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8 results on '"Solorzano, Jacobo"'

2. Digitize your Biology! Modeling multicellular systems through interpretable cell behavior

Author

Johnson, Jeanette A.I., primary, Stein-O'Brien, Genevieve L, additional, Booth, Max, additional, Heiland, Randy, additional, Kurtoglu, Furkan, additional, Bergman, Daniel, additional, Bucher, Elmar, additional, Deshpande, Atul, additional, Forjaz, Andre, additional, Getz, Michael, additional, Godet, Ines, additional, Lyman, Melissa, additional, Metzcar, John, additional, Mitchell, Jacob, additional, Raddatz, Andrew, additional, Rocha, Heber L., additional, Solorzano, Jacobo, additional, Sundus, Aneequa, additional, Wang, Yafei, additional, Gilkes, Daniele M., additional, Kagohara, Luciane T., additional, Kiemen, Ashley L., additional, Thompson, Elizabeth D., additional, Wirtz, Denis, additional, Wu, Pei-Hsun, additional, Zaidi, Neeha, additional, Zheng, Lei, additional, Zimmerman, Jacquelyn W., additional, Jaffee, Elizabeth M., additional, Chang, Young Hwan, additional, Coussens, Lisa, additional, Gray, Joe, additional, Heiser, Laura M., additional, Fertig, Elana J., additional, and Macklin, Paul, additional

Published
2023
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3. A genome-wide computational approach to define microRNA-Polycomb/trithorax gene regulatory circuits in Drosophila: microRNA-Polycomb/trithorax circuits

Author

Agencia Estatal de Investigación (España), Ministerio de Ciencia e Innovación (España), Solorzano, Jacobo, Carrillo Santa de Pau, Enrique, Laguna, Teresa, Busturia, Ana, Agencia Estatal de Investigación (España), Ministerio de Ciencia e Innovación (España), Solorzano, Jacobo, Carrillo Santa de Pau, Enrique, Laguna, Teresa, and Busturia, Ana

Abstract

Characterization of gene regulatory networks is fundamental to understanding homeostatic development. This process can be simplified by analyzing relatively simple genomes such as the genome of Drosophila melanogaster. In this work we have developed a computational framework in Drosophila to explore for the presence of gene regulatory circuits between two large groups of transcriptional regulators: the epigenetic group of the Polycomb/trithorax (PcG/trxG) proteins and the microRNAs (miRNAs). We have searched genome-wide for miRNA targets in PcG/trxG transcripts as well as for Polycomb Response Elements (PREs) in miRNA genes. Our results show that 10% of the analyzed miRNAs could be controlling PcG/trxG gene expression, while 40% of those miRNAs are putatively controlled by the selected set of PcG/trxG proteins. The integration of these analyses has resulted in the predicted existence of 3 classes of miRNA-PcG/trxG crosstalk interactions that define potential regulatory circuits. In the first class, miRNA-PcG circuits are defined by miRNAs that reciprocally crosstalk with PcG. In the second, miRNA-trxG circuits are defined by miRNAs that reciprocally crosstalk with trxG. In the third class, miRNA-PcG/trxG shared circuits are defined by miRNAs that crosstalk with both PcG and trxG regulators. These putative regulatory circuits may uncover a novel mechanism in Drosophila for the control of PcG/trxG and miRNAs levels of expression. The computational framework developed here for Drosophila melanogaster can serve as a model case for similar analyses in other species. Moreover, our work provides, for the first time, a new and useful resource for the Drosophila community to consult prior to experimental studies investigating the epigenetic regulatory networks of miRNA-PcG/trxG mediated gene expression.

Published
2023

5. Abstract PO-088: Classification based on efficiency of mRNA translation reveals a metabolically-dependent subtype of pancreatic cancer

Author

Shin, Sauyeun, primary, Nicolle, Remy, additional, Liauzun, Mehdi, additional, Solorzano, Jacobo, additional, Brunel, Alexia, additional, Jean, Christine, additional, Samain, Remi, additional, Raffenne, Jerôme, additional, Neuzillet, Cindy, additional, Joffre, Carine, additional, Rocci, Stephane, additional, Iovanna, Juan, additional, Dusetti, Nelson, additional, Larsson, Ola, additional, Pyronnet, Stephane, additional, Bousquet, Corinne, additional, and Martineau, Yvan, additional

Published
2021
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7. Translatome-based classification reveals a dual metabolic dependency of a new tumor subtype of pancreatic cancer

Author

Shin, Sauyeun, primary, Nicolle, Remy, additional, Jean, Christine, additional, Samain, Remi, additional, Ayadi, Mira, additional, Raffenne, Jerome, additional, Brunel, Alexia, additional, Solorzano, Jacobo, additional, Neuzillet, Cindy, additional, Joffre, Carine, additional, Rocchi, Stephane, additional, Iovanna, Juan, additional, Dusetti, Nelson, additional, Larsson, Ola, additional, Pyronnet, Stephane, additional, Bousquet, Corinne, additional, and Martineau, Yvan, additional

Published
2020
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8. Digitize your Biology! Modeling multicellular systems through interpretable cell behavior.

Author

Johnson JAI, Stein-O'Brien GL, Booth M, Heiland R, Kurtoglu F, Bergman DR, Bucher E, Deshpande A, Forjaz A, Getz M, Godet I, Lyman M, Metzcar J, Mitchell J, Raddatz A, Rocha H, Solorzano J, Sundus A, Wang Y, Gilkes D, Kagohara LT, Kiemen AL, Thompson ED, Wirtz D, Wu PH, Zaidi N, Zheng L, Zimmerman JW, Jaffee EM, Hwan Chang Y, Coussens LM, Gray JW, Heiser LM, Fertig EJ, and Macklin P

Abstract

Cells are fundamental units of life, constantly interacting and evolving as dynamical systems. While recent spatial multi-omics can quantitate individual cells' characteristics and regulatory programs, forecasting their evolution ultimately requires mathematical modeling. We develop a conceptual framework-a cell behavior hypothesis grammar-that uses natural language statements (cell rules) to create mathematical models. This allows us to systematically integrate biological knowledge and multi-omics data to make them computable. We can then perform virtual "thought experiments" that challenge and extend our understanding of multicellular systems, and ultimately generate new testable hypotheses. In this paper, we motivate and describe the grammar, provide a reference implementation, and demonstrate its potential through a series of examples in tumor biology and immunotherapy. Altogether, this approach provides a bridge between biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale, allowing the community to extrapolate from single-cell characterization to emergent multicellular behavior., Competing Interests: Declaration of interests JZ receives other support from Roche/Genentech. LZ receives grant support from Bristol-Myers Squibb, Merck, Astrazeneca, iTeos, Amgen, NovaRock, Inxmed, and Halozyme. LZ is a paid consultant/Advisory Board Member at Biosion, Alphamab, NovaRock, Ambrx, Akrevia/Xilio, QED, Tempus, Pfizer, Novagenesis, Snow Lake Capitals, Amberstone, Tavotek Lab, ClinicalTrial Options, LLC, and Mingruizhiyao. LZ holds shares at Amberstone, Alphamab, Cellaration, and Mingruizhiyao. EJ reports other support from Abmeta, Adventris, personal fees from Achilles, DragonFly, Neuvogen, Parker Institute, CPRIT, Surge, Mestag, Medical Home Group, and HDTbio, grants from Lustgarten, and other grant support from Genentech, BMS, NeoTX, and Break Through Cancer outside the submitted work. Dr. Jaffee is the Dana and Albert “Cubby” Broccoli Professor of Oncology. EJF is on the Scientific Advisory of Resistance Bio/Viosera Therapeutics, a paid consultant for Merck and Mestag, and receives research funds from Abbvie Inc and Roche/Genetech.

Published
2023
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