1
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Chen Y, Liang Z, Lai M. Targeting the devil: Strategies against cancer-associated fibroblasts in colorectal cancer. Transl Res 2024; 270:81-93. [PMID: 38614213 DOI: 10.1016/j.trsl.2024.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 04/06/2024] [Accepted: 04/10/2024] [Indexed: 04/15/2024]
Abstract
Cancer-associated fibroblasts (CAFs), as significant constituents of the tumor microenvironment (TME), play a pivotal role in the progression of cancers, including colorectal cancer (CRC). In this comprehensive review, we presented the origins and activation mechanisms of CAFs in CRC, elaborating on how CAFs drive tumor progression through their interactions with CRC cells, immune cells, vascular endothelial cells, and the extracellular matrix within the TME. We systematically outline the intricate web of interactions among CAFs, tumor cells, and other TME components, and based on this complex interplay, we summarize various therapeutic strategies designed to target CAFs in CRC. It is also essential to recognize that CAFs represent a highly heterogeneous group, encompassing various subtypes such as myofibroblastic CAF (myCAF), inflammatory CAF (iCAF), antigen-presenting CAF (apCAF), vessel-associated CAF (vCAF). Herein, we provide a summary of studies investigating the heterogeneity of CAFs in CRC and the characteristic expression patterns of each subtype. While the majority of CAFs contribute to the exacerbation of CRC malignancy, recent findings have revealed specific subtypes that exert inhibitory effects on CRC progression. Nevertheless, the comprehensive landscape of CAF heterogeneity still awaits exploration. We also highlight pivotal unanswered questions that need to be addressed before CAFs can be recognized as feasible targets for cancer treatment. In conclusion, the aim of our review is to elucidate the significance and challenges of advancing in-depth research on CAFs, while outlining the pathway to uncover the complex roles of CAFs in CRC and underscore their significant potential as therapeutic targets.
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Affiliation(s)
- Yuting Chen
- Department of Pathology, and Department of Pathology of Sir Run Run Shaw Hospital, Research Unit of Intelligence Classification of Tumor Pathology and Precision Therapy of Chinese Academy of Medical Sciences (2019RU042), Zhejiang University School of Medicine, Hangzhou, 310058, China; Department of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China; Key Laboratory of Disease Proteomics of Zhejiang Province, Department of Pathology, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Zhiyong Liang
- Department of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Maode Lai
- Department of Pathology, and Department of Pathology of Sir Run Run Shaw Hospital, Research Unit of Intelligence Classification of Tumor Pathology and Precision Therapy of Chinese Academy of Medical Sciences (2019RU042), Zhejiang University School of Medicine, Hangzhou, 310058, China; Key Laboratory of Disease Proteomics of Zhejiang Province, Department of Pathology, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
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2
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Curvello R, Berndt N, Hauser S, Loessner D. Recreating metabolic interactions of the tumour microenvironment. Trends Endocrinol Metab 2024; 35:518-532. [PMID: 38212233 DOI: 10.1016/j.tem.2023.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/05/2023] [Accepted: 12/12/2023] [Indexed: 01/13/2024]
Abstract
Tumours are heterogeneous tissues containing diverse populations of cells and an abundant extracellular matrix (ECM). This tumour microenvironment prompts cancer cells to adapt their metabolism to survive and grow. Besides epigenetic factors, the metabolism of cancer cells is shaped by crosstalk with stromal cells and extracellular components. To date, most experimental models neglect the complexity of the tumour microenvironment and its relevance in regulating the dynamics of the metabolism in cancer. We discuss emerging strategies to model cellular and extracellular aspects of cancer metabolism. We highlight cancer models based on bioengineering, animal, and mathematical approaches to recreate cell-cell and cell-matrix interactions and patient-specific metabolism. Combining these approaches will improve our understanding of cancer metabolism and support the development of metabolism-targeting therapies.
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Affiliation(s)
- Rodrigo Curvello
- Department of Chemical and Biological Engineering, Faculty of Engineering, Monash University, Melbourne, Victoria, Australia
| | - Nikolaus Berndt
- Department of Molecular Toxicology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany; Institute of Computer-assisted Cardiovascular Medicine, Deutsches Herzzentrum der Charité, Berlin, Germany; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Sandra Hauser
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Department of Radiopharmaceutical and Chemical Biology, Dresden, Germany
| | - Daniela Loessner
- Department of Chemical and Biological Engineering, Faculty of Engineering, Monash University, Melbourne, Victoria, Australia; Leibniz Institute of Polymer Research Dresden e.V., Max Bergmann Center of Biomaterials, Dresden, Germany; Department of Materials Science and Engineering, Faculty of Engineering, Monash University, Melbourne, Victoria, Australia; Department of Anatomy and Developmental Biology, Biomedicine Discovery Institute, Faculty of Medicine, Nursing and Health Science, Monash University, Melbourne, Victoria, Australia.
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3
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Tavakoli N, Fong EJ, Coleman A, Huang YK, Bigger M, Doche ME, Kim S, Lenz HJ, Graham NA, Macklin P, Finley SD, Mumenthaler SM. Merging Metabolic Modeling and Imaging for Screening Therapeutic Targets in Colorectal Cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.24.595756. [PMID: 38826317 PMCID: PMC11142224 DOI: 10.1101/2024.05.24.595756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Cancer-associated fibroblasts (CAFs) play a key role in metabolic reprogramming and are well-established contributors to drug resistance in colorectal cancer (CRC). To exploit this metabolic crosstalk, we integrated a systems biology approach that identified key metabolic targets in a data-driven method and validated them experimentally. This process involved high-throughput computational screening to investigate the effects of enzyme perturbations predicted by a computational model of CRC metabolism to understand system-wide effects efficiently. Our results highlighted hexokinase (HK) as one of the crucial targets, which subsequently became our focus for experimental validation using patient-derived tumor organoids (PDTOs). Through metabolic imaging and viability assays, we found that PDTOs cultured in CAF conditioned media exhibited increased sensitivity to HK inhibition. Our approach emphasizes the critical role of integrating computational and experimental techniques in exploring and exploiting CRC-CAF crosstalk.
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Affiliation(s)
- Niki Tavakoli
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Emma J. Fong
- Ellison Institute of Technology, Los Angeles, CA, 90064, USA
| | - Abigail Coleman
- Ellison Institute of Technology, Los Angeles, CA, 90064, USA
| | - Yu-Kai Huang
- Ellison Institute of Technology, Los Angeles, CA, 90064, USA
| | - Mathias Bigger
- Ellison Institute of Technology, Los Angeles, CA, 90064, USA
- Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, 90089, USA
| | | | - Seungil Kim
- Ellison Institute of Technology, Los Angeles, CA, 90064, USA
| | - Heinz-Josef Lenz
- Division of Medical Oncology, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, 90033, USA
| | - Nicholas A. Graham
- Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, 90089, USA
| | - Paul Macklin
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 46202, USA
| | - Stacey D. Finley
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
- Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, 90089, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA
| | - Shannon M. Mumenthaler
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
- Ellison Institute of Technology, Los Angeles, CA, 90064, USA
- Division of Medical Oncology, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, 90033, USA
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4
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Wang J, Novick S. Peptide set test: a peptide-centric strategy to infer differentially expressed proteins. BIOINFORMATICS (OXFORD, ENGLAND) 2024; 40:btae270. [PMID: 38632081 DOI: 10.1093/bioinformatics/btae270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 03/20/2024] [Accepted: 04/16/2024] [Indexed: 04/19/2024]
Abstract
MOTIVATION The clinical translation of mass spectrometry-based proteomics has been challenging due to limited statistical power caused by large technical variability and inter-patient heterogeneity. Bottom-up proteomics provides an indirect measurement of proteins through digested peptides. This raises the question whether peptide measurements can be used directly to better distinguish differentially expressed proteins. RESULTS We present a novel method called the peptide set test, which detects coordinated changes in the expression of peptides originating from the same protein and compares them to the rest of the peptidome. Applying our method to data from a published spike-in experiment and simulations demonstrates improved sensitivity without compromising precision, compared to aggregation-based approaches. Additionally, applying the peptide set test to compare the tumor proteomes of tamoxifen-sensitive and tamoxifen-resistant breast cancer patients reveals significant alterations in peptide levels of collagen XII, suggesting an association between collagen XII-mediated matrix reassembly and tamoxifen resistance. Our study establishes the peptide set test as a powerful peptide-centric strategy to infer differential expression in proteomics studies. AVAILABILITY AND IMPLEMENTATION Peptide set test (PepSetTest) is publicly available at https://github.com/JmWangBio/PepSetTest.
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Affiliation(s)
- Junmin Wang
- Data Sciences and Quantitative Biology, Discovery Sciences, Biopharmaceuticals R&D, AstraZeneca, Gaithersburg, MD 20878, United States
| | - Steven Novick
- Global Statistical Sciences, Eli Lilly, Indianapolis, IN 46285, United States
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5
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Baghdassarian HM, Lewis NE. Resource allocation in mammalian systems. Biotechnol Adv 2024; 71:108305. [PMID: 38215956 PMCID: PMC11182366 DOI: 10.1016/j.biotechadv.2023.108305] [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: 08/03/2023] [Revised: 12/17/2023] [Accepted: 12/18/2023] [Indexed: 01/14/2024]
Abstract
Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.
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Affiliation(s)
- Hratch M Baghdassarian
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA; Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA.
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6
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Gelbach PE, Cetin H, Finley SD. Flux sampling in genome-scale metabolic modeling of microbial communities. BMC Bioinformatics 2024; 25:45. [PMID: 38287239 PMCID: PMC10826046 DOI: 10.1186/s12859-024-05655-3] [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: 06/21/2023] [Accepted: 01/15/2024] [Indexed: 01/31/2024] Open
Abstract
BACKGROUND Microbial communities play a crucial role in ecosystem function through metabolic interactions. Genome-scale modeling is a promising method to understand these interactions and identify strategies to optimize the community. Flux balance analysis (FBA) is most often used to predict the flux through all reactions in a genome-scale model; however, the fluxes predicted by FBA depend on a user-defined cellular objective. Flux sampling is an alternative to FBA, as it provides the range of fluxes possible within a microbial community. Furthermore, flux sampling can capture additional heterogeneity across a population, especially when cells exhibit sub-maximal growth rates. RESULTS In this study, we simulate the metabolism of microbial communities and compare the metabolic characteristics found with FBA and flux sampling. With sampling, we find significant differences in the predicted metabolism, including an increase in cooperative interactions and pathway-specific changes in predicted flux. CONCLUSIONS Our results suggest the importance of sampling-based approaches to evaluate metabolic interactions. Furthermore, we emphasize the utility of flux sampling in quantitatively studying interactions between cells and organisms.
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Affiliation(s)
- Patrick E Gelbach
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Handan Cetin
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA
| | - Stacey D Finley
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA.
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA.
- Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, 90089, USA.
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7
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Zhang H, Yue X, Chen Z, Liu C, Wu W, Zhang N, Liu Z, Yang L, Jiang Q, Cheng Q, Luo P, Liu G. Define cancer-associated fibroblasts (CAFs) in the tumor microenvironment: new opportunities in cancer immunotherapy and advances in clinical trials. Mol Cancer 2023; 22:159. [PMID: 37784082 PMCID: PMC10544417 DOI: 10.1186/s12943-023-01860-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 09/13/2023] [Indexed: 10/04/2023] Open
Abstract
Despite centuries since the discovery and study of cancer, cancer is still a lethal and intractable health issue worldwide. Cancer-associated fibroblasts (CAFs) have gained much attention as a pivotal component of the tumor microenvironment. The versatility and sophisticated mechanisms of CAFs in facilitating cancer progression have been elucidated extensively, including promoting cancer angiogenesis and metastasis, inducing drug resistance, reshaping the extracellular matrix, and developing an immunosuppressive microenvironment. Owing to their robust tumor-promoting function, CAFs are considered a promising target for oncotherapy. However, CAFs are a highly heterogeneous group of cells. Some subpopulations exert an inhibitory role in tumor growth, which implies that CAF-targeting approaches must be more precise and individualized. This review comprehensively summarize the origin, phenotypical, and functional heterogeneity of CAFs. More importantly, we underscore advances in strategies and clinical trials to target CAF in various cancers, and we also summarize progressions of CAF in cancer immunotherapy.
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Affiliation(s)
- Hao Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Xinghai Yue
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
- Department of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Zhe Chen
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Chao Liu
- Department of Neurosurgery, Central Hospital of Zhuzhou, Zhuzhou, China
| | - Wantao Wu
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, China
| | - Nan Zhang
- College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Zaoqu Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Liping Yang
- Department of Laboratory Medicine, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Qing Jiang
- Department of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
| | - Peng Luo
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
| | - Guodong Liu
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
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8
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Gelbach PE, Finley SD. Genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer. iScience 2023; 26:107569. [PMID: 37664588 PMCID: PMC10474475 DOI: 10.1016/j.isci.2023.107569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 05/24/2023] [Accepted: 08/07/2023] [Indexed: 09/05/2023] Open
Abstract
Colorectal cancer (CRC) shows high incidence and mortality, partly due to the tumor microenvironment (TME), which is viewed as an active promoter of disease progression. Macrophages are among the most abundant cells in the TME. These immune cells are generally categorized as M1, with inflammatory and anti-cancer properties, or M2, which promote tumor proliferation and survival. Although the M1/M2 subclassification scheme is strongly influenced by metabolism, the metabolic divergence between the subtypes remains poorly understood. Therefore, we generated a suite of computational models that characterize the M1- and M2-specific metabolic states. Our models show key differences between the M1 and M2 metabolic networks and capabilities. We leverage the models to identify metabolic perturbations that cause the metabolic state of M2 macrophages to more closely resemble M1 cells. Overall, this work increases understanding of macrophage metabolism in CRC and elucidates strategies to promote the metabolic state of anti-tumor macrophages.
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Affiliation(s)
- Patrick E. Gelbach
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Stacey D. Finley
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
- Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA
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9
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Gelbach PE, Finley SD. Flux Sampling in Genome-scale Metabolic Modeling of Microbial Communities. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.18.537368. [PMID: 37197028 PMCID: PMC10173371 DOI: 10.1101/2023.04.18.537368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Microbial communities play a crucial role in ecosystem function through metabolic interactions. Genome-scale modeling is a promising method to understand these interactions. Flux balance analysis (FBA) is most often used to predict the flux through all reactions in a genome-scale model. However, the fluxes predicted by FBA depend on a user-defined cellular objective. Flux sampling is an alternative to FBA, as it provides the range of fluxes possible within a microbial community. Furthermore, flux sampling may capture additional heterogeneity across cells, especially when cells exhibit sub-maximal growth rates. In this study, we simulate the metabolism of microbial communities and compare the metabolic characteristics found with FBA and flux sampling. We find significant differences in the predicted metabolism with sampling, including increased cooperative interactions and pathway-specific changes in predicted flux. Our results suggest the importance of sampling-based and objective function-independent approaches to evaluate metabolic interactions and emphasize their utility in quantitatively studying interactions between cells and organisms.
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Affiliation(s)
- Patrick E. Gelbach
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Stacey D. Finley
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
- Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA
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10
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Gelbach PE, Finley SD. Ensemble-based genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.09.532000. [PMID: 36993493 PMCID: PMC10052244 DOI: 10.1101/2023.03.09.532000] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
1Colorectal cancer (CRC) shows high incidence and mortality, partly due to the tumor microenvironment, which is viewed as an active promoter of disease progression. Macrophages are among the most abundant cells in the tumor microenvironment. These immune cells are generally categorized as M1, with inflammatory and anti-cancer properties, or M2, which promote tumor proliferation and survival. Although the M1/M2 subclassification scheme is strongly influenced by metabolism, the metabolic divergence between the subtypes remains poorly understood. Therefore, we generated a suite of computational models that characterize the M1- and M2-specific metabolic states. Our models show key differences between the M1 and M2 metabolic networks and capabilities. We leverage the models to identify metabolic perturbations that cause the metabolic state of M2 macrophages to more closely resemble M1 cells. Overall, this work increases understanding of macrophage metabolism in CRC and elucidates strategies to promote the metabolic state of anti-tumor macrophages.
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Affiliation(s)
- Patrick E. Gelbach
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Stacey D. Finley
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
- Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA
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11
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Liang Q, Zhou XH. Role of cancer-associated fibroblasts in colorectal cancer. Shijie Huaren Xiaohua Zazhi 2023; 31:134-142. [DOI: 10.11569/wcjd.v31.i4.134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/28/2023] Open
Abstract
Colorectal cancer (CRC) is a malignancy that has a high incidence in all countries around the world. Cancer-associated fibroblasts (CAFs) are a vital component of the tumor microenvironment (TME), playing an important role in the development of CRC. CAFs can release multiple cytokines and exosomes, activating a variety of related signaling pathways and boosting the processes of the invasion, metastasis, metabolism, drug resistance, and immunosuppression in CRC. Thus, CAFs are a prognostic marker and therapeutic target for CRC. Understanding the role and mechanism of CAFs can provide new insights for the treatment of CRC.
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Affiliation(s)
- Qiao Liang
- Graduate School of Youjiang Medical College for Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China
| | - Xi-Han Zhou
- Department of Gastroenterology, Affiliated Hospital of Youjiang Medical College Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China
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12
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Liang Q, Zhou XH, Shen GF, Zhu F, Lian HF, Li X, Zheng JY, Li JP, Deng SM, Huang R. Role of cancer-associated fibroblasts in colorectal cancer. Shijie Huaren Xiaohua Zazhi 2023; 31:129-137. [DOI: 10.11569/wcjd.v31.i4.129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/28/2023] Open
Abstract
Colorectal cancer (CRC) is a malignancy that has a high incidence in all countries around the world. Cancer-associated fibroblasts (CAFs) are a vital component of the tumor microenvironment (TME), playing an important role in the development of CRC. CAFs can release multiple cytokines and exosomes, activating a variety of related signaling pathways and boosting the processes of the invasion, metastasis, metabolism, drug resistance, and immunosuppression in CRC. Thus, CAFs are a prognostic marker and therapeutic target for CRC. Understanding the role and mechanism of CAFs can provide new insights for the treatment of CRC.
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Affiliation(s)
- Qiao Liang
- Graduate School of Youjiang Medical College for Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China
| | - Xi-Han Zhou
- Department of Gastroenterology, Affiliated Hospital of Youjiang Medical College Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China
| | - Gao-Fei Shen
- Department of Gastroenterology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an 710000, Shaanxi Province, China
| | - Fei Zhu
- Department of Gastroenterology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an 710000, Shaanxi Province, China
| | - Hui-Fen Lian
- Department of Gastroenterology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an 710000, Shaanxi Province, China
| | - Xin Li
- Department of Gastroenterology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an 710000, Shaanxi Province, China
| | - Jun-Yi Zheng
- Department of Gastroenterology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an 710000, Shaanxi Province, China
| | - Jin-Peng Li
- Department of Gastroenterology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an 710000, Shaanxi Province, China
| | - Shui-Miao Deng
- Department of Gastroenterology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an 710000, Shaanxi Province, China
| | - Rui Huang
- Department of Gastroenterology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an 710000, Shaanxi Province, China
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13
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Warburg effect in colorectal cancer: the emerging roles in tumor microenvironment and therapeutic implications. J Hematol Oncol 2022; 15:160. [PMID: 36319992 PMCID: PMC9628128 DOI: 10.1186/s13045-022-01358-5] [Citation(s) in RCA: 64] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 09/26/2022] [Indexed: 11/07/2022] Open
Abstract
Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related death worldwide. Countless CRC patients undergo disease progression. As a hallmark of cancer, Warburg effect promotes cancer metastasis and remodels the tumor microenvironment, including promoting angiogenesis, immune suppression, cancer-associated fibroblasts formation and drug resistance. Targeting Warburg metabolism would be a promising method for the treatment of CRC. In this review, we summarize information about the roles of Warburg effect in tumor microenvironment to elucidate the mechanisms governing Warburg effect in CRC and to identify novel targets for therapy.
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