@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 {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 {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 {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 {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} }