• cns cancer
• rnai

• Adult
• Humans
• Animals
• Mice
• MicroRNAs/genetics
• Glioblastoma/genetics
• Biopsy
• Cell Death
• Disease Models, Animal

• adrenocortical carcinoma
• immunology
• prognosis
• signatures
• tumor microenvironment

• Adrenal Cortex Neoplasms/genetics
• Adrenal Cortex Neoplasms/metabolism
• Adrenal Cortex Neoplasms/pathology
• Adrenocortical Carcinoma/genetics
• Adrenocortical Carcinoma/metabolism
• Adrenocortical Carcinoma/pathology
• Biomarkers, Tumor/genetics
• Gene Expression Regulation, Neoplastic
• Humans
• Prognosis
• Tumor Microenvironment/genetics

• Science and Technology Commission of Shanghai Municipality
• Shanghai Hospital Development Center

• Bioinformatics
• CNS tumors
• Datasets
• Glioblastoma
• Glioma
• miRNA

• Cervical cancer
• immune
• long non-coding RNA (lncRNA)
• signature
• survival

• ADAMTS
• C-Myc
• CXCR4
• K-Ras
• MMP9
• metastasis
• miR-33b
• ovarian cancer

Skin cutaneous melanoma (SKCM) is the most aggressive skin cancer that results in high morbidity and mortality rate worldwide. Immune-related long non-coding RNAs (IRlncRs) play an important role in regulating gene expression in tumors. Therefore, in this study, we aimed to identify IRlncRs signature that could predict prognosis and therapeutic targets for melanoma irrespective of the gene expression levels.

RNA-sequencing data were obtained from The Cancer Genome Atlas (TCGA). IRlncRs were identified using co-expression analysis and recognized using univariate analysis. The impact of IRlncRs on survival was analyzed using a modified least absolute shrinkage and selection operator (Lasso) regression model. A 1-year survival receiver operating characteristic curve was constructed, and the area under the curve was calculated to identify the optimal cut-off point to distinguish between high and low-risk groups in patients with SKCM. Furthermore, integrative analysis was performed to identify the impact of clinicopathological features, chemotherapeutic treatment, tumor-infiltrating immune cells, and mutant genes on survival.

A total of 28 IRlncRs significantly associated with survival were identified. Seventeen IRlncRs pairs were used to build a survival risk model that could be used to distinguish between low and high-risk groups. The high-risk group was negatively associated with tumor-infiltrating immune cells and had a higher half inhibitory centration for chemotherapeutic agents such as cisplatin and vinblastine. Additionally, the high-risk group had a positive correlation with the expression of specific mutant genes such as BRAF and KIT.

Our findings demonstrate that some IRlncRs have a significant correlation with survival and therapeutic targets for SKCM patients and may provide new insight into the clinical diagnosis and treatment strategies for SKCM patients.

• immune-related gene
• long non-coding RNA signature
• melanoma
• prognosis
• the cancer genome atlas

The dysregulated long noncoding RNAs (lncRNAs) have been described to be crucial regulators in the progression of ovarian carcinoma. The infiltration status of immune cells is also related to the clinical outcomes in ovarian carcinoma. The present research is aimed at constructing an immune-associated lncRNA signature with potential prognostic value for ovarian carcinoma patients.

We obtained 379 ovarian carcinoma cases with available clinical data and transcriptome data from The Cancer Genome Atlas database to evaluate the infiltration status of immune cells, thereby generating high and low immune cell infiltration groups. According to the expression of the immune-associated lncRNA signature, the risk score of each case was calculated. The high- and low-risk groups were classified using the median risk score as threshold.

A total of 169 immune-associated lncRNAs that differentially expressed in ovarian carcinoma were included. According to the Lasso regression analysis and Cox univariate and multivariate analyses, 5 immune-associated lncRNAs, including AC134312.1, AL133467.1, CHRM3-AS2, LINC01722, and LINC02207, were identified as a predictive signature with significant prognostic value in ovarian carcinoma. The following Kaplan-Meier analysis, ROC analysis, and Cox univariate and multivariate analyses further suggested that the predicted signature may be an independent prognosticator for patients with ovarian carcinoma. The following gene set enrichment analysis showed that this 5 immune-associated lncRNAs signature was significantly related to the hedgehog pathway, basal cell carcinoma, Wnt signaling pathway, cytokine receptor interaction, antigen processing and presentation, and T cell receptor pathway.

: This study suggested a predictive model with 5 immune-associated lncRNAs that has an independent prognostic value for ovarian carcinoma patients.

Malignant glioma with a mesenchymal (MES) signature is characterized by shorter survival time due to aggressive dissemination and resistance to chemoradiotherapy. Here, this study used the TCGA database as the training set and the CGGA database as the testing set. Consensus clustering was performed on the two data sets, and it was found that two groups had distinguished prognostic and molecular features. Cox analysis and Lasso regression analysis were used to construct MES signature-based risk score model of glioma. Our results show that MES signature-based risk score model can be used to assess the prognosis of glioma. Three methods (ROC curve analyses, univariate Cox regression analysis, multivariate Cox regression analysis) were used to investigate the prognostic role of texture parameters. The result showed that the MES-related gene signature was proved to be an independent prognostic factor for glioma. Furthermore, functional analysis of the gene related to the risk signature showed that the genes sets were closely related to the malignant process of tumors. Finally, FCGR2A and EHD2 were selected for functional verification. Silencing these two genes inhibited the proliferation, migration and invasion of gliomas and reduced the expression of mesenchymal marker genes. Collectively, MES-related risk signature seems to provide a novel target for predicting the prognosis and treatment of glioma.

• gene signature
• glioma
• mesenchymal
• prognosis
• proliferation

• TCGA
• autophagy
• bladder cancer
• lncRNA
• prognostic indicator

The incidence of stage I and stage II lung adenocarcinoma (LUAD) is likely to increase with the introduction of annual screening programs for high-risk individuals. We aimed to identify a reliable prognostic signature with immune-related genes that can predict prognosis and help making individualized management for patients with early-stage LUAD.

The public LUAD cohorts were obtained from the large-scale databases including 4 microarray data sets from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA) LUAD cohort. Only early-stage patients with clinical information were included. Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set). The prognostic signature was developed using the overlapped prognostic genes based on a risk score method. Kaplan–Meier curve with log-rank test and time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic value and performance of this signature, respectively. Furthermore, the robustness of this prognostic signature was further validated in TCGA-LUAD and GSE72094 cohorts.

A prognostic immune signature consisting of 21 immune-related genes was constructed using the training set. The prognostic signature significantly stratified patients into high- and low-risk groups in terms of overall survival (OS) in training data set, including GSE30219 (HR = 4.31, 95% CI 2.29–8.11; P = 6.16E−06), GSE31210 (HR = 11.91, 95% CI 4.15–34.19; P = 4.10E−06), GSE50081 (HR = 3.63, 95% CI 1.90–6.95; P = 9.95E−05), the combined data set (HR = 3.15, 95% CI 1.98–5.02; P = 1.26E−06) and the validation data set, including TCGA-LUAD (HR = 2.16, 95% CI 1.49–3.13; P = 4.54E−05) and GSE72094 (HR = 2.95, 95% CI 1.86–4.70; P = 4.79E−06). Multivariate cox regression analysis demonstrated that the 21-gene signature could serve as an independent prognostic factor for OS after adjusting for other clinical factors. ROC curves revealed that the immune signature achieved good performance in predicting OS for early-stage LUAD. Several biological processes, including regulation of immune effector process, were enriched in the immune signature. Moreover, the combination of the signature with tumor stage showed more precise classification for prognosis prediction and treatment design.

Our study proposed a robust immune-related prognostic signature for estimating overall survival in early-stage LUAD, which may be contributed to make more accurate survival risk stratification and individualized clinical management for patients with early-stage LUAD.

• Immune-related genes
• Lung adenocarcinoma
• Overall survival
• Prognosis
• Risk score

• DNA damage
• H3K36me3
• LINE-1 methylation
• MGMT methylation
• occupational PAH exposure

• immune-related
• lncRNA signature
• muscle-invasive bladder cancer
• nomogram
• prognostic model

• Glioma
• Immunosuppression
• Prognosis
• Tumor-associated macrophages

• Glioblastoma
• N 6-Methyladenosine
• RNA microarray
• RNA sequencing
• lncRNAs

• adjuvant therapy
• age
• genomic alteration
• glioblastoma
• prognosis

• diffuse glioma
• lipid metabolism
• prognosis
• progression
• signature

As aldehyde dehydrogenase (ALDH) is a novel stem cell marker, increasing studies have confirmed that high ALDH activity promotes tumorigenesis and progression in cancers. Some preliminary studies have found that ALDH1A3 may play an important role in glioma malignant progression, but so far there was no conclusive conclusion. The purpose of our study was to elucidate the mechanisms by which ALDH1A3 regulated in glioma and to provide practical tools for clinical application. Aldefluor, flow cytometry sorting and qRT-PCR were performed to verify the role of ALDH1A3 in ALDH activity maintenance. Transwell, immunofluorescence, glycolytic assays, and orthotopic xenograft models were used to explore ALDH1A3 bio-functions in GBM. LASSO-COX, COX survival analysis and Kaplan–Meier analysis were used to establish the prognostic evaluation system and predict postoperative chemotherapy sensitivity of GBMs. Our integrated study found that (1) ALDH1A3 associates with mesenchymal differentiation of GBM in Eastern and Western world patients. (2) ALDH1A3 plays a critical role in ALDH activity maintenance. (3) ALDH1A3 is an activator of mesenchymal transformation in GBM. (4) ALDH1A3-derived PMT markers’ molecular signature can predict 1-, 2-, and 3-year survival rates of GBMs precisely. In conclusion, ALDH1A3 was a major contributor to ALDH activity and a key driver in triggering mesenchymal transformation in GBM. ALDH1A3-based molecular classification scheme can help to improve guidance for prognosis forecasting and individualized treatment decision making for GBM patients.

• Glioblastoma
• Invasion
• Migration
• Proliferation
• STC2
• miR-184

• Brain Neoplasms/metabolism
• Brain Neoplasms/mortality
• Brain Neoplasms/pathology
• Cell Line, Tumor
• Cell Movement/genetics
• Cell Proliferation/genetics
• Gene Expression Regulation, Neoplastic/genetics
• Glioblastoma/metabolism
• Glioblastoma/mortality
• Glioblastoma/pathology
• Glycoproteins/biosynthesis
• Glycoproteins/genetics
• Humans
• Intercellular Signaling Peptides and Proteins/biosynthesis
• Intercellular Signaling Peptides and Proteins/genetics
• MicroRNAs/genetics
• MicroRNAs/metabolism
• Neoplasm Invasiveness/genetics
• Neoplasm Invasiveness/pathology
• Survival Rate

• TGFBR2
• ceRNA network
• mesenchymal subtype
• micNETs

• Animals
• Brain Neoplasms/pathology
• Carcinogenesis
• Cell Line, Tumor
• Disease Models, Animal
• Gene Expression Regulation
• Gene Regulatory Networks
• Glioblastoma/pathology
• Heterografts
• Humans
• Mice
• MicroRNAs/analysis
• MicroRNAs/biosynthesis
• Neoplasm Transplantation
• RNA, Messenger/analysis
• RNA, Messenger/biosynthesis
• Transcriptome
• Transforming Growth Factor beta/metabolism

• Glioblastoma
• MicroRNAs (miRNAs)
• O-6-methylguanine-DNA methyltransferase (MGMT)
• epigenetic silencing
• promoter methylation

• Brain metastases
• Brain tumor
• CNS
• CSF
• CTC
• Central nervous system
• Cerebrospinal fluid
• Circulating tumor DNA
• Circulating tumor cells
• Liquid biopsy
• RNA
• cfDNA
• ctDNA
• miRNA

To identify a gene-based signature as a novel prognostic model in lower grade gliomas.

A gene signature developed from HOXA7, SLC2A4RG and MN1 could segregate patients into low and high risk score groups with different overall survival (OS), and was validated in TCGA RNA-seq and GSE16011 mRNA array datasets. Receiver operating characteristic (ROC) was performed to show that the three-gene signature was more sensitive and specific than histology, grade, age, IDH1 mutation and 1p/19q co-deletion. Gene Set Enrichment Analysis (GSEA) and GO analysis showed high-risk samples were associated with tumor associated macrophages (TAMs) and highly invasive phenotypes. Moreover, HOXA7-siRNA inhibited migration and invasion in vitro, and downregulated MMP9 at the protein level in U251 glioma cells.

A cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group. TCGA RNA-seq and GSE16011 mRNA array datasets were used for validation. Regression analyses and linear risk score assessment were performed for the identification of the three-gene signature comprising HOXA7, SLC2A4RG and MN1.

We established a three-gene signature for lower grade gliomas, which could independently predict overall survival (OS) of lower grade glioma patients with higher sensitivity and specificity compared with other clinical characteristics. These findings indicate that the three-gene signature is a new prognostic model that could provide improved OS prediction and accurate therapies for lower grade glioma patients.

• gene signature
• lower grade glioma
• prognosis
• risk score

High grade gliomas contribute to most brain tumor mortality. A few studies reported that the immune system affected glioma development, and immune biomarkers helped understand the disease and formulate effective immunotherapy for patients. Currently, no B lymphocyte-based prognostic signature was reported in gliomas. By applying 78 B cell lineage-specific genes, we conducted a whole-genome gene expression analysis in 782 high grade gliomas derived from three independent datasets by Cox regression analysis and risk score method for signature identification, and then used Gene Ontology, Gene Set Enrichment Analysis, and other statistical methods for functional annotations of the signature-defined differences. We developed a five B cell-associated gene signature for prognosis of high grade glioma patients, which is independent of clinicopathological and genetic features. The signature identified high risk patients suitable for chemoradiotherapy, whereas low risk patients should rule out chemotherapy with radiotherapy only. We found that tumors of TCGA Mesenchymal subtype and wild type IDH1 were preferentially stratified to the high risk group, which bore strong immunosuppressive microenvironment, while tumors of TCGA Proneural subtype and mutated IDH1 were significantly accumulated to the low risk group, which exhibited less immunosuppressive state. The five B cell-associated gene signature predicts poor survival of high risk patients bearing strong immunosuppression and helps select optimal therapeutic regimens for glioma patients.

• biomarker
• glioma
• immune system
• prognosis
• tumor-infiltrating B cells

Cancer biomarkers with a strong predictive power for diagnosis/prognosis and a potential to be therapeutic targets have not yet been fully established. Here we employed a loss-of-function screen in glioblastoma (GBM), an infiltrative brain tumor with a dismal prognosis, and identified 20 survival kinase genes (SKGs). Survival analyses using The Cancer Genome Atlas (TCGA) datasets revealed that the expression of CDCP1, CDKL5, CSNK1E, IRAK3, LATS2, PRKAA1, STK3, TBRG4, and ULK4 stratified GBM prognosis with or without temozolomide (TMZ) treatment as a covariate. For the first time, we found that GBM patients with a high level of NEK9 and PIK3CB had a greater chance of having recurrent tumors. The expression of CDCP1, IGF2R, IRAK3, LATS2, PIK3CB, ULK4, or VRK1 in primary GBM tumors was associated with recurrence-related prognosis. Notably, the level of PIK3CB in recurrent tumors was much higher than that in newly diagnosed ones. Congruent with these results, genes in the PI3K/AKT pathway showed a significantly strong correlation with recurrence rate, further highlighting the pivotal role of PIK3CB in the disease progression. Importantly, 17 SKGs together presented a novel GBM prognostic signature. SKGs identified herein are associated with recurrence rate and present prognostic significance in GBM, thereby becoming attractive therapeutic targets.

• PIK3CB
• glioblastoma
• prognosis
• survival kinase genes
• tumor recurrence

Glioma is a malignant nervous system tumor with a high fatality rate and poor prognosis. MicroRNAs (miRNAs) are important post-transcriptional modulators of glioma initiation and progression. Tumor progression often results from dysfunctional co-operation between pathways regulated by miRNAs. We therefore constructed a glioma progression-related miRNA-pathway crosstalk network that not only revealed some key miRNA-pathway patterns, but also helped characterize the functional roles of miRNAs during glioma progression. Our data indicate that crosstalk between cell cycle and p53 pathways is associated with grade II to grade III progression, while cell communications-related pathways involving regulation of actin cytoskeleton and adherens junctions are associated with grade IV glioblastoma progression. Furthermore, miRNAs and their crosstalk pathways may be useful for stratifying glioma and glioblastoma patients into groups with short or long survival times. Our data indicate that a combination of miRNA and pathway crosstalk information can be used for survival prediction.

• glioma progression
• miRNAs
• pathway crosstalk

• Anaplastic glioma
• Immune
• Long non-coding RNA
• RNA microarray
• Signature

Glioblastomas are among the most lethal cancers; however, recent advances in survival have increased the need for better prognostic markers. microRNAs (miRNAs) hold great prognostic potential being deregulated in glioblastomas and highly stable in stored tissue specimens. Moreover, miRNAs control multiple genes representing an additional level of gene regulation possibly more prognostically powerful than a single gene. The aim of the study was to identify a novel miRNA signature with the ability to separate patients into prognostic subgroups. Samples from 40 glioblastoma patients were included retrospectively; patients were comparable on all clinical aspects except overall survival enabling patients to be categorized as short-term or long-term survivors based on median survival. A miRNome screening was employed, and a prognostic profile was developed using leave-one-out cross-validation. We found that expression patterns of miRNAs; particularly the four miRNAs: hsa-miR-107_st, hsa-miR-548x_st, hsa-miR-3125_st and hsa-miR-331-3p_st could determine short- and long-term survival with a predicted accuracy of 78%. Heatmap dendrograms dichotomized glioblastomas into prognostic subgroups with a significant association to survival in univariate (HR 8.50; 95% CI 3.06–23.62; p<0.001) and multivariate analysis (HR 9.84; 95% CI 2.93–33.06; p<0.001). Similar tendency was seen in The Cancer Genome Atlas (TCGA) using a 2-miRNA signature of miR-107 and miR-331 (miR sum score), which were the only miRNAs available in TCGA. In TCGA, patients with O6-methylguanine-DNA-methyltransferase (MGMT) unmethylated tumors and low miR sum score had the shortest survival. Adjusting for age and MGMT status, low miR sum score was associated with a poorer prognosis (HR 0.66; 95% CI 0.45–0.97; p = 0.033). A Kyoto Encyclopedia of Genes and Genomes analysis predicted the identified miRNAs to regulate genes involved in cell cycle regulation and survival. In conclusion, the biology of miRNAs is complex, but the identified 4-miRNA expression pattern could comprise promising biomarkers in glioblastoma stratifying patients into short- and long-term survivors.

Worldwide, approximately 2% of new cancers are of the brain. Five-year survival rates among brain cancer patients have been reported as a little over a third. Differences in clinical outcomes between brain tumor patients of different races remain poorly understood.

A retrospective chart review was performed on brain tumor resection patients≥18 years old. Demographics, treatment variables, and survival outcomes were collected. Primary outcomes were length of stay, recurrence rate, progression-free survival (PFS), and overall survival (OS).

A total of 452 patients were included in analysis. Females and males had nearly a 1:1 ratio (n=242 and n=220, respectively). Mean age was 54.8 years (SD: 14.5 range: 18–90). Females composed 69% (n=48) of Asian patients; males constituted 31% (n=22). Mean age of the Asian patients was 55.9 years (SD: 14.6 range: 26–89). Asian-only cohort tumor pathologies included glioblastoma (GBM) (n=14), high-grade glioma (n=7), low-grade glioma (n=4), meningioma (n=38), and metastases (n=7). Of the 185 meningioma patients, non-Asian patients comprised 79% of the group (n=146). Of the 65 GBM patients in total, non-Asian patients made up 89% of the GBM cohort (n=58). There were no statistically significant differences between these groups of both cohorts in recurrence (p=0.1580 and p=0.6294, respectively), PFS (p=0.9662 and p=0.4048, respectively), or OS (p=0.3711 and p=0.8183, respectively).

Studies evaluating the survival between patients of different racial backgrounds against several tumor varieties are rare. Patients of certain racial backgrounds may need additional consideration when being attended to despite the same mutational composition as their counterparts. Repeated studies using national databases may yield more conclusive results.

• Biomarkers
• Brain neoplasms
• Glioblastoma
• Meningioma
• Race

• Biomarkers
• Glioblastoma (GBM)
• MicroRNAs (miRNAs)
• miRNA-based therapies

Glioblastoma (GBM) is the most common and aggressive type of primary human brain tumor in China. Dysregulated microRNA (miRNA/miR) expression has been hypothesized to serve a role in the tumorigenesis and progression of human GBM. To explore the potential mechanisms affecting GBM tumorigenesis, the function of miR-518b in regulating GBM cell proliferation and angiogenesis was examined in vitro by CCK-8 and tube formation assay and in vivo by xenograft assay. The present study demonstrated that the expression of miR-518b was downregulated in GBM tissues and in GBM cell lines (U87 and U251). In addition, the expression levels of miR-518b were highly associated with tumor size, World Health Organization grade and prognosis. Furthermore, overexpression of miR-518b suppressed GBM cell proliferation and angiogenesis, and induced GBM cell apoptosis in vitro and in vivo. Overexpression of miR-518b also inhibited the expression of platelet-derived growth factor receptor β (PDGFRB), and the present study confirmed that the 3′ untranslated region (3′UTR) of PDGFRB was a direct target of miR-518b. In conclusion, to the best of our knowledge, the present study is the first to present evidence suggesting that miR-518b may serve as a potential marker and target in GBM treatment.

• EGFR/EGFRvIII
• Hippo
• Notch
• TGFβ
• miR-524

Anaplastic gliomas are characterized by variable clinical and genetic features, but there are few studies focusing on the substratification of anaplastic gliomas. To identify a more objective and applicable classification of anaplastic gliomas, we analyzed whole genome mRNA expression profiling of four independent datasets. Univariate Cox regression, linear risk score formula and receiver operating characteristic (ROC) curve were applied to derive a gene signature with best prognostic performance. The corresponding clinical and molecular information were further analyzed for interpretation of the different prognosis and the independence of the signature. Gene ontology (GO), Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA) were performed for functional annotation of the differences. We found a three-gene signature, by applying which, the anaplastic gliomas could be divided into low risk and high risk groups. The two groups showed a high concordance with grade II and grade IV gliomas, respectively. The high risk group was more aggressive and complex. The three-gene signature showed diagnostic and prognostic value in anaplastic gliomas.

• anaplastic glioma
• diagnosis
• mRNA
• prognosis
• signature

Recent studies indicated that some glycolytic enzymes are complicated, multifaceted proteins rather than simple components of the glycolytic pathway. FBP1 plays a vital role in glucose metabolism, but its role in gastric cancer tumorigenesis and metastasis has not been fully understood.

The prognostic value of FBP1 was first studied in The Cancer Genome Atlas (TCGA) database and validated in in-house database. The effect of FBP1 on cell proliferation and metastasis was examined in vitro. Nonparametric test and Log-rank test were used to evaluate the clinical significance of FBP1 expression.

In the TCGA cohort, FBP1 mRNA level were shown to be predictive of overall survival in gastric cancer (P = 0.029). In the validation cohort, FBP1 expression were inversely correlated with advanced N stage (P = 0.021) and lymphovascular invasion (P = 0.011). Multivariate Cox regression analysis demonstrated that FBP1 was an independent predictor for both overall survival (P = 0.004) and disease free survival (P<0.001). Functional studies demonstrated that ectopic FBP1 expression inhibited proliferation and invasion in gastric cancer cells, while silencing FBP1 expression had opposite effects (P<0.05). Mechanically, FBP1 serves as a tumor suppressor by inhibiting epithelial-mesenchymal transition (EMT).

Downregulation of FBP1 promotes gastric cancer metastasis by facilitating EMT and acts as a potential prognostic factor and therapeutic target in gastric cancer.

• Adult
• Aged
• Aged, 80 and over
• Blotting, Western
• Cell Line, Tumor
• Cell Movement/genetics
• Cell Movement/physiology
• DNA Helicases/genetics
• DNA Helicases/metabolism
• DNA-Binding Proteins/genetics
• DNA-Binding Proteins/metabolism
• Epithelial-Mesenchymal Transition/genetics
• Epithelial-Mesenchymal Transition/physiology
• Female
• Humans
• Male
• Middle Aged
• Neoplasm Invasiveness/genetics
• Neoplasm Invasiveness/pathology
• Prognosis
• RNA-Binding Proteins
• Stomach Neoplasms/genetics
• Stomach Neoplasms/metabolism
• Stomach Neoplasms/pathology

• DNA methylation
• astrocytomas
• biomarkers
• brain tumors
• cancer
• epigenetic regulation
• genetic
• glioblastoma
• gliomas
• targeted therapy

• MGMT promoter methylation
• glioblastoma
• miRNA
• predictive model
• prognosis

• Apoptosis
• CYR 61
• Colorectal cancer
• MACC1
• MicroRNA

Accumulating evidence demonstrates that defining molecular subtypes based on objective genetic alterations may permit a more rational, patient-specific approach to molecular targeted therapy across various cancers. The objective of this study was to subtype primary glioblastoma (pGBM) based on MicroRNA (miRNA) profiling in Chinese population. Here, miRNA expression profiles from 82 pGBM samples were analyzed and 78 independent pGBM samples were used for qRT-PCR validation. We found that two distinct subgroups with different prognosis and chemosensitivities to temozolomide (TMZ) in Chinese pGBM samples. One subtype is TMZ chemoresistant (termed the TCR subtype) and confers a poor prognosis. The other subtype is TMZ-chemosensitive (termed the TCS subtype) and confers a relatively better prognosis compared with the TCR subtype. A classifier consisting of seven miRNAs was then identified (miR-1280, miR-1238, miR-938 and miR-423-5p (overexpressed in the TCR subtype); and let-7i, miR-151-3p and miR-93 (downregulated in the TCR subtype)), which could be used to assign pGBM samples to the corresponding subtype. The classifier was validated using both internal and external samples. Meanwhile, the genetic alterations of the TCR and TCS subtypes were also analyzed. The TCR subtype was characterized by no IDH1 mutation, and EGFR and Ki-67 overexpression. The TCS subtype displayed the opposite situation. Taken together, the results indicate a distinct subgroup with poor prognosis and TMZ-chemoresistance.

• IDH1 mutation
• glioblastoma
• microRNA
• temozolomide

• gene expression
• glioblastoma
• molecular alterations
• outcome prediction
• recurrence

• Biomarker
• Glioblastoma
• MicroRNA

• Biomarkers, Tumor/genetics
• Biomarkers, Tumor/metabolism
• Brain Neoplasms/diagnosis
• Brain Neoplasms/genetics
• Brain Neoplasms/metabolism
• Glioblastoma/diagnosis
• Glioblastoma/genetics
• Glioblastoma/metabolism
• Humans
• MicroRNAs

Mutations in isocitrate dehydrogenase 1 (IDH1) are found in >70% of secondary glioblastomas and lower-grade gliomas (grades II–III). Among the numerous phenotypic differences between IDH1 mutant and wild-type glioma patients, the most salient is an improved survival rate for patients with a mutation. MicroRNAs (miRNAs) are a class of small, non-coding, single-stranded RNAs that can negatively regulate gene expression at the post-transcriptional level, predominantly by binding to the 3′-untranslated region of their target mRNAs. The dysregulated expression of several miRNAs has been reported to modulate glioma progression; however, it is unclear whether mutations in IDH1 regulate glioma cell proliferation through miRNA dysregulation. In the present study, stable overexpression of IDH1^WT or IDH1^R132H was established in the U87 glioma cell line. It was found that IDH1^R132H decreased cell proliferation of U87 glioma cells by inducing the expression of the miRNA miR-128a. This process was dependent on the transcription factor hypoxia inducible factor-1α (HIF-1α), which binds to a hypoxia response element in the promoter of miR-128a. Furthermore, miR-128a negatively regulated the expression of B-cell-specific Moloney murine leukemia virus integration site 1 protein (Bmi-1), which is involved in suppressing cell proliferation. These findings suggest that the IDH1^R132H-HIF-1α-miR-128a-Bmi-1 pathway is involved in glioma cell proliferation.

The goal of this work was to explore the most effective miRNAs affecting glioblastoma multiforme (GBM) phenotype transition and malignant progression. We annotated 491 TCGA samples’ miRNA expression profiles according to their mRNA-based subtypes and found that the mesenchymal tumors had significantly decreased miR-181 family expression compared with the other three subtypes while the proneural subtype harbored extremely high miR-181 family expression. Patients with high miR-181 family expression had longer overall survival (p = 0.0031). We also confirmed that NF-κB-targeting genes and the EMT (epithelial-mesenchymal transition) pathway were inversely correlated with miR-181 family expression and that the entire miR-181 family inhibited glioma cell invasion and proliferation; of these, miR-181b was the most effective suppressor. Furthermore, miR-181b was validated to suppress EMT by targeting KPNA4 and was associated with survival outcome in the TCGA and CGGA datasets and in another independent cohort. The EMT-inhibitory effect of miR-181b was lost after KPNA4 expression was restored. We also identified the antitumorigenic activity of miR-181b in vitro and in vivo. Our results showed that miR-181 family expression was closely correlated with TCGA subtypes and patients’ overall survival, indicating that miR-181b, a tumor-suppressive miRNA, could be a novel therapeutic candidate for treating gliomas.

• Glioma
• biomarkers
• cell cycle
• microRNAs
• transcription factor

• Adolescent
• Adult
• Aged
• Aged, 80 and over
• Brain Neoplasms/diagnosis
• Brain Neoplasms/genetics
• Brain Neoplasms/mortality
• Brain Neoplasms/pathology
• Chemokine CCL2/genetics
• Chemokine CXCL10/genetics
• Cytokines/genetics
• DNA Methylation
• Glioblastoma/diagnosis
• Glioblastoma/genetics
• Glioblastoma/mortality
• Glioblastoma/pathology
• Humans
• Interleukin-10 Receptor beta Subunit/genetics
• Interleukin-17/genetics
• Macrophages/pathology
• Microglia/pathology
• Middle Aged
• Phenotype
• Prognosis
• Proportional Hazards Models
• Receptors, CCR2/genetics
• Receptors, Interleukin-17/genetics
• Risk Factors
• Survival Analysis
• Transcriptome
• Young Adult