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Shyam S, Ramu S, Sehgal M, Jolly MK. A systems-level analysis of the mutually antagonistic roles of RKIP and BACH1 in dynamics of cancer cell plasticity. J R Soc Interface 2023; 20:20230389. [PMID: 37963558 PMCID: PMC10645512 DOI: 10.1098/rsif.2023.0389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 10/20/2023] [Indexed: 11/16/2023] Open
Abstract
Epithelial-mesenchymal transition (EMT) is an important axis of phenotypic plasticity-a hallmark of cancer metastasis. Raf kinase-B inhibitor protein (RKIP) and BTB and CNC homology 1 (BACH1) are reported to influence EMT. In breast cancer, they act antagonistically, but the exact nature of their roles in mediating EMT and associated other axes of plasticity remains unclear. Here, analysing transcriptomic data, we reveal their antagonistic trends in a pan-cancer manner in terms of association with EMT, metabolic reprogramming and immune evasion via PD-L1. Next, we developed and simulated a mechanism-based gene regulatory network that captures how RKIP and BACH1 engage in feedback loops with drivers of EMT and stemness. We found that RKIP and BACH1 belong to two antagonistic 'teams' of players-while BACH1 belonged to the one driving pro-EMT, stem-like and therapy-resistant cell states, RKIP belonged to the one enabling pro-epithelial, less stem-like and therapy-sensitive phenotypes. Finally, we observed that low RKIP levels and upregulated BACH1 levels associated with worse clinical outcomes in many cancer types. Together, our systems-level analysis indicates that the emergent dynamics of underlying regulatory network enable the antagonistic patterns of RKIP and BACH1 with various axes of cancer cell plasticity, and with patient survival data.
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Affiliation(s)
- Sai Shyam
- Department of Bioengineering, Indian Institute of Science, Bangalore 560012, India
| | - Soundharya Ramu
- Department of Bioengineering, Indian Institute of Science, Bangalore 560012, India
| | - Manas Sehgal
- Department of Bioengineering, Indian Institute of Science, Bangalore 560012, India
| | - Mohit Kumar Jolly
- Department of Bioengineering, Indian Institute of Science, Bangalore 560012, India
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Li Y, Sair AT, Zhao W, Li T, Liu RH. Ferulic Acid Mediates Metabolic Syndrome via the Regulation of Hepatic Glucose and Lipid Metabolisms and the Insulin/IGF-1 Receptor/PI3K/AKT Pathway in Palmitate-Treated HepG2 Cells. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:14706-14717. [PMID: 36367981 DOI: 10.1021/acs.jafc.2c05676] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Ferulic acid (FA) is one of the most abundant bound phenolics in whole grains, partly contributing to its preventive effects on metabolic syndrome (MetS). The study aims to investigate if FA mediates MetS through the regulation of hepatic metabolisms and the insulin receptor related pathways in the palmitate-treated HepG2 cells (MetS model). We found that FA (50, 100, and 200 μM) dramatically ameliorated the lipid accumulation in the MetS model. FA significantly decreased the activities of the gluconeogenic enzymes, G6Pase and PEPCK, downregulated the lipogenic enzyme FAS-1, and upregulated the lipolytic enzyme CPT-1 by regulating a series of transcriptional factors including HNF4α, FOXO-1, SREBP-1c, and PPAR-γ. Notably, we found that FA's ability to alleviate MetS is achieved by activating the insulin receptor/PI3K/AKT pathway. Our results validated the effects of FA on mediating the metabolic disorders of lipid and glucose pathways and unveiled its potential intracellular mechanisms for the prevention of MetS.
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Affiliation(s)
- Yitong Li
- Department of Food Science, YanGuFang Company Laboratory, 245 Stocking Hall, Cornell University, Ithaca, New York 14853, United States
| | - Ali Tahir Sair
- Department of Food Science, YanGuFang Company Laboratory, 245 Stocking Hall, Cornell University, Ithaca, New York 14853, United States
| | - Weiyang Zhao
- Department of Food Science, YanGuFang Company Laboratory, 245 Stocking Hall, Cornell University, Ithaca, New York 14853, United States
| | - Tong Li
- Department of Food Science, YanGuFang Company Laboratory, 245 Stocking Hall, Cornell University, Ithaca, New York 14853, United States
| | - Rui Hai Liu
- Department of Food Science, YanGuFang Company Laboratory, 245 Stocking Hall, Cornell University, Ithaca, New York 14853, United States
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Dynamics of hepatocyte-cholangiocyte cell-fate decisions during liver development and regeneration. iScience 2022; 25:104955. [PMID: 36060070 PMCID: PMC9437857 DOI: 10.1016/j.isci.2022.104955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 05/17/2022] [Accepted: 08/12/2022] [Indexed: 11/25/2022] Open
Abstract
The immense regenerative potential of the liver is attributed to the ability of its two key cell types – hepatocytes and cholangiocytes – to trans-differentiate to one another either directly or through intermediate progenitor states. However, the dynamic features of decision-making between these cell-fates during liver development and regeneration remains elusive. Here, we identify a core gene regulatory network comprising c/EBPα, TGFBR2, and SOX9 which is multistable in nature, enabling three distinct cell states – hepatocytes, cholangiocytes, and liver progenitor cells (hepatoblasts/oval cells) – and stochastic switching among them. Predicted expression signature for these three states are validated through multiple bulk and single-cell transcriptomic datasets collected across developmental stages and injury-induced liver repair. This network can also explain the experimentally observed spatial organization of phenotypes in liver parenchyma and predict strategies for efficient cellular reprogramming. Our analysis elucidates how the emergent dynamics of underlying regulatory networks drive diverse cell-fate decisions in liver development and regeneration. Identified minimal regulatory network to model liver development and regeneration Changes in phenotypic landscapes by in-silico perturbations of regulatory networks Ability to explain physiological spatial patterning of liver cell types Decoded strategies for efficient reprogramming among liver cell phenotypes
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Cancer: More than a geneticist’s Pandora’s box. J Biosci 2022. [DOI: 10.1007/s12038-022-00254-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Li R, Tan CP, Xu Y, Liu Y. Alteration of Endogenous Fatty Acids Profile and Lipid Metabolism in Rats Caused by a High‐Colleseed Oil and a High‐Sunflower Oil Diet. EUR J LIPID SCI TECH 2021. [DOI: 10.1002/ejlt.202100100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Ruizhi Li
- State Key Laboratory of Food Science and Technology School of Food Science and Technology National Engineering Research Center for Functional Food National Engineering Laboratory for Cereal Fermentation Technology Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province Jiangnan University 1800 Lihu Road Wuxi Jiangsu 214122 P. R. China
| | - Chin Ping Tan
- Department of Food Technology Faculty of Food Science and Technology Universiti Putra Malaysia Serdang Selangor 43400 Malaysia
| | - Yong‐Jiang Xu
- State Key Laboratory of Food Science and Technology School of Food Science and Technology National Engineering Research Center for Functional Food National Engineering Laboratory for Cereal Fermentation Technology Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province Jiangnan University 1800 Lihu Road Wuxi Jiangsu 214122 P. R. China
| | - Yuanfa Liu
- State Key Laboratory of Food Science and Technology School of Food Science and Technology National Engineering Research Center for Functional Food National Engineering Laboratory for Cereal Fermentation Technology Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province Jiangnan University 1800 Lihu Road Wuxi Jiangsu 214122 P. R. China
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Somepalli G, Sahoo S, Singh A, Hannenhalli S. Prioritizing and characterizing functionally relevant genes across human tissues. PLoS Comput Biol 2021; 17:e1009194. [PMID: 34270548 PMCID: PMC8284802 DOI: 10.1371/journal.pcbi.1009194] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 06/17/2021] [Indexed: 11/29/2022] Open
Abstract
Knowledge of genes that are critical to a tissue's function remains difficult to ascertain and presents a major bottleneck toward a mechanistic understanding of genotype-phenotype links. Here, we present the first machine learning model-FUGUE-combining transcriptional and network features, to predict tissue-relevant genes across 30 human tissues. FUGUE achieves an average cross-validation auROC of 0.86 and auPRC of 0.50 (expected 0.09). In independent datasets, FUGUE accurately distinguishes tissue or cell type-specific genes, significantly outperforming the conventional metric based on tissue-specific expression alone. Comparison of tissue-relevant transcription factors across tissue recapitulate their developmental relationships. Interestingly, the tissue-relevant genes cluster on the genome within topologically associated domains and furthermore, are highly enriched for differentially expressed genes in the corresponding cancer type. We provide the prioritized gene lists in 30 human tissues and an open-source software to prioritize genes in a novel context given multi-sample transcriptomic data.
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Affiliation(s)
- Gowthami Somepalli
- Department of Computer Science, University of Maryland, College Park, Maryland, United States of America
| | - Sarthak Sahoo
- Undergraduate program, Indian Institute of Science, Bengaluru, India
| | - Arashdeep Singh
- Cancer Data Science Lab, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Sridhar Hannenhalli
- Cancer Data Science Lab, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
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Hati S, Duddu AS, Jolly MK. Operating principles of circular toggle polygons. Phys Biol 2021; 18. [PMID: 33730700 DOI: 10.1088/1478-3975/abef79] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/17/2021] [Indexed: 11/12/2022]
Abstract
Decoding the dynamics of cellular decision-making and cell differentiation is a central question in cell and developmental biology. A common network motif involved in many cell-fate decisions is a mutually inhibitory feedback loop between two self-activating 'master regulators' A and B, also called as toggle switch. Typically, it can allow for three stable states-(high A, low B), (low A, high B) and (medium A, medium B). A toggle triad-three mutually repressing regulators A, B and C, i.e. three toggle switches arranged circularly (between A and B, between B and C, and between A and C)-can allow for six stable states: three 'single positive' and three 'double positive' ones. However, the operating principles of larger toggle polygons, i.e. toggle switches arranged circularly to form a polygon, remain unclear. Here, we simulate using both discrete and continuous methods the dynamics of different sized toggle polygons. We observed a pattern in their steady state frequency depending on whether the polygon was an even or odd numbered one. The even-numbered toggle polygons result in two dominant states with consecutive components of the network expressing alternating high and low levels. The odd-numbered toggle polygons, on the other hand, enable more number of states, usually twice the number of components with the states that follow 'circular permutation' patterns in their composition. Incorporating self-activations preserved these trends while increasing the frequency of multistability in the corresponding network. Our results offer insights into design principles of circular arrangement of regulatory units involved in cell-fate decision making, and can offer design strategies for synthesizing genetic circuits.
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Affiliation(s)
- Souvadra Hati
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India.,Undergraduate Programme, Indian Institute of Science, Bangalore, India
| | - Atchuta Srinivas Duddu
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
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Chauhan L, Ram U, Hari K, Jolly MK. Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer. eLife 2021; 10:e64522. [PMID: 33729159 PMCID: PMC8012062 DOI: 10.7554/elife.64522] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Accepted: 03/16/2021] [Indexed: 02/07/2023] Open
Abstract
Phenotypic (non-genetic) heterogeneity has significant implications for the development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unraveled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origins of such phenotypic heterogeneity are poorly understood in most cancers. Here, we investigate a regulatory network underlying phenotypic heterogeneity in small cell lung cancer, a devastating disease with no molecular targeted therapy. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two teams of players that mutually inhibit each other, but members of a team activate one another, forming a 'toggle switch' between the two teams. Deciphering these topological signatures in cancer-related regulatory networks can unravel their 'latent' design principles and offer a rational approach to characterize phenotypic heterogeneity in a tumor.
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Affiliation(s)
- Lakshya Chauhan
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
- Undergraduate Programme, Indian Institute of ScienceBangaloreIndia
| | - Uday Ram
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
- Undergraduate Programme, Indian Institute of ScienceBangaloreIndia
| | - Kishore Hari
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
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Singh D, Bocci F, Kulkarni P, Jolly MK. Coupled Feedback Loops Involving PAGE4, EMT and Notch Signaling Can Give Rise to Non-genetic Heterogeneity in Prostate Cancer Cells. ENTROPY (BASEL, SWITZERLAND) 2021; 23:288. [PMID: 33652914 PMCID: PMC7996788 DOI: 10.3390/e23030288] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 02/18/2021] [Accepted: 02/23/2021] [Indexed: 12/12/2022]
Abstract
Non-genetic heterogeneity is emerging as a crucial factor underlying therapy resistance in multiple cancers. However, the design principles of regulatory networks underlying non-genetic heterogeneity in cancer remain poorly understood. Here, we investigate the coupled dynamics of feedback loops involving (a) oscillations in androgen receptor (AR) signaling mediated through an intrinsically disordered protein PAGE4, (b) multistability in epithelial-mesenchymal transition (EMT), and c) Notch-Delta-Jagged signaling mediated cell-cell communication, each of which can generate non-genetic heterogeneity through multistability and/or oscillations. Our results show how different coupling strengths between AR and EMT signaling can lead to monostability, bistability, or oscillations in the levels of AR, as well as propagation of oscillations to EMT dynamics. These results reveal the emergent dynamics of coupled oscillatory and multi-stable systems and unravel mechanisms by which non-genetic heterogeneity in AR levels can be generated, which can act as a barrier to most existing therapies for prostate cancer patients.
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Affiliation(s)
- Divyoj Singh
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Undergraduate Programme, Indian Institute of Science, Bangalore 560012, India
| | - Federico Bocci
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA;
- NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, CA 92697, USA
| | - Prakash Kulkarni
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA;
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
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Saxena K, Srikrishnan S, Celia-Terrassa T, Jolly MK. OVOL1/2: Drivers of Epithelial Differentiation in Development, Disease, and Reprogramming. Cells Tissues Organs 2020; 211:183-192. [PMID: 32932250 DOI: 10.1159/000511383] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Accepted: 08/26/2020] [Indexed: 11/19/2022] Open
Abstract
OVOL proteins (OVOL1 and OVOL2), vertebrate homologs of Drosophila OVO, are critical regulators of epithelial lineage determination and differentiation during embryonic development in tissues such as kidney, skin, mammary epithelia, and testis. OVOL can inhibit epithelial-mesenchymal transition and/or can promote mesenchymal-epithelial transition. Moreover, they can regulate the stemness of cancer cells, thus playing an important role during cancer cell metastasis. Due to their central role in differentiation and maintenance of epithelial lineage, OVOL overexpression has been shown to be capable of reprogramming fibroblasts to epithelial cells. Here, we review the roles of OVOL-mediated epithelial differentiation across multiple contexts, including embryonic development, cancer progression, and cellular reprogramming.
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Affiliation(s)
- Kritika Saxena
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | | | - Toni Celia-Terrassa
- Cancer Research Program, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Mohit Kumar Jolly
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India,
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