Dataset Information

Lack of human cytomegalovirus expression in single cells from glioblastoma tumors and cell lines.

ABSTRACT: The relationship between human cytomegalovirus (HCMV) and glioblastoma (GBM) is an ongoing debate with extensive evidence supporting or refuting its existence through molecular assays, pre-clinical studies, and clinical trials. We focus primarily on the crux of the debate, detection of HCMV in GBM samples using molecular assays. We propose that these differences in detection could be affected by cellular heterogeneity. To take this into account, we align the single-cell RNA sequencing (scRNA-seq) reads from five GBM tumors and two cell lines to HCMV and analyze the alignments for evidence of (i) complete viral transcripts and (ii) low-abundance viral reads. We found that neither tumor nor cell line samples showed conclusive evidence of full HCMV viral transcripts. We also identified low-abundance reads aligned across all tumors, with two tumors having higher alignment rates than the rest of the tumor samples. This work is meant to rigorously test for HCMV RNA expression at a single cell level in GBM samples and examine the possible utility of single cell data in tumor virology.

SUBMITTER: Johnson TS

PROVIDER: S-EPMC5656548 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Lack of human cytomegalovirus expression in single cells from glioblastoma tumors and cell lines.

Johnson Travis S TS Abrams Zachary B ZB Mo Xiaokui X Zhang Yan Y Huang Kun K

Journal of neurovirology 20170710 5

The relationship between human cytomegalovirus (HCMV) and glioblastoma (GBM) is an ongoing debate with extensive evidence supporting or refuting its existence through molecular assays, pre-clinical studies, and clinical trials. We focus primarily on the crux of the debate, detection of HCMV in GBM samples using molecular assays. We propose that these differences in detection could be affected by cellular heterogeneity. To take this into account, we align the single-cell RNA sequencing (scRNA-seq ...[more]

PMID: 28695489

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Project description:BackgroundIt is well-known that glioblastoma contains self-renewing, stem-like subpopulation with the ability to sustain tumor growth. These cells - called cancer stem-like cells - share certain phenotypic characteristics with untransformed stem cells and are resistant to many conventional cancer therapies, which might explain the limitations in curing human malignancies. Thus, the identification of genes controlling the differentiation of these stem-like cells is becoming a successful therapeutic strategy, owing to the promise of novel targets for treating malignancies.MethodsRecently, we developed SWIM, a software able to unveil a small pool of genes - called switch genes - critically associated with drastic changes in cell phenotype. Here, we applied SWIM to the expression profiling of glioblastoma stem-like cells and conventional glioma cell lines, in order to identify switch genes related to stem-like phenotype.ResultsSWIM identifies 171 switch genes that are all down-regulated in glioblastoma stem-like cells. This list encompasses genes like CAV1, COL5A1, COL6A3, FLNB, HMMR, ITGA3, ITGA5, MET, SDC1, THBS1, and VEGFC, involved in "ECM-receptor interaction" and "focal adhesion" pathways. The inhibition of switch genes highly correlates with the activation of genes related to neural development and differentiation, such as the 4-core OLIG2, POU3F2, SALL2, SOX2, whose induction has been shown to be sufficient to reprogram differentiated glioblastoma into stem-like cells. Among switch genes, the transcription factor FOSL1 appears as the brightest star since: it is down-regulated in stem-like cells; it highly negatively correlates with the 4-core genes that are all up-regulated in stem-like cells; the promoter regions of the 4-core genes harbor a consensus binding motif for FOSL1.ConclusionsWe suggest that the inhibition of switch genes in stem-like cells could induce the deregulation of cell communication pathways, contributing to neoplastic progression and tumor invasiveness. Conversely, their activation could restore the physiological equilibrium between cell adhesion and migration, hampering the progression of cancer. Moreover, we posit FOSL1 as promising candidate to orchestrate the differentiation of cancer stem-like cells by repressing the 4-core genes' expression, which severely halts cancer growth and might affect the therapeutic outcome. We suggest FOSL1 as novel putative therapeutic and prognostic biomarker, worthy of further investigation.

Dataset Information

Lack of human cytomegalovirus expression in single cells from glioblastoma tumors and cell lines.

Publications

Lack of human cytomegalovirus expression in single cells from glioblastoma tumors and cell lines.

Similar Datasets

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