Dataset Information

Single-cell RNA-seq reveals a subpopulation of prostate cancer cells with enhanced cell cycle-related transcription and attenuated androgen response

ABSTRACT: Increasing evidence indicates that minor subpopulations intrinsic to androgen-independence are present in prostate cancer cells, poised to become clonal dominance under prolonged androgen-deprivation selection. To stratify different subpopulations, we conduct transcriptome profiling of 144 single LNCaP prostate cancer cells treated and untreated with androgen after cell cycle synchronization. At least eight subpopulations of LNCaP cells are identified, revealing a previously unappreciable level of cellular heterogeneity to androgen stimulation. One subpopulation displays stem-like features, the advanced growth of which depends more on enhanced expression of 10 cell cycle-related genes and less on androgen-dependent signaling. Concordant upregulation of these genes appears to be linked to recurrent prostate cancers and can be used for early detection of tumors that subsequently develop androgen independence. Moreover, this single-cell approach provides a better understanding of how cancer cells respond heterogeneously to androgen-deprivation therapies and to reveal which subpopulations are resistant to this treatment.

ORGANISM(S): Homo sapiens

PROVIDER: GSE99795 | GEO | 2018/03/02

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Following androgen ablation therapy (AAT), the vast majority of prostate cancer patients develop treatment resistance with a median time of 18-24 months to disease progression. To identify molecular targets that aid in prostate cancer cell survival and contribute to the androgen independent phenotype, we evaluated changes in LNCaP cell gene expression during 12 months of androgen deprivation. At time points reflecting critical growth and phenotypic changes, we performed Affymetrix expression array analysis to examine the effects of androgen deprivation during the acute response, during the period of apparent quiescence, and during the emergence of highly proliferative, androgen-independent prostate cancer cells (LNCaP-AI). We discovered alterations in gene expression for a host of molecules associated with promoting prostate cancer cell growth and survival, regulating cell cycle progression, apoptosis and adrenal androgen metabolism, in addition to AR co-regulators and markers of neuroendocrine disease. These findings illustrate the complexity and unpredictable nature of cancer cell biology and contribute greatly to our understanding of how prostate cancer cells likely survive AAT. The value of this longitudinal approach lies in the ability to examine gene expression changes throughout the cellular response to androgen deprivation; it provides a more dynamic illustration of those genes which contribute to disease progression in addition to specific genes which constitute a malignant androgen-independent phenotype. In conclusion, it is of great importance that we employ new approaches, such as the one proposed here, to continue exploring the cellular mechanisms of therapy resistance and identify promising targets to improve cancer therapeutics. Experiment Overall Design: To identify molecular targets that aid in prostate cancer cell survival and contribute to the androgen independent phenotype, we evaluated changes in LNCaP cell gene expression during 12 months of androgen deprivation. At time points reflecting critical growth and phenotypic changes, we performed Affymetrix expression array analysis to examine the effects of androgen deprivation during the acute response, during the period of apparent quiescence, and during the emergence of highly proliferative, androgen-independent prostate cancer cells (LNCaP-AI).

Dataset Information

Single-cell RNA-seq reveals a subpopulation of prostate cancer cells with enhanced cell cycle-related transcription and attenuated androgen response

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets