN directly interacted with MMS19 and competitively disrupted MMS19-based cytosolic iron-sulfur (Fe-S) cluster assembly (CIA) machinery in differentiated glioma cells. PTEN was specifically succinated at cysteine (C) 211 in GSCs compared with matched differentiated glioma cells. Isotope tracing coupled with mass spectrometry analysis confirmed that fumarate, generated by adenylosuccinate lyase (ADSL) in the de novo purine synthesis pathway that is highly activated in GSCs, promoted PTEN C211 succination. This modification abrogated the interaction between PTEN and MMS19, reactivating the CIA machinery pathway in GSCs. Functionally, inhibiting PTEN C211 succination by reexpressing a PTEN C211S mutant, depleting ADSL by shRNAs, or consuming fumarate by the US Food and Drug Administration-approved prescription drug N-acetylcysteine (NAC) impaired GSC maintenance. Reexpressing PTEN C211S or treating with NAC sensitized GSC-derived brain tumors to temozolomide and irradiation, the standard-of-care treatments for patients with glioblastoma, by slowing CIA machinery-mediated DNA damage repair. These findings reveal an immediately practicable strategy to target GSCs to treat glioblastoma by combination therapy with repurposed NAC.

Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis.

Given the extremely high inter-patient heterogeneity among acute myeloid leukemia (AML), identifying biomarkers for prognostic assessment and therapeutic guidance is crucial. Cell surface markers (CSMs) have been shown to play an important role in AML leukemogenesis and progression. In this study, we evaluate the prognostic potential of all human CSMs in AML patients based on differential gene expression analysis and univariate Cox regression analysis. Utilizing multi-model analysis, including Adaptive LASSO regression, LASSO regression, and Elastic Net, we construct a 9-CSMs prognostic model for risk stratification of AML patients. The predictive value of the 9-CSMs risk score is further confirmed in three independent datasets. Multivariate Cox regression analysis shows that the risk score is an independent prognostic factor for AML patients. AML patients with high 9-CSMs risk scores have shorter overall and event-free survival time than those with lower scores. Notably, our single-cell RNA-seq analysis indicates that patients with high 9-CSMs risk scores exhibit chemotherapy resistance. Further, PI3K inhibitors are identified as potential treatments for these high-risk patients. In conclusion, we construct a 9-CSMs prognostic model which is an independent prognostic factor for the survival of AML patients and has the potential to guide drug therapy.

IFI35 regulates non-canonical NF-κB signaling to maintain glioblastoma stem cells and recruit tumor-associated macrophages.

Glioblastoma (GBM) is the most aggressive malignant primary brain tumor characterized by a highly heterogeneous and immunosuppressive tumor microenvironment (TME). The symbiotic interactions between glioblastoma stem cells (GSCs) and tumor-associated macrophages (TAM) in the TME are critical for tumor progression. Here, we identified that IFI35, a transcriptional regulatory factor, plays both cell-intrinsic and cell-extrinsic roles in maintaining GSCs and the immunosuppressive TME. IFI35 induced non-canonical NF-kB signaling through proteasomal processing of p105 to the DNA-binding transcription factor p50, which heterodimerizes with RELB (RELB/p50), and activated cell chemotaxis in a cell-autonomous manner. Further, IFI35 induced recruitment and maintenance of M2-like TAMs in TME in a paracrine manner. Targeting IFI35 effectively suppressed in vivo tumor growth and prolonged survival of orthotopic xenograft-bearing mice. Collectively, these findings reveal the tumor-promoting functions of IFI35 and suggest that targeting IFI35 or its downstream effectors may provide effective approaches to improve GBM treatment.

Prioritizing human cancer microRNAs based on genes' functional consistency between microRNA and cancer.

The identification of human cancer-related microRNAs (miRNAs) is important for cancer biology research. Although several identification methods have achieved remarkable success, they have overlooked the functional information associated with miRNAs. We present a computational framework that can be used to prioritize human cancer miRNAs by measuring the association between cancer and miRNAs based on the functional consistency score (FCS) of the miRNA target genes and the cancer-related genes. This approach proved successful in identifying the validated cancer miRNAs for 11 common human cancers with area under ROC curve (AUC) ranging from 71.15% to 96.36%. The FCS method had a significant advantage over miRNA differential expression analysis when identifying cancer-related miRNAs with a fine regulatory mechanism, such as miR-27a in colorectal cancer. Furthermore, a case study examining thyroid cancer showed that the FCS method can uncover novel cancer-related miRNAs such as miR-27a/b, which were showed significantly upregulated in thyroid cancer samples by qRT-PCR analysis. Our method can be used on a web-based server, CMP (cancer miRNA prioritization) and is freely accessible at http://bioinfo.hrbmu.edu.cn/CMP. This time- and cost-effective computational framework can be a valuable complement to experimental studies and can assist with future studies of miRNA involvement in the pathogenesis of cancers.

Noninvasive radiomics model reveals macrophage infiltration in glioma.

Preoperative MRI is an essential diagnostic and therapeutic reference for gliomas. This study aims to evaluate the prognostic aspect of a radiomics biomarker for glioma and further investigate its relationship with tumor microenvironment and macrophage infiltration. We covered preoperative MRI of 664 glioma patients from three independent datasets: Jiangsu Province Hospital (JSPH, n = 338), The Cancer Genome Atlas dataset (TCGA, n = 252), and Repository of Molecular Brain Neoplasia Data (REMBRANDT, n = 74). Incorporating a multistep post-processing workflow, 20 radiomics features (Rads) were selected and a radiomics survival biomarker (RadSurv) was developed, proving highly efficient in risk stratification of gliomas (cut-off = 1.06), as well as lower-grade gliomas (cut-off = 0.64) and glioblastomas (cut-off = 1.80) through three fixed cut-off values. Through immune infiltration analysis, we found a positive correlation between RadSurv and macrophage infiltration (RMΦ = 0.297, p < 0.001; RM2Φ = 0.241, p < 0.001), further confirmed by immunohistochemical-staining (glioblastomas, n = 32) and single-cell sequencing (multifocal glioblastomas, n = 2). In conclusion, RadSurv acts as a strong prognostic biomarker for gliomas, exhibiting a non-negligible positive correlation with macrophage infiltration, especially with M2 macrophage, which strongly suggests the promise of radiomics-based models as a preoperative alternative to conventional genomics for predicting tumor macrophage infiltration and provides clinical guidance for immunotherapy.