@article {79, title = {BioSig3D: High Content Screening of Three-Dimensional Cell Culture Models}, journal = {PLoS One}, volume = {11}, year = {2016}, month = {2016}, pages = {e0148379}, abstract = {

BioSig3D is a computational platform for high-content screening of three-dimensional (3D) cell culture models that are imaged in full 3D volume. It provides an end-to-end solution for designing high content screening assays, based on colony organization that is derived from segmentation of nuclei in each colony. BioSig3D also enables visualization of raw and processed 3D volumetric data for quality control, and integrates advanced bioinformatics analysis. The system consists of multiple computational and annotation modules that are coupled together with a strong use of controlled vocabularies to reduce ambiguities between different users. It is a web-based system that allows users to: design an experiment by defining experimental variables, upload a large set of volumetric images into the system, analyze and visualize the dataset, and either display computed indices as a heatmap, or phenotypic subtypes for heterogeneity analysis, or download computed indices for statistical analysis or integrative biology. BioSig3D has been used to profile baseline colony formations with two experiments: (i) morphogenesis of a panel of human mammary epithelial cell lines (HMEC), and (ii) heterogeneity in colony formation using an immortalized non-transformed cell line. These experiments reveal intrinsic growth properties of well-characterized cell lines that are routinely used for biological studies. BioSig3D is being released with seed datasets and video-based documentation.

}, issn = {1932-6203}, doi = {10.1371/journal.pone.0148379}, author = {Bilgin, Cemal Cagatay and Fontenay, Gerald and Cheng, Qingsu and Hang Chang and Ju Han and Parvin, Bahram} } @article {241, title = {Stiffness of the microenvironment upregulates ERBB2 expression in 3D cultures of MCF10A within the range of mammographic density.}, journal = {Sci Rep}, volume = {6}, year = {2016}, month = {2016}, pages = {28987}, abstract = {

The effects of the stiffness of the microenvironment on the molecular response of 3D colony organization, at the maximum level of mammographic density (MD), are investigated. Phenotypic profiling reveals that 3D colony formation is heterogeneous and increased stiffness of the microenvironment, within the range of the MD, correlates with the increased frequency of aberrant 3D colony formation. Further integrative analysis of the genome-wide transcriptome and phenotypic profiling hypothesizes overexpression of ERBB2 in the premalignant MCF10A cell lines at a stiffness value that corresponds to the collagen component at high mammographic density. Subsequently, ERBB2 overexpression has been validated in the same cell line. Similar experiments with a more genetically stable cell line of 184A1 also revealed an increased frequency of aberrant colony formation with the increased stiffness; however, 184A1 did not demonstrate overexpression of ERBB2 at the same stiffness value of the high MD. These results suggest that stiffness exacerbates premalignant cell line of MCF10A.

}, issn = {2045-2322}, doi = {10.1038/srep28987}, author = {Cheng, Qingsu and Bilgin, Cemal Cagatay and Fonteney, Gerald and Hang Chang and Henderson, Matthew and Han, Ju and Parvin, Bahram} } @article {242, title = {When machine vision meets histology: A comparative evaluation of model architecture for classification of histology sections.}, journal = {Med Image Anal}, volume = {35}, year = {2016}, month = {2016 Sep 9}, pages = {530-543}, abstract = {

Classification of histology sections in large cohorts, in terms of distinct regions of microanatomy (e.g., stromal) and histopathology (e.g., tumor, necrosis), enables the quantification of tumor composition, and the construction of predictive models of genomics and clinical outcome. To tackle the large technical variations and biological heterogeneities, which are intrinsic in large cohorts, emerging systems utilize either prior knowledge from pathologists or unsupervised feature learning for invariant representation of the underlying properties in the data. However, to a large degree, the architecture for tissue histology classification remains unexplored and requires urgent systematical investigation. This paper is the first attempt to provide insights into three fundamental questions in tissue histology classification: I. Is unsupervised feature learning preferable to human engineered features? II. Does cellular saliency help? III. Does the sparse feature encoder contribute to recognition? We show that (a) in I, both Cellular Morphometric Feature and features from unsupervised feature learning lead to superior performance when compared to SIFT and [Color, Texture]; (b) in II, cellular saliency incorporation impairs the performance for systems built upon pixel-/patch-level features; and (c) in III, the effect of the sparse feature encoder is correlated with the robustness of features, and the performance can be consistently improved by the multi-stage extension of systems built upon both Cellular Morphmetric Feature and features from unsupervised feature learning. These insights are validated with two cohorts of Glioblastoma Multiforme (GBM) and Kidney Clear Cell Carcinoma (KIRC).

}, issn = {1361-8423}, doi = {10.1016/j.media.2016.08.010}, author = {Zhong, Cheng and Han, Ju and Borowsky, Alexander and Parvin, Bahram and Wang, Yunfu and Hang Chang} } @article {76, title = {Stress signaling from human mammary epithelial cells contributes to phenotypes of mammographic density}, journal = {Cancer Res}, volume = {74}, year = {2014}, month = {2014 Sep 15}, pages = {5032-44}, abstract = {

Telomere malfunction and other types of DNA damage induce an activin A-dependent stress response in mortal nontumorigenic human mammary epithelial cells that subsequently induces desmoplastic-like phenotypes in neighboring fibroblasts. Some characteristics of this fibroblast/stromal response, such as reduced adipocytes and increased extracellular matrix content, are observed not only in tumor tissues but also in disease-free breast tissues at high risk for developing cancer, especially high mammographic density tissues. We found that these phenotypes are induced by repression of the fatty acid translocase CD36, which is seen in desmoplastic and disease-free high mammographic density tissues. In this study, we show that epithelial cells from high mammographic density tissues have more DNA damage signaling, shorter telomeres, increased activin A secretion and an altered DNA damage response compared with epithelial cells from low mammographic density tissues. Strikingly, both telomere malfunction and activin A expression in epithelial cells can repress CD36 expression in adjacent fibroblasts. These results provide new insights into how high mammographic density arises and why it is associated with breast cancer risk, with implications for the definition of novel invention targets (e.g., activin A and CD36) to prevent breast cancer.

}, keywords = {Antigens, CD36, Breast Neoplasms, DNA Damage, Epithelial Cells, Female, Humans, Mammary Glands, Human, Phenotype, Signal Transduction}, issn = {1538-7445}, doi = {10.1158/0008-5472.CAN-13-3390}, author = {DeFilippis, Rosa Anna and Fordyce, Colleen and Patten, Kelley and Hang Chang and Zhao, Jianxin and Fontenay, Gerald V and Kerlikowske, Karla and Parvin, Bahram and Tlsty, Thea D} } @article {81, title = {Breast fibroblasts modulate early dissemination, tumorigenesis, and metastasis through alteration of extracellular matrix characteristics}, journal = {Neoplasia}, volume = {15}, year = {2013}, month = {2013 Mar}, pages = {249-62}, abstract = {

A wealth of evidence has now demonstrated that the microenvironment in which a tumorigenic cell evolves is as critical to its evolution as the genetic mutations it accrues. However, there is still relatively little known about how signals from the microenvironment contribute to the early events in the progression to malignancy. To address this question, we used a premalignant mammary model to examine how fibroblasts, and the extracellular matrix (ECM) proteins they secrete, influence progression to malignancy. Their effect on metastatic malignant cells was also assessed for comparison. We found that carcinoma-associated fibroblasts, and the distinct aligned ECM they deposit, can cause both premalignant and malignant mammary epithelial cells to assume a mesenchymal morphology that is associated with increased dissemination and metastasis, while benign reduction mammoplasty fibroblasts favor the maintenance of an epithelial morphology and constrain early dissemination, tumor growth, and metastasis. Our results suggest that normalizing the organization of the ECM could be effective in limiting systemic dissemination and tumor growth.

}, keywords = {Animals, Breast, Cell Line, Tumor, Cell Transformation, Neoplastic, Coculture Techniques, Epithelial Cells, Extracellular Matrix, Extracellular Signal-Regulated MAP Kinases, Female, Fibroblasts, Humans, Lung Neoplasms, Mammary Neoplasms, Experimental, Neoplasm Metastasis, Phenotype, Proto-Oncogene Proteins c-jun, rho GTP-Binding Proteins, Signal Transduction, Transforming Growth Factor beta}, issn = {1476-5586}, author = {Dumont, Nancy and Liu, Bob and DeFilippis, Rosa Anna and Hang Chang and Rabban, Joseph T and Karnezis, Anthony N and Tjoe, Judy A and Marx, James and Parvin, Bahram and Tlsty, Thea D} } @article {82, title = {CD36 repression activates a multicellular stromal program shared by high mammographic density and tumor tissues}, journal = {Cancer Discov}, volume = {2}, year = {2012}, month = {2012 Sep}, pages = {826-39}, abstract = {

UNLABELLED: Although high mammographic density is considered one of the strongest risk factors for invasive breast cancer, the genes involved in modulating this clinical feature are unknown. Tissues of high mammographic density share key histologic features with stromal components within malignant lesions of tumor tissues, specifically low adipocyte and high extracellular matrix (ECM) content. We show that CD36, a transmembrane receptor that coordinately modulates multiple protumorigenic phenotypes, including adipocyte differentiation, angiogenesis, cell-ECM interactions, and immune signaling, is greatly repressed in multiple cell types of disease-free stroma associated with high mammographic density and tumor stroma. Using both in vitro and in vivo assays, we show that CD36 repression is necessary and sufficient to recapitulate the above-mentioned phenotypes observed in high mammographic density and tumor tissues. Consistent with a functional role for this coordinated program in tumorigenesis, we observe that clinical outcomes are strongly associated with CD36 expression.

SIGNIFICANCE: CD36 simultaneously controls adipocyte content and matrix accumulation and is coordinately repressed in multiple cell types within tumor and high mammographic density stroma, suggesting that activation of this stromal program is an early event in tumorigenesis. Levels of CD36 and extent of mammographic density are both modifiable factors that provide potential for intervention.

}, keywords = {Adipocytes, Animals, Antigens, CD36, Breast Neoplasms, Cell Differentiation, Female, Humans, Mammography, Mice, Mice, Knockout, Risk Factors, Signal Transduction, Stromal Cells}, issn = {2159-8290}, doi = {10.1158/2159-8290.CD-12-0107}, author = {DeFilippis, Rosa Anna and Hang Chang and Dumont, Nancy and Rabban, Joseph T and Chen, Yunn-Yi and Fontenay, Gerald V and Berman, Hal K and Gauthier, Mona L and Zhao, Jianxin and Hu, Donglei and Marx, James J and Tjoe, Judy A and Ziv, Elad and Febbraio, Maria and Kerlikowske, Karla and Parvin, Bahram and Tlsty, Thea D} } @article {83, title = {Identification of fluorescent compounds with non-specific binding property via high throughput live cell microscopy}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e28802}, abstract = {

INTRODUCTION: Compounds exhibiting low non-specific intracellular binding or non-stickiness are concomitant with rapid clearing and in high demand for live-cell imaging assays because they allow for intracellular receptor localization with a high signal/noise ratio. The non-stickiness property is particularly important for imaging intracellular receptors due to the equilibria involved.

METHOD: Three mammalian cell lines with diverse genetic backgrounds were used to screen a combinatorial fluorescence library via high throughput live cell microscopy for potential ligands with high in- and out-flux properties. The binding properties of ligands identified from the first screen were subsequently validated on plant root hair. A correlative analysis was then performed between each ligand and its corresponding physiochemical and structural properties.

RESULTS: The non-stickiness property of each ligand was quantified as a function of the temporal uptake and retention on a cell-by-cell basis. Our data shows that (i) mammalian systems can serve as a pre-screening tool for complex plant species that are not amenable to high-throughput imaging; (ii) retention and spatial localization of chemical compounds vary within and between each cell line; and (iii) the structural similarities of compounds can infer their non-specific binding properties.

CONCLUSION: We have validated a protocol for identifying chemical compounds with non-specific binding properties that is testable across diverse species. Further analysis reveals an overlap between the non-stickiness property and the structural similarity of compounds. The net result is a more robust screening assay for identifying desirable ligands that can be used to monitor intracellular localization. Several new applications of the screening protocol and results are also presented.

}, keywords = {Animals, Arabidopsis, Cell Line, Cell Survival, Combinatorial Chemistry Techniques, Fluorescent Dyes, Humans, Ligands, Mice, Microscopy, Small Molecule Libraries}, issn = {1932-6203}, doi = {10.1371/journal.pone.0028802}, author = {Nath, Sangeeta and Spencer, Virginia A and Ju Han and Hang Chang and Zhang, Kai and Fontenay, Gerald V and Anderson, Charles and Hyman, Joel M and Nilsen-Hamilton, Marit and Chang, Young-Tae and Parvin, Bahram} } @article {289, title = {Inference of causal networks from time-varying transcriptome data via sparse coding.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e42306}, abstract = {

Temporal analysis of genome-wide data can provide insights into the underlying mechanism of the biological processes in two ways. First, grouping the temporal data provides a richer, more robust representation of the underlying processes that are co-regulated. The net result is a significant dimensional reduction of the genome-wide array data into a smaller set of vocabularies for bioinformatics analysis. Second, the computed set of time-course vocabularies can be interrogated for a potential causal network that can shed light on the underlying interactions. The method is coupled with an experiment for investigating responses to high doses of ionizing radiation with and without a small priming dose. From a computational perspective, inference of a causal network can rapidly become computationally intractable with the increasing number of variables. Additionally, from a bioinformatics perspective, larger networks always hinder interpretation. Therefore, our method focuses on inferring the simplest network that is computationally tractable and interpretable. The method first reduces the number of temporal variables through consensus clustering to reveal a small set of temporal templates. It then enforces simplicity in the network configuration through the sparsity constraint, which is further regularized by requiring continuity between consecutive time points. We present intermediate results for each computational step, and apply our method to a time-course transcriptome dataset for a cell line receiving a challenge dose of ionizing radiation with and without a prior priming dose. Our analyses indicate that (i) the priming dose increases the diversity of the computed templates (e.g., diversity of transcriptome signatures); thus, increasing the network complexity; (ii) as a result of the priming dose, there are a number of unique templates with delayed and oscillatory profiles; and (iii) radiation-induced stress responses are enriched through pathway and subnetwork studies.

}, keywords = {Gene Expression Profiling, Genome-Wide Association Study, Humans, Radiation, Ionizing, Transcriptome}, issn = {1932-6203}, doi = {10.1371/journal.pone.0042306}, author = {Zhang, Kai and Ju Han and Groesser, Torsten and Fontenay, Gerald and Parvin, Bahram} } @article {84, title = {Persistence of γ-H2AX and 53BP1 foci in proliferating and non-proliferating human mammary epithelial cells after exposure to γ-rays or iron ions}, journal = {Int J Radiat Biol}, volume = {87}, year = {2011}, month = {2011 Jul}, pages = {696-710}, abstract = {

PURPOSE: To investigate γ-H2AX (phosphorylated histone H2AX) and 53BP1 (tumour protein 53 binding protein No. 1) foci formation and removal in proliferating and non-proliferating human mammary epithelial cells (HMEC) after exposure to sparsely and densely ionising radiation under different cell culture conditions.

MATERIAL AND METHODS: HMEC cells were grown either as monolayers (2D) or in extracellular matrix to allow the formation of acinar structures in vitro (3D). Foci numbers were quantified by image analysis at various time points after exposure.

RESULTS: Our results reveal that in non-proliferating cells under 2D and 3D cell culture conditions, iron-ion induced γ-H2AX foci were still present at 72 h after exposure, although 53BP1 foci returned to control levels at 48 h. In contrast in proliferating HMEC, both γ-H2AX and 53BP1 foci decreased to control levels during the 24-48 h time interval after irradiation under 2D conditions. Foci numbers decreased faster after γ-ray irradiation and returned to control levels by 12 h regardless of marker, cell proliferation status, and cell culture condition.

CONCLUSIONS: The disappearance of radiation-induced γ-H2AX and 53BP1 foci in HMEC has different dynamics that depend on radiation quality and proliferation status. Notably, the general patterns do not depend on the cell culture condition (2D versus 3D). We speculate that the persistent γ-H2AX foci in iron-ion irradiated non-proliferating cells could be due to limited availability of double-strand break (DSB) repair pathways in G0/G1-phase, or that repair of complex DSB requires replication or chromatin remodelling.

}, keywords = {Cell Line, Cell Proliferation, Gamma Rays, Heavy Ions, Histones, Humans, Iron, Mammary Glands, Human, Tumor Suppressor Protein p53}, issn = {1362-3095}, doi = {10.3109/09553002.2010.549535}, author = {Groesser, Torsten and Hang Chang and Gerald Fontenay and Chen, James and Costes, Sylvain V and Helen Barcellos-Hoff, Mary and Parvin, Bahram and Rydberg, Bjorn} } @article {86, title = {Linking changes in epithelial morphogenesis to cancer mutations using computational modeling}, journal = {PLoS Comput Biol}, volume = {6}, year = {2010}, month = {2010}, abstract = {

Most tumors arise from epithelial tissues, such as mammary glands and lobules, and their initiation is associated with the disruption of a finely defined epithelial architecture. Progression from intraductal to invasive tumors is related to genetic mutations that occur at a subcellular level but manifest themselves as functional and morphological changes at the cellular and tissue scales, respectively. Elevated proliferation and loss of epithelial polarization are the two most noticeable changes in cell phenotypes during this process. As a result, many three-dimensional cultures of tumorigenic clones show highly aberrant morphologies when compared to regular epithelial monolayers enclosing the hollow lumen (acini). In order to shed light on phenotypic changes associated with tumor cells, we applied the bio-mechanical IBCell model of normal epithelial morphogenesis quantitatively matched to data acquired from the non-tumorigenic human mammary cell line, MCF10A. We then used a high-throughput simulation study to reveal how modifications in model parameters influence changes in the simulated architecture. Three parameters have been considered in our study, which define cell sensitivity to proliferative, apoptotic and cell-ECM adhesive cues. By mapping experimental morphologies of four MCF10A-derived cell lines carrying different oncogenic mutations onto the model parameter space, we identified changes in cellular processes potentially underlying structural modifications of these mutants. As a case study, we focused on MCF10A cells expressing an oncogenic mutant HER2-YVMA to quantitatively assess changes in cell doubling time, cell apoptotic rate, and cell sensitivity to ECM accumulation when compared to the parental non-tumorigenic cell line. By mapping in vitro mutant morphologies onto in silico ones we have generated a means of linking the morphological and molecular scales via computational modeling. Thus, IBCell in combination with 3D acini cultures can form a computational/experimental platform for suggesting the relationship between the histopathology of neoplastic lesions and their underlying molecular defects.

}, keywords = {Apoptosis, Breast Neoplasms, Cell Proliferation, Computer Simulation, Epithelium, Extracellular Matrix, Female, Humans, Mammary Glands, Human, Models, Biological, Morphogenesis, Mutation, Receptor, ErbB-2}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1000900}, author = {Rejniak, Katarzyna A and Wang, Shizhen E and Bryce, Nicole S and Hang Chang and Parvin, Bahram and Jourquin, Jerome and Estrada, Lourdes and Gray, Joe W and Arteaga, Carlos L and Weaver, Alissa M and Quaranta, Vito and Anderson, Alexander R A} } @article {87, title = {Molecular predictors of 3D morphogenesis by breast cancer cell lines in 3D culture}, journal = {PLoS Comput Biol}, volume = {6}, year = {2010}, month = {2010 Feb}, pages = {e1000684}, abstract = {

Correlative analysis of molecular markers with phenotypic signatures is the simplest model for hypothesis generation. In this paper, a panel of 24 breast cell lines was grown in 3D culture, their morphology was imaged through phase contrast microscopy, and computational methods were developed to segment and represent each colony at multiple dimensions. Subsequently, subpopulations from these morphological responses were identified through consensus clustering to reveal three clusters of round, grape-like, and stellate phenotypes. In some cases, cell lines with particular pathobiological phenotypes clustered together (e.g., ERBB2 amplified cell lines sharing the same morphometric properties as the grape-like phenotype). Next, associations with molecular features were realized through (i) differential analysis within each morphological cluster, and (ii) regression analysis across the entire panel of cell lines. In both cases, the dominant genes that are predictive of the morphological signatures were identified. Specifically, PPARgamma has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPARgamma has been validated through two supporting biological assays.

}, keywords = {Biomarkers, Tumor, Breast Neoplasms, Cell Culture Techniques, Cell Line, Tumor, Female, Gene Expression Profiling, Histocytochemistry, Humans, Image Processing, Computer-Assisted, Models, Biological, Phenotype, PPAR gamma, Receptor, ErbB-2, Reproducibility of Results}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1000684}, author = {Han, Ju and Chang, Hang and Giricz, Orsi and Lee, Genee Y and Baehner, Frederick L and Gray, Joe W and Bissell, Mina J and Kenny, Paraic A and Parvin, Bahram} } @article {88, title = {Multidimensional profiling of cell surface proteins and nuclear markers}, journal = {IEEE/ACM Trans Comput Biol Bioinform}, volume = {7}, year = {2010}, month = {2010 Jan-Mar}, pages = {80-90}, abstract = {

Cell membrane proteins play an important role in tissue architecture and cell-cell communication. We hypothesize that segmentation and multidimensional characterization of the distribution of cell membrane proteins, on a cell-by-cell basis, enable improved classification of treatment groups and identify important characteristics that can otherwise be hidden. We have developed a series of computational steps to 1) delineate cell membrane protein signals and associate them with a specific nucleus; 2) compute a coupled representation of the multiplexed DNA content with membrane proteins; 3) rank computed features associated with such a multidimensional representation; 4) visualize selected features for comparative evaluation through heatmaps; and 5) discriminate between treatment groups in an optimal fashion. The novelty of our method is in the segmentation of the membrane signal and the multidimensional representation of phenotypic signature on a cell-by-cell basis. To test the utility of this method, the proposed computational steps were applied to images of cells that have been irradiated with different radiation qualities in the presence and absence of other small molecules. These samples are labeled for their DNA content and E-cadherin membrane proteins. We demonstrate that multidimensional representations of cell-by-cell phenotypes improve predictive and visualization capabilities among different treatment groups, and identify hidden variables.

}, keywords = {Cadherins, Cell Membrane, Cell Nucleus, Computer Simulation, DNA, Gene Expression Profiling, Membrane Proteins, Models, Biological}, issn = {1557-9964}, doi = {10.1109/TCBB.2008.134}, author = {Ju Han and Hang Chang and Andarawewa, Kumari and Yaswen, Paul and Barcellos-Hoff, Mary Helen and Parvin, Bahram} }