Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Lineage analysis of basal epithelial cells reveals their unexpected plasticity and supports a cell of origin model for prostate cancer heterogeneity

ABSTRACT: We used RNA-seq to compare the expression profiles of mouse prostate tumors originated from epithelial basal cells to those originated from luminal cells. We next generated expression signatures for both basal and luminal origin tumors by comparison of tumor samples to their respective controls. By comparing luminal to basal signatures we identified a prognostic molecular signature for prostate cancer patient survival. Pten was deleted in prostate basal or luminal cells to induce tumor formation and tumor expression profiles were analyzed by RNA-seq.

ORGANISM(S): Mus musculus

SUBMITTER: Antonina Mitrofanova

PROVIDER: E-GEOD-39509 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Lineage analysis of basal epithelial cells reveals their unexpected plasticity and supports a cell-of-origin model for prostate cancer heterogeneity.

Wang Zhu A ZA Mitrofanova Antonina A Bergren Sarah K SK Abate-Shen Cory C Cardiff Robert D RD Califano Andrea A Shen Michael M MM

Nature cell biology 20130224 3

A key issue in cancer biology is whether oncogenic transformation of different cell types of origin within an adult tissue gives rise to distinct tumour subtypes that differ in their prognosis and/or treatment response. We now show that initiation of prostate tumours in basal or luminal epithelial cells in mouse models results in tumours with distinct molecular signatures that are predictive of human patient outcomes. Furthermore, our analysis of untransformed basal cells reveals an unexpected a ...[more]

PMID: 23434823

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Project description:Dysregulated choline metabolism is a well-known feature of breast cancer, but the underlying mechanisms are not fully understood. In this study, the metabolomic and transcriptomic characteristics of a large panel of human breast cancer xenograft models were mapped, with focus on choline metabolism. Methods: Tumor specimens from 34 patient-derived xenograft models were collected and divided in two. One part was examined using high-resolution magic angle spinning (HR-MAS) MR spectroscopy while another part was analysed using gene expression microarrays. Expression data of genes encoding proteins in the choline metabolism pathway were analysed and correlated to the levels of choline (Cho), phosphocholine (PCho) and glycerophosphocholine (GPC) using Pearson’s correlation analysis. For comparison purposes, metabolic and gene expression data were collected from human breast tumors belonging to corresponding molecular subgroups. Results: Most of the xenograft models were classified as basal-like (N=19) or luminal B (N=7). These two subgroups showed significantly different choline metabolic and gene expression profiles. The luminal B xenografts were characterized by a high PCho/GPC ratio while the basal-like xenografts were characterized by highly variable PCho/GPC ratio. Also, Cho, PCho and GPC levels were correlated to expression of several genes encoding proteins in the choline metabolism pathway, including choline kinase alpha (CHKA) and glycerophosphodiester phosphodiesterase domain containing 5 (GDPD5). These characteristics were similar to those found in human tumor samples. Discussion: The higher PCho/GPC ratio found in luminal B compared with most basal-like breast cancer xenograft models and human tissue samples do not correspond to results observed from in vitro studies. It is likely that microenvironmental factors play a role in the in vivo regulation of choline metabolism. Cho, PCho and GPC were correlated to different choline pathway-encoding genes in luminal B compared with basal-like xenografts, suggesting that regulation of choline metabolism may vary between different breast cancer subgroups. The concordance between the metabolic and gene expression profiles from xenograft models with breast cancer tissue samples from patients indicates that these xenografts are representative models of human breast cancer and represent relevant models to study tumor metabolism in vivo. Gene expression was measured in 30 human breast cancer xenografts, one sample from each model

Dataset Information

Lineage analysis of basal epithelial cells reveals their unexpected plasticity and supports a cell of origin model for prostate cancer heterogeneity

Publications

Lineage analysis of basal epithelial cells reveals their unexpected plasticity and supports a cell-of-origin model for prostate cancer heterogeneity.

Similar Datasets

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