1
|
Hashem M, Mohandesi Khosroshahi E, Aliahmady M, Ghanei M, Soofi Rezaie Y, alsadat Jafari Y, rezaei F, Khodaparast eskadehi R, Kia Kojoori K, jamshidian F, Nabavi N, Rashidi M, Hasani Sadi F, Taheriazam A, Entezari M. Non-coding RNA transcripts, incredible modulators of cisplatin chemo-resistance in bladder cancer through operating a broad spectrum of cellular processes and signaling mechanism. Noncoding RNA Res 2024; 9:560-582. [PMID: 38515791 PMCID: PMC10955558 DOI: 10.1016/j.ncrna.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 01/12/2024] [Accepted: 01/14/2024] [Indexed: 03/23/2024] Open
Abstract
Bladder cancer (BC) is a highly frequent neoplasm in correlation with significant rate of morbidity, mortality, and cost. The onset of BC is predominantly triggered by environmental and/or occupational exposures to carcinogens, such as tobacco. There are two distinct pathways by which BC can be developed, including non-muscle-invasive papillary tumors (NMIBC) and non-papillary (or solid) muscle-invasive tumors (MIBC). The Cancer Genome Atlas project has further recognized key genetic drivers of MIBC along with its subtypes with particular properties and therapeutic responses; nonetheless, NMIBC is the predominant BC presentation among the suffering individuals. Radical cystoprostatectomy, radiotherapy, and chemotherapy have been verified to be the common therapeutic interventions in metastatic tumors, among which chemotherapeutics are more conventionally utilized. Although multiple chemo drugs have been broadly administered for BC treatment, cisplatin is reportedly the most effective chemo drug against the corresponding malignancy. Notwithstanding, tumor recurrence is usually occurred following the consumption of cisplatin regimens, particularly due to the progression of chemo-resistant trait. In this framework, non-coding RNAs (ncRNAs), as abundant RNA transcripts arise from the human genome, are introduced to serve as crucial contributors to tumor expansion and cisplatin chemo-resistance in bladder neoplasm. In the current review, we first investigated the best-known ncRNAs, i.e. microRNAs (miRNAs), long ncRNAs (lncRNAs), and circular RNAs (circRNAs), correlated with cisplatin chemo-resistance in BC cells and tissues. We noticed that these ncRNAs could mediate the BC-related cisplatin-resistant phenotype through diverse cellular processes and signaling mechanisms, reviewed here. Eventually, diagnostic and prognostic potential of ncRNAs, as well as their therapeutic capabilities were highlighted in regard to BC management.
Collapse
Affiliation(s)
- Mehrdad Hashem
- Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Elaheh Mohandesi Khosroshahi
- Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Melika Aliahmady
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Morvarid Ghanei
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Yasamin Soofi Rezaie
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Yasamin alsadat Jafari
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
- Department of Biology, East Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Fatemeh rezaei
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
- Department of Biology, East Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Ramtin Khodaparast eskadehi
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
- Department of Biology, East Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Kimia Kia Kojoori
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
- Department of Biology, East Tehran Branch, Islamic Azad University, Tehran, Iran
| | - faranak jamshidian
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
- Department of Biology, East Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Noushin Nabavi
- Department of Urologic Sciences and Vancouver Prostate Centre, University of British Columbia, V6H3Z6, Vancouver, BC, Canada
| | - Mohsen Rashidi
- The Health of Plant and Livestock Products Research Center, Mazandaran University of Medical Sciences, Sari, Iran
- Department Pharmacology, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
| | - Farzaneh Hasani Sadi
- General Practitioner, Kerman University of Medical Sciences, Kerman, 7616913555, Iran
| | - Afshin Taheriazam
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
- Department of Orthopedics, Faculty of Medicine, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Maliheh Entezari
- Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| |
Collapse
|
2
|
Haake SM, Rios BL, Pozzi A, Zent R. Integrating integrins with the hallmarks of cancer. Matrix Biol 2024; 130:20-35. [PMID: 38677444 DOI: 10.1016/j.matbio.2024.04.003] [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: 01/09/2024] [Revised: 04/02/2024] [Accepted: 04/23/2024] [Indexed: 04/29/2024]
Abstract
Epithelial cells adhere to a specialized extracellular matrix called the basement membrane which allows them to polarize and form epithelial tissues. The extracellular matrix provides essential physical scaffolding and biochemical and biophysical cues required for tissue morphogenesis, differentiation, function, and homeostasis. Epithelial cell adhesion to the extracellular matrix (i.e., basement membrane) plays a critical role in organizing epithelial tissues, separating the epithelial cells from the stroma. Epithelial cell detachment from the basement membrane classically results in death, though detachment or invasion through the basement membrane represents a critical step in carcinogenesis. Epithelial cells bind to the extracellular matrix via specialized matrix receptors, including integrins. Integrins are transmembrane receptors that form a mechanical linkage between the extracellular matrix and the intracellular cytoskeleton and are required for anchorage-dependent cellular functions such as proliferation, migration, and invasion. The role of integrins in the development, growth, and dissemination of multiple types of carcinomas has been investigated by numerous methodologies, which has led to great complexity. To organize this vast array of information, we have utilized the "Hallmarks of Cancer" from Hanahan and Weinberg as a convenient framework to discuss the role of integrins in the pathogenesis of cancers. This review explores this biology and how its complexity has impacted the development of integrin-targeted anti-cancer therapeutics.
Collapse
Affiliation(s)
- Scott M Haake
- Division of Hematology, Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Veterans Affairs, Nashville, TN, USA; Vanderbilt-Ingram Cancer Center, Nashville, TN, USA; Cancer Biology Program, Vanderbilt University, Nashville, TN, USA.
| | - Brenda L Rios
- Vanderbilt-Ingram Cancer Center, Nashville, TN, USA; Cancer Biology Program, Vanderbilt University, Nashville, TN, USA
| | - Ambra Pozzi
- Department of Veterans Affairs, Nashville, TN, USA; Vanderbilt-Ingram Cancer Center, Nashville, TN, USA; Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Roy Zent
- Department of Veterans Affairs, Nashville, TN, USA; Vanderbilt-Ingram Cancer Center, Nashville, TN, USA; Cancer Biology Program, Vanderbilt University, Nashville, TN, USA; Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
| |
Collapse
|
3
|
Balog S, de Almeida MS, Taladriz-Blanco P, Rothen-Rutishauser B, Petri-Fink A. Does the surface charge of the nanoparticles drive nanoparticle-cell membrane interactions? Curr Opin Biotechnol 2024; 87:103128. [PMID: 38581743 DOI: 10.1016/j.copbio.2024.103128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 03/08/2024] [Accepted: 03/13/2024] [Indexed: 04/08/2024]
Abstract
Classical Coulombic interaction, characterized by electrostatic interactions mediated through surface charges, is often regarded as the primary determinant in nanoparticles' (NPs) cellular association and internalization. However, the intricate physicochemical properties of particle surfaces, biomolecular coronas, and cell surfaces defy this oversimplified perspective. Moreover, the nanometrological techniques employed to characterize NPs in complex physiological fluids often exhibit limited accuracy and reproducibility. A more comprehensive understanding of nanoparticle-cell membrane interactions, extending beyond attractive forces between oppositely charged surfaces, necessitates the establishment of databases through rigorous physical, chemical, and biological characterization supported by nanoscale analytics. Additionally, computational approaches, such as in silico modeling and machine learning, play a crucial role in unraveling the complexities of these interactions.
Collapse
Affiliation(s)
- Sandor Balog
- Adolphe Merkle Institute, University of Fribourg, National Center of Competence in Research Bio-Inspired Materials, Chemin des Verdiers 4, 1700 Fribourg, Switzerland
| | - Mauro Sousa de Almeida
- Adolphe Merkle Institute, University of Fribourg, National Center of Competence in Research Bio-Inspired Materials, Chemin des Verdiers 4, 1700 Fribourg, Switzerland
| | - Patricia Taladriz-Blanco
- Adolphe Merkle Institute, University of Fribourg, National Center of Competence in Research Bio-Inspired Materials, Chemin des Verdiers 4, 1700 Fribourg, Switzerland
| | - Barbara Rothen-Rutishauser
- Adolphe Merkle Institute, University of Fribourg, National Center of Competence in Research Bio-Inspired Materials, Chemin des Verdiers 4, 1700 Fribourg, Switzerland
| | - Alke Petri-Fink
- Adolphe Merkle Institute, University of Fribourg, National Center of Competence in Research Bio-Inspired Materials, Chemin des Verdiers 4, 1700 Fribourg, Switzerland; Department of Chemistry, University of Fribourg, Chemin du Musée 9, 1700 Fribourg, Switzerland.
| |
Collapse
|
4
|
Kuo YP, Nombela-Arrieta C, Carja O. A theory of evolutionary dynamics on any complex population structure reveals stem cell niche architecture as a spatial suppressor of selection. Nat Commun 2024; 15:4666. [PMID: 38821923 PMCID: PMC11143212 DOI: 10.1038/s41467-024-48617-2] [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: 07/18/2023] [Accepted: 05/02/2024] [Indexed: 06/02/2024] Open
Abstract
How the spatial arrangement of a population shapes its evolutionary dynamics has been of long-standing interest in population genetics. Most previous studies assume a small number of demes or symmetrical structures that, most often, act as well-mixed populations. Other studies use network theory to study more heterogeneous spatial structures, however they usually assume small, regular networks, or strong constraints on the strength of selection considered. Here we build network generation algorithms, conduct evolutionary simulations and derive general analytic approximations for probabilities of fixation in populations with complex spatial structure. We build a unifying evolutionary theory across network families and derive the relevant selective parameter, which is a combination of network statistics, predictive of evolutionary dynamics. We also illustrate how to link this theory with novel datasets of spatial organization and use recent imaging data to build the cellular spatial networks of the stem cell niches of the bone marrow. Across a wide variety of parameters, we find these networks to be strong suppressors of selection, delaying mutation accumulation in this tissue. We also find that decreases in stem cell population size also decrease the suppression strength of the tissue spatial structure.
Collapse
Affiliation(s)
- Yang Ping Kuo
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - César Nombela-Arrieta
- Department of Medical Oncology and Hematology, University and University Hospital Zurich, Zurich, Switzerland
| | - Oana Carja
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
| |
Collapse
|
5
|
Luque LM, Carlevaro CM, Rodriguez-Lomba E, Lomba E. In silico study of heterogeneous tumour-derived organoid response to CAR T-cell therapy. Sci Rep 2024; 14:12307. [PMID: 38811838 PMCID: PMC11137006 DOI: 10.1038/s41598-024-63125-5] [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: 02/19/2024] [Accepted: 05/24/2024] [Indexed: 05/31/2024] Open
Abstract
Chimeric antigen receptor (CAR) T-cell therapy is a promising immunotherapy for treating cancers. This method consists in modifying the patients' T-cells to directly target antigen-presenting cancer cells. One of the barriers to the development of this type of therapies, is target antigen heterogeneity. It is thought that intratumour heterogeneity is one of the leading determinants of therapeutic resistance and treatment failure. While understanding antigen heterogeneity is important for effective therapeutics, a good therapy strategy could enhance the therapy efficiency. In this work we introduce an agent-based model (ABM), built upon a previous ABM, to rationalise the outcomes of different CAR T-cells therapies strategies over heterogeneous tumour-derived organoids. We found that one dose of CAR T-cell therapy should be expected to reduce the tumour size as well as its growth rate, however it may not be enough to completely eliminate it. Moreover, the amount of free CAR T-cells (i.e. CAR T-cells that did not kill any cancer cell) increases as we increase the dosage, and so does the risk of side effects. We tested different strategies to enhance smaller dosages, such as enhancing the CAR T-cells long-term persistence and multiple dosing. For both approaches an appropriate dosimetry strategy is necessary to produce "effective yet safe" therapeutic results. Moreover, an interesting emergent phenomenon results from the simulations, namely the formation of a shield-like structure of cells with low antigen expression. This shield turns out to protect cells with high antigen expression. Finally we tested a multi-antigen recognition therapy to overcome antigen escape and heterogeneity. Our studies suggest that larger dosages can completely eliminate the organoid, however the multi-antigen recognition increases the risk of side effects. Therefore, an appropriate small dosages dosimetry strategy is necessary to improve the outcomes. Based on our results, it is clear that a proper therapeutic strategy could enhance the therapies outcomes. In that direction, our computational approach provides a framework to model treatment combinations in different scenarios and to explore the characteristics of successful and unsuccessful treatments.
Collapse
Affiliation(s)
- Luciana Melina Luque
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, EH16 4UU, UK.
| | - Carlos Manuel Carlevaro
- Instituto de Física de Líquidos y Sistemas Biológicos, Consejo Nacional de Investigaciones Científicas y Técnicas, 1900, La Plata, Argentina
- Departamento de Ingeniería Mecánica, Universidad Tecnológica Nacional, Facultad Regional La Plata, 1900, La Plata, Argentina
| | | | - Enrique Lomba
- Instituto de Química Física Blas Cabrera, Consejo Superior de Investigaciones Científicas, 28006, Madrid, Spain
| |
Collapse
|
6
|
Brézin L, Korolev KS. Mechanically-driven growth and competition in a Voronoi model of tissues. ARXIV 2024:arXiv:2405.07899v1. [PMID: 38800651 PMCID: PMC11118596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
The mechanisms leading cells to acquire a fitness advantage and establish themselves in a population are paramount to understanding the development and growth of cancer. Although there are many works that study separately either the evolutionary dynamics or the mechanics of cancer, little has been done to couple evolutionary dynamics to mechanics. To address this question, we study a confluent model of tissue using a Self-Propelled Voronoi (SPV) model with stochastic growth rates that depend on the mechanical variables of the system. The SPV model is an out-of-equilibrium model of tissue derived from an energy functional that has a jamming/unjamming transition between solid-like and liquid-like states. By considering several scenarios of mutants invading a resident population in both phases, we determine the range of parameters that confer a fitness advantage and show that the preferred area and perimeter are the most relevant ones. We find that the liquid-like state is more resistant to invasion and show that the outcome of the competition can be determined from the simulation of a non-growing mixture. Moreover, a mean-field approximation can accurately predict the fate of a mutation affecting mechanical properties of a cell. Our results can be used to infer evolutionary dynamics from tissue images, understand cancer-suppressing effects of tissue mechanics, and even search for mechanics-based therapies.
Collapse
Affiliation(s)
- Louis Brézin
- Department of Physics, Graduate Program in Bioinformatics and Biological Design Center, Boston University, Boston, Massachusetts 02215, USA
| | - Kirill S. Korolev
- Department of Physics, Graduate Program in Bioinformatics and Biological Design Center, Boston University, Boston, Massachusetts 02215, USA
| |
Collapse
|
7
|
Colyer B, Bak M, Basanta D, Noble R. A seven-step guide to spatial, agent-based modelling of tumour evolution. Evol Appl 2024; 17:e13687. [PMID: 38707992 PMCID: PMC11064804 DOI: 10.1111/eva.13687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 03/27/2024] [Accepted: 03/29/2024] [Indexed: 05/07/2024] Open
Abstract
Spatial agent-based models are frequently used to investigate the evolution of solid tumours subject to localized cell-cell interactions and microenvironmental heterogeneity. As spatial genomic, transcriptomic and proteomic technologies gain traction, spatial computational models are predicted to become ever more necessary for making sense of complex clinical and experimental data sets, for predicting clinical outcomes, and for optimizing treatment strategies. Here we present a non-technical step by step guide to developing such a model from first principles. Stressing the importance of tailoring the model structure to that of the biological system, we describe methods of increasing complexity, from the basic Eden growth model up to off-lattice simulations with diffusible factors. We examine choices that unavoidably arise in model design, such as implementation, parameterization, visualization and reproducibility. Each topic is illustrated with examples drawn from recent research studies and state of the art modelling platforms. We emphasize the benefits of simpler models that aim to match the complexity of the phenomena of interest, rather than that of the entire biological system. Our guide is aimed at both aspiring modellers and other biologists and oncologists who wish to understand the assumptions and limitations of the models on which major cancer studies now so often depend.
Collapse
Affiliation(s)
- Blair Colyer
- Department of MathematicsCity, University of LondonLondonUK
| | - Maciej Bak
- Department of MathematicsCity, University of LondonLondonUK
| | - David Basanta
- Department of Integrated Mathematical OncologyH. Lee Moffitt Cancer Center and Research InstituteTampaFloridaUSA
| | - Robert Noble
- Department of MathematicsCity, University of LondonLondonUK
| |
Collapse
|
8
|
Aguadé-Gorgorió G, Anderson AR, Solé R. Modeling tumors as species-rich ecological communities. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.22.590504. [PMID: 38712062 PMCID: PMC11071393 DOI: 10.1101/2024.04.22.590504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Many advanced cancers resist therapeutic intervention. This process is fundamentally related to intra-tumor heterogeneity: multiple cell populations, each with different mutational and phenotypic signatures, coexist within a tumor and its metastatic nodes. Like species in an ecosystem, many cancer cell populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity nor are able to predict its consequences. Here we propose that the Generalized Lotka-Volterra model (GLV), a standard tool to describe complex, species-rich ecological communities, provides a suitable framework to describe the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties, such as outgrowth and multistability, provide a new understanding of the disease. Additionally, we discuss potential extensions of the model and their application to three active areas of cancer research, namely phenotypic plasticity, the cancer-immune interplay and the resistance of metastatic tumors to treatment. Our work outlines a set of questions and a tentative road map for further research in cancer ecology.
Collapse
Affiliation(s)
| | - Alexander R.A. Anderson
- Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, USA
| | - Ricard Solé
- ICREA-Complex Systems Lab, UPF-PRBB, Dr. Aiguader 80, 08003 Barcelona, Spain
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
| |
Collapse
|
9
|
Liu X, Zhang K, Kaya NA, Jia Z, Wu D, Chen T, Liu Z, Zhu S, Hillmer AM, Wuestefeld T, Liu J, Chan YS, Hu Z, Ma L, Jiang L, Zhai W. Tumor phylogeography reveals block-shaped spatial heterogeneity and the mode of evolution in Hepatocellular Carcinoma. Nat Commun 2024; 15:3169. [PMID: 38609353 PMCID: PMC11015015 DOI: 10.1038/s41467-024-47541-9] [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: 08/04/2022] [Accepted: 03/26/2024] [Indexed: 04/14/2024] Open
Abstract
Solid tumors are complex ecosystems with heterogeneous 3D structures, but the spatial intra-tumor heterogeneity (sITH) at the macroscopic (i.e., whole tumor) level is under-explored. Using a phylogeographic approach, we sequence genomes and transcriptomes from 235 spatially informed sectors across 13 hepatocellular carcinomas (HCC), generating one of the largest datasets for studying sITH. We find that tumor heterogeneity in HCC segregates into spatially variegated blocks with large genotypic and phenotypic differences. By dissecting the transcriptomic heterogeneity, we discover that 30% of patients had a "spatially competing distribution" (SCD), where different spatial blocks have distinct transcriptomic subtypes co-existing within a tumor, capturing the critical transition period in disease progression. Interestingly, the tumor regions with more advanced transcriptomic subtypes (e.g., higher cell cycle) often take clonal dominance with a wider geographic range, rejecting neutral evolution for SCD patients. Extending the statistical tests for detecting natural selection to many non-SCD patients reveal varying levels of selective signal across different tumors, implying that many evolutionary forces including natural selection and geographic isolation can influence the overall pattern of sITH. Taken together, tumor phylogeography unravels a dynamic landscape of sITH, pinpointing important evolutionary and clinical consequences of spatial heterogeneity in cancer.
Collapse
Affiliation(s)
- Xiaodong Liu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Ke Zhang
- Department of General Surgery, Beijing Ditan Hospital, Capital Medical University, No. 8, Jingshun East Street, Chaoyang District, Beijing, P.R. China
| | - Neslihan A Kaya
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Zhe Jia
- Department of General Surgery, Beijing Ditan Hospital, Capital Medical University, No. 8, Jingshun East Street, Chaoyang District, Beijing, P.R. China
| | - Dafei Wu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Tingting Chen
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Zhiyuan Liu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Sinan Zhu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Centre for Quantitative Medicine, Program in Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Axel M Hillmer
- Institute of Pathology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Torsten Wuestefeld
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Jin Liu
- Centre for Quantitative Medicine, Program in Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Yun Shen Chan
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Zheng Hu
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Liang Ma
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
| | - Li Jiang
- Department of General Surgery, Beijing Ditan Hospital, Capital Medical University, No. 8, Jingshun East Street, Chaoyang District, Beijing, P.R. China.
| | - Weiwei Zhai
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
| |
Collapse
|
10
|
Hall D. Equations describing semi-confluent cell growth (I) Analytical approximations. Biophys Chem 2024; 307:107173. [PMID: 38241828 DOI: 10.1016/j.bpc.2024.107173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 12/27/2023] [Accepted: 01/05/2024] [Indexed: 01/21/2024]
Abstract
A set of differential equations with analytical solutions are presented that can quantitatively account for variable degrees of contact inhibition on cell growth in two- and three-dimensional cultures. The developed equations can be used for comparative purposes when assessing contribution of higher-order effects, such as culture geometry and nutrient depletion, on mean cell growth rate. These equations also offer experimentalists the opportunity to characterize cell culture experiments using a single reductive parameter.
Collapse
Affiliation(s)
- Damien Hall
- WPI Nano Life Science Institute, Kanazawa University, Kakumamachi, Kanazawa, Ishikawa 920-1164, Japan.
| |
Collapse
|
11
|
Imodoye SO, Adedokun KA, Bello IO. From complexity to clarity: unravelling tumor heterogeneity through the lens of tumor microenvironment for innovative cancer therapy. Histochem Cell Biol 2024; 161:299-323. [PMID: 38189822 DOI: 10.1007/s00418-023-02258-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/06/2023] [Indexed: 01/09/2024]
Abstract
Despite the tremendous clinical successes recorded in the landscape of cancer therapy, tumor heterogeneity remains a formidable challenge to successful cancer treatment. In recent years, the emergence of high-throughput technologies has advanced our understanding of the variables influencing tumor heterogeneity beyond intrinsic tumor characteristics. Emerging knowledge shows that drivers of tumor heterogeneity are not only intrinsic to cancer cells but can also emanate from their microenvironment, which significantly favors tumor progression and impairs therapeutic response. Although much has been explored to understand the fundamentals of the influence of innate tumor factors on cancer diversity, the roles of the tumor microenvironment (TME) are often undervalued. It is therefore imperative that a clear understanding of the interactions between the TME and other tumor intrinsic factors underlying the plastic molecular behaviors of cancers be identified to develop patient-specific treatment strategies. This review highlights the roles of the TME as an emerging factor in tumor heterogeneity. More particularly, we discuss the role of the TME in the context of tumor heterogeneity and explore the cutting-edge diagnostic and therapeutic approaches that could be used to resolve this recurring clinical conundrum. We conclude by speculating on exciting research questions that can advance our understanding of tumor heterogeneity with the goal of developing customized therapeutic solutions.
Collapse
Affiliation(s)
- Sikiru O Imodoye
- Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
| | - Kamoru A Adedokun
- Department of Immunology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, 14263, USA
| | - Ibrahim O Bello
- Department of Oral Medicine and Diagnostic Sciences, College of Dentistry, King Saud University, Riyadh, Saudi Arabia.
- Department of Pathology, University of Helsinki, Haartmaninkatu 3, 00014, Helsinki, Finland.
| |
Collapse
|
12
|
Conner SJ, Guarin JR, Le TT, Fatherree JP, Kelley C, Payne SL, Parker SR, Bloomer H, Zhang C, Salhany K, McGinn RA, Henrich E, Yui A, Srinivasan D, Borges H, Oudin MJ. Cell morphology best predicts tumorigenicity and metastasis in vivo across multiple TNBC cell lines of different metastatic potential. Breast Cancer Res 2024; 26:43. [PMID: 38468326 PMCID: PMC10929179 DOI: 10.1186/s13058-024-01796-8] [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: 06/14/2023] [Accepted: 02/26/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Metastasis is the leading cause of death in breast cancer patients. For metastasis to occur, tumor cells must invade locally, intravasate, and colonize distant tissues and organs, all steps that require tumor cell migration. The majority of studies on invasion and metastasis rely on human breast cancer cell lines. While it is known that these cells have different properties and abilities for growth and metastasis, the in vitro morphological, proliferative, migratory, and invasive behavior of these cell lines and their correlation to in vivo behavior is poorly understood. Thus, we sought to classify each cell line as poorly or highly metastatic by characterizing tumor growth and metastasis in a murine model of six commonly used human triple-negative breast cancer xenografts, as well as determine which in vitro assays commonly used to study cell motility best predict in vivo metastasis. METHODS We evaluated the liver and lung metastasis of human TNBC cell lines MDA-MB-231, MDA-MB-468, BT549, Hs578T, BT20, and SUM159 in immunocompromised mice. We characterized each cell line's cell morphology, proliferation, and motility in 2D and 3D to determine the variation in these parameters between cell lines. RESULTS We identified MDA-MB-231, MDA-MB-468, and BT549 cells as highly tumorigenic and metastatic, Hs578T as poorly tumorigenic and metastatic, BT20 as intermediate tumorigenic with poor metastasis to the lungs but highly metastatic to the livers, and SUM159 as intermediate tumorigenic but poorly metastatic to the lungs and livers. We showed that metrics that characterize cell morphology are the most predictive of tumor growth and metastatic potential to the lungs and liver. Further, we found that no single in vitro motility assay in 2D or 3D significantly correlated with metastasis in vivo. CONCLUSIONS Our results provide an important resource for the TNBC research community, identifying the metastatic potential of 6 commonly used cell lines. Our findings also support the use of cell morphological analysis to investigate the metastatic potential and emphasize the need for multiple in vitro motility metrics using multiple cell lines to represent the heterogeneity of metastasis in vivo.
Collapse
Affiliation(s)
- Sydney J Conner
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Justinne R Guarin
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Thanh T Le
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Jackson P Fatherree
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Charlotte Kelley
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Samantha L Payne
- Department of Biomedical Sciences, University of Guelph, 50 Stone Rd E, Guelph, ON, Canada
| | - Savannah R Parker
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Hanan Bloomer
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Crystal Zhang
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Kenneth Salhany
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Rachel A McGinn
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Emily Henrich
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Anna Yui
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Deepti Srinivasan
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Hannah Borges
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA
| | - Madeleine J Oudin
- Department of Biomedical Engineering, Tufts University, 200 College Ave, Medford, MA, 02155, USA.
| |
Collapse
|
13
|
Tan RZ. Tumour Growth Mechanisms Determine Effectiveness of Adaptive Therapy in Glandular Tumours. Interdiscip Sci 2024; 16:73-90. [PMID: 37776475 DOI: 10.1007/s12539-023-00586-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 09/03/2023] [Accepted: 09/06/2023] [Indexed: 10/02/2023]
Abstract
In cancer treatment, adaptive therapy holds promise for delaying the onset of recurrence through regulating the competition between drug-sensitive and drug-resistant cells. Adaptive therapy has been studied in well-mixed models assuming free mixing of all cells and spatial models considering the interactions of single cells with their immediate adjacent cells. Both models do not reflect the spatial structure in glandular tumours where intra-gland cellular interaction is high, while inter-gland interaction is limited. Here, we use mathematical modelling to study the effects of adaptive therapy on glandular tumours that expand using either glandular fission or invasive growth. A two-dimensional, lattice-based model of sites containing sensitive and resistant cells within individual glands is developed to study the evolution of glandular tumour cells under continuous and adaptive therapies. We found that although both growth models benefit from adaptive therapy's ability to prevent recurrence, invasive growth benefits more from it than fission growth. This difference is due to the migration of daughter cells into neighboring glands that is absent in fission but present in invasive growth. The migration resulted in greater mixing of cells, enhancing competition induced by adaptive therapy. By varying the initial spatial spread and location of the resistant cells within the tumour, we found that modifying the conditions within the resistant cells containing glands affect both fission and invasive growth. However, modifying the conditions surrounding these glands affect invasive growth only. Our work reveals the interplay between growth mechanism and tumour topology in modulating the effectiveness of cancer therapy.
Collapse
Affiliation(s)
- Rui Zhen Tan
- Engineering Cluster, Singapore Institute of Technology, 10 Dover Drive, Singapore, 138683, Singapore.
| |
Collapse
|
14
|
Rachman T, Bartlett D, LaFramboise W, Wagner P, Schwartz R, Carja O. Modeling the Effect of Spatial Structure on Solid Tumor Evolution and Circulating Tumor DNA Composition. Cancers (Basel) 2024; 16:844. [PMID: 38473206 PMCID: PMC10930890 DOI: 10.3390/cancers16050844] [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: 01/18/2024] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 03/14/2024] Open
Abstract
Circulating tumor DNA (ctDNA) monitoring, while sufficiently advanced to reflect tumor evolution in real time and inform cancer diagnosis, treatment, and prognosis, mainly relies on DNA that originates from cell death via apoptosis or necrosis. In solid tumors, chemotherapy and immune infiltration can induce spatially variable rates of cell death, with the potential to bias and distort the clonal composition of ctDNA. Using a stochastic evolutionary model of boundary-driven growth, we study how elevated cell death on the edge of a tumor can simultaneously impact driver mutation accumulation and the representation of tumor clones and mutation detectability in ctDNA. We describe conditions in which invasive clones are over-represented in ctDNA, clonal diversity can appear elevated in the blood, and spatial bias in shedding can inflate subclonal variant allele frequencies (VAFs). Additionally, we find that tumors that are mostly quiescent can display similar biases but are far less detectable, and the extent of perceptible spatial bias strongly depends on sequence detection limits. Overall, we show that spatially structured shedding might cause liquid biopsies to provide highly biased profiles of tumor state. While this may enable more sensitive detection of expanding clones, it could also increase the risk of targeting a subclonal variant for treatment. Our results indicate that the effects and clinical consequences of spatially variable cell death on ctDNA composition present an important area for future work.
Collapse
Affiliation(s)
- Thomas Rachman
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Pittsburgh, PA 15213, USA
| | - David Bartlett
- Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh, PA 15224, USA
| | - William LaFramboise
- Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh, PA 15224, USA
| | - Patrick Wagner
- Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh, PA 15224, USA
| | - Russell Schwartz
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Oana Carja
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| |
Collapse
|
15
|
Islam M, Yang Y, Simmons AJ, Shah VM, Pavan MK, Xu Y, Tasneem N, Chen Z, Trinh LT, Molina P, Ramirez-Solano MA, Sadien I, Dou J, Chen K, Magnuson MA, Rathmell JC, Macara IG, Winton D, Liu Q, Zafar H, Kalhor R, Church GM, Shrubsole MJ, Coffey RJ, Lau KS. Temporal recording of mammalian development and precancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.18.572260. [PMID: 38187699 PMCID: PMC10769302 DOI: 10.1101/2023.12.18.572260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Key to understanding many biological phenomena is knowing the temporal ordering of cellular events, which often require continuous direct observations [1, 2]. An alternative solution involves the utilization of irreversible genetic changes, such as naturally occurring mutations, to create indelible markers that enables retrospective temporal ordering [3-8]. Using NSC-seq, a newly designed and validated multi-purpose single-cell CRISPR platform, we developed a molecular clock approach to record the timing of cellular events and clonality in vivo , while incorporating assigned cell state and lineage information. Using this approach, we uncovered precise timing of tissue-specific cell expansion during murine embryonic development and identified new intestinal epithelial progenitor states by their unique genetic histories. NSC-seq analysis of murine adenomas and single-cell multi-omic profiling of human precancers as part of the Human Tumor Atlas Network (HTAN), including 116 scRNA-seq datasets and clonal analysis of 418 human polyps, demonstrated the occurrence of polyancestral initiation in 15-30% of colonic precancers, revealing their origins from multiple normal founders. Thus, our multimodal framework augments existing single-cell analyses and lays the foundation for in vivo multimodal recording, enabling the tracking of lineage and temporal events during development and tumorigenesis.
Collapse
|
16
|
Rachman T, Bartlett D, Laframboise W, Wagner P, Schwartz R, Carja O. Modeling the effect of spatial structure on solid tumor evolution and ctDNA composition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.10.566658. [PMID: 37986965 PMCID: PMC10659436 DOI: 10.1101/2023.11.10.566658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Circulating tumor DNA (ctDNA) monitoring, while sufficiently advanced to reflect tumor evolution in real time and inform on cancer diagnosis, treatment, and prognosis, mainly relies on DNA that originates from cell death via apoptosis or necrosis. In solid tumors, chemotherapy and immune infiltration can induce spatially variable rates of cell death, with the potential to bias and distort the clonal composition of ctDNA. Using a stochastic evolutionary model of boundary-driven growth, we study how elevated cell death on the edge of a tumor can simultaneously impact driver mutation accumulation and the representation of tumor clones and mutation detectability in ctDNA. We describe conditions in which invasive clones end up over-represented in ctDNA, clonal diversity can appear elevated in the blood, and spatial bias in shedding can inflate subclonal variant allele frequencies (VAFs). Additionally, we find that tumors that are mostly quiescent can display similar biases, but are far less detectable, and the extent of perceptible spatial bias strongly depends on sequence detection limits. Overall, we show that spatially structured shedding might cause liquid biopsies to provide highly biased profiles of tumor state. While this may enable more sensitive detection of expanding clones, it could also increase the risk of targeting a subclonal variant for treatment. Our results indicate that the effects and clinical consequences of spatially variable cell death on ctDNA composition present an important area for future work.
Collapse
Affiliation(s)
- Thomas Rachman
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology
| | - David Bartlett
- Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh PA
| | | | - Patrick Wagner
- Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh PA
| | - Russell Schwartz
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Oana Carja
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| |
Collapse
|
17
|
Li H, Yang Z, Tu F, Deng L, Han Y, Fu X, Wang L, Gu D, Werner B, Huang W. Mutation divergence over space in tumour expansion. J R Soc Interface 2023; 20:20230542. [PMID: 37989227 PMCID: PMC10681009 DOI: 10.1098/rsif.2023.0542] [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: 09/16/2023] [Accepted: 10/30/2023] [Indexed: 11/23/2023] Open
Abstract
Mutation accumulation in tumour evolution is one major cause of intra-tumour heterogeneity (ITH), which often leads to drug resistance during treatment. Previous studies with multi-region sequencing have shown that mutation divergence among samples within the patient is common, and the importance of spatial sampling to obtain a complete picture in tumour measurements. However, quantitative comparisons of the relationship between mutation heterogeneity and tumour expansion modes, sampling distances as well as the sampling methods are still few. Here, we investigate how mutations diverge over space by varying the sampling distance and tumour expansion modes using individual-based simulations. We measure ITH by the Jaccard index between samples and quantify how ITH increases with sampling distance, the pattern of which holds in various sampling methods and sizes. We also compare the inferred mutation rates based on the distributions of variant allele frequencies under different tumour expansion modes and sampling sizes. In exponentially fast expanding tumours, a mutation rate can always be inferred for any sampling size. However, the accuracy compared with the true value decreases when the sampling size decreases, where small sampling sizes result in a high estimate of the mutation rate. In addition, such an inference becomes unreliable when the tumour expansion is slow, such as in surface growth.
Collapse
Affiliation(s)
- Haiyang Li
- Group of Theoretical Biology, The State Key Laboratory of Bio-control, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, People’s Republic of China
- Evolutionary Dynamics Group, Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Zixuan Yang
- Group of Theoretical Biology, The State Key Laboratory of Bio-control, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, People’s Republic of China
| | - Fengyu Tu
- Group of Theoretical Biology, The State Key Laboratory of Bio-control, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, People’s Republic of China
| | - Lijuan Deng
- Group of Theoretical Biology, The State Key Laboratory of Bio-control, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, People’s Republic of China
| | - Yuqing Han
- Group of Theoretical Biology, The State Key Laboratory of Bio-control, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, People’s Republic of China
| | - Xing Fu
- Group of Theoretical Biology, The State Key Laboratory of Bio-control, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, People’s Republic of China
| | - Long Wang
- Group of Theoretical Biology, The State Key Laboratory of Bio-control, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, People’s Republic of China
| | - Di Gu
- The first affiliated hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China
| | - Benjamin Werner
- Evolutionary Dynamics Group, Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Weini Huang
- Group of Theoretical Biology, The State Key Laboratory of Bio-control, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, People’s Republic of China
- School of Mathematical Sciences, Queen Mary University of London, London, UK
| |
Collapse
|
18
|
Tkadlec J, Kaveh K, Chatterjee K, Nowak MA. Evolutionary dynamics of mutants that modify population structure. J R Soc Interface 2023; 20:20230355. [PMID: 38016637 PMCID: PMC10684346 DOI: 10.1098/rsif.2023.0355] [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: 06/23/2023] [Accepted: 11/01/2023] [Indexed: 11/30/2023] Open
Abstract
Natural selection is usually studied between mutants that differ in reproductive rate, but are subject to the same population structure. Here we explore how natural selection acts on mutants that have the same reproductive rate, but different population structures. In our framework, population structure is given by a graph that specifies where offspring can disperse. The invading mutant disperses offspring on a different graph than the resident wild-type. We find that more densely connected dispersal graphs tend to increase the invader's fixation probability, but the exact relationship between structure and fixation probability is subtle. We present three main results. First, we prove that if both invader and resident are on complete dispersal graphs, then removing a single edge in the invader's dispersal graph reduces its fixation probability. Second, we show that for certain island models higher invader's connectivity increases its fixation probability, but the magnitude of the effect depends on the exact layout of the connections. Third, we show that for lattices the effect of different connectivity is comparable to that of different fitness: for large population size, the invader's fixation probability is either constant or exponentially small, depending on whether it is more or less connected than the resident.
Collapse
Affiliation(s)
- Josef Tkadlec
- Department of Mathematics, Harvard University, Cambridge, MA 02138, USA
- Computer Science Institute, Charles University, Prague, Czech Republic
| | - Kamran Kaveh
- Department of Applied Mathematics, University of Washington, Seattle, WA 98195, USA
| | - Krishnendu Chatterjee
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Martin A. Nowak
- Department of Mathematics, Harvard University, Cambridge, MA 02138, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| |
Collapse
|
19
|
Alamoudi E, Schälte Y, Müller R, Starruß J, Bundgaard N, Graw F, Brusch L, Hasenauer J. FitMultiCell: simulating and parameterizing computational models of multi-scale and multi-cellular processes. Bioinformatics 2023; 39:btad674. [PMID: 37947308 PMCID: PMC10666203 DOI: 10.1093/bioinformatics/btad674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 10/25/2023] [Accepted: 11/07/2023] [Indexed: 11/12/2023] Open
Abstract
MOTIVATION Biological tissues are dynamic and highly organized. Multi-scale models are helpful tools to analyse and understand the processes determining tissue dynamics. These models usually depend on parameters that need to be inferred from experimental data to achieve a quantitative understanding, to predict the response to perturbations, and to evaluate competing hypotheses. However, even advanced inference approaches such as approximate Bayesian computation (ABC) are difficult to apply due to the computational complexity of the simulation of multi-scale models. Thus, there is a need for a scalable pipeline for modeling, simulating, and parameterizing multi-scale models of multi-cellular processes. RESULTS Here, we present FitMultiCell, a computationally efficient and user-friendly open-source pipeline that can handle the full workflow of modeling, simulating, and parameterizing for multi-scale models of multi-cellular processes. The pipeline is modular and integrates the modeling and simulation tool Morpheus and the statistical inference tool pyABC. The easy integration of high-performance infrastructure allows to scale to computationally expensive problems. The introduction of a novel standard for the formulation of parameter inference problems for multi-scale models additionally ensures reproducibility and reusability. By applying the pipeline to multiple biological problems, we demonstrate its broad applicability, which will benefit in particular image-based systems biology. AVAILABILITY AND IMPLEMENTATION FitMultiCell is available open-source at https://gitlab.com/fitmulticell/fit.
Collapse
Affiliation(s)
- Emad Alamoudi
- Life and Medical Sciences Institute, University of Bonn, Bonn 53113, Germany
| | - Yannik Schälte
- Life and Medical Sciences Institute, University of Bonn, Bonn 53113, Germany
- Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg 85764, Germany
- Center for Mathematics, Chair of Mathematical Modeling of Biological Systems, Technische Universität München, Garching 85748, Germany
| | - Robert Müller
- Center of Information Services and High Performance Computing (ZIH), Technische Universität Dresden, Dresden 01062, Germany
| | - Jörn Starruß
- Center of Information Services and High Performance Computing (ZIH), Technische Universität Dresden, Dresden 01062, Germany
| | - Nils Bundgaard
- BioQuant—Center for Quantitative Biology, Heidelberg University, Heidelberg 69120, Germany
| | - Frederik Graw
- BioQuant—Center for Quantitative Biology, Heidelberg University, Heidelberg 69120, Germany
- Interdisciplinary Center for Scientific Computing, Heidelberg University, Heidelberg 69120, Germany
- Department of Medicine 5, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen 91054, Germany
| | - Lutz Brusch
- Center of Information Services and High Performance Computing (ZIH), Technische Universität Dresden, Dresden 01062, Germany
| | - Jan Hasenauer
- Life and Medical Sciences Institute, University of Bonn, Bonn 53113, Germany
- Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg 85764, Germany
- Center for Mathematics, Chair of Mathematical Modeling of Biological Systems, Technische Universität München, Garching 85748, Germany
| |
Collapse
|
20
|
Martínez-Calvo A, Trenado-Yuste C, Lee H, Gore J, Wingreen NS, Datta SS. Interfacial morphodynamics of proliferating microbial communities. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.23.563665. [PMID: 37961366 PMCID: PMC10634769 DOI: 10.1101/2023.10.23.563665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
In microbial communities, various cell types often coexist by occupying distinct spatial domains. What determines the shape of the interface between such domains-which in turn influences the interactions between cells and overall community function? Here, we address this question by developing a continuum model of a 2D spatially-structured microbial community with two distinct cell types. We find that, depending on the balance of the different cell proliferation rates and substrate friction coefficients, the interface between domains is either stable and smooth, or unstable and develops finger-like protrusions. We establish quantitative principles describing when these different interfacial behaviors arise, and find good agreement both with the results of previous experimental reports as well as new experiments performed here. Our work thus helps to provide a biophysical basis for understanding the interfacial morphodynamics of proliferating microbial communities, as well as a broader range of proliferating active systems.
Collapse
|
21
|
Schneider F, Kaczorowski A, Jurcic C, Kirchner M, Schwab C, Schütz V, Görtz M, Zschäbitz S, Jäger D, Stenzinger A, Hohenfellner M, Duensing S, Duensing A. Digital Spatial Profiling Identifies the Tumor Periphery as a Highly Active Biological Niche in Clear Cell Renal Cell Carcinoma. Cancers (Basel) 2023; 15:5050. [PMID: 37894418 PMCID: PMC10605891 DOI: 10.3390/cancers15205050] [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: 06/21/2023] [Revised: 10/03/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is characterized by a high degree of intratumoral heterogeneity (ITH). Besides genomic ITH, there is considerable functional ITH, which encompasses spatial niches with distinct proliferative and signaling activities. The full extent of functional spatial heterogeneity in ccRCC is incompletely understood. In the present study, a total of 17 ccRCC tissue specimens from different sites (primary tumor, n = 11; local recurrence, n = 1; distant metastasis, n = 5) were analyzed using digital spatial profiling (DSP) of protein expression. A total of 128 regions of interest from the tumor periphery and tumor center were analyzed for the expression of 46 proteins, comprising three major signaling pathways as well as immune cell markers. Results were correlated to clinico-pathological variables. The differential expression of granzyme B was validated using conventional immunohistochemistry and was correlated to the cancer-specific patient survival. We found that a total of 37 proteins were differentially expressed between the tumor periphery and tumor center. Thirty-five of the proteins were upregulated in the tumor periphery compared to the center. These included proteins involved in cell proliferation, MAPK and PI3K/AKT signaling, apoptosis regulation, epithelial-to-mesenchymal transition, as well as immune cell markers. Among the most significantly upregulated proteins in the tumor periphery was granzyme B. Granzyme B upregulation in the tumor periphery correlated with a significantly reduced cancer-specific patient survival. In conclusion, this study highlights the unique cellular contexture of the tumor periphery in ccRCC. The correlation between granzyme B upregulation in the tumor periphery and patient survival suggests local selection pressure for aggressive tumor growth and disease progression. Our results underscore the potential of spatial biology for biomarker discovery in ccRCC and cancer in general.
Collapse
Affiliation(s)
- Felix Schneider
- Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Im Neuenheimer Feld 517, D-69120 Heidelberg, Germany
| | - Adam Kaczorowski
- Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Im Neuenheimer Feld 517, D-69120 Heidelberg, Germany
| | - Christina Jurcic
- Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Im Neuenheimer Feld 517, D-69120 Heidelberg, Germany
| | - Martina Kirchner
- Institute of Pathology, University Hospital Heidelberg, Im Neuenheimer Feld 224, D-69120 Heidelberg, Germany
| | - Constantin Schwab
- Institute of Pathology, University Hospital Heidelberg, Im Neuenheimer Feld 224, D-69120 Heidelberg, Germany
| | - Viktoria Schütz
- Department of Urology, University Hospital Heidelberg, and National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 420, D-69120 Heidelberg, Germany
| | - Magdalena Görtz
- Department of Urology, University Hospital Heidelberg, and National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 420, D-69120 Heidelberg, Germany
| | - Stefanie Zschäbitz
- Department of Medical Oncology, University Hospital Heidelberg, and National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 460, D-69120 Heidelberg, Germany
| | - Dirk Jäger
- Department of Medical Oncology, University Hospital Heidelberg, and National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 460, D-69120 Heidelberg, Germany
| | - Albrecht Stenzinger
- Institute of Pathology, University Hospital Heidelberg, Im Neuenheimer Feld 224, D-69120 Heidelberg, Germany
| | - Markus Hohenfellner
- Department of Urology, University Hospital Heidelberg, and National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 420, D-69120 Heidelberg, Germany
| | - Stefan Duensing
- Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Im Neuenheimer Feld 517, D-69120 Heidelberg, Germany
- Department of Urology, University Hospital Heidelberg, and National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 420, D-69120 Heidelberg, Germany
| | - Anette Duensing
- Department of Urology, University Hospital Heidelberg, and National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 420, D-69120 Heidelberg, Germany
- Cancer Therapeutics Program, UPMC Hillman Cancer Center, 5117 Centre Avenue, Pittsburgh, PA 15213, USA
- Department of Pathology, University of Pittsburgh School of Medicine, 200 Lothrop Street, Pittsburgh, PA 15213, USA
- Precision Oncology of Urological Malignancies, Department of Urology, University Hospital Heidelberg, Im Neuenheimer Feld 517, D-69120 Heidelberg, Germany
| |
Collapse
|
22
|
Liao P, Huang Q, Zhang J, Su Y, Xiao R, Luo S, Wu Z, Zhu L, Li J, Hu Q. How single-cell techniques help us look into lung cancer heterogeneity and immunotherapy. Front Immunol 2023; 14:1238454. [PMID: 37671151 PMCID: PMC10475738 DOI: 10.3389/fimmu.2023.1238454] [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: 06/11/2023] [Accepted: 08/03/2023] [Indexed: 09/07/2023] Open
Abstract
Lung cancer patients tend to have strong intratumoral and intertumoral heterogeneity and complex tumor microenvironment, which are major contributors to the efficacy of and drug resistance to immunotherapy. From a new perspective, single-cell techniques offer an innovative way to look at the intricate cellular interactions between tumors and the immune system and help us gain insights into lung cancer and its response to immunotherapy. This article reviews the application of single-cell techniques in lung cancer, with focuses directed on the heterogeneity of lung cancer and the efficacy of immunotherapy. This review provides both theoretical and experimental information for the future development of immunotherapy and personalized treatment for the management of lung cancer.
Collapse
Affiliation(s)
- Pu Liao
- Department of Pathology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Pulmonary Diseases of Ministry of Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qi Huang
- Department of Respiratory and Critical Care Medicine, Hubei Province Clinical Research Center for Major Respiratory Diseases, National Health Commission (NHC) Key Laboratory of Pulmonary Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jiwei Zhang
- Department of Pathology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Pulmonary Diseases of Ministry of Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuan Su
- Key Laboratory of Pulmonary Diseases of Ministry of Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Respiratory and Critical Care Medicine, Hubei Province Clinical Research Center for Major Respiratory Diseases, National Health Commission (NHC) Key Laboratory of Pulmonary Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Rui Xiao
- Key Laboratory of Pulmonary Diseases of Ministry of Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine; Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shengquan Luo
- Key Laboratory of Pulmonary Diseases of Ministry of Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine; Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zengbao Wu
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Liping Zhu
- Key Laboratory of Pulmonary Diseases of Ministry of Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine; Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiansha Li
- Key Laboratory of Pulmonary Diseases of Ministry of Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Institute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qinghua Hu
- Key Laboratory of Pulmonary Diseases of Ministry of Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine; Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| |
Collapse
|
23
|
Shi X, Pang Q, Nian X, Jiang A, Shi H, Liu W, Gan X, Gao Y, Yang Y, Ji J, Tan X, Xiao C, Zhang W. Integrative transcriptome and proteome analyses of clear cell renal cell carcinoma develop a prognostic classifier associated with thrombus. Sci Rep 2023; 13:9778. [PMID: 37328520 PMCID: PMC10276054 DOI: 10.1038/s41598-023-36978-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 06/13/2023] [Indexed: 06/18/2023] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) with venous tumor thrombus (VTT) is associated with poor prognosis. Our integrative analyses of transcriptome and proteome reveal distinctive molecular features of ccRCC with VTT, and yield the development of a prognostic classifier to facilitate ccRCC molecular subtyping and treatment. The RNA sequencing and mass spectrometry were performed in normal-tumor-thrombus tissue triples of five ccRCC patients. Statistical analysis, GO and KEGG enrichment analysis, and protein-protein interaction network construction were used to interpret the transcriptomic and proteomic data. A six-gene-based classifier was developed to predict patients' survival using Cox regression, which was validated in an independent cohort. Transcriptomic analysis identified 1131 tumorigenesis-associated differentially expressed genes (DEGs) and 856 invasion-associated DEGs. Overexpression of transcription factor EGR2 in VTT indicated its important role in tumor invasion. Furthermore, proteomic analysis showed 597 tumorigenesis-associated differentially expressed proteins (DEPs) and 452 invasion-associated DEPs. The invasion-associated DEPs showed unique enrichment in DNA replication, lysine degradation, and PPAR signaling pathway. Integration of transcriptome and proteome reveals 142 tumorigenesis-associated proteins and 84 invasion-associated proteins displaying changes consistent with corresponding genes in transcriptomic profiling. Based on their different expression patterns among normal-tumor-thrombus triples, RAB25 and GGT5 were supposed to play a consistent role in both tumorigenesis and invasion processes, while SHMT2 and CADM4 might play the opposite roles in tumorigenesis and thrombus invasion. A prognostic classifier consisting of six DEGs (DEPTOR, DPEP1, NAT8, PLOD2, SLC7A5, SUSD2) performed satisfactorily in predicting survival of ccRCC patients (HR = 4.41, P < 0.001), which was further validated in an independent cohort of 40 cases (HR = 5.52, P = 0.026). Our study revealed the transcriptomic and proteomic profiles of ccRCC patients with VTT, and identified the distinctive molecular features associated with VTT. The six-gene-based prognostic classifier developed by integrative analyses may facilitate ccRCC molecular subtyping and treatment.
Collapse
Affiliation(s)
- Xiaolei Shi
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Qingyang Pang
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Xinwen Nian
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Aimin Jiang
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Haoqing Shi
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Wenqiang Liu
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Xinxin Gan
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Yisha Gao
- Department of Pathology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Yiren Yang
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Jin Ji
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Xiaojie Tan
- Department of Epidemiology, Naval Medical University, 800 Xiangyin Rd, Shanghai, 200433, China
| | - Chengwu Xiao
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China.
| | - Wei Zhang
- Department of Urology, Changhai Hospital, Naval Medical University, 168 Changhai Rd, Shanghai, 200433, China.
| |
Collapse
|
24
|
Conner S, Guarin JR, Le TT, Fatherree J, Kelley C, Payne S, Salhany K, McGinn R, Henrich E, Yui A, Parker S, Srinivasan D, Bloomer H, Borges H, Oudin MJ. Cell morphology best predicts tumorigenicity and metastasis in vivo across multiple TNBC cell lines of different metastatic potential. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.14.544969. [PMID: 37398306 PMCID: PMC10312673 DOI: 10.1101/2023.06.14.544969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Background Metastasis is the leading cause of death in breast cancer patients. For metastasis to occur, tumor cells must invade locally, intravasate, and colonize distant tissues and organs, all steps that require tumor cell migration. The majority of studies on invasion and metastasis rely on human breast cancer cell lines. While it is known that these cells have different properties and abilities for growth and metastasis, the in vitro morphological, proliferative, migratory, and invasive behavior of these cell lines and their correlation to in vivo behavior is poorly understood. Thus, we sought to classify each cell line as poorly or highly metastatic by characterizing tumor growth and metastasis in a murine model of six commonly used human triple-negative breast cancer xenografts, as well as determine which in vitro assays commonly used to study cell motility best predict in vivo metastasis. Methods We evaluated the liver and lung metastasis of human TNBC cell lines MDA-MB-231, MDA-MB-468, BT549, Hs578T, BT20, and SUM159 in immunocompromised mice. We characterized each cell line's cell morphology, proliferation, and motility in 2D and 3D to determine the variation in these parameters between cell lines. Results We identified MDA-MB-231, MDA-MB-468, and BT549 cells as highly tumorigenic and metastatic, Hs578T as poorly tumorigenic and metastatic, BT20 as intermediate tumorigenic with poor metastasis to the lungs but highly metastatic to the livers, and SUM159 as intermediate tumorigenic but poorly metastatic to the lungs and livers. We showed that metrics that characterize cell morphology are the most predictive of tumor growth and metastatic potential to the lungs and liver. Further, we found that no single in vitro motility assay in 2D or 3D significantly correlated with metastasis in vivo. Conclusions Our results provide an important resource for the TNBC research community, identifying the metastatic potential of 6 commonly used cell lines. Our findings also support the use of cell morphological analysis to investigate the metastatic potential and emphasize the need for multiple in vitro motility metrics using multiple cell lines to represent the heterogeneity of metastasis in vivo.
Collapse
Affiliation(s)
- Sydney Conner
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Justinne R. Guarin
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Thanh T. Le
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | | | - Charlotte Kelley
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Samantha Payne
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Ken Salhany
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Rachel McGinn
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Emily Henrich
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Anna Yui
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Savannah Parker
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Deepti Srinivasan
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Hanan Bloomer
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Hannah Borges
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| | - Madeleine J. Oudin
- Department of Biomedical Engineering, 200 College Avenue, Tufts University, Medford MA 02155, USA
| |
Collapse
|
25
|
Hallatschek O, Datta SS, Drescher K, Dunkel J, Elgeti J, Waclaw B, Wingreen NS. Proliferating active matter. NATURE REVIEWS. PHYSICS 2023; 5:1-13. [PMID: 37360681 PMCID: PMC10230499 DOI: 10.1038/s42254-023-00593-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 05/02/2023] [Indexed: 06/28/2023]
Abstract
The fascinating patterns of collective motion created by autonomously driven particles have fuelled active-matter research for over two decades. So far, theoretical active-matter research has often focused on systems with a fixed number of particles. This constraint imposes strict limitations on what behaviours can and cannot emerge. However, a hallmark of life is the breaking of local cell number conservation by replication and death. Birth and death processes must be taken into account, for example, to predict the growth and evolution of a microbial biofilm, the expansion of a tumour, or the development from a fertilized egg into an embryo and beyond. In this Perspective, we argue that unique features emerge in these systems because proliferation represents a distinct form of activity: not only do the proliferating entities consume and dissipate energy, they also inject biomass and degrees of freedom capable of further self-proliferation, leading to myriad dynamic scenarios. Despite this complexity, a growing number of studies document common collective phenomena in various proliferating soft-matter systems. This generality leads us to propose proliferation as another direction of active-matter physics, worthy of a dedicated search for new dynamical universality classes. Conceptual challenges abound, from identifying control parameters and understanding large fluctuations and nonlinear feedback mechanisms to exploring the dynamics and limits of information flow in self-replicating systems. We believe that, by extending the rich conceptual framework developed for conventional active matter to proliferating active matter, researchers can have a profound impact on quantitative biology and reveal fascinating emergent physics along the way.
Collapse
Affiliation(s)
- Oskar Hallatschek
- Departments of Physics and Integrative Biology, University of California, Berkeley, CA US
- Peter Debye Institute for Soft Matter Physics, Leipzig University, Leipzig, Germany
| | - Sujit S. Datta
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ USA
| | | | - Jörn Dunkel
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Jens Elgeti
- Theoretical Physics of Living Matter, Institute of Biological Information Processing, Forschungszentrum Jülich, Jülich, Germany
| | - Bartek Waclaw
- Dioscuri Centre for Physics and Chemistry of Bacteria, Institute of Physical Chemistry PAN, Warsaw, Poland
- School of Physics and Astronomy, The University of Edinburgh, JCMB, Edinburgh, UK
| | - Ned S. Wingreen
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ USA
- Department of Molecular Biology, Princeton University, Princeton, NJ USA
| |
Collapse
|
26
|
Yang J, Teng Y. Harnessing cancer stem cell-derived exosomes to improve cancer therapy. J Exp Clin Cancer Res 2023; 42:131. [PMID: 37217932 DOI: 10.1186/s13046-023-02717-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 05/18/2023] [Indexed: 05/24/2023] Open
Abstract
Cancer stem cells (CSCs) are the key "seeds" for tumor initiation and development, metastasis, and recurrence. Because of the function of CSCs in tumor development and progression, research in this field has intensified and CSCs are viewed as a new therapeutic target. Exosomes carrying a wide range of DNA, RNA, lipids, metabolites, and cytosolic and cell-surface proteins are released outside of the originating cells through the fusion of multivesicular endosomes or multivesicular bodies with the plasma membrane. It has become evident that CSC-derived exosomes play a significant role in almost all "hallmarks" of cancer. For example, exosomes from CSCs can maintain a steady state of self-renewal in the tumor microenvironment and regulate microenvironmental cells or distant cells to help cancer cells escape immune surveillance and induce immune tolerance. However, the function and therapeutic value of CSC-derived exosomes and the underlying molecular mechanisms are still largely undefined. To provide an overview of the possible role of CSC-derived exosomes and targeting strategies, we summarize relevant research progress, highlight the potential impact of detecting or targeting CSC-derived exosomes on cancer treatment, and discuss opportunities and challenges based on our experience and insights in this research area. A more thorough understanding of the characteristics and function of CSC-derived exosomes may open new avenues to the development of new clinical diagnostic/prognostic tools and therapies to prevent tumor resistance and relapse.
Collapse
Affiliation(s)
- Jianqiang Yang
- Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University School of Medicine, 201 Dowman Dr, Atlanta, GA, 30322, USA
| | - Yong Teng
- Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University School of Medicine, 201 Dowman Dr, Atlanta, GA, 30322, USA.
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, 30322, USA.
| |
Collapse
|
27
|
Traulsen A, Glynatsi NE. The future of theoretical evolutionary game theory. Philos Trans R Soc Lond B Biol Sci 2023; 378:20210508. [PMID: 36934760 PMCID: PMC10024985 DOI: 10.1098/rstb.2021.0508] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 12/06/2022] [Indexed: 03/21/2023] Open
Abstract
Evolutionary game theory is a truly interdisciplinary subject that goes well beyond the limits of biology. Mathematical minds get hooked up in simple models for evolution and often gradually move into other parts of evolutionary biology or ecology. Social scientists realize how much they can learn from evolutionary thinking and gradually transfer insight that was originally generated in biology. Computer scientists can use their algorithms to explore a new field where machines not only learn from the environment, but also from each other. The breadth of the field and the focus on a few very popular issues, such as cooperation, comes at a price: several insights are re-discovered in different fields under different labels with different heroes and modelling traditions. For example, reciprocity or spatial structure are treated differently. Will we continue to develop things in parallel? Or can we converge to a single set of ideas, a single tradition and eventually a single software repository? Or will these fields continue to cross-fertilize each other, learning from each other and engaging in a constructive exchange between fields? Ultimately, the popularity of evolutionary game theory rests not only on its explanatory power, but also on the intuitive character of its models. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.
Collapse
Affiliation(s)
- Arne Traulsen
- Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Nikoleta E. Glynatsi
- Max Planck Research Group: Dynamics of Social Behavior, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| |
Collapse
|
28
|
Salavaty A, Azadian E, Naik SH, Currie PD. Clonal selection parallels between normal and cancer tissues. Trends Genet 2023; 39:358-380. [PMID: 36842901 DOI: 10.1016/j.tig.2023.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 01/12/2023] [Accepted: 01/26/2023] [Indexed: 02/28/2023]
Abstract
Clonal selection and drift drive both normal tissue and cancer development. However, the biological mechanisms and environmental conditions underpinning these processes remain to be elucidated. Clonal selection models are centered in Darwinian evolutionary theory, where some clones with the fittest features are selected and populate the tissue or tumor. We suggest that different subclasses of stem cells, each of which is responsible for a distinct feature of the selection process, share common features between normal and cancer conditions. While active stem cells populate the tissue, dormant cells account for tissue replenishment/regeneration in both normal and cancerous tissues. We also discuss potential mechanisms that drive clonal drift, their interactions with clonal selection, and their similarities during normal and cancer tissue development.
Collapse
Affiliation(s)
- Adrian Salavaty
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC 3800, Australia; Systems Biology Institute Australia, Monash University, Clayton, VIC 3800, Australia.
| | - Esmaeel Azadian
- Immunology Division, Walter and Eliza Hall Institute, Parkville, VIC, Australia; Department of Medical Biology, University of Melbourne, Parkville, VIC, Australia; Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia
| | - Shalin H Naik
- Immunology Division, Walter and Eliza Hall Institute, Parkville, VIC, Australia; Department of Medical Biology, University of Melbourne, Parkville, VIC, Australia; Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia
| | - Peter D Currie
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC 3800, Australia; EMBL Australia, Monash University, Clayton, VIC 3800, Australia.
| |
Collapse
|
29
|
Hamis S, Somervuo P, Ågren JA, Tadele DS, Kesseli J, Scott JG, Nykter M, Gerlee P, Finkelshtein D, Ovaskainen O. Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems. J Math Biol 2023; 86:68. [PMID: 37017776 PMCID: PMC10076412 DOI: 10.1007/s00285-023-01903-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 01/13/2023] [Accepted: 03/09/2023] [Indexed: 04/06/2023]
Abstract
Theoretical and applied cancer studies that use individual-based models (IBMs) have been limited by the lack of a mathematical formulation that enables rigorous analysis of these models. However, spatial cumulant models (SCMs), which have arisen from theoretical ecology, describe population dynamics generated by a specific family of IBMs, namely spatio-temporal point processes (STPPs). SCMs are spatially resolved population models formulated by a system of differential equations that approximate the dynamics of two STPP-generated summary statistics: first-order spatial cumulants (densities), and second-order spatial cumulants (spatial covariances). We exemplify how SCMs can be used in mathematical oncology by modelling theoretical cancer cell populations comprising interacting growth factor-producing and non-producing cells. To formulate model equations, we use computational tools that enable the generation of STPPs, SCMs and mean-field population models (MFPMs) from user-defined model descriptions (Cornell et al. Nat Commun 10:4716, 2019). To calculate and compare STPP, SCM and MFPM-generated summary statistics, we develop an application-agnostic computational pipeline. Our results demonstrate that SCMs can capture STPP-generated population density dynamics, even when MFPMs fail to do so. From both MFPM and SCM equations, we derive treatment-induced death rates required to achieve non-growing cell populations. When testing these treatment strategies in STPP-generated cell populations, our results demonstrate that SCM-informed strategies outperform MFPM-informed strategies in terms of inhibiting population growths. We thus demonstrate that SCMs provide a new framework in which to study cell-cell interactions, and can be used to describe and perturb STPP-generated cell population dynamics. We, therefore, argue that SCMs can be used to increase IBMs' applicability in cancer research.
Collapse
Affiliation(s)
- Sara Hamis
- Tampere Institute for Advanced Study, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
- Department of Biological and Environmental Science, University of Jyväskylä, Jyväskylä, Finland.
| | - Panu Somervuo
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
| | - J Arvid Ågren
- Department of Evolutionary Biology, Uppsala University, Uppsala, Sweden
- Department of Translational Hematology and Oncology Research, Cleveland Clinic, Cleveland, OH, USA
| | - Dagim Shiferaw Tadele
- Department of Translational Hematology and Oncology Research, Cleveland Clinic, Cleveland, OH, USA
- Department for Medical Genetics, Oslo University Hospital, Ullevål, Oslo, Norway
| | - Juha Kesseli
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Centre, Tampere, Finland
| | - Jacob G Scott
- Department of Translational Hematology and Oncology Research, Cleveland Clinic, Cleveland, OH, USA
- Case Western Reserve School of Medicine, Cleveland, OH, USA
- Department of Radiation Oncology, Cleveland Clinic, Cleveland, OH, USA
| | - Matti Nykter
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Centre, Tampere, Finland
- Foundation for the Finnish Cancer Institute, Helsinki, Finland
| | - Philip Gerlee
- Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
- Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Dmitri Finkelshtein
- Department of Mathematics, Faculty of Science and Engineering, Swansea University, Swansea, UK
| | - Otso Ovaskainen
- Department of Biological and Environmental Science, University of Jyväskylä, Jyväskylä, Finland
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
- Department of Biology, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim, Norway
| |
Collapse
|
30
|
Lewinsohn MA, Bedford T, Müller NF, Feder AF. State-dependent evolutionary models reveal modes of solid tumour growth. Nat Ecol Evol 2023; 7:581-596. [PMID: 36894662 PMCID: PMC10089931 DOI: 10.1038/s41559-023-02000-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 01/26/2023] [Indexed: 03/11/2023]
Abstract
Spatial properties of tumour growth have profound implications for cancer progression, therapeutic resistance and metastasis. Yet, how spatial position governs tumour cell division remains difficult to evaluate in clinical tumours. Here, we demonstrate that faster division on the tumour periphery leaves characteristic genetic patterns, which become evident when a phylogenetic tree is reconstructed from spatially sampled cells. Namely, rapidly dividing peripheral lineages branch more extensively and acquire more mutations than slower-dividing centre lineages. We develop a Bayesian state-dependent evolutionary phylodynamic model (SDevo) that quantifies these patterns to infer the differential division rates between peripheral and central cells. We demonstrate that this approach accurately infers spatially varying birth rates of simulated tumours across a range of growth conditions and sampling strategies. We then show that SDevo outperforms state-of-the-art, non-cancer multi-state phylodynamic methods that ignore differential sequence evolution. Finally, we apply SDevo to single-time-point, multi-region sequencing data from clinical hepatocellular carcinomas and find evidence of a three- to six-times-higher division rate on the tumour edge. With the increasing availability of high-resolution, multi-region sequencing, we anticipate that SDevo will be useful in interrogating spatial growth restrictions and could be extended to model non-spatial factors that influence tumour progression.
Collapse
Affiliation(s)
- Maya A Lewinsohn
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
| | - Trevor Bedford
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Nicola F Müller
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
| | - Alison F Feder
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
| |
Collapse
|
31
|
Schwarz S, Nientiedt C, Prigge ES, Kaczorowski A, Geisler C, Porcel CL, von Knebel Doeberitz M, Hohenfellner M, Duensing S. Senescent Tumor Cells Are Frequently Present at the Invasion Front: Implications for Improving Disease Control in Patients with Locally Advanced Prostate Cancer. Pathobiology 2023; 90:312-321. [PMID: 37004506 PMCID: PMC10614482 DOI: 10.1159/000530430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 03/22/2023] [Indexed: 04/03/2023] Open
Abstract
INTRODUCTION Local tumor invasion is a critical factor for the outcome of men with prostate cancer. In particular, seminal vesicle invasion (SVI) has been reported to be associated with a more unfavorable prognosis. A better understanding of the functional state of invading prostate cancer cells is crucial to develop novel therapeutic strategies for patients with locally advanced disease. METHODS The prognostic impact of local tumor progression was ascertained in over 1,000 men with prostate cancer. Prostate cancer specimens were stained by double-immunohistochemistry for the proliferation marker Ki-67 and the senescence marker p16INK4A. The migratory properties of senescent prostate cancer cells were analyzed in vitro using a wound healing assay and immunofluorescence microscopy for p16INK4A. RESULTS We confirm the notion that patients with SVI have a more unfavorable prognosis than patients with extraprostatic extension alone. Surprisingly, we found that the tumor invasion front frequently harbors p16INK4A-positive and Ki-67-negative, i.e., senescent, tumor cells. While the intraprostatic tumor periphery was a hotspot for both proliferation and expression of p16INK4A, the area of SVI showed less proliferative activity but was at the same time a hotspot of cells with increased nuclear p16INK4A expression. Senescence was associated with an accelerated migration of prostate cancer cells in vitro. CONCLUSION This proof-of-concept study shows that invading prostate cancer cells frequently show signs of cellular senescence. This finding may open new avenues for neoadjuvant and adjuvant treatment concepts in men with locally advanced prostate cancer.
Collapse
Affiliation(s)
- Sebastian Schwarz
- Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany
| | - Cathleen Nientiedt
- Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany
- Department of Medical Oncology, University Hospital Heidelberg and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Elena-Sophie Prigge
- Department of Applied Tumor Biology, Institute of Pathology, University Hospital Heidelberg and Clinical Cooperation Unit Applied Tumor Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Adam Kaczorowski
- Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany
| | - Christine Geisler
- Department of Urology, University Hospital Heidelberg, National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | - Carlota Lucena Porcel
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
- Tissue Bank of the National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Magnus von Knebel Doeberitz
- Department of Applied Tumor Biology, Institute of Pathology, University Hospital Heidelberg and Clinical Cooperation Unit Applied Tumor Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Markus Hohenfellner
- Department of Urology, University Hospital Heidelberg, National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | - Stefan Duensing
- Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany
- Department of Urology, University Hospital Heidelberg, National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| |
Collapse
|
32
|
Aberrant HMGA2 Expression Sustains Genome Instability That Promotes Metastasis and Therapeutic Resistance in Colorectal Cancer. Cancers (Basel) 2023; 15:cancers15061735. [PMID: 36980621 PMCID: PMC10046046 DOI: 10.3390/cancers15061735] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 03/06/2023] [Accepted: 03/11/2023] [Indexed: 03/16/2023] Open
Abstract
Colorectal cancer (CRC) is one of the most lethal cancers worldwide, accounting for nearly ~10% of all cancer diagnoses and deaths. Current therapeutic approaches have considerably increased survival for patients diagnosed at early stages; however, ~20% of CRC patients are diagnosed with late-stage, metastatic CRC, where 5-year survival rates drop to 6–13% and treatment options are limited. Genome instability is an enabling hallmark of cancer that confers increased acquisition of genetic alterations, mutations, copy number variations and chromosomal rearrangements. In that regard, research has shown a clear association between genome instability and CRC, as the accumulation of aberrations in cancer-related genes provides subpopulations of cells with several advantages, such as increased proliferation rates, metastatic potential and therapeutic resistance. Although numerous genes have been associated with CRC, few have been validated as predictive biomarkers of metastasis or therapeutic resistance. A growing body of evidence suggests a member of the High-Mobility Group A (HMGA) gene family, HMGA2, is a potential biomarker of metastatic spread and therapeutic resistance. HMGA2 is expressed in embryonic tissues and is frequently upregulated in aggressively growing cancers, including CRC. As an architectural, non-histone chromatin binding factor, it initiates chromatin decompaction to facilitate transcriptional regulation. HMGA2 maintains the capacity for stem cell renewal in embryonic and cancer tissues and is a known promoter of epithelial-to-mesenchymal transition in tumor cells. This review will focus on the known molecular mechanisms by which HMGA2 exerts genome protective functions that contribute to cancer cell survival and chemoresistance in CRC.
Collapse
|
33
|
Streck A, Kaufmann TL, Schwarz RF. SMITH: spatially constrained stochastic model for simulation of intra-tumour heterogeneity. Bioinformatics 2023; 39:7056642. [PMID: 36825830 PMCID: PMC10010604 DOI: 10.1093/bioinformatics/btad102] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 02/10/2023] [Accepted: 02/23/2023] [Indexed: 02/25/2023] Open
Abstract
MOTIVATION Simulations of cancer evolution are highly useful to study the effects of selection and mutation rates on cellular fitness. However, most methods are either lattice-based and cannot simulate realistically sized tumours, or they omit spatial constraints and lack the clonal dynamics of real-world tumours. RESULTS Stochastic model of intra-tumour heterogeneity (SMITH) is an efficient and explainable model of cancer evolution that combines a branching process with a new confinement mechanism limiting clonal growth based on the size of the individual clones as well as the overall tumour population. We demonstrate how confinement is sufficient to induce the rich clonal dynamics observed in spatial models and cancer samples across tumour types, while allowing for a clear geometric interpretation and simulation of 1 billion cells within a few minutes on a desktop PC. AVAILABILITY AND IMPLEMENTATION SMITH is implemented in C# and freely available at https://bitbucket.org/schwarzlab/smith. For visualizations, we provide the accompanying Python package PyFish at https://bitbucket.org/schwarzlab/pyfish. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Adam Streck
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany.,Institute for Computational Cancer Biology (ICCB), Center for Integrated Oncology (CIO), Cancer Research Center Cologne Essen (CCCE), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Tom L Kaufmann
- BIFOLD-Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.,Institute for Computational Cancer Biology (ICCB), Center for Integrated Oncology (CIO), Cancer Research Center Cologne Essen (CCCE), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Roland F Schwarz
- Institute for Computational Cancer Biology (ICCB), Center for Integrated Oncology (CIO), Cancer Research Center Cologne Essen (CCCE), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,BIFOLD-Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.,Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| |
Collapse
|
34
|
Haughey MJ, Bassolas A, Sousa S, Baker AM, Graham TA, Nicosia V, Huang W. First passage time analysis of spatial mutation patterns reveals sub-clonal evolutionary dynamics in colorectal cancer. PLoS Comput Biol 2023; 19:e1010952. [PMID: 36913406 PMCID: PMC10035892 DOI: 10.1371/journal.pcbi.1010952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 03/23/2023] [Accepted: 02/14/2023] [Indexed: 03/14/2023] Open
Abstract
The signature of early cancer dynamics on the spatial arrangement of tumour cells is poorly understood, and yet could encode information about how sub-clones grew within the expanding tumour. Novel methods of quantifying spatial tumour data at the cellular scale are required to link evolutionary dynamics to the resulting spatial architecture of the tumour. Here, we propose a framework using first passage times of random walks to quantify the complex spatial patterns of tumour cell population mixing. First, using a simple model of cell mixing we demonstrate how first passage time statistics can distinguish between different pattern structures. We then apply our method to simulated patterns of mutated and non-mutated tumour cell population mixing, generated using an agent-based model of expanding tumours, to explore how first passage times reflect mutant cell replicative advantage, time of emergence and strength of cell pushing. Finally, we explore applications to experimentally measured human colorectal cancer, and estimate parameters of early sub-clonal dynamics using our spatial computational model. We infer a wide range of sub-clonal dynamics, with mutant cell division rates varying between 1 and 4 times the rate of non-mutated cells across our sample set. Some mutated sub-clones emerged after as few as 100 non-mutant cell divisions, and others only after 50,000 divisions. The majority were consistent with boundary driven growth or short-range cell pushing. By analysing multiple sub-sampled regions in a small number of samples, we explore how the distribution of inferred dynamics could inform about the initial mutational event. Our results demonstrate the efficacy of first passage time analysis as a new methodology in spatial analysis of solid tumour tissue, and suggest that patterns of sub-clonal mixing can provide insights into early cancer dynamics.
Collapse
Affiliation(s)
- Magnus J. Haughey
- School of Mathematical Sciences, Queen Mary University of London, London, United Kingdom
| | - Aleix Bassolas
- School of Mathematical Sciences, Queen Mary University of London, London, United Kingdom
| | - Sandro Sousa
- School of Mathematical Sciences, Queen Mary University of London, London, United Kingdom
| | - Ann-Marie Baker
- Centre for Evolution and Cancer, Institute of Cancer Research, London, United Kingdom
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Trevor A. Graham
- Centre for Evolution and Cancer, Institute of Cancer Research, London, United Kingdom
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Vincenzo Nicosia
- School of Mathematical Sciences, Queen Mary University of London, London, United Kingdom
| | - Weini Huang
- School of Mathematical Sciences, Queen Mary University of London, London, United Kingdom
| |
Collapse
|
35
|
Wu B, Shi X, Jiang M, Liu H. Cross-talk between cancer stem cells and immune cells: potential therapeutic targets in the tumor immune microenvironment. Mol Cancer 2023; 22:38. [PMID: 36810098 PMCID: PMC9942413 DOI: 10.1186/s12943-023-01748-4] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 02/15/2023] [Indexed: 02/24/2023] Open
Abstract
Ongoing research has revealed that the existence of cancer stem cells (CSCs) is one of the biggest obstacles in the current cancer therapy. CSCs make an influential function in tumor progression, recurrence and chemoresistance due to their typical stemness characteristics. CSCs are preferentially distributed in niches, and those niche sites exhibit characteristics typical of the tumor microenvironment (TME). The complex interactions between CSCs and TME illustrate these synergistic effects. The phenotypic heterogeneity within CSCs and the spatial interactions with the surrounding tumor microenvironment led to increased therapeutic challenges. CSCs interact with immune cells to protect themselves against immune clearance by exploiting the immunosuppressive function of multiple immune checkpoint molecules. CSCs also can protect themselves against immune surveillance by excreting extracellular vesicles (EVs), growth factors, metabolites and cytokines into the TME, thereby modulating the composition of the TME. Therefore, these interactions are also being considered for the therapeutic development of anti-tumor agents. We discuss here the immune molecular mechanisms of CSCs and comprehensively review the interplay between CSCs and the immune system. Thus, studies on this topic seem to provide novel ideas for reinvigorating therapeutic approaches to cancer.
Collapse
Affiliation(s)
- Bo Wu
- grid.459742.90000 0004 1798 5889Department of General Surgery, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, 110042 China
| | - Xiang Shi
- grid.459742.90000 0004 1798 5889Department of Thoracic Surgery, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, 110042 China
| | - Meixi Jiang
- grid.412644.10000 0004 5909 0696Department of Neurology, The Fourth Affiliated Hospital, China Medical University, Shenyang, 110032 China
| | - Hongxu Liu
- Department of Thoracic Surgery, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, 110042, China.
| |
Collapse
|
36
|
Unraveling the Impact of Intratumoral Heterogeneity on EGFR Tyrosine Kinase Inhibitor Resistance in EGFR-Mutated NSCLC. Int J Mol Sci 2023; 24:ijms24044126. [PMID: 36835536 PMCID: PMC9964908 DOI: 10.3390/ijms24044126] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 02/14/2023] [Accepted: 02/17/2023] [Indexed: 02/22/2023] Open
Abstract
The advent of tyrosine kinase inhibitors (TKIs) for treating epidermal growth factor receptor (EGFR)-mutated non-small-cell lung cancer (NSCLC) has been a game changer in lung cancer therapy. However, patients often develop resistance to the drugs within a few years. Despite numerous studies that have explored resistance mechanisms, particularly in regards to collateral signal pathway activation, the underlying biology of resistance remains largely unknown. This review focuses on the resistance mechanisms of EGFR-mutated NSCLC from the standpoint of intratumoral heterogeneity, as the biological mechanisms behind resistance are diverse and largely unclear. There exist various subclonal tumor populations in an individual tumor. For lung cancer patients, drug-tolerant persister (DTP) cell populations may have a pivotal role in accelerating the evolution of tumor resistance to treatment through neutral selection. Cancer cells undergo various changes to adapt to the new tumor microenvironment caused by drug exposure. DTP cells may play a crucial role in this adaptation and may be fundamental in mechanisms of resistance. Intratumoral heterogeneity may also be precipitated by DNA gains and losses through chromosomal instability, and the role of extrachromosomal DNA (ecDNA) may play an important role. Significantly, ecDNA can increase oncogene copy number alterations and enhance intratumoral heterogeneity more effectively than chromosomal instability. Additionally, advances in comprehensive genomic profiling have given us insights into various mutations and concurrent genetic alterations other than EGFR mutations, inducing primary resistance in the context of tumor heterogeneity. Understanding the mechanisms of resistance is clinically crucial since these molecular interlayers in cancer-resistance mechanisms may help to devise novel and individualized anticancer therapeutic approaches.
Collapse
|
37
|
Stoffel EM, Brand RE, Goggins M. Pancreatic Cancer: Changing Epidemiology and New Approaches to Risk Assessment, Early Detection, and Prevention. Gastroenterology 2023; 164:752-765. [PMID: 36804602 DOI: 10.1053/j.gastro.2023.02.012] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/10/2023] [Accepted: 02/11/2023] [Indexed: 02/23/2023]
Abstract
Pancreatic cancer usually results in poor survival with limited options for treatment, as most affected individuals present with advanced disease. Early detection of preinvasive pancreatic neoplasia and identifying molecular therapeutic targets provide opportunities for extending survival. Although screening for pancreatic cancer is currently not recommended for the general population, emerging evidence indicates that pancreatic surveillance can improve outcomes for individuals in certain high-risk groups. Changes in the epidemiology of pancreatic cancer, experience from pancreatic surveillance, and discovery of novel biomarkers provide a roadmap for new strategies for pancreatic cancer risk assessment, early detection, and prevention.
Collapse
Affiliation(s)
- Elena M Stoffel
- Division of Gastroenterology, University of Michigan Medical School, Ann Arbor, Michigan.
| | - Randall E Brand
- Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Michael Goggins
- Departments of Medicine and Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, Maryland
| |
Collapse
|
38
|
Yamamoto A, Doak AE, Cheung KJ. Orchestration of Collective Migration and Metastasis by Tumor Cell Clusters. ANNUAL REVIEW OF PATHOLOGY 2023; 18:231-256. [PMID: 36207009 DOI: 10.1146/annurev-pathmechdis-031521-023557] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Metastatic dissemination has lethal consequences for cancer patients. Accruing evidence supports the hypothesis that tumor cells can migrate and metastasize as clusters of cells while maintaining contacts with one another. Collective metastasis enables tumor cells to colonize secondary sites more efficiently, resist cell death, and evade the immune system. On the other hand, tumor cell clusters face unique challenges for dissemination particularly during systemic dissemination. Here, we review recent progress toward understanding how tumor cell clusters overcome these disadvantages as well as mechanisms they utilize to gain advantages throughout the metastatic process. We consider useful models for studying collective metastasis and reflect on how the study of collective metastasis suggests new opportunities for eradicating and preventing metastatic disease.
Collapse
Affiliation(s)
- Ami Yamamoto
- Translational Research Program, Public Health Sciences and Human Biology Divisions, Fred Hutchinson Cancer Center, Seattle, Washington, USA; , , .,Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, Washington, USA
| | - Andrea E Doak
- Translational Research Program, Public Health Sciences and Human Biology Divisions, Fred Hutchinson Cancer Center, Seattle, Washington, USA; , , .,Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, Washington, USA
| | - Kevin J Cheung
- Translational Research Program, Public Health Sciences and Human Biology Divisions, Fred Hutchinson Cancer Center, Seattle, Washington, USA; , ,
| |
Collapse
|
39
|
Chu J, Li Y, He M, Zhang H, Yang L, Yang M, Liu J, Cui C, Hong L, Hu X, Zhou L, Li T, Li C, Fan H, Jiang G, Lang T. Zinc finger and SCAN domain containing 1, ZSCAN1, is a novel stemness-related tumor suppressor and transcriptional repressor in breast cancer targeting TAZ. Front Oncol 2023; 13:1041688. [PMID: 36923432 PMCID: PMC10009259 DOI: 10.3389/fonc.2023.1041688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Accepted: 01/30/2023] [Indexed: 03/02/2023] Open
Abstract
Introduction Cancer stem cells (CSCs) targeted therapy holds the potential for improving cancer management; identification of stemness-related genes in CSCs is necessary for its development. Methods The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets were used for survival analysis. ZSCAN1 correlated genes was identified by Spearman correlation analysis. Breast cancer stem-like cells (BCSLCs) were isolated by sorting CD44+CD24- cells from suspension cultured breast cancer (BC) spheroids. The sphere-forming capacity and sphere- and tumor-initiating capacities were determined by sphere formation and limiting dilution assays. The relative gene expression was determined by qRT-PCR, western blot. Lentivirus system was used for gene manipulation. Nuclear run-on assay was employed to examine the levels of nascent mRNAs. DNA pull-down and Chromatin immunoprecipitation (ChIP) assays were used for determining the interaction between protein and target DNA fragments. Luciferase reporter assay was used for evaluating the activity of the promoter. Results and discussion ZSCAN1 is aberrantly suppressed in BC, and this suppression indicates a bad prognosis. Ectopic expression of ZSCAN1 inhibited the proliferation, clonogenicity, and tumorigenicity of BC cells. ZSCAN1-overexpressing BCSLCs exhibited weakened stemness properties. Normal human mammary epithelial (HMLE) cells with ZSCAN1 depletion exhibited enhanced stemness properties. Mechanistic studies showed that ZSCAN1 directly binds to -951 ~ -925bp region of WWTR1 (encodes TAZ) promoter, inhibits WWTR1 transcription, thereby inhibiting the stemness of BCSCs. Our work thus revealed ZSCAN1 as a novel stemness-related tumor suppressor and transcriptional repressor in BC.
Collapse
Affiliation(s)
- Jian Chu
- Department of Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Yunzhe Li
- College of Bioengineering, Chongqing University, Chongqing, China
| | - Misi He
- Department of Gynecologic Oncology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Hui Zhang
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Lingling Yang
- School of Medicine, Chongqing University, Chongqing, China
| | - Muyao Yang
- College of Bioengineering, Chongqing University, Chongqing, China
| | - Jingshu Liu
- Obstetrics and Gynecology Department, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Chenxi Cui
- School of Medicine, Chongqing University, Chongqing, China
| | - Liquan Hong
- Department of Clinical Laboratory, Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Xingchi Hu
- Department of General Surgery, Yancheng City No.1 People's Hospital, Yancheng, Jiangsu, China
| | - Lei Zhou
- School of Optometry, Department of Applied Biology and Chemical Technology, Research Centre for SHARP Vision (RCSV), The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China.,Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Hong Kong, Hong Kong SAR, China
| | - Tangya Li
- Department of General Surgery, Yancheng City No.1 People's Hospital, Yancheng, Jiangsu, China
| | - Changchun Li
- Department of General Surgery, Yancheng City No.1 People's Hospital, Yancheng, Jiangsu, China
| | - Huiwen Fan
- Department of General Surgery, Yancheng City No.1 People's Hospital, Yancheng, Jiangsu, China
| | - Guoqin Jiang
- Department of Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Tingyuan Lang
- Department of Gynecologic Oncology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China.,Reproductive Medicine Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| |
Collapse
|
40
|
Stochastic Fluctuations Drive Non-genetic Evolution of Proliferation in Clonal Cancer Cell Populations. Bull Math Biol 2022; 85:8. [PMID: 36562835 DOI: 10.1007/s11538-022-01113-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 11/30/2022] [Indexed: 12/24/2022]
Abstract
Evolutionary dynamics allows us to understand many changes happening in a broad variety of biological systems, ranging from individuals to complete ecosystems. It is also behind a number of remarkable organizational changes that happen during the natural history of cancers. These reflect tumour heterogeneity, which is present at all cellular levels, including the genome, proteome and phenome, shaping its development and interrelation with its environment. An intriguing observation in different cohorts of oncological patients is that tumours exhibit an increased proliferation as the disease progresses, while the timescales involved are apparently too short for the fixation of sufficient driver mutations to promote explosive growth. Here, we discuss how phenotypic plasticity, emerging from a single genotype, may play a key role and provide a ground for a continuous acceleration of the proliferation rate of clonal populations with time. We address this question by combining the analysis of real-time growth of non-small-cell lung carcinoma cells (N-H460) together with stochastic and deterministic mathematical models that capture proliferation trait heterogeneity in clonal populations to elucidate the contribution of phenotypic transitions on tumour growth dynamics.
Collapse
|
41
|
Evolutionary rescue of resistant mutants is governed by a balance between radial expansion and selection in compact populations. Nat Commun 2022; 13:7916. [PMID: 36564390 PMCID: PMC9789051 DOI: 10.1038/s41467-022-35484-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 12/06/2022] [Indexed: 12/24/2022] Open
Abstract
Mutation-mediated treatment resistance is one of the primary challenges for modern antibiotic and anti-cancer therapy. Yet, many resistance mutations have a substantial fitness cost and are subject to purifying selection. How emerging resistant lineages may escape purifying selection via subsequent compensatory mutations is still unclear due to the difficulty of tracking such evolutionary rescue dynamics in space and time. Here, we introduce a system of fluorescence-coupled synthetic mutations to show that the probability of evolutionary rescue, and the resulting long-term persistence of drug resistant mutant lineages, is dramatically increased in dense microbial populations. By tracking the entire evolutionary trajectory of thousands of resistant lineages in expanding yeast colonies we uncover an underlying quasi-stable equilibrium between the opposing forces of radial expansion and natural selection, a phenomenon we term inflation-selection balance. Tailored computational models and agent-based simulations corroborate the fundamental nature of the observed effects and demonstrate the potential impact on drug resistance evolution in cancer. The described phenomena should be considered when predicting multi-step evolutionary dynamics in any mechanically compact cellular population, including pathogenic microbial biofilms and solid tumors. The insights gained will be especially valuable for the quantitative understanding of response to treatment, including emerging evolution-based therapy strategies.
Collapse
|
42
|
Seferbekova Z, Lomakin A, Yates LR, Gerstung M. Spatial biology of cancer evolution. Nat Rev Genet 2022; 24:295-313. [PMID: 36494509 DOI: 10.1038/s41576-022-00553-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/04/2022] [Indexed: 12/13/2022]
Abstract
The natural history of cancers can be understood through the lens of evolution given that the driving forces of cancer development are mutation and selection of fitter clones. Cancer growth and progression are spatial processes that involve the breakdown of normal tissue organization, invasion and metastasis. For these reasons, spatial patterns are an integral part of histological tumour grading and staging as they measure the progression from normal to malignant disease. Furthermore, tumour cells are part of an ecosystem of tumour cells and their surrounding tumour microenvironment. A range of new spatial genomic, transcriptomic and proteomic technologies offers new avenues for the study of cancer evolution with great molecular and spatial detail. These methods enable precise characterizations of the tumour microenvironment, cellular interactions therein and micro-anatomical structures. In conjunction with spatial genomics, it emerges that tumours and microenvironments co-evolve, which helps explain observable patterns of heterogeneity and offers new routes for therapeutic interventions.
Collapse
|
43
|
Househam J, Heide T, Cresswell GD, Spiteri I, Kimberley C, Zapata L, Lynn C, James C, Mossner M, Fernandez-Mateos J, Vinceti A, Baker AM, Gabbutt C, Berner A, Schmidt M, Chen B, Lakatos E, Gunasri V, Nichol D, Costa H, Mitchinson M, Ramazzotti D, Werner B, Iorio F, Jansen M, Caravagna G, Barnes CP, Shibata D, Bridgewater J, Rodriguez-Justo M, Magnani L, Sottoriva A, Graham TA. Phenotypic plasticity and genetic control in colorectal cancer evolution. Nature 2022; 611:744-753. [PMID: 36289336 PMCID: PMC9684078 DOI: 10.1038/s41586-022-05311-x] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 09/01/2022] [Indexed: 12/12/2022]
Abstract
Genetic and epigenetic variation, together with transcriptional plasticity, contribute to intratumour heterogeneity1. The interplay of these biological processes and their respective contributions to tumour evolution remain unknown. Here we show that intratumour genetic ancestry only infrequently affects gene expression traits and subclonal evolution in colorectal cancer (CRC). Using spatially resolved paired whole-genome and transcriptome sequencing, we find that the majority of intratumour variation in gene expression is not strongly heritable but rather 'plastic'. Somatic expression quantitative trait loci analysis identified a number of putative genetic controls of expression by cis-acting coding and non-coding mutations, the majority of which were clonal within a tumour, alongside frequent structural alterations. Consistently, computational inference on the spatial patterning of tumour phylogenies finds that a considerable proportion of CRCs did not show evidence of subclonal selection, with only a subset of putative genetic drivers associated with subclone expansions. Spatial intermixing of clones is common, with some tumours growing exponentially and others only at the periphery. Together, our data suggest that most genetic intratumour variation in CRC has no major phenotypic consequence and that transcriptional plasticity is, instead, widespread within a tumour.
Collapse
Affiliation(s)
- Jacob Househam
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Timon Heide
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
- Computational Biology Research Centre, Human Technopole, Milan, Italy
| | - George D Cresswell
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Inmaculada Spiteri
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Chris Kimberley
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Luis Zapata
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Claire Lynn
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Chela James
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Maximilian Mossner
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | | | | | - Ann-Marie Baker
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Calum Gabbutt
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Alison Berner
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Melissa Schmidt
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Bingjie Chen
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Eszter Lakatos
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Vinaya Gunasri
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Daniel Nichol
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Helena Costa
- UCL Cancer Institute, University College London, London, UK
| | - Miriam Mitchinson
- Histopathology Department, University College London Hospitals NHS Foundation Trust, London, UK
| | - Daniele Ramazzotti
- Department of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy
| | - Benjamin Werner
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Francesco Iorio
- Computational Biology Research Centre, Human Technopole, Milan, Italy
| | - Marnix Jansen
- UCL Cancer Institute, University College London, London, UK
| | - Giulio Caravagna
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
- Department of Mathematics and Geosciences, University of Trieste, Trieste, Italy
| | - Chris P Barnes
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Darryl Shibata
- Department of Pathology, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | | | | | - Luca Magnani
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Andrea Sottoriva
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
- Computational Biology Research Centre, Human Technopole, Milan, Italy.
| | - Trevor A Graham
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK.
| |
Collapse
|
44
|
van den Bosch T, Derks S, Miedema DM. Chromosomal Instability, Selection and Competition: Factors That Shape the Level of Karyotype Intra-Tumor Heterogeneity. Cancers (Basel) 2022; 14:cancers14204986. [PMID: 36291770 PMCID: PMC9600040 DOI: 10.3390/cancers14204986] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/07/2022] [Accepted: 10/09/2022] [Indexed: 12/03/2022] Open
Abstract
Simple Summary Each cancer consists of billions of cells. These cells are far from identical; hence, the population of cells that constitute a tumor is heterogeneous. A salient property that varies between cells in a tumor is their karyotype, the number and configuration of the chromosomes. The level of karyotype heterogeneity can be used to predict the survival of a patient. In this review, we describe the processes that shape the level of karyotype heterogeneity in a cancer. Abstract Intra-tumor heterogeneity (ITH) is a pan-cancer predictor of survival, with high ITH being correlated to a dismal prognosis. The level of ITH is, hence, a clinically relevant characteristic of a malignancy. ITH of karyotypes is driven by chromosomal instability (CIN). However, not all new karyotypes generated by CIN are viable or competitive, which limits the amount of ITH. Here, we review the cellular processes and ecological properties that determine karyotype ITH. We propose a framework to understand karyotype ITH, in which cells with new karyotypes emerge through CIN, are selected by cell intrinsic and cell extrinsic selective pressures, and propagate through a cancer in competition with other malignant cells. We further discuss how CIN modulates the cell phenotype and immune microenvironment, and the implications this has for the subsequent selection of karyotypes. Together, we aim to provide a comprehensive overview of the biological processes that shape the level of karyotype heterogeneity.
Collapse
Affiliation(s)
- Tom van den Bosch
- Laboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam University Medical Centers—Location AMC, 1105 AZ Amsterdam, The Netherlands
- Oncode Institute, 1105 AZ Amsterdam, The Netherlands
| | - Sarah Derks
- Oncode Institute, 1105 AZ Amsterdam, The Netherlands
- Department of Medical Oncology, Amsterdam University Medical Centers—Location VUmc, 1081 HV Amsterdam, The Netherlands
- Correspondence: (S.D.); (D.M.M.)
| | - Daniël M. Miedema
- Laboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam University Medical Centers—Location AMC, 1105 AZ Amsterdam, The Netherlands
- Oncode Institute, 1105 AZ Amsterdam, The Netherlands
- Correspondence: (S.D.); (D.M.M.)
| |
Collapse
|
45
|
Li M, Zhou J, Zhang Z, Li J, Wang F, Ma L, Tian X, Mao Z, Yang Y. Exosomal miR-485-3p derived from pancreatic ductal epithelial cells inhibits pancreatic cancer metastasis through targeting PAK1. Chin Med J (Engl) 2022; 135:2326-2337. [PMID: 36535010 PMCID: PMC9771326 DOI: 10.1097/cm9.0000000000002154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Cell competition is an important feature in pancreatic cancer (PC) progression, but the underlying mechanism remains elusive. This study aims to explore the role of exosomes derived from normal pancreatic ductal epithelial cells involved in PC progression. METHODS PC cells and pancreatic stellate cells (PSCs) were treated with exosomes isolated from pancreatic ductal epithelial cells. Cell proliferation was assessed by CCK8 assays. Cell migration and invasion were assessed by Transwell assays. PC and matched adjacent non-tumor tissue specimens were obtained from 46 patients pathologically diagnosed with PC at Peking University First Hospital from 2013 to 2017. Tissue miR-485-3p and p21-activated kinase-1 (PAK1) expression was examined by real-time polymerase chain reaction (RT-PCR), and the relationship of the two was analyzed using Pearman's product-moment correlation. The clinical significance of miR-485-3p was analyzed using the Chi-square test, Wilcoxon rank-sum test, and Fisher exact probability, respectively. The binding of miR-485-3p to PAK1 5'-untranslated region (5'-UTR) was examined by luciferase assay. PC cells were xenografted into nude mice as a PC metastasis model. RESULTS Exosomes from pancreatic ductal epithelial cells suppressed PC cell migration and invasion as well as the secretion and migration of PSCs. MiR-485-3p was enriched in the exosomes of pancreatic ductal epithelial cells but deficient in those of PC cells and PSCs, in accordance with the lower level in PSCs and PC cells than that in pancreatic ductal cells. And the mature miR-485-3p could be delivered into these cells by the exosomes secreted by normal pancreatic duct cells, to inhibit PC cell migration and invasion. Clinical data analysis showed that miR-485-3p was significantly decreased in PC tissues (P < 0.05) and was negatively associated with lymphovascular invasion (P = 0.044). As a direct target of miR-485-3p, PAK1 was found to exert an inhibitory effect on PC cells, and there was a significantly negative correlation between the expression levels of miR-485-3p and PAK1 (r = -0.6525, P < 0.0001) in PC tissues. Moreover, miR-485-3p could suppress PC metastasis in vivo by targeting p21-activated kinase-1. CONCLUSIONS Exosomal miR-485-3p delivered by normal pancreatic ductal epithelial cells into PC cells inhibits PC metastasis by directly targeting PAK1. The restoration of miR-485-3p by exosomes or some other vehicle might be a novel approach for PC treatment.
Collapse
Affiliation(s)
- Mingzhe Li
- Department of General Surgery, Peking University First Hospital, Beijing 100034, China
- Department of Urology, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, Zhejiang 310016, China
| | - Jiaxin Zhou
- Department of General Surgery, Peking University First Hospital, Beijing 100034, China
| | - Zhengkui Zhang
- Department of General Surgery, Peking University First Hospital, Beijing 100034, China
| | - Jisong Li
- Department of General Surgery, Peking University First Hospital, Beijing 100034, China
- Department of Gastrointestinal Surgery, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, China
| | - Feng Wang
- Department of General Surgery, Peking University First Hospital, Beijing 100034, China
| | - Ling Ma
- Department of Surgical Oncology, Peking University Ninth School of Clinical Medicine (Beijing Shijitan Hospital, Capital Medical University), Beijing 100038, China
| | - Xiaodong Tian
- Department of General Surgery, Peking University First Hospital, Beijing 100034, China
| | - Zebin Mao
- Department of Medical Biochemistry and Molecular Biology, Peking University Health Science Center, Beijing 100191, China
| | - Yinmo Yang
- Department of General Surgery, Peking University First Hospital, Beijing 100034, China
| |
Collapse
|
46
|
Peuhu E, Jacquemet G, Scheele CL, Isomursu A, Laisne MC, Koskinen LM, Paatero I, Thol K, Georgiadou M, Guzmán C, Koskinen S, Laiho A, Elo LL, Boström P, Hartiala P, van Rheenen J, Ivaska J. MYO10-filopodia support basement membranes at pre-invasive tumor boundaries. Dev Cell 2022; 57:2350-2364.e7. [DOI: 10.1016/j.devcel.2022.09.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 08/26/2022] [Accepted: 09/28/2022] [Indexed: 11/03/2022]
|
47
|
Genetic and microenvironmental intra-tumor heterogeneity impacts colorectal cancer evolution and metastatic development. Commun Biol 2022; 5:937. [PMID: 36085309 PMCID: PMC9463147 DOI: 10.1038/s42003-022-03884-x] [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: 03/08/2022] [Accepted: 08/23/2022] [Indexed: 11/08/2022] Open
Abstract
AbstractColorectal cancer (CRC) is a highly diverse disease, where different genomic instability pathways shape genetic clonal diversity and tumor microenvironment. Although intra-tumor heterogeneity has been characterized in primary tumors, its origin and consequences in CRC outcome is not fully understood. Therefore, we assessed intra- and inter-tumor heterogeneity of a prospective cohort of 136 CRC samples. We demonstrate that CRC diversity is forged by asynchronous forms of molecular alterations, where mutational and chromosomal instability collectively boost CRC genetic and microenvironment intra-tumor heterogeneity. We were able to depict predictor signatures of cancer-related genes that can foresee heterogeneity levels across the different tumor consensus molecular subtypes (CMS) and primary tumor location. Finally, we show that high genetic and microenvironment heterogeneity are associated with lower metastatic potential, whereas late-emerging copy number variations favor metastasis development and polyclonal seeding. This study provides an exhaustive portrait of the interplay between genetic and microenvironment intra-tumor heterogeneity across CMS subtypes, depicting molecular events with predictive value of CRC progression and metastasis development.
Collapse
|
48
|
Liu Y, Chen C, Wang X, Sun Y, Zhang J, Chen J, Shi Y. An Epigenetic Role of Mitochondria in Cancer. Cells 2022; 11:cells11162518. [PMID: 36010594 PMCID: PMC9406960 DOI: 10.3390/cells11162518] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/03/2022] [Accepted: 08/09/2022] [Indexed: 12/14/2022] Open
Abstract
Mitochondria are not only the main energy supplier but are also the cell metabolic center regulating multiple key metaborates that play pivotal roles in epigenetics regulation. These metabolites include acetyl-CoA, α-ketoglutarate (α-KG), S-adenosyl methionine (SAM), NAD+, and O-linked beta-N-acetylglucosamine (O-GlcNAc), which are the main substrates for DNA methylation and histone post-translation modifications, essential for gene transcriptional regulation and cell fate determination. Tumorigenesis is attributed to many factors, including gene mutations and tumor microenvironment. Mitochondria and epigenetics play essential roles in tumor initiation, evolution, metastasis, and recurrence. Targeting mitochondrial metabolism and epigenetics are promising therapeutic strategies for tumor treatment. In this review, we summarize the roles of mitochondria in key metabolites required for epigenetics modification and in cell fate regulation and discuss the current strategy in cancer therapies via targeting epigenetic modifiers and related enzymes in metabolic regulation. This review is an important contribution to the understanding of the current metabolic-epigenetic-tumorigenesis concept.
Collapse
Affiliation(s)
- Yu’e Liu
- Tongji University Cancer Center, Shanghai Tenth People’s Hospital of Tongji University, School of Medicine, Tongji University, Shanghai 200092, China
| | - Chao Chen
- Department of Neurosurgery, Changhai Hospital, Second Military Medical University, 168 Changhai Road, Shanghai 200433, China
| | - Xinye Wang
- Tongji University Cancer Center, Shanghai Tenth People’s Hospital of Tongji University, School of Medicine, Tongji University, Shanghai 200092, China
| | - Yihong Sun
- Tongji University Cancer Center, Shanghai Tenth People’s Hospital of Tongji University, School of Medicine, Tongji University, Shanghai 200092, China
| | - Jin Zhang
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Juxiang Chen
- Department of Neurosurgery, Changhai Hospital, Second Military Medical University, 168 Changhai Road, Shanghai 200433, China
- Correspondence: (J.C.); (Y.S.)
| | - Yufeng Shi
- Tongji University Cancer Center, Shanghai Tenth People’s Hospital of Tongji University, School of Medicine, Tongji University, Shanghai 200092, China
- Clinical Center for Brain and Spinal Cord Research, Tongji University, Shanghai 200092, China
- Correspondence: (J.C.); (Y.S.)
| |
Collapse
|
49
|
Coggan H, Page KM. The role of evolutionary game theory in spatial and non-spatial models of the survival of cooperation in cancer: a review. JOURNAL OF THE ROYAL SOCIETY, INTERFACE 2022; 19:20220346. [PMID: 35975562 PMCID: PMC9382458 DOI: 10.1098/rsif.2022.0346] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Evolutionary game theory (EGT) is a branch of mathematics which considers populations of individuals interacting with each other to receive pay-offs. An individual’s pay-off is dependent on the strategy of its opponent(s) as well as on its own, and the higher its pay-off, the higher its reproductive fitness. Its offspring generally inherit its interaction strategy, subject to random mutation. Over time, the composition of the population shifts as different strategies spread or are driven extinct. In the last 25 years there has been a flood of interest in applying EGT to cancer modelling, with the aim of explaining how cancerous mutations spread through healthy tissue and how intercellular cooperation persists in tumour-cell populations. This review traces this body of work from theoretical analyses of well-mixed infinite populations through to more realistic spatial models of the development of cooperation between epithelial cells. We also consider work in which EGT has been used to make experimental predictions about the evolution of cancer, and discuss work that remains to be done before EGT can make large-scale contributions to clinical treatment and patient outcomes.
Collapse
Affiliation(s)
- Helena Coggan
- Department of Mathematics, University College London, London, UK
| | - Karen M Page
- Department of Mathematics, University College London, London, UK
| |
Collapse
|
50
|
Laws of Spatially Structured Population Dynamics on a Lattice. PHYSICS 2022. [DOI: 10.3390/physics4030052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
We consider spatial population dynamics on a lattice, following a type of a contact (birth–death) stochastic process. We show that simple mathematical approximations for the density of cells can be obtained in a variety of scenarios. In the case of a homogeneous cell population, we derive the cellular density for a two-dimensional (2D) spatial lattice with an arbitrary number of neighbors, including the von Neumann, Moore, and hexagonal lattice.are not allowed in the abstract, please move them to the main text, please remember to check the order of references in the full text after revision. We then turn our attention to evolutionary dynamics, where mutant cells of different properties can be generated. For disadvantageous mutants, we derive an approximation for the equilibrium density representing the selection–mutation balance. For neutral and advantageous mutants, we show that simple scaling (power) laws for the numbers of mutants in expanding populations hold in 2D and 3D, under both flat (planar) and range population expansion. These models have relevance for studies in ecology and evolutionary biology, as well as biomedical applications including the dynamics of drug-resistant mutants in cancer and bacterial biofilms.
Collapse
|