Therapy-, Gender- and Race-specific microRNA Markers, Target Genes and Networks Related to Glioblastoma Recurrence and Survival

Department of Animal Sciences, University of Illinois, Urbana, IL 61801, USA.
Cancer genomics & proteomics 07/2011; 8(4):173-83.
Source: PubMed


To identify and study targets of microRNA biomarkers of glioblastoma survival across events (death and recurrence) and phases (life expectancy or post-diagnostic) using functional and network analyses.
microRNAs associated with glioblastoma survival within and across race, gender, recurrence, and therapy cohorts were identified using 253 individuals, 534 microRNAs, Cox survival model, cross-validation, discriminant analyses, and cross-study comparison.
All 45 microRNAs revealed as being associated with survival were confirmed in independent cancer studies and 25 in glioblastoma studies. Thirty-nine and six microRNAs (including hsa-miR-222) were associated with one and multiple glioblastoma survival indicators, respectively. Nineteen and 26 microRNAs exhibited cohort-dependent (including hsa-miR-10b with therapy and hsa-miR-486 with race) and independent associations with glioblastoma, respectively.
Sensory perception and G protein-coupled receptor processes were enriched among microRNA gene targets also associated with survival and network visualization highlighted their relations. These findings can help to improve prognostic tools and personalized treatments.

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Available from: Nick VL Serão
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    • "In another study including 38 GBM samples, miR-21, miR-181c, miR-195, and miR-196b were associated with survival of GBM patients [32]. Using TCGA dataset with 253 individuals, 23 and 19 miRNAs were defined to be associated with OS and PFS, respectively [7]. Also, in another publication with 222 GBM samples, a risk score, formulated on the basis of expression signatures of 10 miRNAs, was associated with GBM patient survival, which was suggested to predict GBM patient survival [33]. "
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    ABSTRACT: Background Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor with poor clinical outcome. Identification and development of new markers could be beneficial for the diagnosis and prognosis of GBM patients. Deregulation of microRNAs (miRNAs or miRs) is involved in GBM. Therefore, we attempted to identify and develop specific miRNAs as prognostic and predictive markers for GBM patient survival. Methods Expression profiles of miRNAs and genes and the corresponding clinical information of 480 GBM samples from The Cancer Genome Atlas (TCGA) dataset were downloaded and interested miRNAs were identified. Patients’ overall survival (OS) and progression-free survival (PFS) associated with interested miRNAs and miRNA-interactions were performed by Kaplan-Meier survival analysis. The impacts of miRNA expressions and miRNA-interactions on survival were evaluated by Cox proportional hazard regression model. Biological processes and network of putative and validated targets of miRNAs were analyzed by bioinformatics. Results In this study, 6 interested miRNAs were identified. Survival analysis showed that high levels of miR-326/miR-130a and low levels of miR-323/miR-329/miR-155/miR-210 were significantly associated with long OS of GBM patients, and also showed that high miR-326/miR-130a and low miR-155/miR-210 were related with extended PFS. Moreover, miRNA-323 and miRNA-329 were found to be increased in patients with no-recurrence or long time to progression (TTP). More notably, our analysis revealed miRNA-interactions were more specific and accurate to discriminate and predict OS and PFS. This interaction stratified OS and PFS related with different miRNA levels more detailed, and could obtain longer span of mean survival in comparison to that of one single miRNA. Moreover, miR-326, miR-130a, miR-155, miR-210 and 4 miRNA-interactions were confirmed for the first time as independent predictors for survival by Cox regression model together with clinicopathological factors: Age, Gender and Recurrence. Plus, the availability and rationality of the miRNA-interaction as predictors for survival were further supported by analysis of network, biological processes, KEGG pathway and correlation analysis with gene markers. Conclusions Our results demonstrates that miR-326, miR-130a, miR-155, miR-210 and the 4 miRNA-interactions could serve as prognostic and predictive markers for survival of GBM patients, suggesting a potential application in improvement of prognostic tools and treatments.
    Full-text · Article · Jan 2013 · Journal of Translational Medicine
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    ABSTRACT: MicroRNAs (miRNAs) are a novel group of short RNAs, about 20‑22 nucleotide in length, that regulate gene expression in a post-transcriptional manner by affecting the stability or translation of mRNAs and play important roles in many biological processes. Many microRNAs have been implicated in glioblastoma. miR-31 is dysregulated in several types of cancer including colon, breast, prostate, gastric and lung cancers. However, the expression and role of miR-31 in glioblastoma are still unclear. In this study, we performed real-time reverse transcriptase polymerase chain reaction (RT-PCR) assays on 10 glioblastoma and 7 normal brain tissues. We found that miR-31 is down-regulated in glioblastoma compared with normal brain tissues. Ectopic expression of miR-31 inhibited migration and invasion ability of U251 glioma cells. Expression profiling analysis revealed that miR-31 affected the cell migration and motility process by regulating migration and invasion related genes. Finally, we demonstrated that miR-31 targeted radixin predominantly via inhibition of protein translation instead of degradation of mRNA.
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    ABSTRACT: Technological applications and novel biomarkers in the field of molecular diagnostics have never been evolving at a more rapid pace. These novel applications have the promise to change the face of clinical care as we move into the era of personalized medicine. While some of these technologies and biomarkers have been adopted by some clinical laboratories, most laboratories face a steep learning curve in bringing these dramatically new and different molecular diagnostic applications on board. Furthermore, interpreting the vast amounts and new types of data produced by these novel applications brings forth challenges for laboratorians and clinicians alike. In this article, we discuss how some of these emerging novel molecular diagnostic technologies and analytes, such as next-generation sequencing, chromosomal microarray, microRNAs and circulating fetal nucleic acids are revolutionizing patient care and personalized medicine.
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