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Your search keyword '"Chow, Eric D"' showing total 16 results
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16 results on '"Chow, Eric D"'

2. Therapeutic algebra of immunomodulatory drug responses at single-cell resolution

Author

Jiang, Jialong, Chen, Sisi, Tsou, Tiffany, McGinnis, Christopher S., Khazaei, Tahmineh, Zhu, Qin, Park, Jong H., Rivaud, Paul, Strazhnik, Inna-Marie, Chow, Eric D., Sivak, David A., Gartner, Zev J., and Thomson, Matt

Subjects
Quantitative Biology - Genomics
Abstract

Therapeutic modulation of immune states is central to the treatment of human disease. However, how drugs and drug combinations impact the diverse cell types in the human immune system remains poorly understood at the transcriptome scale. Here, we apply single-cell mRNA-seq to profile the response of human immune cells to 502 immunomodulatory drugs alone and in combination. We develop a unified mathematical model that quantitatively describes the transcriptome scale response of myeloid and lymphoid cell types to individual drugs and drug combinations through a single inferred regulatory network. The mathematical model reveals how drug combinations generate novel, macrophage and T-cell states by recruiting combinations of gene expression programs through both additive and non-additive drug interactions. A simplified drug response algebra allows us to predict the continuous modulation of immune cell populations between activated, resting and hyper-inhibited states through combinatorial drug dose titrations. Our results suggest that transcriptome-scale mathematical models could enable the design of therapeutic strategies for programming the human immune system using combinations of therapeutics., Comment: 19 pages, 5 figures

Published
2022

3. Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution.

Author

Yang, Dian, Jones, Matthew G, Naranjo, Santiago, Rideout, William M, 3rd, Min, Kyung Hoi Joseph, Ho, Raymond, Wu, Wei, Replogle, Joseph M, Page, Jennifer L, Quinn, Jeffrey J, Horns, Felix, Qiu, Xiaojie, Chen, Michael Z, Freed-Pastor, William A, McGinnis, Christopher S, Patterson, David M, Gartner, Zev J, Chow, Eric D, Bivona, Trever G, Chan, Michelle M, Yosef, Nir, Jacks, Tyler, and Weissman, Jonathan S

Subjects
Animals, Genes, ras, Mice, Neoplasms: genetics, Phylogeny, Whole Exome Sequencing
Abstract

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth and expansion to neighboring and distal tissues. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma and tracked tumor evolution from single-transformed cells to metastatic tumors at unprecedented resolution. We found that the loss of the initial, stable alveolar-type2-like state was accompanied by a transient increase in plasticity. This was followed by the adoption of distinct transcriptional programs that enable rapid expansion and, ultimately, clonal sweep of stable subclones capable of metastasizing. Finally, tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates progression by creating novel trajectories. Our study elucidates the hierarchical nature of tumor evolution and, more broadly, enables in-depth studies of tumor progression.

Published
2022

4. Supplementary Table 2 from Immune Modulation with RANKL Blockade through Denosumab Treatment in Patients with Cancer

Author

Chang, Hewitt, primary, Marquez, Jaqueline, primary, Chen, Brandon K., primary, Kim, Daniel M., primary, Cheng, Michael L., primary, Liu, Eric V., primary, Yang, Hai, primary, Zhang, Li, primary, Sinha, Meenal, primary, Cheung, Alexander, primary, Kwek, Serena S., primary, Chow, Eric D., primary, Bridge, Mark, primary, Aggarwal, Rahul R., primary, Friedlander, Terence W., primary, Small, Eric J., primary, Anderson, Mark, primary, and Fong, Lawrence, primary

Published
2024
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5. Supplementary Table 3 from Immune Modulation with RANKL Blockade through Denosumab Treatment in Patients with Cancer

Author

Chang, Hewitt, primary, Marquez, Jaqueline, primary, Chen, Brandon K., primary, Kim, Daniel M., primary, Cheng, Michael L., primary, Liu, Eric V., primary, Yang, Hai, primary, Zhang, Li, primary, Sinha, Meenal, primary, Cheung, Alexander, primary, Kwek, Serena S., primary, Chow, Eric D., primary, Bridge, Mark, primary, Aggarwal, Rahul R., primary, Friedlander, Terence W., primary, Small, Eric J., primary, Anderson, Mark, primary, and Fong, Lawrence, primary

Published
2024
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6. Supplementary Figure 4 from Immune Modulation with RANKL Blockade through Denosumab Treatment in Patients with Cancer

Author

Chang, Hewitt, primary, Marquez, Jaqueline, primary, Chen, Brandon K., primary, Kim, Daniel M., primary, Cheng, Michael L., primary, Liu, Eric V., primary, Yang, Hai, primary, Zhang, Li, primary, Sinha, Meenal, primary, Cheung, Alexander, primary, Kwek, Serena S., primary, Chow, Eric D., primary, Bridge, Mark, primary, Aggarwal, Rahul R., primary, Friedlander, Terence W., primary, Small, Eric J., primary, Anderson, Mark, primary, and Fong, Lawrence, primary

Published
2024
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7. Supplementary Figure 5 from Immune Modulation with RANKL Blockade through Denosumab Treatment in Patients with Cancer

Author

Chang, Hewitt, primary, Marquez, Jaqueline, primary, Chen, Brandon K., primary, Kim, Daniel M., primary, Cheng, Michael L., primary, Liu, Eric V., primary, Yang, Hai, primary, Zhang, Li, primary, Sinha, Meenal, primary, Cheung, Alexander, primary, Kwek, Serena S., primary, Chow, Eric D., primary, Bridge, Mark, primary, Aggarwal, Rahul R., primary, Friedlander, Terence W., primary, Small, Eric J., primary, Anderson, Mark, primary, and Fong, Lawrence, primary

Published
2024
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8. Supplementary Figure 1 from Immune Modulation with RANKL Blockade through Denosumab Treatment in Patients with Cancer

Author

Chang, Hewitt, primary, Marquez, Jaqueline, primary, Chen, Brandon K., primary, Kim, Daniel M., primary, Cheng, Michael L., primary, Liu, Eric V., primary, Yang, Hai, primary, Zhang, Li, primary, Sinha, Meenal, primary, Cheung, Alexander, primary, Kwek, Serena S., primary, Chow, Eric D., primary, Bridge, Mark, primary, Aggarwal, Rahul R., primary, Friedlander, Terence W., primary, Small, Eric J., primary, Anderson, Mark, primary, and Fong, Lawrence, primary

Published
2024
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9. Supplementary Figure 3 from Immune Modulation with RANKL Blockade through Denosumab Treatment in Patients with Cancer

Author

Chang, Hewitt, primary, Marquez, Jaqueline, primary, Chen, Brandon K., primary, Kim, Daniel M., primary, Cheng, Michael L., primary, Liu, Eric V., primary, Yang, Hai, primary, Zhang, Li, primary, Sinha, Meenal, primary, Cheung, Alexander, primary, Kwek, Serena S., primary, Chow, Eric D., primary, Bridge, Mark, primary, Aggarwal, Rahul R., primary, Friedlander, Terence W., primary, Small, Eric J., primary, Anderson, Mark, primary, and Fong, Lawrence, primary

Published
2024
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10. Supplementary Table 1 from Immune Modulation with RANKL Blockade through Denosumab Treatment in Patients with Cancer

Author

Chang, Hewitt, primary, Marquez, Jaqueline, primary, Chen, Brandon K., primary, Kim, Daniel M., primary, Cheng, Michael L., primary, Liu, Eric V., primary, Yang, Hai, primary, Zhang, Li, primary, Sinha, Meenal, primary, Cheung, Alexander, primary, Kwek, Serena S., primary, Chow, Eric D., primary, Bridge, Mark, primary, Aggarwal, Rahul R., primary, Friedlander, Terence W., primary, Small, Eric J., primary, Anderson, Mark, primary, and Fong, Lawrence, primary

Published
2024
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11. Data from Immune Modulation with RANKL Blockade through Denosumab Treatment in Patients with Cancer

Author

Chang, Hewitt, primary, Marquez, Jaqueline, primary, Chen, Brandon K., primary, Kim, Daniel M., primary, Cheng, Michael L., primary, Liu, Eric V., primary, Yang, Hai, primary, Zhang, Li, primary, Sinha, Meenal, primary, Cheung, Alexander, primary, Kwek, Serena S., primary, Chow, Eric D., primary, Bridge, Mark, primary, Aggarwal, Rahul R., primary, Friedlander, Terence W., primary, Small, Eric J., primary, Anderson, Mark, primary, and Fong, Lawrence, primary

Published
2024
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12. Supplementary Figure 2 from Immune Modulation with RANKL Blockade through Denosumab Treatment in Patients with Cancer

Author

Chang, Hewitt, primary, Marquez, Jaqueline, primary, Chen, Brandon K., primary, Kim, Daniel M., primary, Cheng, Michael L., primary, Liu, Eric V., primary, Yang, Hai, primary, Zhang, Li, primary, Sinha, Meenal, primary, Cheung, Alexander, primary, Kwek, Serena S., primary, Chow, Eric D., primary, Bridge, Mark, primary, Aggarwal, Rahul R., primary, Friedlander, Terence W., primary, Small, Eric J., primary, Anderson, Mark, primary, and Fong, Lawrence, primary

Published
2024
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13. Immune modulation with RANKL blockade through denosumab treatment in patients with cancer

Author

Chang, Hewitt, primary, Marquez Garcia, Jaqueline, additional, Chen, Brandon K., additional, Kim, Daniel M., additional, Cheng, Michael L., additional, Liu, Eric V., additional, Yang, Hai, additional, Zhang, Li, additional, Sinha, Meenal, additional, Cheung, Alexander, additional, Kwek, Serena S., additional, Chow, Eric D., additional, Bridge, Mark, additional, Aggarwal, Rahul R., additional, Friedlander, Terence W., additional, Small, Eric J., additional, Anderson, Mark, additional, and Fong, Lawrence, additional

Published
2024
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14. D-SPIN constructs gene regulatory network models from multiplexed scRNA-seq data revealing organizing principles of cellular perturbation response

Author

Jiang, Jialong, Chen, Sisi, Tsou, Tiffany, McGinnis, Christopher S., Khazaei, Tahmineh, Zhu, Qin, Park, Jong H., Strazhnik, Inna-Marie, Hanna, John, Chow, Eric D., Sivak, David A., Gartner, Zev J., Thomson, Matt, Jiang, Jialong, Chen, Sisi, Tsou, Tiffany, McGinnis, Christopher S., Khazaei, Tahmineh, Zhu, Qin, Park, Jong H., Strazhnik, Inna-Marie, Hanna, John, Chow, Eric D., Sivak, David A., Gartner, Zev J., and Thomson, Matt

Abstract

Gene regulatory networks within cells modulate the expression of the genome in response to signals and changing environmental conditions. Reconstructions of gene regulatory networks can reveal the information processing and control principles used by cells to maintain homeostasis and execute cell-state transitions. Here, we introduce a computational framework, D-SPIN, that generates quantitative models of generegulatory networks from single-cell mRNA-seq data sets collected across thousands of distinct perturbation conditions. D-SPIN models the cell as a collection of interacting gene-expression programs, and constructs a probabilistic model to infer regulatory interactions between gene-expression programs and external perturbations. Using large Perturb-seq and drug-response datasets, we demonstrate that D-SPIN models reveal the organization of cellular pathways, sub-functions of macromolecular complexes, and the logic of cellular regulation of transcription, translation, metabolism, and protein degradation in response to gene knockdown perturbations. D-SPIN can also be applied to dissect drug response mechanisms in heterogeneous cell populations, elucidating how combinations of immunomodulatory drugs can induce novel cell states through additive recruitment of gene expression programs. D-SPIN provides a computational framework for constructing interpretable models of gene-regulatory networks to reveal principles of cellular information processing and physiological control.

Published
2023

15. D-SPIN constructs gene regulatory network models from multiplexed scRNA-seq data revealing organizing principles of cellular perturbation response

Author

Jiang, Jialong, primary, Chen, Sisi, additional, Tsou, Tiffany, additional, McGinnis, Christopher S, additional, Khazaei, Tahmineh, additional, Zhu, Qin, additional, Park, Jong H, additional, Strazhnik, Inna-Marie, additional, Hanna, John, additional, Chow, Eric D, additional, Sivak, David A, additional, Gartner, Zev J, additional, and Thomson, Matt, additional

Published
2023
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