Sameer S. Bajikar

A time- and matrix-dependent TGFBR3–JUND–KRT5 regulatory circuit in single breast epithelial cells and basal-like premalignancies

Basal-like breast carcinoma is characterized by poor prognosis and high intratumour heterogeneity. In an immortalized basal-like breast epithelial cell line, we identified two anticorrelated gene-expression programs that arise among single extracellular matrix (ECM)-attached cells during organotypic three-dimensional culture. The first contains multiple TGF-β-related genes including TGFBR3, whereas the second contains JUND and the basal-like marker KRT5. TGFBR3 and JUND interconnect through four negative-feedback loops to form a circuit that exhibits spontaneous damped oscillations in three-dimensional culture. The TGFBR3–JUND circuit is conserved in some premalignant lesions that heterogeneously express KRT5. The circuit depends on ECM engagement, as detachment causes a rewiring that is triggered by RPS6 dephosphorylation and maintained by juxtacrine tenascin C, which is critical for intraductal colonization of basal-like breast cancer cells in vivo. Intratumour heterogeneity need not stem from partial differentiation and could instead reflect dynamic toggling of cells between expression states that are not cell autonomous.

Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles

Significance Cell-to-cell variations in gene regulation occur in a number of biological contexts, such as development and cancer. Discovering regulatory heterogeneities in an unbiased manner is difficult owing to the population averaging that is required for most global molecular methods. Here, we show that we can infer single-cell regulatory states by mathematically deconvolving global measurements taken as averages from small groups of cells. This averaging-and-deconvolution approach allows us to quantify single-cell regulatory heterogeneities while avoiding the measurement noise of global single-cell techniques. Our method is particularly relevant to solid tissues, where single-cell dissociation and molecular profiling is especially problematic. Regulated changes in gene expression underlie many biological processes, but globally profiling cell-to-cell variations in transcriptional regulation is problematic when measuring single cells. Transcriptome-wide identification of regulatory heterogeneities can be robustly achieved by randomly collecting small numbers of cells followed by statistical analysis. However, this stochastic-profiling approach blurs out the expression states of the individual cells in each pooled sample. Here, we show that the underlying distribution of single-cell regulatory states can be deconvolved from stochastic-profiling data through maximum-likelihood inference. Guided by the mechanisms of transcriptional regulation, we formulated plausible mixture models for cell-to-cell regulatory heterogeneity and maximized the resulting likelihood functions to infer model parameters. Inferences were validated both computationally and experimentally for different mixture models, which included regulatory states for multicellular function that were occupied by as few as 1 in 40 cells of the population. Importantly, when the method was extended to programs of heterogeneously coexpressed transcripts, we found that population-level inferences were much more accurate with pooled samples than with one-cell samples when the extent of sampling was limited. Our deconvolution method provides a means to quantify the heterogeneous regulation of molecular states efficiently and gain a deeper understanding of the heterogeneous execution of cell decisions.

Bone Marrow–Derived Cell-Specific Chemokine (C-C Motif) Receptor-2 Expression is Required for Arteriolar Remodeling

Objective—Bone marrow-derived cells (BMCs) and inflammatory chemokine receptors regulate arteriogenesis and angiogenesis. Here, we tested whether arteriolar remodeling in response to an inflammatory stimulus is dependent on BMC-specific chemokine (C-C motif) receptor 2 (CCR2) expression and whether this response involves BMC transdifferentiation into smooth muscle. Methods and Results—Dorsal skinfold window chambers were implanted into C57Bl/6 wild-type (WT) mice, as well as the following bone marrow chimeras (donor-host): WT-WT, CCR2−/−-WT, WT-CCR2−/−, and EGFP+-WT. One day after implantation, tissue MCP-1 levels rose from “undetectable” to 463pg/mg, and the number of EGFP+ cells increased more than 4-fold, indicating marked inflammation. A 66% (28 &mgr;m) increase in maximum arteriolar diameter was observed over 7 days in WT-WT mice. This arteriolar remodeling response was completely abolished in CCR2−/−-WT mice but largely rescued in WT-CCR2−/− mice. EGFP+ BMCs were numerous throughout the tissue, but we found no evidence that EGFP+ BMCs transdifferentiate into smooth muscle, based on examination of >800 arterioles and venules. Conclusions—BMC-specific CCR2 expression is required for injury/inflammation-associated arteriolar remodeling, but this response is not characterized by the differentiation of BMCs into smooth muscle.

Multiscale models of cell signaling.

Computational models of signal transduction face challenges of scale below the resolution of a single cell. Here, we organize these challenges around three key interfaces for multiscale models of cell signaling: molecules to pathways, pathways to networks, and networks to outcomes. Each interface requires its own set of computational approaches and systems-level data, and no single approach or dataset can effectively bridge all three interfaces. This suggests that realistic “whole-cell” models of signaling will need to agglomerate different model types that span critical intracellular scales. Future multiscale models will be valuable for understanding the impact of signaling mutations or population variants that lead to cellular diseases such as cancer.

Automated brightfield morphometry of 3D organoid populations by OrganoSeg

Spheroid and organoid cultures are powerful in vitro models for biology, but size and shape diversity within the culture is largely ignored. To streamline morphometric profiling, we developed OrganoSeg, an open-source software that integrates segmentation, filtering, and analysis for archived brightfield images of 3D culture. OrganoSeg is more accurate and flexible than existing platforms, and we illustrate its potential by stratifying 5167 breast-cancer spheroid and 5743 colon and colorectal-cancer organoid morphologies. Organoid transcripts grouped by morphometric signature heterogeneity were enriched for biological processes not prominent in the original RNA sequencing data. OrganoSeg enables complete, objective quantification of brightfield phenotypes, which may give insight into the molecular and multicellular mechanisms of organoid regulation.

Abstract 5225: Single-cell gene-expression programs and basal-like breast cancer.

Basal-like carcinoma is a subtype of breast cancer that is characterized by poor prognosis and high intratumor heterogeneity. In basal-like breast epithelia, we have identified two anticorrelated gene-expression programs that arise among single extracellular matrix (ECM)-attached cells during organotypic 3D culture. The first program contains multiple TGFβ-related genes including TGFBR3, and its heterogeneous induction is critical to suppress ductal branching. The second program contains JUND together with the basal-like marker, KRT5. Homogenizing JUND expression in single cells leads to 3D acini with bridged lumina that are similar to cribiform ductal carcinoma in situ. TGFBR3 and JUND together comprise a circuit that is interconnected via four negative-feedback loops. Computational modeling of the circuit predicts damped, antiphase oscillations upon stimulation with endogenous impulses of TGFβ-like ligand, and we directly observe these spontaneous responses in 3D culture by live-cell imaging. The TGFBR3-JUND circuit is remarkably conserved in early basal-like tumors that heterogeneously express KRT5, suggesting that asynchronous circuit dynamics are active in this patient subset. We further show that the circuit is strongly dependent on ECM engagement, as detachment leads to a rewiring that is triggered by RPS6 dephosphorylation and maintained by juxtacrine signaling from tenascin C. Breast tumor heterogeneity need not stem from partial basal-like differentiation and could instead reflect dynamic toggling of individual cells between expression states. Citation Format: Chun-Chao Wang, Leen Jamal, Sameer S. Bajikar, Kristen A. Atkins, Kevin A. Janes. Single-cell gene-expression programs and basal-like breast cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5225. doi:10.1158/1538-7445.AM2013-5225

Abstract 4949: A dynamic TGFBR3-JUND expression circuit in single basal-like breast epithelial cells

Basal-like carcinoma is a subtype of breast cancer that is characterized by poor prognosis and high intratumor heterogeneity. In basal-like breast epithelia, we have identified two anticorrelated gene-expression programs that arise among single extracellular matrix (ECM)-attached cells during organotypic 3D culture. The first program contains multiple TGFβ-related genes including TGFBR3, and its heterogeneous induction is critical to suppress ductal branching. The second program contains JUND together with the basal-like marker, KRT5. Homogenizing JUND expression in single cells leads to 3D acini with bridged lumina that are similar to cribiform ductal carcinoma in situ. TGFBR3 and JUND together comprise a circuit that is interconnected via four negative-feedback loops. Computational modeling of the circuit predicts damped, antiphase oscillations upon stimulation with endogenous impulses of TGFβ-like ligand, and we directly observe these spontaneous responses in 3D culture by live-cell imaging. The TGFBR3-JUND circuit and its ECM-dependent regulation are remarkably conserved in early basal-like tumors that heterogeneously express KRT5, suggesting that asynchronous circuit dynamics are active in this patient subset. Preliminary studies suggested this intrinsic single-cell expression circuit might be regulated by a transcription factor, Nrf2, and a tumor suppressor, menin. Together, breast tumor heterogeneity need not stem from partial basal-like differentiation and could instead reflect dynamic toggling of individual cells between expression states. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4949. doi:1538-7445.AM2012-4949

Abstract SY17-01: Heterogeneous single-cell expression programs and basal-like breast cancer

Cell-to-cell variations and asymmetries in gene and protein expression play an important role in development and tumorigenesis. But, how do we identify the heterogeneities in the first place? In this talk, I will present results from a new technique called “stochastic sampling” that attempts to address this general problem. Stochastic sampling involves the repeated, random selection of very small cell populations (∼10 cells) followed by quantitative gene-expression profiling and simple statistical analysis (Nat Methods 7:311-7 [2010]). We combined laser-capture microdissection, a customized single-cell amplification protocol, quantitative PCR, and oligonucleotide microarrays to implement stochastic sampling in a 3-D in vitro model of breast-epithelial acinar morphogenesis. Our analysis identified hundreds of genes whose expression dichotomizes when human breast-epithelial cells are cultured as gland-like acinar structures. Very few of these non-uniformities could have been predicted from standard microarray data, indicating the unique information provided by the stochastic-profiling approach. We are currently working to unravel the mechanisms that interconnect a reciprocal dichotomy between transforming growth factor-β (TGFβ) signaling and the junD transcription factor. We find that TGFβ receptor 3 (TGFBR3) is heterogeneously induced during morphogenesis, and blocking its non-uniform induction causes branching morphogenesis in 3-D culture. Addition of recombinant growth-differentation factor 11 (GDF11), a TGFβ-family ligand whose endogenous expression is heterogeneous, potently suppresses branching caused by TGFBR3 knockdown. Single-cell expression of these TGFβ-family genes is anticorrelated with JUND mRNA, and constitutive expression of JUND causes a distinct phenotype reminiscent of cribiform ductal carcinoma in situ. The interconnections between TGFβ signaling, TGFBR3, and JUND create a network motif that could give rise to oscillations, and our preliminary work suggests that TGFβ signaling activity oscillates sporadically with a period of ∼6-8 hr. Asynchronous single-cell oscillations provide an explanation for why TGFBR3, GDF11, and JUND were first revealed by stochastic profiling. This endogenous TGFBR-JUND pathway may be particularly relevant for a subtype of breast cancer, called basal-like carcinoma, which is known to be strongly heterogeneous at the single-cell level. In 3-D culture, the basal cytokeratin KRT5 is tightly coexpressed with JUND in cells attached to basement membrane. Remarkably, this correlation switches to an anticorrelation when cells are detached from basement membrane, and we observe the same dependencies in basal-like breast cancers with heterogeneous Krt5 protein expression. The single-cell programs identified by stochastic profiling in the 3-D culture model may thus have particular translational relevance to heterogeneous basal-like breast cancer, which is the most lethal subtype yet described. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr SY17-01. doi:10.1158/1538-7445.AM2011-SY17-01