Luminal progenitor and fetal mammary stem cell expression features predict breast tumor response to neoadjuvant chemotherapy - PubMed (original) (raw)

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

Adam D Pfefferle et al. Breast Cancer Res Treat. 2015 Jan.

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.

PubMed Disclaimer

Figures

Fig. 1

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)

Fig. 2

Comparison of mammary subpopulations across studies. a Unsupervised hierarchical clustering was performed with the normal human mammary subpopulation dataset using any gene that had a log2 absolute expression value greater than three in at least four samples. b Pearson correlations were determined between the average expressions of each study’s subpopulations using all genes. c The first three principle components were determined across the human mammary subpopulation dataset

Fig. 3

_Homo sapiens_-enriched gene signatures. a HsEnriched gene signatures were identified for each mammary subpopulation. First, the overlap of genes highly expressed within each subpopulation across studies was determined. This overlapping gene set was further filtered to remove genes also identified as enriched in another subpopulation to limit the signature to genes specific to an individual subpopulation. The remaining genes comprised the HsEnriched gene signature for that subpopulation, as indicated by the shaded box. b The standardized average expression of the four HsEnriched gene signatures was calculated across three human datasets and displayed by intrinsic tumor subtype. c A nearest centroid predictor using the HsEnriched gene signatures was used to determine which epithelial features each tumor most represented. To reduce spurious findings, any tumor with a negative silhouette width was considered to have a weak association and was labeled as ‘unclassified’

Fig. 4

_Mus musculus_-enriched gene signatures. a MmEnriched gene signatures were identified for each mammary subpopulation. First, the overlap of genes highly expressed within each subpopulation across studies was determined. This overlapping gene set was further filtered to remove genes also identified as enriched in another subpopulation to limit the signature to genes specific to an individual subpopulation. The remaining genes comprised the MmEnriched gene signature for that subpopulation, as indicated by the shaded box. b The standardized average expression of the five MmEnriched gene signatures was calculated across a murine dataset and displayed by intrinsic tumor class. c A nearest centroid predictor using the MmEnriched gene signatures was used to determine which epithelial features each tumor most represented. To reduce spurious findings, any tumor with a negative silhouette width was considered to have a weak association and was labeled as ‘unclassified’

Fig. 5

fMaSC-enriched gene signatures. a The univariate logistic regression odds ratio predicting pathologic complete response to neoadjuvant anthracycline and taxane chemotherapy was determined using a 702 patient dataset, with the 95 % confidence interval shown as a forest plot. A single ‘*’ indicates that the signature was univariate significant, while ‘***’ indicates that the signature was both univariate and multivariate significant (p < 0.05). b Pearson correlations of multivariate significant gene signatures and proliferation were determined. c The standardized average expression of the fMaSC-MmEnriched signature and its two refined signatures were calculated across three human datasets and displayed by intrinsic tumor subtype. d Genes in the fMaSC-MmEnriched-refined1 signature. e Genes in the fMaSC-MmEnriched-refined2 signature

References

1. Gjorevski N, Nelson CM. Integrated morphodynamic signalling of the mammary gland. Nat Rev Mol Cell Biol. 2011;12:581–593. doi: 10.1038/nrm3168. - DOI - PubMed
1. Van Keymeulen A, Rocha AS, Ousset M, Beck B, Bouvencourt G, Rock J, Sharma N, Dekoninck S, Blanpain C. Distinct stem cells contribute to mammary gland development and maintenance. Nature. 2011;479:189–193. doi: 10.1038/nature10573. - DOI - PubMed
1. Santagata S, Thakkar A, Ergonul A, Wang B, Woo T, Hu R, Harrell JC, McNamara G, Schwede M, Culhane AC, Kindelberger D, Rodig S, Richardson A, Schnitt SJ, Tamimi RM, Ince TA. Taxonomy of breast cancer based on normal cell phenotype predicts outcome. J Clin Invest. 2014;124:859–870. doi: 10.1172/JCI70941. - DOI - PMC - PubMed
1. Visvader JE, Stingl J. Mammary stem cells and the differentiation hierarchy: current status and perspectives. Genes Dev. 2014;28:1143–1158. doi: 10.1101/gad.242511.114. - DOI - PMC - PubMed
1. Visvader JE. Keeping abreast of the mammary epithelial hierarchy and breast tumorigenesis. Genes Dev. 2009;23:2563–2577. doi: 10.1101/gad.1849509. - DOI - PMC - PubMed

Luminal progenitor and fetal mammary stem cell expression features predict breast tumor response to neoadjuvant chemotherapy - PubMed (original) (raw)