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2. Deep learning models for histologic grading of breast cancer and association with disease prognosis

Author

Jaroensri, Ronnachai, Wulczyn, Ellery, Hegde, Narayan, Brown, Trissia, Flament-Auvigne, Isabelle, Tan, Fraser, Cai, Yuannan, Nagpal, Kunal, Rakha, Emad A., Dabbs, David J., Olson, Niels, Wren, James H., Thompson, Elaine E., Seetao, Erik, Robinson, Carrie, Miao, Melissa, Beckers, Fabien, Corrado, Greg S., Peng, Lily H., Mermel, Craig H., Liu, Yun, Steiner, David F., and Chen, Po-Hsuan Cameron

Published
2022
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6. Enabling precision medicine via standard communication of HTS provenance, analysis, and results

Author

Alterovitz, Gil, primary, Dean, Dennis, additional, Goble, Carole, additional, Crusoe, Michael R., additional, Soiland-Reyes, Stian, additional, Bell, Amanda, additional, Hayes, Anais, additional, Suresh, Anita, additional, Purkayastha, Anjan, additional, King, Charles H., additional, Taylor, Dan, additional, Johanson, Elaine, additional, Thompson, Elaine E., additional, Donaldson, Eric, additional, Morizono, Hiroki, additional, Tsang, Hsinyi, additional, Vora, Jeet K., additional, Goecks, Jeremy, additional, Yao, Jianchao, additional, Almeida, Jonas S., additional, Keeney, Jonathon, additional, Addepalli, KanakaDurga, additional, Krampis, Konstantinos, additional, Smith, Krista M., additional, Guo, Lydia, additional, Walderhaug, Mark, additional, Schito, Marco, additional, Ezewudo, Matthew, additional, Guimera, Nuria, additional, Walsh, Paul, additional, Kahsay, Robel, additional, Gottipati, Srikanth, additional, Rodwell, Timothy C., additional, Bloom, Toby, additional, Lai, Yuching, additional, Simonyan, Vahan, additional, and Mazumder, Raja, additional

Published
2018
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8. In Vitro Cytokine Licensing Induces Persistent Permissive Chromatin at the IDO1 Promoter

Author

Rovira Gonzalez, Yazmin I., Lynch, Patrick J., Thompson, Elaine E., Stultz, Brian G., and Hursh, Deborah A.

Subjects
Cryopreservation, Tumor Necrosis Factor-alpha, Acetylation, Mesenchymal Stem Cells, Chromatin Assembly and Disassembly, Lymphocyte Activation, Article, Chromatin, Interferon-gamma, Gene Expression Regulation, Cytokines, Humans, Indoleamine-Pyrrole 2,3,-Dioxygenase, RNA, Messenger, Transcription Initiation Site, Promoter Regions, Genetic, Cells, Cultured
Abstract

Mesenchymal stromal cells (MSCs) are being investigated as therapies for inflammatory diseases due to their immunosuppressive capacity. Interferon (IFN)-γ treatment primes MSC immunosuppression partially through induction of Indoleamine 2,3-dioxygenase (IDO1), which depletes tryptophan necessary to support proliferation of activated T cells. We investigated the role of histone modifications in the timing and maintenance of induced IDO1 expression in MSCs under clinical manufacturing conditions, such as cryopreservation.We used chromatin immunoprecipitation and quantitative polymerase chain reaction (PCR) to assay levels of transcriptionally permissive acetylated H3K9 and repressive trimethylated H3K9 histone modifications surrounding the transcriptional start site for IDO1, and reverse transcriptase PCR and immunoblotting to detect messenger RNA (mRNA) and protein.MSCs derived from three donors approached maximum IDO1 mRNA levels following 24 hours of in vitro cytokine treatment. Induction of IDO1 expression correlated with increased acetylation of H3K9 concomitant with reduction of trimethylated H3K9 modifications at the promoter. Examination of two additional donors confirmed this result. While induced IDO1 levels decreased within 2 days after cytokine removal and freeze thawing, the activated chromatin state was maintained. Upon re-exposure to cytokines, previously primed MSCs accumulated near-maximum IDO1 mRNA levels within 4-8 h.Our data indicate that in vitro priming of MSCs causes chromatin remodeling at the IDO1 promoter, that this alteration is maintained during processing commonly used to prepare MSCs for clinical use and that, once primed, MSCs are poised for IDO1 expression even in the absence of cytokines.

Published
2016

9. High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis

Author

Simonyan, Vahan, primary, Chumakov, Konstantin, additional, Dingerdissen, Hayley, additional, Faison, William, additional, Goldweber, Scott, additional, Golikov, Anton, additional, Gulzar, Naila, additional, Karagiannis, Konstantinos, additional, Vinh Nguyen Lam, Phuc, additional, Maudru, Thomas, additional, Muravitskaja, Olesja, additional, Osipova, Ekaterina, additional, Pan, Yang, additional, Pschenichnov, Alexey, additional, Rostovtsev, Alexandre, additional, Santana-Quintero, Luis, additional, Smith, Krista, additional, Thompson, Elaine E., additional, Tkachenko, Valery, additional, Torcivia-Rodriguez, John, additional, Voskanian, Alin, additional, Wan, Quan, additional, Wang, Jing, additional, Wu, Tsung-Jung, additional, Wilson, Carolyn, additional, and Mazumder, Raja, additional

Published
2016
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11. Chromatin Changes at the PPAR‐γ2Promoter During Bone Marrow‐Derived Multipotent Stromal Cell Culture Correlate With Loss of Gene Activation Potential

Author

Lynch, Patrick J., Thompson, Elaine E., McGinnis, Kathleen, Rovira Gonzalez, Yazmin I., Lo Surdo, Jessica, Bauer, Steven R., and Hursh, Deborah A.

Abstract

Bone marrow‐derived multipotent stromal cells (BM‐MSCs) display a broad range of therapeutically valuable properties, including the capacity to form skeletal tissues and dampen immune system responses. However, to use BM‐MSCs in a clinical setting, amplification is required, which may introduce epigenetic changes that affect biological properties. Here we used chromatin immunoprecipitation to compare post‐translationally modified histones at a subset of gene promoters associated with developmental and environmental plasticity in BM‐MSCs from multiple donors following culture expansion. At many locations, we observed localization of both transcriptionally permissive (H3K4me3) and repressive (H3K27me3) histone modifications. These chromatin signatures were consistent among BM‐MSCs from multiple donors. Since promoter activity depends on the relative levels of H3K4me3 and H3K27me3, we examined the ratio of H3K4me3 to H3K27me3 (K4/K27) at promoters during culture expansion. The H3K4me3 to H3K27me3 ratios were maintained at most assayed promoters over time. The exception was the adipose‐tissue specific promoter for the PPAR‐γ2isoform of PPAR‐γ, which is a critical positive regulator of adipogenesis. At PPAR‐γ2, we observed a change in K4/K27 levels favoring the repressed chromatin state during culture. This change correlated with diminished promoter activity in late passage cells exposed to adipogenic stimuli. In contrast to BM‐MSCs and osteoblasts, lineage‐restricted preadipocytes exhibited levels of H3K4me3 and H3K27me3 that favored the permissive chromatin state at PPAR‐γ2. These results demonstrate that locus‐specific changes in H3K4me3 and H3K27me3 levels can occur during BM‐MSC culture that may affect their properties. StemCells2015;33:2169–2181

Published
2015
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12. Using machine learning to improve anaphylaxis case identification in medical claims data.

Author

Kural KC, Mazo I, Walderhaug M, Santana-Quintero L, Karagiannis K, Thompson EE, Kelman JA, and Goud R

Abstract

Objectives: Anaphylaxis is a severe life-threatening allergic reaction, and its accurate identification in healthcare databases can harness the potential of "Big Data" for healthcare or public health purposes., Materials and Methods: This study used claims data obtained between October 1, 2015 and February 28, 2019 from the CMS database to examine the utility of machine learning in identifying incident anaphylaxis cases. We created a feature selection pipeline to identify critical features between different datasets. Then a variety of unsupervised and supervised methods were used (eg, Sammon mapping and eXtreme Gradient Boosting) to train models on datasets of differing data quality, which reflects the varying availability and potential rarity of ground truth data in medical databases., Results: Resulting machine learning model accuracies ranged from 47.7% to 94.4% when tested on ground truth data. Finally, we found new features to help experts enhance existing case-finding algorithms., Discussion: Developing precise algorithms to detect medical outcomes in claims can be a laborious and expensive process, particularly for conditions presented and coded diversely. We found it beneficial to filter out highly potent codes used for data curation to identify underlying patterns and features. To improve rule-based algorithms where necessary, researchers could use model explainers to determine noteworthy features, which could then be shared with experts and included in the algorithm., Conclusion: Our work suggests machine learning models can perform at similar levels as a previously published expert case-finding algorithm, while also having the potential to improve performance or streamline algorithm construction processes by identifying new relevant features for algorithm construction., Competing Interests: None declared., (Published by Oxford University Press on behalf of the American Medical Informatics Association 2024.)

Published
2024
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