Coexpression analysis of CD133 and CD44 identifies proneural and mesenchymal subtypes of glioblastoma multiforme

Accumulating evidence suggests that the stem cell markers CD133 and CD44 indicate molecular subtype in Glioblastoma Multiforme (GBM). Gene coexpression analysis of The Cancer Genome Atlas GBM dataset was undertaken to compare markers of the Glioblastoma Stem-Progenitor Cell (GSPC) phenotype. Pearson correlation identified genes coexpressed with stem cell markers, which were then used to build a gene signature that classifies patients based on a CD133 coexpression module signature (CD133-M) or CD44-M subtype. CD133-M tumors were enriched for the Proneural (PN) GBM subtype compared to Mesenchymal (MES) subtype for CD44-M tumors. Gene set enrichment identified DNA replication/cell cycle genes in the CD133-M and invasion/migration in CD44-M, while functional experiments showed enhanced cellular growth in CD133 expressing cells and enhanced invasion in cells expressing CD44. As with the 4 major molecular subtypes of GBM, there was no long-term survival difference between CD44-M and CD133-M patients, although CD44-M patients responded better to temozolomide while CD133-M patients benefited from radiotherapy. The use of a targeted coexpression approach to predict functional properties of surface marker expressing cells is novel, and in the context of GBM, supports accumulating evidence that CD133 and CD44 protein marker expression correlates with molecular subtype.status: publishe

A comprehensive meta-analysis of circulation miRNAs in glioma as potential diagnostic biomarker

<div><p>Glioma is the most common malignant intracranial tumour. Recently, several publications have suggested that miRNAs can be used as potential diagnostic biomarkers of glioma. Here we performed a meta-analysis to identify the diagnostic accuracy of differentially expressed circulating miRNAs in gliomas. Using PubMed, Medline and Cochrane databases, we searched for studies which evaluated a single or panel of miRNAs from circulating blood as potential biomarkers of glioma. Sixteen publications involving 23 studies of miRNAs from serum or plasma met our criteria and were included in this meta-analysis. The pooled diagnostic parameters were calculated by random effect models and overall diagnostic performance of altered miRNAs was illustrated by the summary receiver operator characteristic (SROC) curves. The pooled sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR) from each study were calculated. The pooled PLR, NLR and Diagnostic Odds Ratio were 6.39 (95% CI, 4.61–8.87), 0.15 (95% CI, 0.11–0.21) and 41.91 (95% CI, 23.15–75.88), respectively. The pooled sensitivity, specificity and area under the curve (AUC) were 0.87 (95% CI, 0.82–0.91), 0.86 (95% CI, 0.82–0.90) and 0.93 (95% CI, 0.91–0.95), respectively. This meta-analysis demonstrated that circulating miRNAs are capable of distinguishing glioma from healthy controls. Circulating miRNAs are promising diagnostic biomarkers for glioma and can potentially be used as a non-invasive early detection.</p></div

Forest plots of all 16 studies included in this meta-analysis.

<p>The pooled <b>A)</b> sensitivity and <b>B)</b> specificity is 0.87 and 0.86, respectively of miRNAs in diagnosis of glioma.</p

Diagram of SROC curves describing the diagnostic performance of miRNAs.

<p><b>A)</b> The PLR and NLR is 6.39 and 0.15 respectively, showing the pre-test probability set as 25%, the positive and negative post-test probability of 68% and 5%, respectively. <b>B)</b> The AUC is 0.93 (95%CI, 0.91–0.95). Each number within a circle represents the order of study identifier in Fig 3.</p

Diagnostic characteristics of each single miRNA and miRNA panel.

<p>Diagnostic characteristics of each single miRNA and miRNA panel.</p

Flow chart of studies selection and quality assessment of studies.

<p><b>A)</b> A total of 16 published articles were included in this meta-analysis after filtering through the inclusion criteria. <b>B)</b> QUADAS-2 assessment. Bar chart showing the summary of risk of bias and applicability concerns, expressed as percentage. Each study occupied the bar equally (1/16, 6.25%). Red: high risk; Yellow: unclear risk; Green: low risk.</p

Characteristics of included circulating miRNA studies in this meta analysis.

<p>Characteristics of included circulating miRNA studies in this meta analysis.</p

A comprehensive meta-analysis of circulation miRNAs in glioma as potential diagnostic biomarker - Fig 4

<p>The diagram shows the (a) goodness-of-fit, (b) bivariate normality, (c) influence and (d) outlier detection analyses. Goodness-of-fit and bivariate normality showed this analysis fitted the model well. Influence analysis identified the most dominant studies in this meta-analysis. Outlier detection demonstrated one study (D’Urso et al and Xiao et al) is outside the standard residual square. Each number within circle represents the order of study identifier in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189452#pone.0189452.g003" target="_blank">Fig 3</a>.</p

Expression of CD133 and CD44 in glioblastoma stem cells correlates with cell proliferation, phenotype stability and intra-tumor heterogeneity

Glioblastoma (GBM) is a heterogeneous tumor of the brain with a poor prognosis due to recurrence and drug resistance following therapy. Genome-wide profiling has revealed the existence of distinct GBM molecular subtypes that respond differently to aggressive therapies. Despite this, molecular subtype does not predict recurrence or drug resistance and overall survival is similar across subtypes. One of the key features contributing to tumor recurrence and resistance to therapy is proposed to be an underlying subpopulation of resistant glioma stem cells (GSC). CD133 expression has been used as a marker of GSCs, however recent evidence suggests the relationship between CD133 expression, GSCs and molecular subtype is more complex than initially proposed. The expression of CD133, Olig2 and CD44 was investigated using patient derived glioma stem-like cells (PDGCs) in vitro and in vivo. Different PDGCs exhibited a characteristic equilibrium of distinct CD133+ and CD44+ subpopulations and the influence of environmental factors on the intra-tumor equilibrium of CD133+ and CD44+ cells in PDGCs was also investigated, with hypoxia inducing a CD44+ to CD133+ shift and chemo-radiotherapy inducing a CD133+ to CD44+ shift. These data suggest that surveillance and modulation of intra-tumor heterogeneity using molecular markers at initial surgery and surgery for recurrent GBM may be important for more effective management of GBM.status: publishe