A three-microRNA signature identifies two subtypes of glioblastoma patients with different clinical outcomes

MiRNAs from the Dlk1-Dio3 locus and miR-224/452 cluster contribute to glioblastoma tumor heterogeneity

Glioblastoma is one of the most common and aggressive brain tumors and has seen few improvements in patient outcomes. Inter-tumor heterogeneity between tumors of different patients as well as intra-tumor heterogeneity of cells within the same tumor challenge the development of effective drugs. MiRNAs play an essential role throughout the developing brain and regulate many key genes involved in oncogenesis, yet their role in driving many of the processes underlying tumor heterogeneity remains unclear. In this study, we highlight miRNAs from the Dlk1-Dio3 and miR-224/452 clusters which may be expressed cell autonomously and have expression that is associated with cell state genes in glioblastoma, most prominently in neural progenitor-like and mesenchymal-like states respectively. These findings implicate these miRNA clusters as potential regulators of glioblastoma intra-tumoral heterogeneity and may serve as valuable biomarkers for cell state identification.

miRNAs and related genetic biomarkers according to the WHO glioma classification: From diagnosis to future therapeutic targets

In the 2021 WHO classification of Tumors of the Central Nervous System, additional molecular characteristics have been included, defining the following adult-type diffuse glioma entities: Astrocytoma IDH-mutant, Oligodendroglioma IDH-mutant and 1p/19q-codeleted, and Glioblastoma IDH-wildtype. Despite advances in genetic analysis, precision oncology, and targeted therapy, malignant adult-type diffuse gliomas remain "hard-to-treat tumors", indicating an urgent need for better diagnostic and therapeutic strategies. In the last decades, miRNA analysis has been a hotspot for researching and developing diagnostic, prognostic, and predictive biomarkers for various disorders, including brain cancer. Scientific interest has recently been directed towards therapeutic applications of miRNAs, with encouraging results. Databases such as NCBI, PubMed, and Medline were searched for a selection of articles reporting the relationship between deregulated miRNAs and genetic aberrations used in the latest WHO CNS classification. The current review discussed the recommended molecular biomarkers and genetic aberrations based on the 2021 WHO classification in adult-type diffuse gliomas, along with associated deregulated miRNAs. Additionally, the study highlights miRNA-based treatment advancements in adults with gliomas.

Characterization of Glioblastoma Cells Response to Regorafenib

Glioblastoma (GBM), the most malignant primary brain tumor in adults. Although not frequent, it has a relevant social impact because the peak incidence coincides with the age of professional maturity. A number of novel treatments have been proposed, yet clinical trials have been disappointing. Recently, a phase II clinical trial (REGOMA) demonstrated that the multikinase inhibitor regorafenib significantly increased the median overall survival (OS) of GBM patients when compared to lomustine-treated patients. On this basis, the National Comprehensive Cancer Network (NCCN) 2020 Guidelines included regorafenib as a preferred regimen in relapsed GBM treatment. Despite the use in GBM patients' therapy, little is known about the molecular mechanisms governing regorafenib effectiveness on the GBM tumor. Here we report an in vitro characterization of GBM tumor cells' response to regorafenib, performed both on cell lines and on patient-derived glioma stem cells (GSCs). Overall, regorafenib significantly reduced cell growth of 2D tumor cell cultures and of 3D tumor spheroids. Strikingly, this effect was accompanied by transcriptional regulation of epithelial to mesenchymal transition (EMT) genes and by an increased ability of surviving tumor cells to invade the surrounding matrix. Taken together, our data suggest that regorafenib limits cell growth, however, it might induce an invasive phenotype.

Glioblastoma Stem-Like Cells (GSCs) with Mesenchymal Signature: Lipid Profiles of Mobile Lipids Obtained with MRS before and after Radio/Chemical Treatments

Glioblastoma is the most common and lethal primary malignant brain tumor in adults. Glioblastoma stem cells (GSCs) promote and are responsible for glioblastoma intratumoral heterogeneity and therapy resistance, due to their two main features: self-renewal and differentiation. Lipids have important biological and physiological functions that are critical for understanding the regulation and control of stem cell fate; lipid metabolism and related unsaturation levels play a possible role as the target of therapeutics to overcome glioblastoma radioresistance. This paper aimed at an in-depth analysis of 13 GSC mesenchymal (MES) lines, two subclones, and a stabilized glioblastoma line (T98G) by magnetic resonance spectroscopy (MRS). Particularly, 2D MRS was used to investigate lipid unsaturation behavior during growth in culture and after treatment with etomoxir and photon beams. MES lines, although belonging to the same genetic and metabolic cluster, showed metabolic heterogeneity when observed by MRS, focusing on lipid signals. Nonetheless, the observed unsaturation level stability for two representative lines after stressful treatments suggests unusual robustness of the unsaturation levels for each line, as a peculiar and intrinsic characteristic of GSCs.

A 3-miRNA Signature Enables Risk Stratification in Glioblastoma Multiforme Patients with Different Clinical Outcomes

Malignant gliomas constitute a complex disease phenotype that demands optimum decision-making as they are highly heterogeneous. Such inter-individual variability also renders optimum patient stratification extremely difficult. microRNA (hsa-miR-20a, hsa-miR-21, hsa-miR-21) expression levels were determined by RT-qPCR, upon FFPE tissue sample collection of glioblastoma multiforme patients (n = 37). In silico validation was then performed through discriminant analysis. Immunohistochemistry images from biopsy material were utilized by a hybrid deep learning system to further cross validate the distinctive capability of patient risk groups. Our standard-of-care treated patient cohort demonstrates no age- or sex- dependence. The expression values of the 3-miRNA signature between the low- (OS > 12 months) and high-risk (OS < 12 months) groups yield a p-value of <0.0001, enabling risk stratification. Risk stratification is validated by a. our random forest model that efficiently classifies (AUC = 97%) patients into two risk groups (low- vs. high-risk) by learning their 3-miRNA expression values, and b. our deep learning scheme, which recognizes those patterns that differentiate the images in question. Molecular-clinical correlations were drawn to classify low- (OS > 12 months) vs. high-risk (OS < 12 months) glioblastoma multiforme patients. Our 3-microRNA signature (hsa-miR-20a, hsa-miR-21, hsa-miR-10a) may further empower glioblastoma multiforme prognostic evaluation in clinical practice and enrich drug repurposing pipelines.

Effects of the Combined Treatment with a G-Quadruplex-Stabilizing Ligand and Photon Beams on Glioblastoma Stem-like Cells: A Magnetic Resonance Study

Glioblastoma multiforme is a malignant primary brain tumor with a poor prognosis and high rates of chemo-radiotherapy failure, mainly due to a small cell fraction with stem-like properties (GSCs). The mechanisms underlying GSC response to radiation need to be elucidated to enhance sensitivity to treatments and to develop new therapeutic strategies. In a previous study, two GSC lines, named line #1 and line #83, responded differently to carbon ions and photon beams, with the differences likely attributable to their own different metabolic fingerprint rather than to radiation type. Data from the literature showed the capability of RHPS4, a G-quadruplex stabilizing ligand, to sensitize the glioblastoma radioresistant U251MG cells to X-rays. The combined metabolic effect of ligand #190, a new RHPS4-derivative showing reduced cardiotoxicity, and a photon beam has been monitored by magnetic resonance (MR) spectroscopy for the two GSC lines, #1 and #83, to reveal whether a synergistic response occurs. MR spectra from both lines were affected by single and combined treatments, but the variations of the analysed metabolites were statistically significant mainly in line #1, without synergistic effects due to combination. The multivariate analysis of ten metabolites shows a separation between control and treated samples in line #1 regardless of treatment type, while separation was not detected in line #83.

Identification and Potential Mechanisms of a 7-MicroRNA Signature That Predicts Prognosis in Patients with Lower-Grade Glioma

Background

Lower-grade glioma is an intracranial cancer that may develop into glioblastoma with high mortality. The main objective of our study is to develop microRNA for LGG patients which will provide novel prognostic biomarkers along with therapeutic targets.

Methods

Clinicopathological data of LGG patients and their RNA expression profile were downloaded through The Cancer Genome Atlas Relevant expression profiles of RNA, and clinicopathological data of the LGG patients had been extracted from the database of "The Cancer Genome Atlas." Differential expression analysis had been conducted for identification of the differentially expressed microRNAs as well as mRNAs in LGG samples and normal ones. ROC curves and K-M plots were plotted to confirm performance and for predictive accuracy. For the confirmation of microRNAs as an independent prognostic factor, an independent prognosis analysis was conducted. Moreover, target differentially expressed genes of these identified prognostic microRNAs that were extracted and protein-protein interaction networks were developed. Moreover, the biological functions of signature were determined through Genome Ontology analysis, genome pathway analysis, and Kyoto Encyclopedia of Genes.

Results

7-microRNA signature was identified that has the ability of categorization of individuals with LGG into high- and low-risk groups on the basis of significant difference in survival during training and testing cohorts (P < 0.001). The 7-microRNA signature had appeared to be robust in predictive accuracy (all AUC> 0.65). It was also approved with multivariate Cox regression along with some traditional clinical practices that we can use 7-microRNA signature for therapeutic purposes as a self-regulating predictive OS factor (P < 0.001). KEGG and Gene Ontology (GO) analyses reported that 7-microRNAs had mainly developed in important pathways related with glioma, e.g., the "cAMP signaling pathway," "glutamatergic synapses," and "calcium signaling pathway".

Conclusion

A newly discovered 7-microRNA signature could be a potential target for the diagnosis and treatment for LGG patients.

Cilium induction triggers differentiation of glioma stem cells

Glioblastoma multiforme (GBM) possesses glioma stem cells (GSCs) that promote self-renewal, tumor propagation, and relapse. Understanding the mechanisms of GSCs self-renewal can offer targeted therapeutic interventions. However, insufficient knowledge of GSCs' fundamental biology is a significant bottleneck hindering these efforts. Here, we show that patient-derived GSCs recruit elevated levels of proteins that ensure the temporal cilium disassembly, leading to suppressed ciliogenesis. Depleting the cilia disassembly complex components is sufficient to induce ciliogenesis in a subset of GSCs via relocating platelet-derived growth factor receptor-alpha (PDGFR-α) to a newly induced cilium. Importantly, restoring ciliogenesis enabled GSCs to switch from self-renewal to differentiation. Finally, using an organoid-based glioma invasion assay and brain xenografts in mice, we establish that ciliogenesis-induced differentiation can prevent the infiltration of GSCs into the brain. Our findings illustrate a role for cilium as a molecular switch in determining GSCs' fate and suggest cilium induction as an attractive strategy to intervene in GSCs proliferation.

Rapid and Efficient Invasion Assay of Glioblastoma in Human Brain Organoids

Glioblastoma (GBM) possesses glioma stem cells (GSCs) that exhibit aggressive invasion behavior in the brain. Current preclinical GBM invasion assays using mouse brain xenografts are time consuming and less efficient. Here, we demonstrate an array of methods that allow rapid and efficient assaying of GSCs invasion in human brain organoids. The assays are versatile to characterize various aspects of GSCs, such as invasion, integration, and interaction with mature neurons of brain organoids. Tissue clearing and quantitative 3D imaging of GSCs in host organoids reveal that invasiveness is inversely correlated with the organoids' age. Importantly, the described invasion assays can distinguish the invasive behaviors of primary and recurrent GSCs. The assays are also amenable to test pharmacological agents. As an example, we show that GI254023X, an inhibitor of ADAM10, could prevent the integration of GSCs into the organoids.

Deregulated expression of the imprinted DLK1-DIO3 region in glioblastoma stemlike cells: tumor suppressor role of lncRNA MEG3

Background

Glioblastoma (GBM) stemlike cells (GSCs) are thought to be responsible for the maintenance and aggressiveness of GBM, the most common primary brain tumor in adults. This study aims at elucidating the involvement of deregulations within the imprinted delta-like homolog 1 gene‒type III iodothyronine deiodinase gene (DLK-DIO3) region on chromosome 14q32 in GBM pathogenesis.

Methods

Real-time PCR analyses were performed on GSCs and GBM tissues. Methylation analyses, gene expression, and reverse-phase protein array profiles were used to investigate the tumor suppressor function of the maternally expressed 3 gene (MEG3).

Results

Loss of expression of genes and noncoding RNAs within the DLK1-DIO3 region was observed in GSCs and GBM tissues compared with normal brain. This downregulation is mainly mediated by epigenetic silencing. Kaplan–Meier analysis indicated that low expression of MEG3 and MEG8 long noncoding (lnc)RNAs significantly correlated with short survival in GBM patients. MEG3 restoration impairs tumorigenic abilities of GSCs in vitro by inhibiting cell growth, migration, and colony formation and decreases in vivo tumor growth, reducing infiltrative growth. These effects were associated with modulation of genes involved in cell adhesion and epithelial-to-mesenchymal transition (EMT).

Conclusion

In GBM, MEG3 acts as a tumor suppressor mainly regulating cell adhesion, EMT, and cell proliferation, thus providing a potential candidate for novel GBM therapies.

A compound downregulation of SRRM2 and miR-27a-3p with upregulation of miR-27b-3p in PBMCs of Parkinson's patients is associated with the early stage onset of disease

Parkinson’s disease (PD) is diagnosed when motor symptoms emerges, which almost 70% of dopamine neurons are lost. Therefore, early diagnosis of PD is crucial to prevent the progress of disease. Blood-based biomarkers, which are minimally invasive, potentially used for diagnosis of PD, including miRNAs. The aim of this study was to assess whether SRRM2 and miR-27a/b-3p could act as early diagnostic biomarkers for PD. Total RNAs from PBMCs of 30 PD’s patients and 14 healthy age and gender matched subjects was extracted. The expression levels of respective genes were assessed. Data were presented applying a two-tailed unpaired t-test and one-way ANOVA. We observed significant down-regulation of SRRM2 (p = 0.0002) and miR-27a-3p (p = 0.0001), and up-regulation of miR-27b-3p (p = 0.02) in PBMCs of Parkinson's patients. Down-regulation of miR-27a-3p is associated with increasing disease severity, whereas the up-regulation of miR-27b-3p was observed mostly at HY-1 and disease duration between 3–5 years. There was a negative correlation between SRRM2 and miR-27b-3p expressions, and miR-27a-3p positively was correlated with miR-27b-3p. Based on functional enrichment analysis, SRRM2 and miR-27a/b-3p acted on common functional pathways. miR-27a/b-3p could potentially predict the progression and severity of PD. Although both miRs had no similarity on expression, a positive correlation between both miRs was identified, supporting their potential role as biomarkers in clinical PD stages. Of note that SRRM2 and miR-27a-3p were able to distinguish PD patients from healthy individuals. Functional analysis of the similarity between genes associated with SRRM2 and miR-27a/b-3p indicates common functional pathways and their dysfunction correlates with molecular etiopathology mechanisms of PD onset.

Short tandem repeat profiling for the authentication of cancer stem-like cells

Colorectal and glioblastoma cancer stem‐like cells (CSCs) are essential for translational research. Cell line authentication by short tandem repeat (STR) profiling ensures reproducibility of results in oncology research. This technique enables to identify mislabeling or cross‐contamination of cell lines. In our study, we provide a reference dataset for a panel of colorectal and glioblastoma CSCs that allows authentication. Each cell line was entered into the cell Line Integrated Molecular Authentication database 2.1 to be compared to the STR profiles of 4485 tumor cell lines. This article also provides clinical data of patients from whom CSCs arose and data on the parent tumor stage and mutations. STR profiles and information of our CSCs are also available in the Cellosaurus database (ExPASy) as identified by unique research resource identifier codes.

Human cell lines obtained from cancer stem‐like cells represent an invaluable model for studying tumor properties. Cell line authentication by short tandem repeat (STR) profiling is an important tool to identify the potential mislabeling or cross‐contamination of cell lines. Here, the authors characterized 18 colorectal cancer stem‐like cell lines from 17 patients and 103 glioblastoma cancer stem‐like cell lines from 95 patients by STR profiling to create a reference dataset that allows the authentication of these cell lines and their identification through a unique research resource identifier. The results will help further ensure the reliability and reproducibility of research experiments.

Extracellular Vesicles Loaded miRNAs as Potential Modulators Shared Between Glioblastoma, and Parkinson's and Alzheimer's Diseases

Glioblastoma (GBM) is the deadliest brain tumor. Its poor prognosis is due to cell heterogeneity, invasiveness, and high vascularization that impede an efficient therapeutic approach. In the past few years, several molecular links connecting GBM to neurodegenerative diseases (NDDs) were identified at preclinical and clinical level. In particular, giving the increasing critical role that epigenetic alterations play in both GBM and NDDs, we deeply analyzed the role of miRNAs, small non-coding RNAs acting epigenetic modulators in several key biological processes. Specific miRNAs, transported by extracellular vesicles (EVs), act as intercellular communication signals in both diseases. In this way, miRNA-loaded EVs modulate GBM tumorigenesis, as they spread oncogenic signaling within brain parenchyma, and control the aggregation of neurotoxic protein (Tau, Aβ-amyloid peptide, and α-synuclein) in NDDs. In this review, we highlight the most promising miRNAs linking GBM and NDDs playing a significant pathogenic role in both diseases.

Identification of Prognostic Model and Biomarkers for Cancer Stem Cell Characteristics in Glioblastoma by Network Analysis of Multi-Omics Data and Stemness Indices

The progression of most human cancers mainly involves the gradual accumulation of the loss of differentiated phenotypes and the sequential acquisition of progenitor and stem cell-like features. Glioblastoma multiforme (GBM) stem cells (GSCs), characterized by self-renewal and therapeutic resistance, play vital roles in GBM. However, a comprehensive understanding of GBM stemness remains elusive. Two stemness indices, mRNAsi and EREG-mRNAsi, were employed to comprehensively analyze GBM stemness. We observed that mRNAsi was significantly related to multi-omics parameters (such as mutant status, sample type, transcriptomics, and molecular subtype). Moreover, potential mechanisms and candidate compounds targeting the GBM stemness signature were illuminated. By combining weighted gene co-expression network analysis with differential analysis, we obtained 18 stemness-related genes, 10 of which were significantly related to survival. Moreover, we obtained a prediction model from both two independent cancer databases that was not only an independent clinical outcome predictor but could also accurately predict the clinical parameters of GBM. Survival analysis and experimental data confirmed that the five hub genes (CHI3L2, FSTL3, RPA3, RRM2, and YTHDF2) could be used as markers for poor prognosis of GBM. Mechanistically, the effect of inhibiting the proliferation of GSCs was attributed to the reduction of the ratio of CD133 and the suppression of the invasiveness of GSCs. The results based on an in vivo xenograft model are consistent with the finding that knockdown of the hub gene inhibits the growth of GSCs in vitro. Our approach could be applied to facilitate the development of objective diagnostic and targeted treatment tools to quantify cancer stemness in clinical tumors, and perhaps lead considerable benefits that could predict tumor prognosis, identify new stemness-related targets and targeted therapies, or improve targeted therapy sensitivity. The five genes identified in this study are expected to be the targets of GBM stem cell therapy.

Different Mechanisms Underlie the Metabolic Response of GBM Stem-Like Cells to Ionizing Radiation: Biological and MRS Studies on Effects of Photons and Carbon Ions

Glioblastoma multiforme (GBM) is a malignant primary brain tumor with very poor prognosis, high recurrence rate, and failure of chemo-radiotherapy, mainly due to a small fraction of cells with stem-like properties (GSCs). To study the mechanisms of GSCs resistance to radiation, two GSC lines, named line #1 and line #83, with different metabolic patterns and clinical outcome, were irradiated with photon beams and carbon ions and assessed by ¹H Magnetic Resonance Spectroscopy (MRS). Both irradiation modalities induced early cytotoxic effects in line #1 with small effects on cell cycle, whereas a proliferative G2/M cytostatic block was observed in line #83. MR spectroscopy signals from mobile lipids (ML) increased in spectra of line #1 after photon and C-ion irradiation with effects on lipid unsaturation level, whereas no effects were detected in line #83 spectra. Gamma-Aminobutyric Acid (GABA), glutamic acid (glu) and Phosphocreatine (pCr) signals showed a significant variation only for line #1 after carbon ion irradiation. Glucose (glc) level and lactate (Lac) extrusion behaved differently in the two lines. Our findings suggest that the differences in irradiation response of GSCs #1 and #83 lines are likely attributable to their different metabolic fingerprint rather than to the different radiation types.

A five-microRNA signature for individualized prognosis evaluation and radiotherapy guidance in patients with diffuse lower-grade glioma

Despite the prognostic value of IDH and other gene mutations found in diffuse glioma, markers that judge individual prognosis of patients with diffuse lower‐grade glioma (LGG) are still lacking. This study aims to develop an expression‐based microRNA signature to provide survival and radiotherapeutic response prediction for LGG patients. MicroRNA expression profiles and relevant clinical information of LGG patients were downloaded from The Cancer Genome Atlas (TCGA; the training group) and the Chinese Glioma Genome Atlas (CGGA; the test group). Cox regression analysis, random survival forests‐variable hunting (RSFVH) screening and receiver operating characteristic (ROC) were used to identify the prognostic microRNA signature. ROC and TimeROC curves were plotted to compare the predictive ability of IDH mutation and the signature. Stratification analysis was conducted in patients with radiotherapy information. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to explore the biological function of the signature. We identified a five‐microRNA signature that can classify patients into low‐risk or high‐risk group with significantly different survival in the training and test datasets (P < 0.001). The five‐microRNA signature was proved to be superior to IDH mutation in survival prediction (AUCtraining = 0.688 vs 0.607). Stratification analysis found the signature could further divide patients after radiotherapy into two risk groups. GO and KEGG analyses revealed that microRNAs from the prognostic signature were mainly enriched in cancer‐associated pathways. The newly discovered five‐microRNA signature could predict survival and radiotherapeutic response of LGG patients based on individual microRNA expression.

Molecular subtyping of cancer: current status and moving toward clinical applications

Cancer is a collection of genetic diseases, with large phenotypic differences and genetic heterogeneity between different types of cancers and even within the same cancer type. Recent advances in genome-wide profiling provide an opportunity to investigate global molecular changes during the development and progression of cancer. Meanwhile, numerous statistical and machine learning algorithms have been designed for the processing and interpretation of high-throughput molecular data. Molecular subtyping studies have allowed the allocation of cancer into homogeneous groups that are considered to harbor similar molecular and clinical characteristics. Furthermore, this has helped researchers to identify both actionable targets for drug design as well as biomarkers for response prediction. In this review, we introduce five frequently applied techniques for generating molecular data, which are microarray, RNA sequencing, quantitative polymerase chain reaction, NanoString and tissue microarray. Commonly used molecular data for cancer subtyping and clinical applications are discussed. Next, we summarize a workflow for molecular subtyping of cancer, including data preprocessing, cluster analysis, supervised classification and subtype characterizations. Finally, we identify and describe four major challenges in the molecular subtyping of cancer that may preclude clinical implementation. We suggest that standardized methods should be established to help identify intrinsic subgroup signatures and build robust classifiers that pave the way toward stratified treatment of cancer patients.

Brain Invasion along Perivascular Spaces by Glioma Cells: Relationship with Blood-Brain Barrier

The question whether perivascular glioma cells invading the brain far from the tumor bulk may disrupt the blood-brain barrier (BBB) represents a crucial issue because under this condition tumor cells would be no more protected from the reach of chemotherapeutic drugs. A recent in vivo study that used human xenolines, demonstrated that single glioma cells migrating away from the tumor bulk are sufficient to breach the BBB. Here, we used brain xenografts of patient-derived glioma stem-like cells (GSCs) to show by immunostaining that in spite of massive perivascular invasion, BBB integrity was preserved in the majority of vessels located outside the tumor bulk. Interestingly, the tumor cells that invaded the brain for the longest distances traveled along vessels with retained BBB integrity. In surgical specimens of malignant glioma, the area of brain invasion showed several vessels with preserved BBB that were surrounded by tumor cells. On transmission electron microscopy, the cell inter-junctions and basal lamina of the brain endothelium were preserved even in conditions in which the tumor cells lay adjacently to blood vessels. In conclusion, BBB integrity associates with extensive perivascular invasion of glioma cells.

Molecular profiling of transcription factors pinpoints MYC-estrogen related receptor α-regulatory factor X5 panel for characterizing the immune microenvironment and predicting the efficacy of immune checkpoint inhibitors in renal cell carcinoma

Transcription factors (TFs) play key roles in biological processes, and previous studies revealed that they can control oncogenic processes. However, the functional impact of TFs on the prognosis of patients with cancer has not been extensively elucidated. In the context of The Cancer Genome Atlas, few studies have focused on the roles of TFs in tumorigenesis. In the present study, a TF-based robust MYC-estrogen related receptor α-regulatory factor X5 (MYC-ESRRA-RFX5) signature was developed for predicting the survival of patients with renal cell carcinoma. Functional enrichment analysis of this signature revealed that it was associated with the immune system of these patients. Further analysis demonstrated that this panel could characterize the immune microenvironment and potentially predicts the effectiveness of immune checkpoint inhibitors. Therefore, the present study recommends future exploration on TF-based biomarkers for their potential as prognostic predictors. Overall, the highlights of this study are: i) This novel study pinpoints a TF panel for the robust prediction of renal cell carcinoma prognosis, and ii) the MYC-ESRRA-RFX5 panel is proposed as a signature for characterizing the immune microenvironment, and to potentially predict the effectiveness of immune checkpoint inhibitors.

microRNA-181d associated with the methylation status of the MGMT gene in Glioblastoma multiforme cancer stem cells submitted to treatments with ionizing radiation and temozolomide

Despite the increased understanding of the oncological mechanisms underlying Glioblastoma multiforme (GBM) pathophysiology, and recent advances in therapeutic strategies such as maximal surgical resection and post-operative radiotherapy with concomitant and adjuvant temozolomide chemotherapy, the prognosis for patients with brain tumors remains limited. Evidences indicate that the assessment of DNA methylation status in cancer stem cells would allow identifying molecules expressed in these cells, to lead to targeted elimination of this critical population from brain tumors, making the glioblastoma treatment more effective. This study aimed to analyze the role of microRNA-181d associated with the methylation status of the O₆-methylguanine methyl transferase (MGMT) gene in Glioblastoma multiforme cancer stem cells subjected to treatment with temozolomide and ionizing radiation. Such responses were analyzed in terms of cell survival, evaluation of the MGMT gene methylation status by MS-HRM (Methylation-Sensitive High Resolution Melting), and analysis of miRNA-181d and MGMT gene expression by relative quantification of mRNA levels in cancer stem cells subjected to treatment with temozolomide and ionizing radiation, isolated or combined. We showed that ionizing radiation and temozolomide reduced the viability of cancer stem cells from GBM patients, as well as modified MGMT gene and miRNA-181d expression in cancer stem cells, suggesting that miRNA-181d interferes in the glioblastoma cancer stem cell response to treatment with temozolomide and ionizing radiation.

Improving the estimation of prognosis for glioblastoma patients by MR based hemodynamic tissue signatures

Advanced MRI and molecular markers have been raised as crucial to improve prognostic models for patients having glioblastoma (GBM) lesions. In particular, different MR perfusion based markers describing vascular intrapatient heterogeneity have been correlated with tumor aggressiveness, and represent key information to understand tumor resistance against effective therapies of these neoplasms. Recently, hemodynamic tissue signature (HTS) markers based on MR perfusion images have been demonstrated to be useful for describing the heterogeneity of GBM at the voxel level, as well as demonstrating significant correlations with the patient's overall survival. In this work, we analyze the abilities of these markers to improve the conventional prognostic models based on clinical, morphological, and demographic features. Our results, in both the regression and classification tests, show that inclusion of the HTS markers improves the reliability of prognostic models. The HTS method is fully automatic and it is available for research use at http://www.oncohabitats.upv.es.

A 4-microRNA signature for survival prognosis in pediatric and adolescent acute myeloid leukemia

Acute myeloid leukemia (AML) is a hematologic malignancy with significant molecular heterogeneity. MicroRNAs (miRNAs) play a critical role in AML diagnosis, pathogenesis, and prognosis of AML. Little has been done to identify a miRNA signature in pediatric and adolescent patients for predicting overall survival. This study aims to identify a panel of miRNA signature that could predict the prognosis of all younger AML patients with all subtypes of AML by analyzing data from The Cancer Genome Atlas (TCGA). A total of 229 patients under 23 years with miRNA data and corresponding clinical data from TCGA database were enrolled in this study. Through conducting multivariate analysis in the training test, it was identified that the high expression of hsa-miR-509 and hsa-miR-542 were independent poor prognostic factors, whereas that of hsa-miR-146a and hsa-miR-3667 had a trend to be favorable factors. A 4-miRNA signature was constructed by these miRNAs considering the weight of each. In testing group and all 229 patients' cohort as well as 59 cytogenetically normal AML (CN-AML) patients' cohort, higher risk score was associated with shorter overall survival (OS). All results were confidential by using powerful statistical analysis. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis were carried out to further develop leukemia-relevant mechanisms supporting the model. The results indicate that the 4-miRNA-based signature is a reliable prognostic biomarker for pediatric and adolescent AML patients.

Metabolic Heterogeneity Evidenced by MRS among Patient-Derived Glioblastoma Multiforme Stem-Like Cells Accounts for Cell Clustering and Different Responses to Drugs

Clustering of patient-derived glioma stem-like cells (GSCs) through unsupervised analysis of metabolites detected by magnetic resonance spectroscopy (MRS) evidenced three subgroups, namely clusters 1a and 1b, with high intergroup similarity and neural fingerprints, and cluster 2, with a metabolism typical of commercial tumor lines. In addition, subclones generated by the same GSC line showed different metabolic phenotypes. Aerobic glycolysis prevailed in cluster 2 cells as demonstrated by higher lactate production compared to cluster 1 cells. Oligomycin, a mitochondrial ATPase inhibitor, induced high lactate extrusion only in cluster 1 cells, where it produced neutral lipid accumulation detected as mobile lipid signals by MRS and lipid droplets by confocal microscopy. These results indicate a relevant role of mitochondrial fatty acid oxidation for energy production in GSCs. On the other hand, further metabolic differences, likely accounting for different therapy responsiveness observed after etomoxir treatment, suggest that caution must be used in considering patient treatment with mitochondria FAO blockers. Metabolomics and metabolic profiling may contribute to discover new diagnostic or prognostic biomarkers to be used for personalized therapies.

Interest of integrins targeting in glioblastoma according to tumor heterogeneity and cancer stem cell paradigm: an update

Glioblastomas are malignant brain tumors with dismal prognosis despite standard treatment with surgery and radio/chemotherapy. These tumors are defined by an important cellular heterogeneity and notably contain a particular subpopulation of Glioblastoma-initiating cells, which recapitulate the heterogeneity of the original Glioblastoma. In order to classify these heterogeneous tumors, genomic profiling has also been undertaken to classify these heterogeneous tumors into several subtypes. Current research focuses on developing therapies, which could take into account this cellular and genomic heterogeneity. Among these targets, integrins are the subject of numerous studies since these extracellular matrix transmembrane receptors notably controls tumor invasion and progression. Moreover, some of these integrins are considered as membrane markers for the Glioblastoma-initiating cells subpopulation. We reviewed here integrin expression according to glioblastoma molecular subtypes and cell heterogeneity. We discussed their roles in glioblastoma invasion, angiogenesis, therapeutic resistance, stemness and microenvironment modulations, and provide an overview of clinical trials investigating integrins in glioblastomas. This review highlights that specific integrins could be identified as selective glioblastoma cells markers and that their targeting represents new diagnostic and/or therapeutic strategies.

CDK4/6 inhibition is more active against the glioblastoma proneural subtype

Glioblastoma (GBM) is the most common and lethal brain tumor. Gene expression profiling has classified GBM into distinct subtypes, including proneural, mesenchymal, and classical, and identifying therapeutic vulnerabilities of these subtypes is an extremely high priority. We leveraged The Cancer Genome Atlas (TCGA) data, in particular for microRNA expression, to seek druggable core pathways in GBM. The E2F1-regulated miR-17˜92 cluster and its analogs are shown to be highly expressed in proneural GBM and in GSC lines, suggesting the E2F cell cycle pathway might be a key driver in proneural GBM. Consistently, CDK4/6 inhibition with palbociclib preferentially inhibited cell proliferation in vitro in a majority of proneural GSCs versus those of other subtypes. Palbociclib treatment significantly prolonged survival of mice with established intracranial xenografts of a proneural GSC line. We show that most of these sensitive PN GSCs expressed higher levels of CDK6 and had intact Rb1, while two GSC lines with CDK4 overexpression and null Rb1 were highly resistant to palbociclib. Importantly, palbociclib treatment of proneural GSCs upregulated mesenchymal-associated markers and downregulated proneural-associated markers, suggesting that CDK4/6 inhibition induced proneural-mesenchymal transition and underscoring the enhanced role of the E2F cell cycle pathway in the proneural subtype. Lastly, the combination of palbociclib and N,N-diethylaminobenzaldehyde, an inhibitor of the mesenchymal driver ALDH1A3, showed strong synergistic inhibitory effects against proneural GSC proliferation. Taken together, our results reveal that proneural GBM has increased vulnerability to CDK4/6 inhibition, and the proneural subtype undergoes dynamic reprogramming upon palbociclib treatment-suggesting the need for a combination therapeutic strategy.

The Role of miRNAs in Angiogenesis, Invasion and Metabolism and Their Therapeutic Implications in Gliomas

MicroRNAs (miRNAs) are small, non-coding, endogenous RNA molecules that function in gene silencing by post-transcriptional regulation of gene expression. The dysregulation of miRNA plays a pivotal role in cancer tumorigenesis, including the development and progression of gliomas. Their small size, stability and ability to target multiple oncogenes have simultaneously distinguished miRNAs as attractive candidates for biomarkers and novel therapeutic targets for glioma patients. In this review, we summarize the most frequently cited miRNAs known to contribute to gliomagenesis and progression by regulating the defining hallmarks of gliomas, including angiogenesis, invasion, and cell metabolism. We also discuss their promising potential as prognostic and predictive biomarkers and novel therapeutic targets, in addition to the challenges that must be overcome before their translation from bench to bedside.