Transcriptomics

Dataset Information

0

Single cell transcriptome dynamics and subpopulation heterogeneity in radiation treated recurrent glioma


ABSTRACT: Radiation is the frontline treatment for malignant gliomas. Intra-tumoral heterogeneity has been proposed to grant cancer cells a superior trajectory and survival advantage to avoid therapeutic interventions including radiation. However, direct evidence to support the hypothesis via the transcriptome dynamics of glioma during radiation therapy is limited. The current study aim to measure the functional subpopulation dynamics before and after radiation treatment that assist the radiation resistance at single cell resolution. We investigate the single cell transcriptome and biological pathways of primary glioma mouse model and post-radiation early/late time point. Specifically, we used the RCAS mouse model for gliomas, which overexpress PDGFRA as the model. Using single cell transcriptome, for the first time, we confirmed the proneural classification of PDGFRA RCAS glioma mouse model and its heterogeneity. We found that recurrent dominant subpopulations are featured with elevated proliferation rate and hypoxia. In addition, we identified a subpopulation of radiation resistant cells in at early time points with elevated stemness. Lastly, the subpopulations composition undergoes large changes at late time point when the tumor recurred. Single cell transcriptome profiling of radiation treated mouse glioma mouse model identified tumor cell subpopulations dynamics. It provides novel insights into the molecular phenotype and biological functions of radiation resistant tumor cell population.

ORGANISM(S): Mus musculus

PROVIDER: GSE76184 | GEO | 2016/12/01

SECONDARY ACCESSION(S): PRJNA306557

REPOSITORIES: GEO

Similar Datasets

2022-07-05 | GSE207264 | GEO
2016-12-16 | GSE79437 | GEO
2014-06-02 | E-GEOD-55061 | biostudies-arrayexpress
2020-07-21 | GSE142168 | GEO
2014-06-02 | GSE55061 | GEO
2021-05-27 | GSE175543 | GEO
2012-10-04 | E-GEOD-30626 | biostudies-arrayexpress
2015-12-23 | E-GEOD-70991 | biostudies-arrayexpress
2011-06-17 | E-GEOD-30016 | biostudies-arrayexpress
2012-10-04 | GSE30626 | GEO