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Luminal progenitor and fetal mammary stem cell expression features predict breast tumor response to neoadjuvant chemotherapy.

Pfefferle AD, Spike BT, Wahl GM, Perou CM - Breast Cancer Res. Treat. (2015)

Bottom Line: Molecular features associated with particular cell types along this hierarchy may contribute to the biological and clinical heterogeneity observed in human breast carcinomas.We found that both human luminal progenitor and mouse fetal mammary stem cell features predicted pCR sensitivity across all breast cancer patients even after controlling for intrinsic subtype, proliferation, and clinical variables.This work identifies new clinically relevant gene signatures and highlights the value of a developmental biology perspective for uncovering relationships between tumor subtypes and their potential normal cellular counterparts.

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA, adamp@email.unc.edu.

ABSTRACT
Mammary gland morphology and physiology are supported by an underlying cellular differentiation hierarchy. Molecular features associated with particular cell types along this hierarchy may contribute to the biological and clinical heterogeneity observed in human breast carcinomas. Investigating the normal cellular developmental phenotypes in breast tumors may provide new prognostic paradigms, identify new targetable pathways, and explain breast cancer subtype etiology. We used transcriptomic profiles coming from fluorescence-activated cell sorted (FACS) normal mammary epithelial cell types from several independent human and murine studies. Using a meta-analysis approach, we derived consensus gene signatures for both species and used these to relate tumors to normal mammary epithelial cell phenotypes. We then compiled a dataset of breast cancer patients treated with neoadjuvant anthracycline and taxane chemotherapy regimens to determine if normal cellular traits predict the likelihood of a pathological complete response (pCR) in a multivariate logistic regression analysis with clinical markers and genomic features such as cell proliferation. Most human and murine tumor subtypes shared some, but not all, features with a specific FACS-purified normal cell type; thus for most tumors a potential distinct cell type of 'origin' could be assigned. We found that both human luminal progenitor and mouse fetal mammary stem cell features predicted pCR sensitivity across all breast cancer patients even after controlling for intrinsic subtype, proliferation, and clinical variables. This work identifies new clinically relevant gene signatures and highlights the value of a developmental biology perspective for uncovering relationships between tumor subtypes and their potential normal cellular counterparts.

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Flowchart of analysis. Normal mammary tissue biopsies were taken from female patients (a) and FACS-enriched into distinct mammary cell subpopulations (b). Transcriptome profiling was performed on each subpopulation using gene expression microarrays by three different studies (c). Within each study, genes highly expressed within each subpopulation were determined using a two-class SAM (d). Genes commonly and specifically enriched within each subpopulation across studies were determined to identify ‘enriched’ gene signatures (e). Each ‘enriched’ signature was refined by supervised hierarchical clustering to identify gene ‘features’ highly correlated across a diverse set of human breast tumors (f). These gene signatures were then used for clinical testing (g)
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Fig1: Flowchart of analysis. Normal mammary tissue biopsies were taken from female patients (a) and FACS-enriched into distinct mammary cell subpopulations (b). Transcriptome profiling was performed on each subpopulation using gene expression microarrays by three different studies (c). Within each study, genes highly expressed within each subpopulation were determined using a two-class SAM (d). Genes commonly and specifically enriched within each subpopulation across studies were determined to identify ‘enriched’ gene signatures (e). Each ‘enriched’ signature was refined by supervised hierarchical clustering to identify gene ‘features’ highly correlated across a diverse set of human breast tumors (f). These gene signatures were then used for clinical testing (g)

Mentions: Several groups have independently obtained transcriptomic profiles of normal human breast cells and compared the genomic biology of these different cell types with human tumors [19–21]. In these studies, normal mammary tissues obtained from female donors were FAC sorted using cell surface markers to enrich for specific mammary subpopulations before microarray analysis (Table 1; Fig. 1). While these initial studies were important, the datasets themselves were relatively small (n = 12 for Lim et al. [19], n = 72 for Shehata et al. [20], n = 18 for Prat et al. [21]), and few if any comparisons across studies were performed. Importantly, FACS-based cell fractionation can only enrich for specific subpopulations. Therefore, transcriptomic profiles reflect features of other contaminating cell types to varying degrees. As such, study-specific biases may be present in any single dataset; therefore, we used consensus information from all three FACS-enriched human transcriptomic datasets to reduce technical and study-specific biases.Table 1


Luminal progenitor and fetal mammary stem cell expression features predict breast tumor response to neoadjuvant chemotherapy.

Pfefferle AD, Spike BT, Wahl GM, Perou CM - Breast Cancer Res. Treat. (2015)

Flowchart of analysis. Normal mammary tissue biopsies were taken from female patients (a) and FACS-enriched into distinct mammary cell subpopulations (b). Transcriptome profiling was performed on each subpopulation using gene expression microarrays by three different studies (c). Within each study, genes highly expressed within each subpopulation were determined using a two-class SAM (d). Genes commonly and specifically enriched within each subpopulation across studies were determined to identify ‘enriched’ gene signatures (e). Each ‘enriched’ signature was refined by supervised hierarchical clustering to identify gene ‘features’ highly correlated across a diverse set of human breast tumors (f). These gene signatures were then used for clinical testing (g)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4308649&req=5

Fig1: Flowchart of analysis. Normal mammary tissue biopsies were taken from female patients (a) and FACS-enriched into distinct mammary cell subpopulations (b). Transcriptome profiling was performed on each subpopulation using gene expression microarrays by three different studies (c). Within each study, genes highly expressed within each subpopulation were determined using a two-class SAM (d). Genes commonly and specifically enriched within each subpopulation across studies were determined to identify ‘enriched’ gene signatures (e). Each ‘enriched’ signature was refined by supervised hierarchical clustering to identify gene ‘features’ highly correlated across a diverse set of human breast tumors (f). These gene signatures were then used for clinical testing (g)
Mentions: Several groups have independently obtained transcriptomic profiles of normal human breast cells and compared the genomic biology of these different cell types with human tumors [19–21]. In these studies, normal mammary tissues obtained from female donors were FAC sorted using cell surface markers to enrich for specific mammary subpopulations before microarray analysis (Table 1; Fig. 1). While these initial studies were important, the datasets themselves were relatively small (n = 12 for Lim et al. [19], n = 72 for Shehata et al. [20], n = 18 for Prat et al. [21]), and few if any comparisons across studies were performed. Importantly, FACS-based cell fractionation can only enrich for specific subpopulations. Therefore, transcriptomic profiles reflect features of other contaminating cell types to varying degrees. As such, study-specific biases may be present in any single dataset; therefore, we used consensus information from all three FACS-enriched human transcriptomic datasets to reduce technical and study-specific biases.Table 1

Bottom Line: Molecular features associated with particular cell types along this hierarchy may contribute to the biological and clinical heterogeneity observed in human breast carcinomas.We found that both human luminal progenitor and mouse fetal mammary stem cell features predicted pCR sensitivity across all breast cancer patients even after controlling for intrinsic subtype, proliferation, and clinical variables.This work identifies new clinically relevant gene signatures and highlights the value of a developmental biology perspective for uncovering relationships between tumor subtypes and their potential normal cellular counterparts.

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA, adamp@email.unc.edu.

ABSTRACT
Mammary gland morphology and physiology are supported by an underlying cellular differentiation hierarchy. Molecular features associated with particular cell types along this hierarchy may contribute to the biological and clinical heterogeneity observed in human breast carcinomas. Investigating the normal cellular developmental phenotypes in breast tumors may provide new prognostic paradigms, identify new targetable pathways, and explain breast cancer subtype etiology. We used transcriptomic profiles coming from fluorescence-activated cell sorted (FACS) normal mammary epithelial cell types from several independent human and murine studies. Using a meta-analysis approach, we derived consensus gene signatures for both species and used these to relate tumors to normal mammary epithelial cell phenotypes. We then compiled a dataset of breast cancer patients treated with neoadjuvant anthracycline and taxane chemotherapy regimens to determine if normal cellular traits predict the likelihood of a pathological complete response (pCR) in a multivariate logistic regression analysis with clinical markers and genomic features such as cell proliferation. Most human and murine tumor subtypes shared some, but not all, features with a specific FACS-purified normal cell type; thus for most tumors a potential distinct cell type of 'origin' could be assigned. We found that both human luminal progenitor and mouse fetal mammary stem cell features predicted pCR sensitivity across all breast cancer patients even after controlling for intrinsic subtype, proliferation, and clinical variables. This work identifies new clinically relevant gene signatures and highlights the value of a developmental biology perspective for uncovering relationships between tumor subtypes and their potential normal cellular counterparts.

Show MeSH
Related in: MedlinePlus