Transcriptome-wide analysis of glioma stem cell specific m6A modifications in long-non-coding RNAs.

The interest in chemical RNA modifications is rapidly growing in the field of molecular biology. Dynamic and reversible alterations of N6-methyladenosine (m6A) RNA modification are responsible for a platter of structural and functional changes in healthy and cancerous cell states. Although many studies reported the link between tumor initiation/progression and m6A modulators, there are few studies exploring transcriptome-wide m6A profile of non-coding RNAs. The aim of current study was to identify glioma stem cell (GSC) specific m6A landscape of long non-coding RNAs (lncRNAs) applying MeRIP-seq approach. MeRIP-seq analysis assigned 77.9% of m6A peaks to mRNAs and 8.16% to lncRNAs. GSCs and differentiated cells showed 76.4% conservation of m6A peaks, while 19.4% were unique to GSCs. Seven novel GSC-specific m6A modified lncRNAs were identified: HRAT92, SLCO4A1-AS1, CEROX1, PVT1, AGAP2-AS1, MIAT, and novel lncRNA gene ENSG00000262223. Analysis disclosed a strong negative correlation between lncRNAs m6A modification rate and expression. MeRIP-seq analysis revealed m6A modifications on previously reported glioma-associated lncRNAs: LINC000461, HOTTIP, CRNDE, TUG1, and XIST. Moreover, current study disclosed that most highly m6A modified lncRNAs primarily contain m6A modifications close to 3' and 5' ends. Our results provide basis and insight for further studies of m6A modifications in non-coding transcriptome of GSCs.

Advanced image analysis-based evaluation of protein antibody microarray chemiluminescence signal improves glioma type identification by blood serum proteins concentrations.

BACKGROUND AND OBJECTIVE: Gliomas are the most common brain tumors usually classified as benign low-grade or aggressive high-grade glioma. One of the promising possibilities of glioma diagnostics and tumor type identification could be based on concentration measurements of glioma secreted proteins in blood. However, several published approaches of quantitative proteomic analysis emphasize limits of one single protein to be used as biomarker of these types of tumors. Simultaneous multi-protein concentrations analysis giving antibody array-based methods suffer from poor measurement accuracy due to technical limitations of imaging systems. METHODS: We applied Principal Component Analysis (PCA) for series of repeated antibody array chemiluminescence images to extract the component representing relative values of protein concentrations, free from zero-mean noise and uneven background illumination - main factors corrupting evaluation result. RESULTS: The proposed method increased accuracy of protein concentration estimates at least 2-fold. Decision tree classifier applied to the relative concentration values of three proteins TIMP-1, PAI-1 and NCAM-1 estimated by proposed image analysis method effectively distinguished between low-grade glioma, high-grade glioma and healthy control subjects showing validation accuracy of 74.9% with the highest positive predictive value of 81.2% for high grade glioma and 57.1% for low grade glioma cases. CONCLUSIONS: PCA-based image processing could be applied in protein antibody microarray and other multitarget detection/evaluation investigations to increase estimation accuracy.

Serum protein triplet TGF-ß1, TIMP-1, and YKL-40 serve as diagnostic and prognostic profile for astrocytoma.

Astrocytoma is the most common glial tumour of the CNS. The most malignant form is grade IV Astrocytoma, also called Glioblastoma. Due to its heterogeneity, aggressiveness and lethal nature scientists are trying to find less invasive methods for early prediction of tumour onset, recurrence, response to therapy and patients' survival. Here, applying decision tree classification algorithm we performed astrocytoma specific protein profile analysis on serum proteins TIMP-1, active and latent form of TGF-ß1, IP-10, ANGPT-1, OPN, and YKL-40 using enzyme-linked immunosorbent detection assay (ELISA). Results have demonstrated that astrocytoma specific profile consisted of three proteins-active form of TGF-ß1, TIMP-1 and YKL-40 and was able to correctly classify 78.0% (103/132) of sample and 83.3% (60/72) of astrocytoma sample. Calculating decision tree algorithm associated with astrocytoma patient survival, prediction model reached an accuracy of 83.3% (60/72). All together these results indicate that glioma detection and prediction from patient serum using glioma associated proteins and applying mathematical classification tools could be achieved, and applying more comprehensive research further could be implemented in clinic.

Nongenotoxic ABCB1 activator tetraphenylphosphonium can contribute to doxorubicin resistance in MX-1 breast cancer cell line.

Hyperactivation of ABC transporter ABCB1 and induction of epithelial-mesenchymal transition (EMT) are the most common mechanism of acquired cancer chemoresistance. This study describes possible mechanisms, that might contribute to upregulation of ABCB1 and synergistically boost the acquisition of doxorubicin (DOX) resistance in breast cancer MX-1 cell line. DOX resistance in MX-1 cell line was induced by a stepwise increase of drug concentration or by pretreatment of cells with an ABCB1 transporter activator tetraphenylphosphonium (TPP+) followed by DOX exposure. Transcriptome analysis of derived cells was performed by human gene expression microarrays and by quantitative PCR. Genetic and epigenetic mechanisms of ABCB1 regulation were evaluated by pyrosequencing and gene copy number variation analysis. Gradual activation of canonical EMT transcription factors with later activation of ABCB1 at the transcript level was observed in DOX-only treated cells, while TPP+ exposure induced considerable activation of ABCB1 at both, mRNA and protein level. The changes in ABCB1 mRNA and protein level were related to the promoter DNA hypomethylation and the increase in gene copy number. ABCB1-active cells were highly resistant to DOX and showed morphological and molecular features of EMT. The study suggests that nongenotoxic ABCB1 inducer can possibly accelerate development of DOX resistance.

The Evaluation of AREG, MMP-2, CHI3L1, GFAP, and OPN Serum Combined Value in Astrocytic Glioma Patients' Diagnosis and Prognosis.

Gliomas account for approximately 70% of primary brain tumors in adults. Of all gliomas, grade IV astrocytoma, also called glioblastoma, has the poorest overall survival, with <5% of patients surviving five years after diagnosis. Due to the aggressiveness, lethal nature, and impaired surgical accessibility of the tumor, early diagnosis of the tumor and, in addition, prediction of the patient's survival time are important. We hypothesize that combining the protein level values of highly recognizable glioblastoma serum biomarkers could help to achieve higher specificity and sensitivity in predicting glioma patient outcome as compared to single markers. The aim of this study was to select the most promising astrocytoma patient overall survival prediction variables from five secretory proteins-glial fibrillary acidic protein (GFAP), matrix metalloproteinase-2 (MMP-2), chitinase 3-like 1 (CHI3L1), osteopontin (OPN), and amphiregulin (AREG)-combining them with routinely used tumor markers to create a Patient Survival Score calculation tool. The study group consisted of 70 astrocytoma patients and 31 healthy controls. We demonstrated that integrating serum CHI3L1 and OPN protein level values and tumor isocitrate dehydrogenase 1 IDH1 mutational status into one parameter could predict low-grade astrocytoma patients' two-year survival with 93.8% accuracy.

Identification of Astrocytoma Blood Serum Protein Profile.

High-grade astrocytomas are some of the most common and aggressive brain cancers, whose signs and symptoms are initially non-specific. Up to the present date, there are no diagnostic tools to observe the early onset of the disease. Here, we analyzed the combination of blood serum proteins, which may play key roles in the tumorigenesis and the progression of glial tumors. Fifty-nine astrocytoma patients and 43 control serums were analyzed using Custom Human Protein Antibody Arrays, including ten targets: ANGPT1, AREG, IGF1, IP10, MMP2, NCAM1, OPN, PAI1, TGFß1, and TIMP1. The decision tree analysis indicates that serums ANGPT1, TIMP1, IP10, and TGFß1 are promising combinations of targets for glioma diagnostic applications. The accuracy of the decision tree algorithm was 73.5% (75/102), which correctly classified 79.7% (47/59) astrocytomas and 65.1% (28/43) healthy controls. The analysis revealed that the relative value of osteopontin (OPN) protein level alone predicted the 12-month survival of glioblastoma (GBM) patients with the specificity of 84%, while the inclusion of the IP10 protein increased model predictability to 92.3%. In conclusion, the serum protein profiles of ANGPT1, TIMP1, IP10, and TGFß1 were associated with the presence of astrocytoma independent of its malignancy grade, while OPN and IP10 were associated with GBM patient survival.

GFAP expression is influenced by astrocytoma grade and rs2070935 polymorphism.

Glial fibrillary acidic protein (GFAP) is an intermediate filament that provides mechanical support to astrocytes. Rs2070935 is a single nucleotide polymorphism (SNP) located in the promoter region of the GFAP gene. The aim of this pilot study is to investigate GFAP expression at mRNA, protein levels and rs2070935 polymorphism in 50 different grade human astrocytoma samples. GFAP expression at mRNA level was measured using quantitative reverse transcription polymerase chain reaction (qRT-PCR) with SYBR Green dye, whereas the translational activity of the following gene was detected using western blot assay. Furthermore, genotypes of rs2070935 were identified using qPCR with TaqMan probes. As a result, GFAP mRNA and protein expression was found to be declining with increasing astrocytoma grade (p < 0.05). A tendency was observed between increased GFAP mRNA expression and shorter grade IV astrocytoma patient survival (p = 0.2117). The rs2070935 CC genotype was found to be associated with increased GFAP translational activity in grade II astrocytoma (p = 0.0238). Possible links between rs2070935 genotypes and alternative splicing of GFAP were also observed. The rs2070935 AA genotype was found to be associated with poor clinical outcome for grade IV astrocytoma patients (p = 0.0007), although the following data should be checked in a larger sample size of astrocytoma patients.

MMP2 is associated with glioma malignancy and patient outcome.

Gliomas are fast growing and usually manifest in an aggressive infiltrative model. MMP2 overexpression is associated with brain tumor malignancy and metastasis formation. The aim of this study was to investigate the influence of MMP2 on glioma formation and clinical outcomes by performing analysis at the DNA, RNA, and protein levels. Methylation status and mRNA level were evaluated in 162 samples; the MMP2 protein level was analyzed in 28 patient preoperative and postoperative blood samples using protein microarray analysis and conventional ELISA. The MMP2 MSP analysis revealed a gradually increasing gene promoter demethylation frequency, and the Kaplan-Meier analysis showed that the methylated gene promoter is related to longer overall survival (Log-rank test X 2 = 12.508, df = 1, P < 0.0001). Relative mRNA expression was significantly downregulated when the promoter was methylated. Pairwise comparison analysis showed statistically significant (Mann-Whitney test, P < 0.05) differences in the MMP2 expression median when comparing different glioma grades. The Kaplan-Meier analysis revealed that low MMP2 expression was associated with better survival (Log-rank test X 2 = 7.732, df = 1, P = 0.005). At the protein level, MMP2 expression in patient sera showed no differences between malignancy grades and patient preoperative and postoperative states, while the ELISA assay showed the tendency of accumulating MMP2 protein in higher malignancy patient sera samples. The Kaplan-Meier analysis showed the tendency of having a shorter survival time with a higher MMP2 protein level in patient sera. MMP2 has a significant role in glioma pathogenesis and could be used as a potential molecular marker for tumor progression.