Modeling precision treatment of breast cancer

Background: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. Results: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. Conclusions: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified

ATM suppresses SATB1-induced malignant progression in breast epithelial cells.

SATB1 drives metastasis when expressed in breast tumor cells by radically reprogramming gene expression. Here, we show that SATB1 also has an oncogenic activity to transform certain non-malignant breast epithelial cell lines. We studied the non-malignant MCF10A cell line, which is used widely in the literature. We obtained aliquots from two different sources (here we refer to them as MCF10A-1 and MCF10A-2), but found them to be surprisingly dissimilar in their responses to oncogenic activity of SATB1. Ectopic expression of SATB1 in MCF10A-1 induced tumor-like morphology in three-dimensional cultures, led to tumor formation in immunocompromised mice, and when injected into tail veins, led to lung metastasis. The number of metastases correlated positively with the level of SATB1 expression. In contrast, SATB1 expression in MCF10A-2 did not lead to any of these outcomes. Yet DNA copy-number analysis revealed that MCF10A-1 is indistinguishable genetically from MCF10A-2. However, gene expression profiling analysis revealed that these cell lines have significantly divergent signatures for the expression of genes involved in oncogenesis, including cell cycle regulation and signal transduction. Above all, the early DNA damage-response kinase, ATM, was greatly reduced in MCF10A-1 cells compared to MCF10A-2 cells. We found the reason for reduction to be phenotypic drift due to long-term cultivation of MCF10A. ATM knockdown in MCF10A-2 and two other non-malignant breast epithelial cell lines, 184A1 and 184B4, enabled SATB1 to induce malignant phenotypes similar to that observed for MCF10A-1. These data indicate a novel role for ATM as a suppressor of SATB1-induced malignancy in breast epithelial cells, but also raise a cautionary note that phenotypic drift could lead to dramatically different functional outcomes

ATM Suppresses SATB1-Induced Malignant Progression in Breast Epithelial Cells

<div><p>SATB1 drives metastasis when expressed in breast tumor cells by radically reprogramming gene expression. Here, we show that SATB1 also has an oncogenic activity to transform certain non-malignant breast epithelial cell lines. We studied the non-malignant MCF10A cell line, which is used widely in the literature. We obtained aliquots from two different sources (here we refer to them as MCF10A-1 and MCF10A-2), but found them to be surprisingly dissimilar in their responses to oncogenic activity of SATB1. Ectopic expression of SATB1 in MCF10A-1 induced tumor-like morphology in three-dimensional cultures, led to tumor formation in immunocompromised mice, and when injected into tail veins, led to lung metastasis. The number of metastases correlated positively with the level of SATB1 expression. In contrast, SATB1 expression in MCF10A-2 did not lead to any of these outcomes. Yet DNA copy-number analysis revealed that MCF10A-1 is indistinguishable genetically from MCF10A-2. However, gene expression profiling analysis revealed that these cell lines have significantly divergent signatures for the expression of genes involved in oncogenesis, including cell cycle regulation and signal transduction. Above all, the early DNA damage-response kinase, ATM, was greatly reduced in MCF10A-1 cells compared to MCF10A-2 cells. We found the reason for reduction to be phenotypic drift due to long-term cultivation of MCF10A. ATM knockdown in MCF10A-2 and two other non-malignant breast epithelial cell lines, 184A1 and 184B4, enabled SATB1 to induce malignant phenotypes similar to that observed for MCF10A-1. These data indicate a novel role for ATM as a suppressor of SATB1-induced malignancy in breast epithelial cells, but also raise a cautionary note that phenotypic drift could lead to dramatically different functional outcomes.</p> </div

SATB1 is endogenously expressed in aggressive breast cancer cell lines and its ectopic expression induces malignant phenotype in non-malignant MCF10A-1, but not in MCF10A-2 cells.

<p><b>A</b>) (Top) Quantitative RT-PCR analysis for SATB1 expression relative to GAPDH in MCF10A cell lines from two different sources (MCF10A-1 and MCF10A-2), 184A1, 184B5 and MCF10A progression series (MCF10A-neoT and CA1d), BT549 and MDA-MB-231. (Bottom) Immunoblot for SATB1 expression using the same cell lines as in quantitative RT-PCR analysis. α-tubulin was used as an internal loading control. <b>B</b>) Immunoblot showing the expression level of SATB1 before and after SATB1 overexpression in MCF10A-1 and MCF10A-2 cells. ß-actin was used as an internal loading control. <b>C</b>) Colony morphologies of MCF10A-1 and MCF10A-2 control and SATB1 overexpressing cells (pLXSN-SATB1: pooled populations), and MDA-MB-231 control and SATB1 depleted (SATB1 shRNA) cells at six days of 3D matrix on-top culturing. Images were captured with Phase 1 at 20X magnification. Scale bars, 100 µm. Note that SATB1 overexpression caused MCF10A-1 to form a mixture of large spheroid and spindle structures, indicated by white and blue arrows, respectively, while it caused MCF10A-2 cells to form larger spheroid structures. The aggressive breast cancer cell line, MDA-MB-231, formed network-like spindle structures, which was inhibited by knockdown of SATB1. <b>D</b>) Invasion assay of MCF10A-1, MCF10A-2, MCF10A-neoT and CA1d cell lines before and after SATB1 overexpression. Parental cells lines are shown in blue; SATB1 overexpressing cells are shown in pink. Error bars indicate s.e.m., n = 3 experiments. <b>E</b>) Vector control (top row) and SATB1-expressing MCF10A-1 (pLXN-SATB1) (bottom two rows) grown on Matrigel were stained for F-actin (red), ß-catenin (green), integrin α6 (green), SATB1 (green) and DAPI (blue). Note that control cells showed the typical acinar structure whereas SATB1-expressing cells showed large spheroid (i) and spindle (ii) structures. No acinar structures were detected in SATB1-expressing MCF10A-1. Scale bars, 15 µm.</p

SATB1 overexpression induces EMT in MCF10A-1 cells.

<p><b>A</b>) Cell proliferation assay to compare the growth over time (days, d) of the parental MCF10A-1 and vector control cells with single-cell-derived SATB1-overexpressing MCF10A-1 clones clone-1 and clone-2 on plastic dishes (2D) or on Matrigel (3D). Error bars indicate ±s.e.m. from three independent experiments. <b>B</b>) Representative photographs of soft agar colonies formed by control and SATB1 overexpressing (clone-1 and clone-2) MCF10A-1 cells after 25 days of culture. The mean colony counts from three replicates are shown. <b>C</b>) Immunoblot analyses for the expression of mesenchymal markers (fibronectin and vimentin), epithelial markers (E-cadherin and ß-catenin) as well as SATB1 target ERBB2 in MDA-MB-231 (parental, control and SATB1-depleted by shRNA1 or shRNA2) and MCF10A-1 (parental, control, clone-1 and clone-2). Cell lysates were prepared from cells cultured on plastic dishes (2D). GAPDH was used as a loading control.</p

The combination of ectopic SATB1 expression and ATM depletion induces aggressive phenotype in non-malignant mammary epithelial cells.

<p><b>A</b>) Immunoblot showing ATM and SATB1 levels before and after SATB1 overexpression (SATB1) and ATM depletion (shATM) in non-malignant MCF10A-1, MCF10A-2, 184A1 and 184B5 cells. α-tubulin was used as an internal loading control. <b>B</b>) Colony morphologies of vector control, ATM depleted (shATM), SATB1 overexpressing (SATB1) and ATM depleted/SATB1 overexpressing (shATM+SATB1) cells generated as in (<b>C</b>). Cells were grown in 3D Matrix on-top cultures. The images were captured with phase 1 at 20X magnification on five days after plating. Scale bars, 100 µm. <b>D</b>) Invasion assay of ATM depleted (shATM), SATB1 overexpressing (SATB1) and ATM depleted/SATB1 overexpressing (shATM+SATB1) cells generated as in (<b>a</b>). Error bars indicate ±s.e.m., n = 3 experiments.</p

Differential response to SATB1 overexpression by MCF10A-1 and MCF10A-2 cells is attributed to their disparate gene expression patterns involved in cell cycle regulation.

<p><b>A</b>) (Left) Gene copy number profiles for MCF10A-1 and MCF10A-2. Each dot represents the copy number for a given SNP that is ordered by genomic position, from chromosome 1 to chromosomes X and Y. Vertical lines represent chromosome boundaries for the autosomes. Data for MCF10A-1 and MCF10A-2 are plotted in green and blue, respectively. The copy number profiles for both cell lines were largely overlapping, indicating that the cell lines are genomically the same. (Right) Copy number correlation between MCF10A-1 and MCF10A-2. Each dot represents copy number for a single SNP, where copy number for the MCF10A-1 cell line is plotted along the x-axis and that for the MCF10A-2 cell line is plotted along the y-axis. The Pearson correlation is 0.96 (p<2.2e-16), which supports the idea that the two cell lines are identical. <b>B</b>) Expression analysis of genes associated with cancer progression in MCF10A-1 and MCF10A-2. Genes are categorized based on their specific biochemical functions. Fold gene expression in MCF10A-1 (blue bar) relative to MCF10A-2 (red dotted line at 1 fold) is shown. Each gene expression level was normalized to the level of GAPDH. <b>C</b>) Expression analysis of genes associated with cell cycle regulation in MCF10A-1 and MCF10A-2. Genes are categorized based on their roles in specific cell cycle phases. The result is shown as in (<b>B</b>).</p