@article {333, title = {Identification of a novel cancer microbiome signature for predicting prognosis of human breast cancer patients.}, journal = {Clin Transl Oncol}, volume = {24}, year = {2022}, month = {2022 Mar}, pages = {597-604}, abstract = {

BACKGROUND: Prognosis of breast cancer (BC) patients differs considerably and identifying reliable prognostic biomarker(s) is imperative. With evidence that the microbiome plays a critical role in the response to cancer therapies, we aimed to identify a cancer microbiome signature for predicting the prognosis of BC patients.

METHODS: The TCGA BC microbiome data (TCGA-BRCA-microbiome) was downloaded from cBioPortal. Univariate and multivariate Cox regression analyses were used to examine association of microbial abundance with overall survival (OS) and to identify a microbial signature for creating a prognostic scoring model. The performance of the scoring model was assessed by the area under the ROC curve (AUC). Nomograms using the microbial signature, clinical factors, and molecular subtypes were established to predict OS and progression-free survival (PFS).

RESULTS: Among 1406 genera, the abundances of 94 genera were significantly associated with BC patient OS in TCGA-BRCA-microbiome dataset. From that set we identified a 15-microbe prognostic signature and developed a 15-microbial abundance prognostic scoring (MAPS) model. Patients in low-risk group significantly prolong OS and PFS as compared to those in high-risk group. The time-dependent ROC curves with MAPS showed good predictive efficacy both in OS and PFS. Moreover, MAPS is an independent prognostic factor for OS and PFS over clinical factors and PAM50-based molecular subtypes and superior to the previously published 12-gene signature. The integration of MAPS into nomograms significantly improved prognosis prediction.

CONCLUSION: MAPS was successfully established to have independent prognostic value, and our study provides a new avenue for developing prognostic biomarkers by microbiome profiling.

}, keywords = {Breast Neoplasms, Female, Humans, Microbiota, Prognosis, Survival Rate}, issn = {1699-3055}, doi = {10.1007/s12094-021-02725-3}, author = {Mao, A W and Barck, H and Young, J and Paley, A and Mao, J -H and Chang, Hang} } @article {334, title = {NaroNet: Discovery of tumor microenvironment elements from highly multiplexed images.}, journal = {Med Image Anal}, volume = {78}, year = {2022}, month = {2022 May}, pages = {102384}, abstract = {

Understanding the spatial interactions between the elements of the tumor microenvironment -i.e. tumor cells. fibroblasts, immune cells- and how these interactions relate to the diagnosis or prognosis of a tumor is one of the goals of computational pathology. We present NaroNet, a deep learning framework that models the multi-scale tumor microenvironment from multiplex-stained cancer tissue images and provides patient-level interpretable predictions using a seamless end-to-end learning pipeline. Trained only with multiplex-stained tissue images and their corresponding patient-level clinical labels, NaroNet unsupervisedly learns which cell phenotypes, cell neighborhoods, and neighborhood interactions have the highest influence to predict the correct label. To this end, NaroNet incorporates several novel and state-of-the-art deep learning techniques, such as patch-level contrastive learning, multi-level graph embeddings, a novel max-sum pooling operation, or a metric that quantifies the relevance that each microenvironment element has in the individual predictions. We validate NaroNet using synthetic data simulating multiplex-immunostained images where a patient label is artificially associated to the -adjustable- probabilistic incidence of different microenvironment elements. We then apply our model to two sets of images of human cancer tissues: 336 seven-color multiplex-immunostained images from 12 high-grade endometrial cancer patients; and 382 35-plex mass cytometry images from 215 breast cancer patients. In both synthetic and real datasets, NaroNet provides outstanding predictions of relevant clinical information while associating those predictions to the presence of specific microenvironment elements.

}, keywords = {Breast Neoplasms, Female, Humans, Prognosis, Tumor Microenvironment}, issn = {1361-8423}, doi = {10.1016/j.media.2022.102384}, author = {Jim{\'e}nez-S{\'a}nchez, Daniel and Ariz, Mikel and Chang, Hang and Matias-Guiu, Xavier and de Andrea, Carlos E and Ortiz-de-Sol{\'o}rzano, Carlos} } @article {326, title = {A new platform for ultra-high dose rate radiobiological research using the BELLA PW laser proton beamline.}, journal = {Sci Rep}, volume = {12}, year = {2022}, month = {2022 01 27}, pages = {1484}, abstract = {

Radiotherapy is the current standard of care for more than 50\% of all cancer patients. Improvements in radiotherapy (RT) technology have increased tumor targeting and normal tissue sparing. Radiations at ultra-high dose rates required for FLASH-RT effects have sparked interest in potentially providing additional differential therapeutic benefits. We present a new experimental platform that is the first one to deliver petawatt laser-driven proton pulses of 2\ MeV energy at 0.2\ Hz repetition rate by means of a compact, tunable active plasma lens beamline to biological samples. Cell monolayers grown over a 10\ mm diameter field were exposed to clinically relevant proton doses ranging from 7 to 35\ Gy at ultra-high instantaneous dose rates of 10\ Gy/s. Dose-dependent cell survival measurements of human normal and tumor cells exposed to LD protons showed significantly higher cell survival of normal-cells compared to tumor-cells for total doses of 7\ Gy and higher, which was not observed to the same extent for X-ray reference irradiations at clinical dose rates. These findings provide preliminary evidence that compact LD proton sources enable a new and promising platform for investigating the physical, chemical and biological mechanisms underlying the FLASH effect.

}, keywords = {Cell Line, Humans, Lasers, Monte Carlo Method, Neoplasms, Proton Therapy, Radiation Oncology, Radiobiology, Radiometry, Radiotherapy Dosage, Synchrotrons}, issn = {2045-2322}, doi = {10.1038/s41598-022-05181-3}, author = {Bin, Jianhui and Obst-Huebl, Lieselotte and Mao, Jian-Hua and Nakamura, Kei and Geulig, Laura D and Chang, Hang and Ji, Qing and He, Li and De Chant, Jared and Kober, Zachary and Gonsalves, Anthony J and Bulanov, Stepan and Celniker, Susan E and Schroeder, Carl B and Geddes, Cameron G R and Esarey, Eric and Simmons, Blake A and Schenkel, Thomas and Blakely, Eleanor A and Steinke, Sven and Snijders, Antoine M} } @article {332, title = {Prospective Study Reveals Host Microbial Determinants of Clinical Response to Fecal Microbiota Transplant Therapy in Type 2 Diabetes Patients.}, journal = {Front Cell Infect Microbiol}, volume = {12}, year = {2022}, month = {2022}, pages = {820367}, abstract = {

Background: Increasing evidence shows that alterations in gut microbiome (GM) contribute to the development of type 2 diabetes mellitus (T2DM), and fecal microbiota transplantation (FMT) successfully treats various human diseases. However, the benefits of FMT therapy to T2DM patients remain unknown.

Methods: We enrolled 17 patients with T2DM for nonblinded, one-armed intervention trial of FMT. A total of 20 healthy individuals were recruited as the baseline control. HbA1c\% and metabolic parameter change were evaluated in 17 T2DM patients 12 weeks after they received FMT from healthy donors. The GM composition was characterized by 16S rRNA gene amplicon sequencing from fecal samples prior to and 12 weeks after FMT treatment.

Results: We found that the GM of T2DM patients was reconstituted by FMT. We observed a statistically significant decrease in HbA1c\% (from 7.565 {\textpm} 0.148 to 7.190 {\textpm} 0.210, p\<0.01), blood glucose (from 8.483 {\textpm} 0.497 to 7.286 {\textpm} 0.454 mmol/L, p\<0.01), and uric acid (from 309.4 {\textpm} 21.5 to 259.1 {\textpm} 15.8 {\textmu}mol/L, p\<0.01) while a significant increase in postprandial C-peptide (from 4.503 {\textpm} 0.600 to 5.471 {\textpm} 0.728 ng/ml, p\<0.01) at 12 weeks after FMT. Closely evaluating the changes in these assays, we found individual variability in response to FMT treatment. Out of 17 T2DM patients, 11 were found to significantly improve T2DM symptoms. The FMT responders have significantly higher levels of the family and the genus (family ) in their pretreated fecal in comparison to nonresponders, which could predict the clinical response with an area under the curve of 0.83.

Conclusion: Our findings suggest that certain T2DM patients can potentially benefit from FMT, and the pretreated abundance of and in the fecal of patients may serve as potential biomarkers for selecting T2DM patients to receive FMT.

}, keywords = {Diabetes Mellitus, Type 2, Fecal Microbiota Transplantation, Feces, Glycated Hemoglobin A, Humans, Prospective Studies, RNA, Ribosomal, 16S, Treatment Outcome}, issn = {2235-2988}, doi = {10.3389/fcimb.2022.820367}, author = {Ding, Dafa and Yong, Huijuan and You, Na and Lu, Wei and Yang, Xu and Ye, Xiaolong and Wang, Yayun and Cai, Tingting and Zheng, Xiaoling and Chen, Hui and Cui, Bota and Zhang, Faming and Liu, Xingyin and Mao, Jian-Hua and Lu, Yibing and Chang, Hang} } @article {330, title = {Contribution of trace element exposure to gestational diabetes mellitus through disturbing the gut microbiome.}, journal = {Environ Int}, volume = {153}, year = {2021}, month = {2021 08}, pages = {106520}, abstract = {

BACKGROUND: A healthy gut microbiome is critical for glucose metabolism during pregnancy. In vivo studies indicate that trace element affects the composition and function of the gut microbiome and potentially leads to metabolic disorders but their relationships are largely unknown. We aimed to investigate whether the gut microbiome plays a role in the relationship between trace element exposure and gestational diabetes mellitus (GDM).

METHODS: In a prospective cohort study, serum levels of 22 trace elements and the fecal gut microbiome composition were assessed in 837 pregnant women in the second trimester between 22 and 24\ weeks of pregnancy prior to GDM diagnosis. Regression and mediation analysis were used to explore the link between element exposure, the gut microbiome, and GDM.

RESULTS: 128 pregnant women (15.3\%) were diagnosed with GDM. No individual trace elements were found significantly associated with GDM. In contrast, the composition of the gut microbiome was dramatically altered in women later diagnosed with GDM and characterized by lower alpha diversity and lower abundance of co-abundance groups (CAGs) composed of genera belonging to Ruminococcaceae, Coriobacteriales, and Lachnospiraceae. Rubidium (Rb) was positively associated with alpha diversity indices while mercury (Hg) and vanadium (V) showed negative associations. Elements including rubidium (Rb), thallium (Tl), arsenic (As), and antimony (Sb) were significantly correlated with GDM-related CAGs and mediation analysis revealed that Rb and Sb were inversely related to GDM risk by altering abundance levels of CAGs enriched for Lachnospiraceae, Coriobacteriales, and Ruminococcaceae.

CONCLUSION: Our study indicates that trace element exposure is associated with specific gut microbiome features that may contribute to GDM development, which could provide a new avenue for intervening in environmental exposure-related GDM.

}, keywords = {Diabetes, Gestational, Feces, Female, Gastrointestinal Microbiome, Humans, Pregnancy, Prospective Studies, Trace Elements}, issn = {1873-6750}, doi = {10.1016/j.envint.2021.106520}, author = {Zhang, Yuqing and Chen, Ting and Zhang, Yiyun and Hu, Qi and Wang, Xu and Chang, Hang and Mao, Jian-Hua and Snijders, Antoine M and Xia, Yankai} } @article {331, title = {Distinct Clinical Impact and Biological Function of Angiopoietin and Angiopoietin-like Proteins in Human Breast Cancer.}, journal = {Cells}, volume = {10}, year = {2021}, month = {2021 09 29}, abstract = {

Secreted angiopoietin/angiopoietin-like (/) proteins are involved in many biological processes. However, the role of these proteins in human breast cancers (BCs) remains largely unclear. Here, we conducted integrated omics analyses to evaluate the clinical impact of / proteins and to elucidate their biological functions. In BCs, we identified rare mutations in / genes, frequent gains of , , and , and frequent losses of , , and , but observed that , , and were robustly downregulated in multiple datasets. The expression levels of , , and were positively correlated with overall survival (OS), while the expression levels of were negatively correlated with OS. Additionally, the expression levels of and were positively correlated with distant metastasis-free survival (DMFS), while the expression levels of and were negatively correlated with DMFS. The prognostic impacts of / genes depended on the molecular subtypes and on clinical factors. We discovered that various / genes were co-expressed with various genes involved in different pathways. Finally, with the exception of , the remaining genes showed significant correlations with cancer-associated fibroblasts, endothelial cells, and microenvironment score, whereas only was significantly correlated with immune score. Our findings provide strong evidence for the distinct clinical impact and biological function of / proteins, but the question of whether some of them could be potential therapeutic targets still needs further investigation in BCs.

}, keywords = {Angiopoietin-like Proteins, Angiopoietins, Breast Neoplasms, Female, Humans, Prognosis}, issn = {2073-4409}, doi = {10.3390/cells10102590}, author = {Yang, Hui and Zhang, Melody and Mao, Xuan-Yu and Chang, Hang and Perez-Losada, Jesus and Mao, Jian-Hua} } @article {329, title = {Genetic background influences the effect of thirdhand smoke exposure on anxiety and memory in Collaborative Cross mice.}, journal = {Sci Rep}, volume = {11}, year = {2021}, month = {2021 06 24}, pages = {13285}, abstract = {

Growing evidence indicates that thirdhand smoke (THS) exposure induces many adverse health effects. However, it is unclear how THS exposure affects behavior and how host genetic background modulates phenotypic changes. Here we used the Collaborative Cross (CC) mouse population-based model to assess behavioral alterations immediately after THS exposure from 4 to 9\ weeks of age. We first measured anxiety-like behavior in six strains using light/dark box combined with a custom multivariate mouse tracking system. We developed an anxiety risk scoring system based on anxiety-related traits and then evaluated the THS impact on them. THS exposure significantly decreased anxiety risk in CC019 (P = 0.002) and CC051 (P = 0.009), but increased anxiety risk in CC036 (P \< 0.001), while the other three strains did not show significant changes in anxiety-related traits. Such differences were driven by female mice for the six measures of anxiety-like behavior. Memory potential was measured in the same cohort of mice using the passive avoidance assay. Both THS-exposed male and female CC019 mice displayed significant memory loss compared to controls while no significant changes were found in the other five strains. This study provides strong evidence that THS exposure leads to strain-dependent changes in anxiety-like behavior and memory, suggesting that host genetic variations play a critical role in individual susceptibility to THS-induced effects.

}, keywords = {Animals, Anxiety, Collaborative Cross Mice, Female, Humans, Male, Memory, Risk Factors, Tobacco Smoke Pollution}, issn = {2045-2322}, doi = {10.1038/s41598-021-92702-1}, author = {He, Li and Wang, Pin and Schick, Suzyann F and Huang, Abel and Jacob, Peyton and Yang, Xu and Xia, Yankai and Snijders, Antoine M and Mao, Jian-Hua and Chang, Hang and Hang, Bo} } @article {328, title = {Thirdhand cigarette smoke leads to age-dependent and persistent alterations in the cecal microbiome of mice.}, journal = {Microbiologyopen}, volume = {10}, year = {2021}, month = {2021 06}, pages = {e1198}, abstract = {

The gut microbiome composition is influenced by many factors including environmental exposures. Here, we investigated the effect of thirdhand cigarette smoke (THS) and exposure age on gut microbiome diversity. C57BL/6 mice were exposed to THS at human exposure relevant levels for three weeks during three different life stages: postnatal (0-3\ weeks of age), pubescent (4-7\ weeks of age), and adult (9-12\ weeks of age), respectively. Cecal microbiome profiles were assessed at 17\ weeks of age by 16S rRNA gene sequencing. We found that age at THS exposure strongly influenced the cecal microbiome composition. Although postnatal THS exposure significantly influenced the microbial composition, pubescent and adulthood exposures only had minor effects. The microbiome of postnatally THS-exposed mice significantly increased several degradation pathways that regulate glycolysis and pyruvate decarboxylation, and significantly decreased coenzyme A biosynthesis and pyrimidine deoxyribonucleoside salvage. Our results indicate that mouse postnatal development is particularly susceptible to persistent THS exposure effects on the gut microbiome.

}, keywords = {Age Factors, Animals, Bacteria, Cecum, Environmental Exposure, Female, Gastrointestinal Microbiome, Humans, Male, Mice, Mice, Inbred C57BL, Smoke, Tobacco, Tobacco Smoke Pollution}, issn = {2045-8827}, doi = {10.1002/mbo3.1198}, author = {He, Li and Zhou, Yan-Xia and Zhang, Yuqing and Hang, Bo and Chang, Hang and Schick, Suzaynn F and Celniker, Susan E and Xia, Yankai and Snijders, Antoine M and Mao, Jian-Hua} } @article {301, title = {Machine Learning in Multimodal Medical Imaging.}, journal = {Biomed Res Int}, volume = {2017}, year = {2017}, month = {2017}, pages = {1278329}, keywords = {Animals, Humans, Image Processing, Computer-Assisted, Machine Learning}, issn = {2314-6141}, doi = {10.1155/2017/1278329}, author = {Xia, Yong and Ji, Zexuan and Krylov, Andrey and Hang Chang and Cai, Weidong} } @article {303, title = {When machine vision meets histology: A comparative evaluation of model architecture for classification of histology sections.}, journal = {Med Image Anal}, volume = {35}, year = {2017}, month = {2017 01}, 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).

}, keywords = {Color, Histological Techniques, Humans, Pattern Recognition, Automated, Unsupervised Machine Learning}, 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, Breast Neoplasms, CD36, DNA Damage, Epithelial Cells, Female, Human, Humans, Mammary Glands, 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, Cell Transformation, Coculture Techniques, Epithelial Cells, Experimental, Extracellular Matrix, Extracellular Signal-Regulated MAP Kinases, Female, Fibroblasts, Humans, Lung Neoplasms, Mammary Neoplasms, Neoplasm Metastasis, Neoplastic, Phenotype, Proto-Oncogene Proteins c-jun, rho GTP-Binding Proteins, Signal Transduction, Transforming Growth Factor beta, Tumor}, 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 {205, title = {FAM83D promotes cell proliferation and motility by downregulating tumor suppressor gene FBXW7.}, journal = {Oncotarget}, volume = {4}, year = {2013}, month = {2013 Dec}, pages = {2476-86}, abstract = {

Amplification of chromosome 20q is frequently found in various types of human cancers, including breast cancer. The list of candidate oncogenes in 20q has expanded over the past decade. Here, we investigate whether FAM83D (family with sequence similarity 83, member D) on chromosome 20q plays any role in breast cancer development. The expression level of FAM83D is significantly elevated in breast cancer cell lines and primary human breast cancers. High expression levels of FAM83D are significantly associated with poor clinical outcome and distant metastasis in breast cancer patients. We show that ectopic expression of FAM83D in human mammary epithelial cells promotes cell proliferation, migration and invasion along with epithelial-mesenchymal transition (EMT). Ablation of FAM83D in breast cancer cells induces apoptosis and consequently inhibits cell proliferation and colony formation. Mechanistic studies reveal that overexpression of FAM83D downregulates FBXW7 expression levels through a physical interaction, which results in elevated protein levels of oncogenic substrates downstream to FBXW7, such as mTOR, whose inhibition by rapamycin can suppress FAM83D-induced cell migration and invasion. The results demonstrate that FAM83D has prognostic value for breast cancer patients and is a novel oncogene in breast cancer development that at least in part acts through mTOR hyper-activation by inhibiting FBXW7.

}, keywords = {Apoptosis, Breast Neoplasms, Cell Cycle Proteins, Cell Growth Processes, Cell Line, Chromosomal Proteins, Down-Regulation, Epithelial-Mesenchymal Transition, F-Box Proteins, Genes, Humans, Microtubule-Associated Proteins, Non-Histone, Prognosis, Transfection, Tumor, Tumor Suppressor, Ubiquitin-Protein Ligases}, issn = {1949-2553}, doi = {10.18632/oncotarget.1581}, author = {Wang, Zeran and Liu, Yueyong and Zhang, Pengju and Zhang, Weiguo and Wang, Weijing and Curr, Kenneth and Wei, Guangwei and Jiang-Hua Mao} } @article {204, title = {Hematein, a casein kinase II inhibitor, inhibits lung cancer tumor growth in a murine xenograft model.}, journal = {Int J Oncol}, volume = {43}, year = {2013}, month = {2013 Nov}, pages = {1517-22}, abstract = {

Casein kinase II (CK2) inhibitors suppress cancer cell growth. In this study, we examined the inhibitory effects of a novel CK2 inhibitor, hematein, on tumor growth in a murine xenograft model. We found that in lung cancer cells, hematein inhibited cancer cell growth, Akt/PKB Ser129 phosphorylation, the Wnt/TCF pathway and increased apoptosis. In a murine xenograft model of lung cancer, hematein inhibited tumor growth without significant toxicity to the mice tested. Molecular docking showed that hematein binds to CK2α in durable binding sites. Collectively, our results suggest that hematein is an allosteric inhibitor of protein kinase CK2 and has antitumor activity to lung cancer.

}, keywords = {Animals, Apoptosis, Blotting, Casein Kinase II, Cultured, Enzyme Inhibitors, Female, Hematoxylin, Humans, Immunoenzyme Techniques, Inbred BALB C, Lung Neoplasms, Mice, Phosphorylation, Proto-Oncogene Proteins c-akt, T Cell Transcription Factor 1, Tumor Cells, Western, Wnt Proteins, Xenograft Model Antitumor Assays}, issn = {1791-2423}, doi = {10.3892/ijo.2013.2087}, author = {Hung, Ming-Szu and Xu, Zhidong and Chen, Yu and Smith, Emmanuel and Jiang-Hua Mao and Hsieh, David and Lin, Yu-Ching and Yang, Cheng-Ta and Jablons, David M and You, Liang} } @article {194, title = {Mass spectrometry imaging for in situ kinetic histochemistry.}, journal = {Sci Rep}, volume = {3}, year = {2013}, month = {2013}, pages = {1656}, abstract = {

Tissues are composed of diverse cell subpopulations each with distinct metabolic characteristics that influence overall behavior. Unfortunately, traditional histopathology imaging techniques are {\textquoteright}blind{\textquoteright} to the spatially ordered metabolic dynamics within tissue. While mass spectrometry imaging enables spatial mapping of molecular composition, resulting images are only a static snapshot in time of molecules involved in highly dynamic processes; kinetic information of flux through metabolic pathways is lacking. To address this limitation, we developed kinetic mass spectrometry imaging (kMSI), a novel technique integrating soft desorption/ionization mass spectrometry with clinically accepted in vivo metabolic labeling of tissue with deuterium to generate images of kinetic information of biological processes. Applied to a tumor, kMSI revealed heterogeneous spatial distributions of newly synthesized versus pre-existing lipids, with altered lipid synthesis patterns distinguishing region-specific intratumor subpopulations. Images also enabled identification and correlation of metabolic activity of specific lipids found in tumor regions of varying grade.

}, keywords = {Cell Line, Equipment Design, Equipment Failure Analysis, Experimental, Humans, Lipids, Mass Spectrometry, Molecular Imaging, Neoplasms, Tumor}, issn = {2045-2322}, doi = {10.1038/srep01656}, author = {Louie, Katherine B and Bowen, Benjamin P and McAlhany, Stephanie and Huang, Yurong and Price, John C and Jiang-Hua Mao and Hellerstein, Marc and Northen, Trent R} } @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, Breast Neoplasms, CD36, Cell Differentiation, Female, Humans, Knockout, Mammography, Mice, 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 {85, title = {Multiscale iterative voting for differential analysis of stress response for 2D and 3D cell culture models}, journal = {J Microsc}, volume = {241}, year = {2011}, month = {2011 Mar}, pages = {315-26}, abstract = {

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.

}, keywords = {Cell Culture Techniques, Cell Line, Computer-Assisted, Epithelial Cells, Humans, Image Processing, Microscopy, Organ Culture Techniques, Physiological, Stress}, issn = {1365-2818}, doi = {10.1111/j.1365-2818.2010.03442.x}, author = {Ju Han and Hang Chang and Yang, Q and Fontenay, G and Groesser, Torsten and Barcellos-Hoff, M Helen and Parvin, B} } @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, Human, Humans, Iron, Mammary Glands, 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, Biological, Breast Neoplasms, Cell Proliferation, Computer Simulation, Epithelium, ErbB-2, Extracellular Matrix, Female, Human, Humans, Mammary Glands, Models, Morphogenesis, Mutation, Receptor}, 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 = {Biological, Biomarkers, Breast Neoplasms, Cell Culture Techniques, Cell Line, Computer-Assisted, ErbB-2, Female, Gene Expression Profiling, Histocytochemistry, Humans, Image Processing, Models, Phenotype, PPAR gamma, Receptor, Reproducibility of Results, Tumor}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1000684}, author = {Han, Ju and Hang Chang 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 {296, title = {Active mask segmentation of fluorescence microscope images.}, journal = {IEEE Trans Image Process}, volume = {18}, year = {2009}, month = {2009 Aug}, pages = {1817-29}, abstract = {

We propose a new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns. It combines the (a) flexibility offered by active-contour methods, (b) speed offered by multiresolution methods, (c) smoothing offered by multiscale methods, and (d) statistical modeling offered by region-growing methods into a fast and accurate segmentation tool. The framework moves from the idea of the "contour" to that of "inside and outside," or masks, allowing for easy multidimensional segmentation. It adapts to the topology of the image through the use of multiple masks. The algorithm is almost invariant under initialization, allowing for random initialization, and uses a few easily tunable parameters. Experiments show that the active mask algorithm matches the ground truth well and outperforms the algorithm widely used in fluorescence microscopy, seeded watershed, both qualitatively, as well as quantitatively.

}, keywords = {Algorithms, Automated, Computer-Assisted, Cytological Techniques, Fluorescence, HeLa Cells, Humans, Image Processing, Microscopy, Pattern Recognition}, issn = {1057-7149}, doi = {10.1109/TIP.2009.2021081}, author = {Srinivasa, Gowri and Fickus, Matthew C and Yusong Guo and Linstedt, Adam D and Kovacevi{\'c}, Jelena} }