TY - JOUR T1 - BioSig3D: High Content Screening of Three-Dimensional Cell Culture Models JF - PLoS One Y1 - 2016 A1 - Bilgin, Cemal Cagatay A1 - Fontenay, Gerald A1 - Cheng, Qingsu A1 - Hang Chang A1 - Ju Han A1 - Parvin, Bahram AB -

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.

VL - 11 IS - 3 ER - TY - CONF T1 - Integrative Analysis of Cellular Morphometric Context Reveals Clinically Relevant Signatures in Lower Grade Glioma T2 - Medical Image Computing and Computer-Assisted Intervention - {MICCAI} 2016 - 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part {I} Y1 - 2016 A1 - Ju Han A1 - Yunfu Wang A1 - Weidong Cai A1 - Alexander Borowsky A1 - Bahram Parvin A1 - Hang Chang JF - Medical Image Computing and Computer-Assisted Intervention - {MICCAI} 2016 - 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part {I} UR - http://dx.doi.org/10.1007/978-3-319-46720-7_9 ER - TY - JOUR T1 - Phenotypic Characterization of Breast Invasive Carcinoma via Transferable Tissue Morphometric Patterns learned from Glioblastoma Multiforme. JF - Proc IEEE Int Symp Biomed Imaging Y1 - 2016 A1 - Han, Ju A1 - Fontenay, Gerald V A1 - Wang, Yunfu A1 - Jiang-Hua Mao A1 - Hang Chang AB -

Quantitative analysis of whole slide images (WSIs) in a large cohort may provide predictive models of clinical outcome. However, the performance of the existing techniques is hindered as a result of large technical variations (e.g., fixation, staining) and biological heterogeneities (e.g., cell type, cell state) that are always present in a large cohort. Although unsupervised feature learning provides a promising way in learning pertinent features without human intervention, its capability can be greatly limited due to the lack of well-curated examples. In this paper, we explored the transferability of knowledge acquired from a well-curated Glioblastoma Multiforme (GBM) dataset through its application to the representation and characterization of tissue histology from the Cancer Genome Atlas (TCGA) Breast Invasive Carcinoma (BRCA) cohort. Our experimental results reveals two major phenotypic subtypes with statistically significantly different survival curves. Further differential expression analysis of these two subtypes indicates enrichment of genes regulated by NF-kB in response to TNF and genes up-regulated in response to IFNG.

VL - 2016 ER - TY - JOUR T1 - Stiffness of the microenvironment upregulates ERBB2 expression in 3D cultures of MCF10A within the range of mammographic density. JF - Sci Rep Y1 - 2016 A1 - Cheng, Qingsu A1 - Bilgin, Cemal Cagatay A1 - Fonteney, Gerald A1 - Hang Chang A1 - Henderson, Matthew A1 - Han, Ju A1 - Parvin, Bahram AB -

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.

VL - 6 ER - TY - JOUR T1 - When machine vision meets histology: A comparative evaluation of model architecture for classification of histology sections. JF - Med Image Anal Y1 - 2016 A1 - Zhong, Cheng A1 - Han, Ju A1 - Borowsky, Alexander A1 - Parvin, Bahram A1 - Wang, Yunfu A1 - Hang Chang AB -

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).

VL - 35 ER - TY - JOUR T1 - Coupled segmentation of nuclear and membrane-bound macromolecules through voting and multiphase level set JF - Pattern Recognition Y1 - 2015 A1 - Hang Chang A1 - Quan Wen A1 - Bahram Parvin VL - 48 UR - http://dx.doi.org/10.1016/j.patcog.2014.10.005 ER - TY - PAT T1 - Diagnostic and prognostic histopathology system using morphometric indices Y1 - 2015 A1 - Bahram Parvin A1 - Hang Chang A1 - Ju Han A1 - Gerald Fontenay ER - TY - PAT T1 - Methods for delineating cellular regions and classifying regions of histopathology and microanatomy Y1 - 2015 A1 - Parvin, B. A1 - Hang Chang A1 - Zhou, Y. UR - http://www.google.com/patents/US20150110381 ER - TY - CONF T1 - Nuclei segmentation via sparsity constrained convolutional regression T2 - 12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015 Y1 - 2015 A1 - Yin Zhou A1 - Hang Chang A1 - Kenneth E. Barner A1 - Bahram Parvin JF - 12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015 UR - http://dx.doi.org/10.1109/ISBI.2015.7164109 ER - TY - CONF T1 - Predictive sparse morphometric context for classification of histology sections T2 - 12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015 Y1 - 2015 A1 - Hang Chang A1 - Paul T. Spellman A1 - Bahram Parvin JF - 12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015 UR - http://dx.doi.org/10.1109/ISBI.2015.7164040 ER - TY - CHAP T1 - Quantification of the Dynamics of DNA Repair to Ionizing Radiation via Colocalization of 53BP1 and γH2AX T2 - Video Bioinformatics: From Live Imaging to Knowledge Y1 - 2015 A1 - Groesser, Torsten A1 - Fontenay, Gerald V. A1 - Ju Han A1 - Hang Chang A1 - Janice Pluth A1 - Bahram Parvin ED - Bir Bhanu ED - Prue Talbot JF - Video Bioinformatics: From Live Imaging to Knowledge PB - Springer SN - 978-3-319-23723-7 ER - TY - JOUR T1 - Stacked Predictive Sparse Decomposition for Classification of Histology Sections JF - International Journal of Computer Vision Y1 - 2015 A1 - Hang Chang A1 - Yin Zhou A1 - Alexander Borowsky A1 - Kenneth E. Barner A1 - Paul T. Spellman A1 - Bahram Parvin VL - 113 UR - http://dx.doi.org/10.1007/s11263-014-0790-9 ER - TY - CONF T1 - Classification of Histology Sections via Multispectral Convolutional Sparse Coding T2 - 2014 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2014, Columbus, OH, USA, June 23-28, 2014 Y1 - 2014 A1 - Yin Zhou A1 - Hang Chang A1 - Kenneth E. Barner A1 - Paul T. Spellman A1 - Bahram Parvin JF - 2014 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2014, Columbus, OH, USA, June 23-28, 2014 UR - http://dx.doi.org/10.1109/CVPR.2014.394 ER - TY - JOUR T1 - Stress signaling from human mammary epithelial cells contributes to phenotypes of mammographic density JF - Cancer Res Y1 - 2014 A1 - DeFilippis, Rosa Anna A1 - Fordyce, Colleen A1 - Patten, Kelley A1 - Hang Chang A1 - Zhao, Jianxin A1 - Fontenay, Gerald V A1 - Kerlikowske, Karla A1 - Parvin, Bahram A1 - Tlsty, Thea D KW - Antigens, CD36 KW - Breast Neoplasms KW - DNA Damage KW - Epithelial Cells KW - Female KW - Humans KW - Mammary Glands, Human KW - Phenotype KW - Signal Transduction AB -

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.

VL - 74 IS - 18 ER - TY - JOUR T1 - Breast fibroblasts modulate early dissemination, tumorigenesis, and metastasis through alteration of extracellular matrix characteristics JF - Neoplasia Y1 - 2013 A1 - Dumont, Nancy A1 - Liu, Bob A1 - DeFilippis, Rosa Anna A1 - Hang Chang A1 - Rabban, Joseph T A1 - Karnezis, Anthony N A1 - Tjoe, Judy A A1 - Marx, James A1 - Parvin, Bahram A1 - Tlsty, Thea D KW - Animals KW - Breast KW - Cell Line, Tumor KW - Cell Transformation, Neoplastic KW - Coculture Techniques KW - Epithelial Cells KW - Extracellular Matrix KW - Extracellular Signal-Regulated MAP Kinases KW - Female KW - Fibroblasts KW - Humans KW - Lung Neoplasms KW - Mammary Neoplasms, Experimental KW - Neoplasm Metastasis KW - Phenotype KW - Proto-Oncogene Proteins c-jun KW - rho GTP-Binding Proteins KW - Signal Transduction KW - Transforming Growth Factor beta AB -

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.

VL - 15 IS - 3 ER - TY - CONF T1 - Characterization of Tissue Histopathology via Predictive Sparse Decomposition and Spatial Pyramid Matching T2 - Medical Image Computing and Computer-Assisted Intervention - {MICCAI} 2013 - 16th International Conference, Nagoya, Japan, September 22-26, 2013, Proceedings, Part {II} Y1 - 2013 A1 - Hang Chang A1 - Nandita Nayak A1 - Paul T. Spellman A1 - Bahram Parvin JF - Medical Image Computing and Computer-Assisted Intervention - {MICCAI} 2013 - 16th International Conference, Nagoya, Japan, September 22-26, 2013, Proceedings, Part {II} UR - http://dx.doi.org/10.1007/978-3-642-40763-5_12 ER - TY - CONF T1 - Classification of Tumor Histology via Morphometric Context T2 - 2013 {IEEE} Conference on Computer Vision and Pattern Recognition, Portland, OR, USA, June 23-28, 2013 Y1 - 2013 A1 - Hang Chang A1 - Alexander Borowsky A1 - Paul T. Spellman A1 - Bahram Parvin JF - 2013 {IEEE} Conference on Computer Vision and Pattern Recognition, Portland, OR, USA, June 23-28, 2013 UR - http://dx.doi.org/10.1109/CVPR.2013.286 ER - TY - CONF T1 - Classification of tumor histopathology via sparse feature learning T2 - {ISBI} Y1 - 2013 A1 - Nandita Nayak A1 - Hang Chang A1 - Alexander Borowsky A1 - Paul T. Spellman A1 - Bahram Parvin JF - {ISBI} UR - http://dx.doi.org/10.1109/ISBI.2013.6556499 ER - TY - JOUR T1 - Integrated profiling of three dimensional cell culture models and 3D microscopy JF - Bioinformatics Y1 - 2013 A1 - Cemal Cagatay Bilgin A1 - Sun Kim A1 - Elle Leung A1 - Hang Chang A1 - Bahram Parvin VL - 29 UR - http://dx.doi.org/10.1093/bioinformatics/btt535 ER - TY - JOUR T1 - Invariant Delineation of Nuclear Architecture in Glioblastoma Multiforme for Clinical and Molecular Association JF - {IEEE} Trans. Med. Imaging Y1 - 2013 A1 - Hang Chang A1 - Ju Han A1 - Alexander Borowsky A1 - Leandro A. Loss A1 - Joe W. Gray A1 - Paul T. Spellman A1 - Bahram Parvin VL - 32 UR - http://dx.doi.org/10.1109/TMI.2012.2231420 ER - TY - CHAP T1 - Molecular Correlates of Morphometric Subtypes in Glioblastoma Multiforme T2 - Computational Systems Biology: From Molecular Mechanisms to Disease: Second Edition Y1 - 2013 A1 - Hang Chang A1 - Gerald Fontenay A1 - Cemal Cagatay Bilgin A1 - Alexander Borowsky A1 - Paul Spellman A1 - Bahram Parvin KW - Glioblastoma multiforme KW - Histology classification KW - Molecular pathology KW - Morphometric subtyping KW - Nuclear segmentation KW - Tumor heterogeneity KW - Tumor histopathology JF - Computational Systems Biology: From Molecular Mechanisms to Disease: Second Edition PB - Elsevier Inc. SN - 9780124059269 ER - TY - CONF T1 - Stacked Predictive Sparse Coding for Classification of Distinct Regions in Tumor Histopathology T2 - {IEEE} International Conference on Computer Vision, {ICCV} 2013, Sydney, Australia, December 1-8, 2013 Y1 - 2013 A1 - Hang Chang A1 - Yin Zhou A1 - Paul T. Spellman A1 - Bahram Parvin JF - {IEEE} International Conference on Computer Vision, {ICCV} 2013, Sydney, Australia, December 1-8, 2013 UR - http://dx.doi.org/10.1109/ICCV.2013.28 ER - TY - CONF T1 - Automatic segmentation and quantification of filamentous structures in electron tomography T2 - {ACM} International Conference on Bioinformatics, Computational Biology and Biomedicine, BCB' 12, Orlando, FL, {USA} - October 08 - 10, 2012 Y1 - 2012 A1 - Leandro A. Loss A1 - George Bebis A1 - Hang Chang A1 - Manfred Auer A1 - Purbasha Sarkar A1 - Bahram Parvin JF - {ACM} International Conference on Bioinformatics, Computational Biology and Biomedicine, BCB' 12, Orlando, FL, {USA} - October 08 - 10, 2012 UR - http://doi.acm.org/10.1145/2382936.2382958 ER - TY - CONF T1 - Batch-invariant nuclear segmentation in whole mount histology sections T2 - 9th {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, {ISBI} 2012, May 2-5, 2012, Barcelona, Spain, Proceedings Y1 - 2012 A1 - Hang Chang A1 - Leandro A. Loss A1 - Paul T. Spellman A1 - Alexander Borowsky A1 - Bahram Parvin JF - 9th {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, {ISBI} 2012, May 2-5, 2012, Barcelona, Spain, Proceedings UR - http://dx.doi.org/10.1109/ISBI.2012.6235683 ER - TY - JOUR T1 - CD36 repression activates a multicellular stromal program shared by high mammographic density and tumor tissues JF - Cancer Discov Y1 - 2012 A1 - DeFilippis, Rosa Anna A1 - Hang Chang A1 - Dumont, Nancy A1 - Rabban, Joseph T A1 - Chen, Yunn-Yi A1 - Fontenay, Gerald V A1 - Berman, Hal K A1 - Gauthier, Mona L A1 - Zhao, Jianxin A1 - Hu, Donglei A1 - Marx, James J A1 - Tjoe, Judy A A1 - Ziv, Elad A1 - Febbraio, Maria A1 - Kerlikowske, Karla A1 - Parvin, Bahram A1 - Tlsty, Thea D KW - Adipocytes KW - Animals KW - Antigens, CD36 KW - Breast Neoplasms KW - Cell Differentiation KW - Female KW - Humans KW - Mammography KW - Mice KW - Mice, Knockout KW - Risk Factors KW - Signal Transduction KW - Stromal Cells AB -

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.

VL - 2 IS - 9 ER - TY - CONF T1 - Detection of 3D filamentous networks from tomographic electron microscopy T2 - 9th {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, {ISBI} 2012, May 2-5, 2012, Barcelona, Spain, Proceedings Y1 - 2012 A1 - Leandro A. Loss A1 - Hang Chang A1 - Purbasha Sarkar A1 - Manfred Auer A1 - Bahram Parvin JF - 9th {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, {ISBI} 2012, May 2-5, 2012, Barcelona, Spain, Proceedings UR - http://dx.doi.org/10.1109/ISBI.2012.6235826 ER - TY - JOUR T1 - Identification of fluorescent compounds with non-specific binding property via high throughput live cell microscopy JF - PLoS One Y1 - 2012 A1 - Nath, Sangeeta A1 - Spencer, Virginia A A1 - Ju Han A1 - Hang Chang A1 - Zhang, Kai A1 - Fontenay, Gerald V A1 - Anderson, Charles A1 - Hyman, Joel M A1 - Nilsen-Hamilton, Marit A1 - Chang, Young-Tae A1 - Parvin, Bahram KW - Animals KW - Arabidopsis KW - Cell Line KW - Cell Survival KW - Combinatorial Chemistry Techniques KW - Fluorescent Dyes KW - Humans KW - Ligands KW - Mice KW - Microscopy KW - Small Molecule Libraries AB -

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.

VL - 7 IS - 1 ER - TY - CONF T1 - Molecular bases of morphometric composition in Glioblastoma multiforme T2 - 9th {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, {ISBI} 2012, May 2-5, 2012, Barcelona, Spain, Proceedings Y1 - 2012 A1 - Ju Han A1 - Hang Chang A1 - Gerald Fontenay A1 - Paul T. Spellman A1 - Alexander Borowsky A1 - Bahram Parvin JF - 9th {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, {ISBI} 2012, May 2-5, 2012, Barcelona, Spain, Proceedings UR - http://dx.doi.org/10.1109/ISBI.2012.6235889 ER - TY - JOUR T1 - Multireference Level Set for the Characterization of Nuclear Morphology in Glioblastoma Multiforme JF - {IEEE} Trans. Biomed. Engineering Y1 - 2012 A1 - Hang Chang A1 - Ju Han A1 - Paul T. Spellman A1 - Bahram Parvin VL - 59 UR - http://dx.doi.org/10.1109/TBME.2012.2218107 ER - TY - CONF T1 - Comparison of sparse coding and kernel methods for histopathological classification of gliobastoma multiforme T2 - Proceedings of the 8th {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, {ISBI} 2011, March 30 - April 2, 2011, Chicago, Illinois, {USA} Y1 - 2011 A1 - Ju Han A1 - Hang Chang A1 - Leandro A. Loss A1 - Kai Zhang A1 - Frederick L. Baehner A1 - Joe W. Gray A1 - Paul T. Spellman A1 - Bahram Parvin JF - Proceedings of the 8th {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, {ISBI} 2011, March 30 - April 2, 2011, Chicago, Illinois, {USA} UR - http://dx.doi.org/10.1109/ISBI.2011.5872505 ER - TY - JOUR T1 - Morphometic analysis of TCGA glioblastoma multiforme JF - {BMC} Bioinformatics Y1 - 2011 A1 - Hang Chang A1 - Gerald Fontenay A1 - Ju Han A1 - Ge Cong A1 - Frederick L. Baehner A1 - Joe W. Gray A1 - Paul T. Spellman A1 - Bahram Parvin VL - 12 UR - http://dx.doi.org/10.1186/1471-2105-12-484 ER - TY - JOUR T1 - Multiscale iterative voting for differential analysis of stress response for 2D and 3D cell culture models JF - J Microsc Y1 - 2011 A1 - Ju Han A1 - Hang Chang A1 - Yang, Q A1 - Fontenay, G A1 - Groesser, Torsten A1 - Barcellos-Hoff, M Helen A1 - Parvin, B KW - Cell Culture Techniques KW - Cell Line KW - Epithelial Cells KW - Humans KW - Image Processing, Computer-Assisted KW - Microscopy KW - Organ Culture Techniques KW - Stress, Physiological AB -

Three-dimensional (2D) cell culture models have emerged as the basis for improved cell systems biology. However, there is a gap in robust computational techniques for segmentation of these model systems that are imaged through confocal or deconvolution microscopy. The main issues are the volume of data, overlapping subcellular compartments and variation in scale or size of subcompartments of interest, which lead to ambiguities for quantitative analysis on a cell-by-cell basis. We address these ambiguities through a series of geometric operations that constrain the problem through iterative voting and decomposition strategies. The main contributions of this paper are to (i) extend the previously developed 2D radial voting to an efficient 3D implementation, (ii) demonstrate application of iterative radial voting at multiple subcellular and molecular scales, and (iii) investigate application of the proposed technology to two endpoints between 2D and 3D cell culture models. These endpoints correspond to kinetics of DNA damage repair as measured by phosphorylation of γH2AX, and the loss of the membrane-bound E-cadherin protein as a result of ionizing radiation. Preliminary results indicate little difference in the kinetics of the DNA damage protein between 2D and 3D cell culture models; however, differences between membrane-bound E-cadherin are more pronounced.

VL - 241 IS - 3 ER - TY - JOUR T1 - Persistence of γ-H2AX and 53BP1 foci in proliferating and non-proliferating human mammary epithelial cells after exposure to γ-rays or iron ions JF - Int J Radiat Biol Y1 - 2011 A1 - Groesser, Torsten A1 - Hang Chang A1 - Gerald Fontenay A1 - Chen, James A1 - Costes, Sylvain V A1 - Helen Barcellos-Hoff, Mary A1 - Parvin, Bahram A1 - Rydberg, Bjorn KW - Cell Line KW - Cell Proliferation KW - Gamma Rays KW - Heavy Ions KW - Histones KW - Humans KW - Iron KW - Mammary Glands, Human KW - Tumor Suppressor Protein p53 AB -

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.

VL - 87 IS - 7 ER - TY - JOUR T1 - Linking Changes in Epithelial Morphogenesis to Cancer Mutations Using Computational Modeling JF - PLoS Computational Biology Y1 - 2010 A1 - Katarzyna A. Rejniak A1 - Shizhen E. Wang A1 - Nicole S. Bryce A1 - Hang Chang A1 - Bahram Parvin A1 - Jerome Jourquin A1 - Lourdes Estrada A1 - Joe W. Gray A1 - Carlos L. Arteaga A1 - Alissa M. Weaver A1 - Vito Quaranta A1 - Alexander R. A. Anderson VL - 6 UR - http://dx.doi.org/10.1371/journal.pcbi.1000900 ER - TY - JOUR T1 - Linking changes in epithelial morphogenesis to cancer mutations using computational modeling JF - PLoS Comput Biol Y1 - 2010 A1 - Rejniak, Katarzyna A A1 - Wang, Shizhen E A1 - Bryce, Nicole S A1 - Hang Chang A1 - Parvin, Bahram A1 - Jourquin, Jerome A1 - Estrada, Lourdes A1 - Gray, Joe W A1 - Arteaga, Carlos L A1 - Weaver, Alissa M A1 - Quaranta, Vito A1 - Anderson, Alexander R A KW - Apoptosis KW - Breast Neoplasms KW - Cell Proliferation KW - Computer Simulation KW - Epithelium KW - Extracellular Matrix KW - Female KW - Humans KW - Mammary Glands, Human KW - Models, Biological KW - Morphogenesis KW - Mutation KW - Receptor, ErbB-2 AB -

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.

VL - 6 IS - 8 ER - TY - JOUR T1 - Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture JF - PLoS Computational Biology Y1 - 2010 A1 - Ju Han A1 - Hang Chang A1 - Orsi Giricz A1 - Genee Y. Lee A1 - Frederick L. Baehner A1 - Joe W. Gray A1 - Mina J. Bissell A1 - Paraic A. Kenny A1 - Bahram Parvin VL - 6 UR - http://dx.doi.org/10.1371/journal.pcbi.1000684 ER - TY - JOUR T1 - Multidimensional profiling of cell surface proteins and nuclear markers JF - IEEE/ACM Trans Comput Biol Bioinform Y1 - 2010 A1 - Ju Han A1 - Hang Chang A1 - Andarawewa, Kumari A1 - Yaswen, Paul A1 - Barcellos-Hoff, Mary Helen A1 - Parvin, Bahram KW - Cadherins KW - Cell Membrane KW - Cell Nucleus KW - Computer Simulation KW - DNA KW - Gene Expression Profiling KW - Membrane Proteins KW - Models, Biological AB -

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.

VL - 7 IS - 1 ER - TY - CONF T1 - Multiphase level set for automated delineation of membrane-bound macromolecules T2 - Proceedings of the 2010 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Rotterdam, The Netherlands, 14-17 April, 2010 Y1 - 2010 A1 - Hang Chang A1 - Bahram Parvin JF - Proceedings of the 2010 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Rotterdam, The Netherlands, 14-17 April, 2010 UR - http://dx.doi.org/10.1109/ISBI.2010.5490389 ER - TY - CONF T1 - A Delaunay Triangulation Approach for Segmenting Clumps of Nuclei T2 - Proceedings of the 2009 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28 - July 1, 2009 Y1 - 2009 A1 - Quan Wen A1 - Hang Chang A1 - Bahram Parvin JF - Proceedings of the 2009 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28 - July 1, 2009 UR - http://dx.doi.org/10.1109/ISBI.2009.5192970 ER - TY - JOUR T1 - Graphical methods for quantifying macromolecules through bright field imaging JF - Bioinformatics Y1 - 2009 A1 - Hang Chang A1 - Rosa Anna DeFilippis A1 - Thea D. Tlsty A1 - Bahram Parvin VL - 25 UR - http://dx.doi.org/10.1093/bioinformatics/btn426 ER - TY - CONF T1 - Morphometric Subtyping for a Panel of Breast Cancer Cell Lines T2 - Proceedings of the 2009 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28 - July 1, 2009 Y1 - 2009 A1 - Ju Han A1 - Hang Chang A1 - Gerald Fontenay A1 - Nicholas J. Wang A1 - Joe W. Gray A1 - Bahram Parvin JF - Proceedings of the 2009 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28 - July 1, 2009 UR - http://dx.doi.org/10.1109/ISBI.2009.5193168 ER - TY - CONF T1 - Structural Annotation of EM Images by Graph Cut T2 - Proceedings of the 2009 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28 - July 1, 2009 Y1 - 2009 A1 - Hang Chang A1 - Manfred Auer A1 - Bahram Parvin JF - Proceedings of the 2009 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28 - July 1, 2009 UR - http://dx.doi.org/10.1109/ISBI.2009.5193249 ER - TY - CONF T1 - A Bayesian approach for image segmentation with shape priors T2 - 2008 {IEEE} Computer Society Conference on Computer Vision and Pattern Recognition {(CVPR} 2008), 24-26 June 2008, Anchorage, Alaska, {USA} Y1 - 2008 A1 - Hang Chang A1 - Qing Yang A1 - Bahram Parvin JF - 2008 {IEEE} Computer Society Conference on Computer Vision and Pattern Recognition {(CVPR} 2008), 24-26 June 2008, Anchorage, Alaska, {USA} UR - http://dx.doi.org/10.1109/CVPR.2008.4587430 ER - TY - CONF T1 - Integrated profiling of cell surface protein and nuclear marker for discriminant analysis T2 - Proceedings of the 2008 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Paris, France, May 14-17, 2008 Y1 - 2008 A1 - Ju Han A1 - Hang Chang A1 - Kumari L. Andarawewa A1 - Paul Yaswen A1 - Mary Helen Barcellos-Hoff A1 - Bahram Parvin JF - Proceedings of the 2008 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Paris, France, May 14-17, 2008 UR - http://dx.doi.org/10.1109/ISBI.2008.4541253 ER - TY - CONF T1 - Scoring histological sections through immunohistochemistry T2 - Proceedings of the 2008 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Paris, France, May 14-17, 2008 Y1 - 2008 A1 - Hang Chang A1 - Rosa Anna DeFilippis A1 - Thea D. Tlsty A1 - Bahrain Parvin JF - Proceedings of the 2008 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Paris, France, May 14-17, 2008 UR - http://dx.doi.org/10.1109/ISBI.2008.4541003 ER - TY - JOUR T1 - Iterative Voting for Inference of Structural Saliency and Characterization of Subcellular Events JF - {IEEE} Trans. Image Processing Y1 - 2007 A1 - Bahram Parvin A1 - Qing Yang A1 - Ju Han A1 - Hang Chang A1 - Bjorn Rydberg A1 - Mary Helen Barcellos-Hoff VL - 16 UR - http://dx.doi.org/10.1109/TIP.2007.891154 ER - TY - CONF T1 - Modeling of Front Evolution with Graph Cut Optimization T2 - Proceedings of the International Conference on Image Processing, {ICIP} 2007, September 16-19, 2007, San Antonio, Texas, {USA} Y1 - 2007 A1 - Hang Chang A1 - Qing Yang A1 - Manfred Auer A1 - Bahram Parvin JF - Proceedings of the International Conference on Image Processing, {ICIP} 2007, September 16-19, 2007, San Antonio, Texas, {USA} UR - http://dx.doi.org/10.1109/ICIP.2007.4378936 ER - TY - CONF T1 - Perceptual Grouping of Membrane Signals in Cell-Based Assays T2 - Proceedings of the 2007 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Washington, DC, USA, April 12-16, 2007 Y1 - 2007 A1 - Hang Chang A1 - Kumari L. Andarawewa A1 - Ju Han A1 - Mary Helen Barcellos-Hoff A1 - Bahram Parvin JF - Proceedings of the 2007 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Washington, DC, USA, April 12-16, 2007 UR - http://dx.doi.org/10.1109/ISBI.2007.356906 ER - TY - CONF T1 - Quantitative Representation of Three-dimensional Cell Culture Models T2 - Proceedings of the 2007 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Washington, DC, USA, April 12-16, 2007 Y1 - 2007 A1 - Hang Chang A1 - Catherine Park A1 - Bahram Parvin JF - Proceedings of the 2007 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Washington, DC, USA, April 12-16, 2007 UR - http://dx.doi.org/10.1109/ISBI.2007.356795 ER - TY - JOUR T1 - Segmentation of heterogeneous blob objects through voting and level set formulation JF - Pattern Recognition Letters Y1 - 2007 A1 - Hang Chang A1 - Qing Yang A1 - Bahram Parvin VL - 28 UR - http://dx.doi.org/10.1016/j.patrec.2007.05.008 ER - TY - CONF T1 - Segmentation of Mammosphere Structures from Volumetric Data T2 - Proceedings of the 2007 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Washington, DC, USA, April 12-16, 2007 Y1 - 2007 A1 - Ju Han A1 - Hang Chang A1 - Qing Yang A1 - Mary Helen Barcellos-Hoff A1 - Bahram Parvin JF - Proceedings of the 2007 {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, Washington, DC, USA, April 12-16, 2007 UR - http://dx.doi.org/10.1109/ISBI.2007.356904 ER - TY - CONF T1 - 3D Segmentation of Mammospheres for Localization Studies T2 - Advances in Visual Computing, Second International Symposium, {ISVC} 2006, Lake Tahoe, NV, USA, November 6-8, 2006 Proceedings, Part {I} Y1 - 2006 A1 - Ju Han A1 - Hang Chang A1 - Qing Yang A1 - Mary Helen Barcellos-Hoff A1 - Bahram Parvin JF - Advances in Visual Computing, Second International Symposium, {ISVC} 2006, Lake Tahoe, NV, USA, November 6-8, 2006 Proceedings, Part {I} UR - http://dx.doi.org/10.1007/11919476_52 ER - TY - CONF T1 - An Iterative Bayesian Approach for Digital Matting T2 - 18th International Conference on Pattern Recognition {(ICPR} 2006), 20-24 August 2006, Hong Kong, China Y1 - 2006 A1 - Hang Chang A1 - Qing Yang A1 - Chunhong Pan JF - 18th International Conference on Pattern Recognition {(ICPR} 2006), 20-24 August 2006, Hong Kong, China UR - http://dx.doi.org/10.1109/ICPR.2006.259 ER - TY - CONF T1 - Segmentation of Three Dimensional Cell Culture Models from a Single Focal Plane T2 - Advances in Visual Computing, Second International Symposium, {ISVC} 2006 Lake Tahoe, NV, USA, November 6-8, 2006. Proceedings, Part {II} Y1 - 2006 A1 - Hang Chang A1 - Bahram Parvin JF - Advances in Visual Computing, Second International Symposium, {ISVC} 2006 Lake Tahoe, NV, USA, November 6-8, 2006. Proceedings, Part {II} UR - http://dx.doi.org/10.1007/11919629_59 ER -