Dataset Information

The Poly (ADP-Ribose) Polymerase inhibitor Veliparib and Radiation Cause Significant Cell Line Dependent Metabolic Changes in Breast Cancer Cells

ABSTRACT: Breast tumors are characterized into different subtypes based on their surface marker expression, which affects their prognosis and treatment. For example, triple negative breast cancer cells (ER-/PR-/Her2-) show reduced susceptibility towards radiotherapy and chemotherapeutic agents. Poly (ADP-ribose) polymerase (PARP) inhibitors have shown promising results in clinical trials, both as single agents and in combination with other chemotherapeutics, in several subtypes of breast cancer patients. PARP1 is involved in DNA repair, apoptosis, and transcriptional regulation and an understanding of the effects of PARP inhibitors, specifically on metabolism, is currently lacking. Here, we have used NMR-based metabolomics to probe the cell line-specific effects of PARP inhibitor and radiation on metabolism in three distinct breast cancer cell lines. Our data reveal several cell line independent metabolic changes upon PARP inhibition, including an increase in taurine. Pathway enrichment and topology analysis identified that nitrogen metabolism, glycine, serine and threonine metabolism, aminoacyl-tRNA biosynthesis and taurine and hypotaurine metabolism were enriched after PARP inhibition in the three breast cancer cell lines. We observed that the majority of metabolic changes due to radiation as well as PARP inhibition were cell line dependent, highlighting the need to understand how these treatments affect cancer cell response via changes in metabolism. Finally, we observed that both PARP inhibition and radiation induced a similar metabolic response in the HCC1937 (BRCA mutant cell line), but not in MCF-7 and MDAMB231 cells, suggesting that radiation and PARP inhibition share similar interactions with metabolic pathways in BRCA mutant cells. Our study emphasizes the importance of differences in metabolic responses to cancer treatments in different subtypes of cancers.

INSTRUMENT(S): Bruker

SUBMITTER: Vijesh Bhute

PROVIDER: MTBLS337 | MetaboLights | 2016-11-07

REPOSITORIES: MetaboLights

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	MTBLS337	Other
	FILES	Other
	a_MTBLS337_breast_cancer_metabolomics_metabolite_profiling_NMR_spectroscopy.txt	Txt
	i_Investigation.txt	Txt
	m_MTBLS337_breast_cancer_metabolomics_metabolite_profiling_NMR_spectroscopy_v2_maf.tsv	Tabular

Items per page:

1 - 5 of 7

Publications

The Poly (ADP-Ribose) Polymerase Inhibitor Veliparib and Radiation Cause Significant Cell Line Dependent Metabolic Changes in Breast Cancer Cells.

Bhute Vijesh J VJ Ma Yan Y Bao Xiaoping X Palecek Sean P SP

Scientific reports 20161104

Breast tumors are characterized into subtypes based on their surface marker expression, which affects their prognosis and treatment. Poly (ADP-ribose) polymerase (PARP) inhibitors have shown promising results in clinical trials, both as single agents and in combination with other chemotherapeutics, in several subtypes of breast cancer patients. Here, we used NMR-based metabolomics to probe cell line-specific effects of the PARP inhibitor Veliparib and radiation on metabolism in three breast canc ...[more]

PMID: 27811964

Similar Datasets

Project description:Introduction: Breast radiotherapy is currently â??one size fits allâ?? regardless of breast cancer subtype (eg. luminal, basal). However, recent clinical data suggests that radiation response may vary significantly among subtypes. Therefore, current practice leads to over- or under-treatment of women whose tumors are more or less radiation responsive. We hypothesized that this clinical variability may be due, in part, to differences in cellular radiation response. Methods: We exposed 16 biologically-diverse breast tumor cell lines to 0 or 5GY radiation. Microarray analysis was performed on RNA harvested from those cell lines. Samples were run in triplicate. Following quality assessment, differential gene expression analysis was performed using a two-way multiplicative linear mixed-effects model. A candidate radiation response biomarkers with biologically plausible role in radiation response, were identified and confirmed at the RNA and protein level with qPCR and Western blotting assays. Induction in human breast tumors was confirmed in 32 patients with paired pre- and post-radiation tumor samples using IHC and microarray analysis. Quantification of protein was performed in a blinded manner and included positive and negative controls. The objective of our study was to identify genomic determinants of radiation sensitivity using clinical samples as well as breast tumor cell lines. In order to identify differences in the radiation response gene expression profiles of specific breast cancer subtypes, we exposed 16 biologically-diverse breast tumor cell lines to 0 or 5GY radiation. Microarray analysis was performed on RNA harvested from those cell lines. Samples were run in triplicate. Following quality assessment, differential gene expression analysis was performed using a two-way multiplicative linear mixed-effects model. Candidate radiation response biomarker with a biologically plausible role in radiation response, were identified and confirmed at the RNA and protein level with qPCR and Western blotting assays. Induction of the genes of interest were further evaluated and confirmed in human breast tumors in 32 breast cancer patients with paired pre- and post-radiation tumor samples using IHC and microarray analysis assays.