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Ramisetty S, Subbalakshmi AR, Pareek S, Mirzapoiazova T, Do D, Prabhakar D, Pisick E, Shrestha S, Achuthan S, Bhattacharya S, Malhotra J, Mohanty A, Singhal SS, Salgia R, Kulkarni P. Leveraging Cancer Phenotypic Plasticity for Novel Treatment Strategies. J Clin Med 2024; 13:3337. [PMID: 38893049 PMCID: PMC11172618 DOI: 10.3390/jcm13113337] [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: 04/22/2024] [Revised: 05/30/2024] [Accepted: 06/03/2024] [Indexed: 06/21/2024] Open
Abstract
Cancer cells, like all other organisms, are adept at switching their phenotype to adjust to the changes in their environment. Thus, phenotypic plasticity is a quantitative trait that confers a fitness advantage to the cancer cell by altering its phenotype to suit environmental circumstances. Until recently, new traits, especially in cancer, were thought to arise due to genetic factors; however, it is now amply evident that such traits could also emerge non-genetically due to phenotypic plasticity. Furthermore, phenotypic plasticity of cancer cells contributes to phenotypic heterogeneity in the population, which is a major impediment in treating the disease. Finally, plasticity also impacts the group behavior of cancer cells, since competition and cooperation among multiple clonal groups within the population and the interactions they have with the tumor microenvironment also contribute to the evolution of drug resistance. Thus, understanding the mechanisms that cancer cells exploit to tailor their phenotypes at a systems level can aid the development of novel cancer therapeutics and treatment strategies. Here, we present our perspective on a team medicine-based approach to gain a deeper understanding of the phenomenon to develop new therapeutic strategies.
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Affiliation(s)
- Sravani Ramisetty
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (S.R.); (A.R.S.); (S.P.); (T.M.); (D.D.); (J.M.); (A.M.); (S.S.S.)
| | - Ayalur Raghu Subbalakshmi
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (S.R.); (A.R.S.); (S.P.); (T.M.); (D.D.); (J.M.); (A.M.); (S.S.S.)
| | - Siddhika Pareek
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (S.R.); (A.R.S.); (S.P.); (T.M.); (D.D.); (J.M.); (A.M.); (S.S.S.)
| | - Tamara Mirzapoiazova
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (S.R.); (A.R.S.); (S.P.); (T.M.); (D.D.); (J.M.); (A.M.); (S.S.S.)
| | - Dana Do
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (S.R.); (A.R.S.); (S.P.); (T.M.); (D.D.); (J.M.); (A.M.); (S.S.S.)
| | - Dhivya Prabhakar
- City of Hope Atlanta, 600 Celebrate Life Parkway, Newnan, GA 30265, USA;
| | - Evan Pisick
- City of Hope Chicago, 2520 Elisha Avenue, Zion, IL 60099, USA;
| | - Sagun Shrestha
- City of Hope Phoenix, 14200 West Celebrate Life Way, Goodyear, AZ 85338, USA;
| | - Srisairam Achuthan
- Center for Informatics, City of Hope National Medical Center, Duarte, CA 91010, USA;
| | - Supriyo Bhattacharya
- Integrative Genomics Core, City of Hope National Medical Center, Duarte, CA 91010, USA;
| | - Jyoti Malhotra
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (S.R.); (A.R.S.); (S.P.); (T.M.); (D.D.); (J.M.); (A.M.); (S.S.S.)
| | - Atish Mohanty
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (S.R.); (A.R.S.); (S.P.); (T.M.); (D.D.); (J.M.); (A.M.); (S.S.S.)
| | - Sharad S. Singhal
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (S.R.); (A.R.S.); (S.P.); (T.M.); (D.D.); (J.M.); (A.M.); (S.S.S.)
| | - Ravi Salgia
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (S.R.); (A.R.S.); (S.P.); (T.M.); (D.D.); (J.M.); (A.M.); (S.S.S.)
| | - Prakash Kulkarni
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (S.R.); (A.R.S.); (S.P.); (T.M.); (D.D.); (J.M.); (A.M.); (S.S.S.)
- Department of Systems Biology, City of Hope National Medical Center, Duarte, CA 91010, USA
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Luddy KA, Teer JK, Freischel A, O’Farrelly C, Gatenby R. Evolutionary selection identifies critical immune-relevant genes in lung cancer subtypes. Front Genet 2022; 13:921447. [PMID: 36092893 PMCID: PMC9451599 DOI: 10.3389/fgene.2022.921447] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 07/07/2022] [Indexed: 11/13/2022] Open
Abstract
In an evolving population, proliferation is dependent on fitness so that a numerically dominant population typically possesses the most well adapted phenotype. In contrast, the evolutionary "losers" typically disappear from the population so that their genetic record is lost. Historically, cancer research has focused on observed genetic mutations in the dominant tumor cell populations which presumably increase fitness. Negative selection, i.e., removal of deleterious mutations from a population, is not observable but can provide critical information regarding genes involved in essential cellular processes. Similar to immunoediting, "evolutionary triage" eliminates mutations in tumor cells that increase susceptibility to the host immune response while mutations that shield them from immune attack increase proliferation and are readily observable (e.g., B2M mutations). These dynamics permit an "inverse problem" analysis linking the fitness consequences of a mutation to its prevalence in a tumor cohort. This is evident in "driver mutations" but, equally important, can identify essential genes in which mutations are seen significantly less than expected by chance. Here we utilized this new approach to investigate evolutionary triage in immune-related genes from TCGA lung adenocarcinoma cohorts. Negative selection differs between the two cohorts and is observed in endoplasmic reticulum aminopeptidase genes, ERAP1 and ERAP2 genes, and DNAM-1/TIGIT ligands. Targeting genes or molecular pathways under positive or negative evolutionary selection may permit new treatment options and increase the efficacy of current immunotherapy.
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Affiliation(s)
- Kimberly A. Luddy
- Cancer Biology and Evolution Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
- Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
| | - Jamie K. Teer
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
| | - Audrey Freischel
- Cancer Biology and Evolution Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
| | - Cliona O’Farrelly
- School of Biochemistry and Immunology, Trinity College Dublin, Trinity Biomedical Sciences Institute, Dublin, Ireland
- School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Robert Gatenby
- Cancer Biology and Evolution Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
- Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
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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.
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Affiliation(s)
- Helena Coggan
- Department of Mathematics, University College London, London, UK
| | - Karen M Page
- Department of Mathematics, University College London, London, UK
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Is There One Key Step in the Metastatic Cascade? Cancers (Basel) 2021; 13:cancers13153693. [PMID: 34359593 PMCID: PMC8345184 DOI: 10.3390/cancers13153693] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 07/17/2021] [Accepted: 07/19/2021] [Indexed: 12/11/2022] Open
Abstract
Simple Summary To successfully metastasize, cancer cells must complete a sequence of obligatory steps called the metastatic cascade. To model the metastatic cascade, we used the framework of the Drake equation, initially created to describe the emergence of intelligent life in the Milky way, using a similar logic of a sequence of obligatory steps. Then within this framework, we used simulations on breast cancer to investigate the contribution of each step to the metastatic cascade. We show that the half-life of circulating tumor cells is one of the most important parameters in the cascade, suggesting that therapies reducing the survival of those cells in the vascular system could significantly reduce the risk of metastasis. Abstract The majority of cancer-related deaths are the result of metastases (i.e., dissemination and establishment of tumor cells at distant sites from the origin), which develop through a multi-step process classically termed the metastatic cascade. The respective contributions of each step to the metastatic process are well described but are also currently not completely understood. Is there, for example, a critical phase that disproportionately affects the probability of the development of metastases in individual patients? Here, we address this question using a modified Drake equation, initially formulated by the astrophysicist Frank Drake to estimate the probability of the emergence of intelligent civilizations in the Milky Way. Using simulations based on realistic parameter values obtained from the literature for breast cancer, we examine, under the linear progression hypothesis, the contribution of each component of the metastatic cascade. Simulations demonstrate that the most critical parameter governing the formation of clinical metastases is the survival duration of circulating tumor cells (CTCs).
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Abstract
Here we advocate Cancer Community Ecology as a valuable focus of study in Cancer Biology. We hypothesize that the heterogeneity and characteristics of cancer cells within tumors should vary systematically in space and time and that cancer cells form local ecological communities within tumors. These communities possess limited numbers of species determined by local conditions, with each species in a community possessing predictable traits that enable them to cope with their particular environment and coexist with each other. We start with a discussion of concepts and assumptions that ecologists use to study closely related species. We then discuss the competitive exclusion principle as a means for knowing when two species should not coexist, and as an opening towards understanding how they can. We present the five major categories of mechanisms of coexistence that operate in nature and suggest that the same mechanisms apply towards understanding the diversification and coexistence of cancer cell species. They are: Food-Safety Tradeoffs, Diet Choice, Habitat Selection, Variance Partitioning, and Competition-Colonization Tradeoffs. For each mechanism, we discuss how it works in nature, how it might work in cancers, and its implications for therapy.
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Affiliation(s)
- Burt P Kotler
- Mitrani Department of Desert Ecology, Blaustein Institutes for Desert Research, 108400Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel
| | - Joel S Brown
- Department of Integrated Mathematical Oncology and Program in Cancer Biology and Evolution, 25301Moffitt Cancer Center, Tampa, FL, USA
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Capp JP, DeGregori J, Nedelcu AM, Dujon AM, Boutry J, Pujol P, Alix-Panabières C, Hamede R, Roche B, Ujvari B, Marusyk A, Gatenby R, Thomas F. Group phenotypic composition in cancer. eLife 2021; 10:63518. [PMID: 33784238 PMCID: PMC8009660 DOI: 10.7554/elife.63518] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 03/09/2021] [Indexed: 12/13/2022] Open
Abstract
Although individual cancer cells are generally considered the Darwinian units of selection in malignant populations, they frequently act as members of groups where fitness of the group cannot be reduced to the average fitness of individual group members. A growing body of studies reveals limitations of reductionist approaches to explaining biological and clinical observations. For example, induction of angiogenesis, inhibition of the immune system, and niche engineering through environmental acidification and/or remodeling of extracellular matrix cannot be achieved by single tumor cells and require collective actions of groups of cells. Success or failure of such group activities depends on the phenotypic makeup of the individual group members. Conversely, these group activities affect the fitness of individual members of the group, ultimately affecting the composition of the group. This phenomenon, where phenotypic makeup of individual group members impacts the fitness of both members and groups, has been captured in the term 'group phenotypic composition' (GPC). We provide examples where considerations of GPC could help in understanding the evolution and clinical progression of cancers and argue that use of the GPC framework can facilitate new insights into cancer biology and assist with the development of new therapeutic strategies.
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Affiliation(s)
- Jean-Pascal Capp
- Toulouse Biotechnology Institute, University of Toulouse, INSA, CNRS, INRAE, Toulouse, France
| | - James DeGregori
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, United States
| | - Aurora M Nedelcu
- Department of Biology, University of New Brunswick, Fredericton, New Brunswick, Canada
| | - Antoine M Dujon
- CREEC/CANECEV, MIVEGEC (CREES), University of Montpellier, CNRS, IRD, Montpellier, France.,Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Geelong, Australia
| | - Justine Boutry
- CREEC/CANECEV, MIVEGEC (CREES), University of Montpellier, CNRS, IRD, Montpellier, France
| | - Pascal Pujol
- CREEC/CANECEV, MIVEGEC (CREES), University of Montpellier, CNRS, IRD, Montpellier, France
| | - Catherine Alix-Panabières
- CREEC/CANECEV, MIVEGEC (CREES), University of Montpellier, CNRS, IRD, Montpellier, France.,Laboratory of Rare Human Circulating Cells (LCCRH), University Medical Centre of Montpellier, Montpellier, France
| | - Rodrigo Hamede
- School of Natural Sciences, University of Tasmania, Hobart, Australia
| | - Benjamin Roche
- CREEC/CANECEV, MIVEGEC (CREES), University of Montpellier, CNRS, IRD, Montpellier, France
| | - Beata Ujvari
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Geelong, Australia.,School of Natural Sciences, University of Tasmania, Hobart, Australia
| | - Andriy Marusyk
- Department of Cancer Physiology, H Lee Moffitt Cancer Center and Research Institute, Tampa, United States
| | - Robert Gatenby
- Department of Cancer Physiology, H Lee Moffitt Cancer Center and Research Institute, Tampa, United States
| | - Frédéric Thomas
- CREEC/CANECEV, MIVEGEC (CREES), University of Montpellier, CNRS, IRD, Montpellier, France
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Kamal Y, Schmit SL, Hoehn HJ, Amos CI, Frost HR. Transcriptomic Differences between Primary Colorectal Adenocarcinomas and Distant Metastases Reveal Metastatic Colorectal Cancer Subtypes. Cancer Res 2019; 79:4227-4241. [PMID: 31239274 PMCID: PMC6697603 DOI: 10.1158/0008-5472.can-18-3945] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Revised: 04/11/2019] [Accepted: 06/20/2019] [Indexed: 12/21/2022]
Abstract
Approximately 20% of colorectal cancer patients with colorectal adenocarcinomas present with metastases at the time of diagnosis, and therapies that specially target these metastases are lacking. We present a novel approach for investigating transcriptomic differences between primary colorectal adenocarcinoma and distant metastases, which may help to identify primary tumors with high risk for future dissemination and to inform the development of metastasis-targeted therapies. To effectively compare the transcriptomes of primary colorectal adenocarcinoma and metastatic lesions at both the gene and pathway levels, we eliminated tissue specificity of the "host" organs where tumors are located and adjusted for confounders such as exposure to chemotherapy and radiation, and identified that metastases were characterized by reduced epithelial-mesenchymal transition (EMT) but increased MYC target and DNA-repair pathway activities. FBN2 and MMP3 were the most differentially expressed genes between primary tumors and metastases. The two subtypes of colorectal adenocarcinoma metastases that were identified, EMT inflammatory and proliferative, were distinct from the consensus molecular subtype (CMS) 3, suggesting subtype exclusivity. In summary, this study highlights transcriptomic differences between primary tumors and colorectal adenocarcinoma metastases and delineates pathways that are activated in metastases that could be targeted in colorectal adenocarcinoma patients with metastatic disease. SIGNIFICANCE: These findings identify a colorectal adenocarcinoma metastasis-specific gene-expression signature that is free from potentially confounding background signals coming from treatment exposure and the normal host tissue that the metastasis is now situated within.
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Affiliation(s)
- Yasmin Kamal
- Department of Biomedical Data Sciences, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
| | - Stephanie L Schmit
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Hannah J Hoehn
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Christopher I Amos
- Department of Biomedical Data Sciences, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
- Dan L. Duncan Comprehensive Cancer Center at Baylor College of Medicine, Houston, Texas
| | - H Robert Frost
- Department of Biomedical Data Sciences, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
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Proteomic investigation of intra-tumor heterogeneity using network-based contextualization - A case study on prostate cancer. J Proteomics 2019; 206:103446. [PMID: 31323421 DOI: 10.1016/j.jprot.2019.103446] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 06/12/2019] [Accepted: 07/08/2019] [Indexed: 12/26/2022]
Abstract
Cancer is a heterogeneous disease, confounding the identification of relevant markers and drug targets. Network-based analysis is robust against noise, potentially offering a promising approach towards biomarker identification. We describe here the application of two network-based methods, qPSP (Quantitative Proteomics Signature Profiling) and PFSNet (Paired Fuzzy SubNetworks), in an intra-tissue proteome data set of prostate tissue samples. Despite high basal variation, we find that traditional statistical analysis may exaggerate the extent of heterogeneity. We also report that network-based analysis outperforms protein-based feature selection with concomitantly higher cross-validation accuracy. Overall, network-based analysis provides emergent signal that boosts sensitivity while retaining good precision. It is a potential means of circumventing heterogeneity for stable biomarker discovery.
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Tokutomi N, Moyret‐Lalle C, Puisieux A, Sugano S, Martinez P. Quantifying local malignant adaptation in tissue-specific evolutionary trajectories by harnessing cancer's repeatability at the genetic level. Evol Appl 2019; 12:1062-1075. [PMID: 31080515 PMCID: PMC6503823 DOI: 10.1111/eva.12781] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 12/03/2018] [Accepted: 02/07/2019] [Indexed: 02/06/2023] Open
Abstract
Cancer is a potentially lethal disease, in which patients with nearly identical genetic backgrounds can develop a similar pathology through distinct combinations of genetic alterations. We aimed to reconstruct the evolutionary process underlying tumour initiation, using the combination of convergence and discrepancies observed across 2,742 cancer genomes from nine tumour types. We developed a framework using the repeatability of cancer development to score the local malignant adaptation (LMA) of genetic clones, as their potential to malignantly progress and invade their environment of origin. Using this framework, we found that premalignant skin and colorectal lesions appeared specifically adapted to their local environment, yet insufficiently for full cancerous transformation. We found that metastatic clones were more adapted to the site of origin than to the invaded tissue, suggesting that genetics may be more important for local progression than for the invasion of distant organs. In addition, we used network analyses to investigate evolutionary properties at the system-level, highlighting that different dynamics of malignant progression can be modelled by such a framework in tumour-type-specific fashion. We find that occurrence-based methods can be used to specifically recapitulate the process of cancer initiation and progression, as well as to evaluate the adaptation of genetic clones to given environments. The repeatability observed in the evolution of most tumour types could therefore be harnessed to better predict the trajectories likely to be taken by tumours and preneoplastic lesions in the future.
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Affiliation(s)
- Natsuki Tokutomi
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier SciencesThe University of TokyoTokyoJapan
| | - Caroline Moyret‐Lalle
- Univ Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Centre Léon BérardCancer Research Center of LyonLyonFrance
| | - Alain Puisieux
- Univ Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Centre Léon BérardCancer Research Center of LyonLyonFrance
| | - Sumio Sugano
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier SciencesThe University of TokyoTokyoJapan
| | - Pierre Martinez
- Univ Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Centre Léon BérardCancer Research Center of LyonLyonFrance
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Singh R, Cho KR. Serous Tubal Intraepithelial Carcinoma or Not? Metastases to Fallopian Tube Mucosa Can Masquerade as In Situ Lesions. Arch Pathol Lab Med 2017; 141:1313-1315. [PMID: 28968160 DOI: 10.5858/arpa.2017-0231-ra] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
CONTEXT - Nonuterine high-grade serous carcinomas (HGSCs) are believed to arise most often from precursors in the fallopian tube referred to as serous tubal intraepithelial carcinomas (STICs). A designation of tubal origin has been suggested for all cases of nonuterine HGSC if a STIC is identified. OBJECTIVE - To highlight that many different types of nongynecologic and gynecologic carcinomas, including HGSC, can metastasize to the tubal mucosa and mimic de novo STIC. DATA SOURCES - A mini-review of several recently published studies that collectively examine STIC-like lesions of the fallopian tube. CONCLUSIONS - The fallopian tube mucosa can be a site of metastasis from carcinomas arising elsewhere, and pathologists should exercise caution in diagnosing STIC without first considering the possibility of metastasis. Routinely used immunohistochemical stains can often be used to determine if a STIC-like lesion is tubal or nongynecologic in origin. In the context of uterine and nonuterine HGSC, STIC may represent a metastasis rather than the site of origin, particularly when widespread disease is present.
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Teoh ST, Lunt SY. Metabolism in cancer metastasis: bioenergetics, biosynthesis, and beyond. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE 2017; 10. [DOI: 10.1002/wsbm.1406] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 08/10/2017] [Accepted: 08/28/2017] [Indexed: 12/13/2022]
Affiliation(s)
- Shao Thing Teoh
- Department of Biochemistry and Molecular Biology; Department of Chemical Engineering and Materials Science, Michigan State University; East Lansing MI USA
| | - Sophia Y. Lunt
- Department of Biochemistry and Molecular Biology; Department of Chemical Engineering and Materials Science, Michigan State University; East Lansing MI USA
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12
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Mechanisms and clinical implications of tumor heterogeneity and convergence on recurrent phenotypes. J Mol Med (Berl) 2017; 95:1167-1178. [PMID: 28871446 DOI: 10.1007/s00109-017-1587-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Revised: 08/11/2017] [Accepted: 08/20/2017] [Indexed: 10/18/2022]
Abstract
Tumor heterogeneity has been identified at various -omic levels. The tumor genome, transcriptome, proteome, and phenome can vary widely across cells in patient tumors and are influenced by tumor cell interactions with heterogeneous physical conditions and cellular components of the tumor microenvironment. Here, we explore the concept that while variation exists at multiple -omic levels, changes at each of these levels converge on the same pathways and lead to convergent phenotypes in tumors that can provide common drug targets. These phenotypes include cellular growth and proliferation, sustained oncogenic signaling, and immune avoidance, among others. Tumor heterogeneity complicates treatment of patient cancers as it leads to varied response to therapies. Identification of convergent cellular phenotypes arising in patient cancers and targeted therapies that reverse them has the potential to transform the way clinicians treat these cancers and to improve patient outcome.
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Shah AB, Rejniak KA, Gevertz JL. Limiting the development of anti-cancer drug resistance in a spatial model of micrometastases. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2016; 13:1185-1206. [PMID: 27775375 PMCID: PMC5113823 DOI: 10.3934/mbe.2016038] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
While chemoresistance in primary tumors is well-studied, much less is known about the influence of systemic chemotherapy on the development of drug resistance at metastatic sites. In this work, we use a hybrid spatial model of tumor response to a DNA damaging drug to study how the development of chemoresistance in micrometastases depends on the drug dosing schedule. We separately consider cell populations that harbor pre-existing resistance to the drug, and those that acquire resistance during the course of treatment. For each of these independent scenarios, we consider one hypothetical cell line that is responsive to metronomic chemotherapy, and another that with high probability cannot be eradicated by a metronomic protocol. Motivated by experimental work on ovarian cancer xenografts, we consider all possible combinations of a one week treatment protocol, repeated for three weeks, and constrained by the total weekly drug dose. Simulations reveal a small number of fractionated-dose protocols that are at least as effective as metronomic therapy in eradicating micrometastases with acquired resistance (weak or strong), while also being at least as effective on those that harbor weakly pre-existing resistant cells. Given the responsiveness of very different theoretical cell lines to these few fractionated-dose protocols, these may represent more effective ways to schedule chemotherapy with the goal of limiting metastatic tumor progression.
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Affiliation(s)
- Ami B. Shah
- Department of Biology, The College of New Jersey, Ewing, NJ, USA
| | - Katarzyna A. Rejniak
- Integrated Mathematical Oncology Department and Center of Excellence in Cancer Imaging and Technology, H. Lee Moffitt Cancer Center and Research Institute, Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA
| | - Jana L. Gevertz
- Department of Mathematics and Statistics, The College of New Jersey, Ewing, NJ, USA
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14
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Thomas F, Nesse RM, Gatenby R, Gidoin C, Renaud F, Roche B, Ujvari B. Evolutionary Ecology of Organs: A Missing Link in Cancer Development? Trends Cancer 2016; 2:409-415. [DOI: 10.1016/j.trecan.2016.06.009] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Revised: 06/28/2016] [Accepted: 06/29/2016] [Indexed: 12/18/2022]
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