Unknown

Dataset Information

0

Transcriptional profiling of dividing tumor cells detects intratumor heterogeneity linked to cell proliferation in a brain tumor model.


ABSTRACT: Intratumor heterogeneity is a primary feature of high-grade gliomas, complicating their therapy. As accumulating evidence suggests that intratumor heterogeneity is a consequence of cellular subsets with different cycling frequencies, we developed a method for transcriptional profiling of gliomas, using a novel technique to dissect the tumors into two fundamental cellular subsets, namely, the proliferating and non-proliferating cell fractions. The tumor fractions were sorted whilst maintaining their molecular integrity, by incorporating the thymidine analog 5-ethynyl-2'-deoxyuridine into actively dividing cells. We sorted the actively dividing versus non-dividing cells from cultured glioma cells, and parental and clonally derived orthotopic tumors, and analyzed them for a number of transcripts. While there was no significant difference in the transcriptional profiles between the two cellular subsets in cultured glioma cells, we demonstrate ?2-6 fold increase in transcripts of cancer and neuronal stem cell and tumor cell migration/invasion markers, and ?2-fold decrease in transcripts of markers of hypoxia and their target genes, in the dividing tumor cells of the orthotopic glioma when compared to their non-proliferative counterparts. This suggests the influence of the brain microenvironment in transcriptional regulation and, thereby, the physiology of glioma cells in vivo. When clonal glioma cells were derived from a parental glioma and the resultant orthotopic tumors were compared, their transcriptional profiles were closely correlated to tumor aggression and consequently, survival of the experimental animals. This study demonstrates the resolution of intratumor heterogeneity for profiling studies based on cell proliferation, a defining feature of cancers, with implications for treatment design.

SUBMITTER: Endaya BB 

PROVIDER: S-EPMC5528932 | BioStudies | 2016-01-01T00:00:00Z

REPOSITORIES: biostudies

Similar Datasets

2020-01-01 | S-EPMC7442699 | BioStudies
2019-01-01 | S-EPMC7161589 | BioStudies
2012-02-24 | E-GEOD-35158 | BioStudies
| S-ECPF-GEOD-35158 | BioStudies
2019-01-01 | S-EPMC6339410 | BioStudies
| S-EPMC2789204 | BioStudies
2020-01-01 | S-EPMC7072286 | BioStudies
2020-01-01 | S-EPMC7158688 | BioStudies
2018-01-01 | S-EPMC6214371 | BioStudies
2017-01-01 | S-EPMC5673996 | BioStudies