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Intersection of FOXO- and RUNX1-Mediated Gene Expression

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Intersection of FOXO- and RUNX1-Mediated Gene Expression Intersection of FOXO- and RUNX1-mediated gene PNAS PLUS expression programs in single breast epithelial cells during morphogenesis and tumor progression Lixin Wanga,1, Joan S. Bruggeb, and Kevin A. Janesa,1,2 aDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908; and bDepartment of Cell Biology, Harvard Medical School, Boston, MA 02115 Edited by Yoshiaki Ito, Institute of Molecular and Cell Biology, Singapore, and accepted by the Editorial Board July 28, 2011 (received for review March 3, 2011) Gene expression networks are complicated by the assortment of be obtained with conventional oligonucleotide microarrays after regulatory factors that bind DNA and modulate transcription PCR-based amplification of cDNA from 10 microdissected cells combinatorially. Single-cell measurements can reveal biological (2, 22, 23). By surveying hundreds of cells overall, stochastic pro- mechanisms hidden by population averages, but their value has filing captures the most reproducible cell to cell expression het- not been fully explored in the context of mRNA regulation. Here, erogeneities in a cell population. Individual transcripts that are we adapted a single-cell expression profiling technique to exam- nonuniformly expressed are then organized by the pattern of their ine the gene expression program downstream of Forkhead box O expression fluctuations to reveal coordinated single-cell programs. (FOXO) transcription factors during 3D breast epithelial acinar mor- In this work, we report a detailed analysis centering around phogenesis. By analyzing patterns of mRNA fluctuations among one class of transcription factors—the FOXOs—whose expres- individual matrix-attached epithelial cells, we found that a subset sion was found to be strongly nonuniform in our initial study of FOXO target genes was jointly regulated by the transcription (2). FOXO proteins are a subgroup of the Forkhead family of factor Runt-related transcription factor 1 (RUNX1). Knockdown of transcriptional regulators that play important roles in cell cycle RUNX1 causes hyperproliferation and abnormal morphogenesis, arrest, stress responses, and cell death (24). All FOXO isoforms both of which require normal FOXO function. Down-regulating recognize a common (A/G)TAAA(T/C)A DNA consensus, which RUNX1 and FOXOs simultaneously causes widespread oxidative is frequently observed in the extended promoters of many genes stress, which arrests proliferation and restores normal acinar mor- (SI Appendix, Table S1) (25, 26). However, FOXOs are often phology. In hormone-negative breast cancers lacking human epi- not redundant, and isoform-specific functions have been widely HER2 fi fi dermal growth factor receptor 2 ( ) ampli cation, we nd that documented (27–29). FOXO transcriptional activity is regulated RUNX1 down-regulation is strongly associated with up-regulation both positively and negatively by phosphorylation and ubiquiti- of FOXO1, which may be required to support growth of RUNX1- nation (30–34). Although FOXOs predominantly function as tran- negative tumors. The coordinate function of these two tumor sup- scriptional activators, they may also act as repressors in certain pressors may provide a failsafe mechanism that inhibits cancer- SYSTEMS BIOLOGY contexts (35). Last, FOXOs can interact with at least a dozen progression. other transcription factors, resulting in altered binding specificity and transcriptional activity (SI Appendix, Table S2) (36). Thus, in heterogeneity | triple-negative | stochastic | systems biology many ways, FOXO proteins are an archetype for the complexity that lies between signal transduction and gene expression. enetically identical mammalian cells often display patterns Here, we asked whether a focused examination of endogenous – Gof gene protein expression that are profoundly different (1 FOXOs by stochastic profiling would yield insights into their 3). Cell to cell heterogeneity has been recognized in cancer for function at the network level. Instead of using constitutively nearly half a century (4, 5). However, only lately have heteroge- active FOXO alleles to homogenize signaling (SI Appendix, neous cell populations been exploited as a means for uncover- Table S3), we quantified fluctuations in FOXO expression and – ing new mechanisms of biological regulation (6 8). With recently activity that occur naturally during 3D organotypic culture of developed techniques that can interrogate single-cell states, we breast epithelial cells (2, 37). By mapping these fluctuations onto are now poised to embrace heterogeneity rather than average it – a panel of FOXO target genes, we discovered that the measured out (9 11). FOXO expression signature divides into two groups with distinct Nonuniformities emerge at the earliest steps of gene expression – single-cell patterns. One of these groups receives a key second (12 14). Therefore, measurements of mRNA expression hetero- input from another transcription factor, RUNX1, which is var- geneity may help to uncover new biology if combined with systems iably active. RUNX1 is required for the proper timing of pro- approaches for analysis (11). This possibility offers a particularly liferative suppression in 3D spheroids, and its stable knockdown rich opportunity for unraveling transcriptional networks, where results in abnormal hyperproliferative acinar structures. In- complex combinations of factors work together to mediate pro- terestingly, this phenotype requires native single-cell regulation grams of gene expression (15). Early pioneering studies initially focused on describing the fundamental kinetics and statistics of transcription in single cells (1, 12–14, 16–19). Now, an open question is how methods that provide single-cell information Author contributions: L.W., J.S.B., and K.A.J. designed research; L.W. and K.A.J. performed should be applied to help understand the coordination of tran- research; L.W., J.S.B., and K.A.J. analyzed data; and J.S.B. and K.A.J. wrote the paper. scriptional programs and their role in cell phenotype (20, 21). The authors declare no conflict of interest. For this purpose, we recently developed a technique called This article is a PNAS Direct Submission. Y.I. is a guest editor invited by the Editorial Board. stochastic profiling (2). Stochastic profiling does not attempt to 1L.W. and K.A.J. contributed equally to this work. quantify mRNA levels in single cells but instead, gleans single- 2To whom correspondence should be addressed. E-mail: [email protected]. cell information by analyzing the statistical fluctuations in 15–20 See Author Summary on page 16499. repeated measurements of 10 cells. The increased amount of This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. starting material allows high-quality, transcriptome-wide data to 1073/pnas.1103423108/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1103423108 PNAS | October 4, 2011 | vol. 108 | no. 40 | E803–E812 Downloaded by guest on September 29, 2021 of FOXO function to withstand the increased oxidative stress expressed was the transcription factor FOXO1. The pattern of caused by RUNX1 knockdown. Combined inhibition of RUNX1 single-cell FOXO1 expression correlated with many transcripts and FOXO leads to an acute state of oxidative stress that induces that had been previously linked to oxidative stress and proliferative proliferation arrest and restores normal 3D morphology. In a suppression, suggesting a coordinated cellular response. Because large study of estrogen receptor (ER)-, progesterone receptor FOXO family transcriptional activity is itself linked to oxidative (PR)-, and HER2-negative breast cancers, we find that reduced stress and proliferation arrest (38, 39), we chose to investigate the RUNX1 expression correlates with FOXO1 up-regulation, which interplay between the expression of FOXOs and FOXO-dependent presumably enables tumor progression. Our results illustrate target genes. how careful single-cell analysis of gene expression can reveal The MCF10A clone 5E (MCF10A-5E) used for 3D culture functional interactions within transcriptional networks that are expresses not only FOXO1 but also FOXO3 (SI Appendix, Fig. important for cancer-relevant cell phenotypes. S1), and we found that both FOXO proteins were heteroge- neously expressed and localized in individual acini during mor- Results phogenesis (Fig. 1A). Together with the two FOXOs, we mon- Dissecting Single-Cell FOXO Coregulation by Stochastic Sampling. We itored time-dependent changes in the levels of 18 transcripts previously cataloged the transcriptional heterogeneities that during morphogenesis: eight genes were validated or reported emerge among individual matrix-attached breast epithelial cells FOXO targets (BTG1, CAV1, CDKN1A, FBXO32, SEMA3C, during acinar morphogenesis in a 3D culture model (2, 37). One SESN1, SOD2, and SOX4)(SI Appendix, Table S3), five genes gene that was predicted with high confidence to be nonuniformly were constitutively expressed (GAPDH, HINT1, PRDX6, S100A6, AB) FOXO1 FOXO3 BTG1 CDKN1A FBXO32 SOD2 SESN1 CAV1 SEMA3C SOX4 10 FOXO1 FOXO3 1 0 -1 Validated FOXO target d induction (log Reported FOXO target Fol 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 E-cadherin DAPI ) PRDX6 HDPAG HINT1 S100A6 UBC CDKN1C KRT10 1BNCC BCL2L13 CCNI 10 1 0 -1 Loading controls d induction (log Other Fol 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 4 6 8 1012 Day of morphogenesis C D p E Log10 (homogeneously expressed) 0 -4 -8 -12 -16 CCNB1 CCNB1 3 KRT10 3 SOD2 Candidate SOD2 BCL2L13 heterogeneities KRT10 2 2 CCNI FBXO32 SOX4 SESN1 FOXO1 1 1 CDKN1C FOXO3 BTG1 CDKN1A CCNI 0 0 FOXO3 BCL2L13 FOXO1 CDKN1A -1 CAV1 -1 FBXO32 CAV1 UBC change from geometric mean SOX4 2 -2 GAPDH -2 SEMA3C BTG1 Log False-discovery rate PRDX6 CDKN1C -3 HINT1 Standard deviations from geometric mean -3 S100A6 SESN1 61 11 9 3412 14 7813 5618 71 12 1015 123456789101112131415161718 10-cell stochastic samplings 10-cell stochastic samplings Fig. 1. Focused stochastic sampling of a FOXO expression dichotomy in 3D breast epithelial cultures.
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