1
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Sakata J, Furusho A, Sugiyama E, Sakane I, Todoroki K, Mizuno H. Development of a highly efficient solubilization method for mass spectrometric analysis of phospholipids in living single cells. ANAL SCI 2024; 40:917-924. [PMID: 38546806 DOI: 10.1007/s44211-024-00542-6] [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: 12/11/2023] [Accepted: 02/20/2024] [Indexed: 04/24/2024]
Abstract
Phospholipids are vital constituents of the cell membrane and aid in signal transduction. Phospholipid profiles vary distinctively with the cell type. Notably, specific phospholipid molecules are present in significantly higher or lower concentrations in cancer cells versus normal cells. In this study, live single-cell mass spectrometry (MS) was developed for analyzing phospholipids at the single-cell level. This method facilitates rapid molecular analysis of cells under microscopic observation. For nanoelectrospray ionization, phospholipids were extracted from single cells isolated in a glass capillary through a high-efficiency process. Cell-derived phosphatidylcholines were detected with high sensitivity when trehalose C14 was added as a solubilizing reagent. Trehalose C14 can solubilize cells at low concentrations owing to its low critical micelle concentration, and exerts minimal matrix effects (such as suppressing ionization and causing peak overlap) in the MS analysis of cellular molecules. Analyses of phospholipids in Raji and HEV0070 cells using the developed method revealed specific peaks of phosphatidylcholine and sphingomyelin in the respective cells. The developed technique not only affords phospholipid profiles at the single-cell level, but also holds promise for identifying biomarkers associated with various diseases, particularly cancer.
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Affiliation(s)
- Jo Sakata
- School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-Ku, Shizuoka, Shizuoka, 422-8526, Japan
| | - Aogu Furusho
- School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-Ku, Shizuoka, Shizuoka, 422-8526, Japan
| | - Eiji Sugiyama
- School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-Ku, Shizuoka, Shizuoka, 422-8526, Japan
| | - Iwao Sakane
- Central Research Institute, ITO EN, Ltd., 21 Mekami, Makinohara, Shizuoka, 421-0516, Japan
| | - Kenichiro Todoroki
- School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-Ku, Shizuoka, Shizuoka, 422-8526, Japan
| | - Hajime Mizuno
- School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-Ku, Shizuoka, Shizuoka, 422-8526, Japan.
- Faculty of Pharmacy, Meijo University, 150 Yagotoyama, Tempaku-Ku, Nagoya, Aichi, 468-8503, Japan.
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2
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Haag F, Hertel A, Tharmaseelan H, Kuru M, Haselmann V, Brochhausen C, Schönberg SO, Froelich MF. Imaging-based characterization of tumoral heterogeneity for personalized cancer treatment. ROFO-FORTSCHR RONTG 2024; 196:262-272. [PMID: 37944935 DOI: 10.1055/a-2175-4622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
With personalized tumor therapy, understanding and addressing the heterogeneity of malignant tumors is becoming increasingly important. Heterogeneity can be found within one lesion (intralesional) and between several tumor lesions emerging from one primary tumor (interlesional). The heterogeneous tumor cells may show a different response to treatment due to their biology, which in turn influences the outcome of the affected patients and the choice of therapeutic agents. Therefore, both intra- and interlesional heterogeneity should be addressed at the diagnostic stage. While genetic and biological heterogeneity are important parameters in molecular tumor characterization and in histopathology, they are not yet addressed routinely in medical imaging. This article summarizes the recently established markers for tumor heterogeneity in imaging as well as heterogeneous/mixed response to therapy. Furthermore, a look at emerging markers is given. The ultimate goal of this overview is to provide comprehensive understanding of tumor heterogeneity and its implications for radiology and for communication with interdisciplinary teams in oncology. KEY POINTS:: · Tumor heterogeneity can be described within one lesion (intralesional) or between several lesions (interlesional).. · The heterogeneous biology of tumor cells can lead to a mixed therapeutic response and should be addressed in diagnostics and the therapeutic regime.. · Quantitative image diagnostics can be enhanced using AI, improved histopathological methods, and liquid profiling in the future..
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Affiliation(s)
- Florian Haag
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Germany
| | - Alexander Hertel
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Germany
| | - Hishan Tharmaseelan
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Germany
| | - Mustafa Kuru
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Germany
| | - Verena Haselmann
- Institute of Clinical Chemistry, Medical Faculty Mannheim of the University of Heidelberg, University Hospital Mannheim, Germany
| | - Christoph Brochhausen
- Institute of Pathology, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany
| | - Stefan O Schönberg
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Germany
| | - Matthias F Froelich
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Germany
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3
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Bose A, Datta S, Mandal R, Ray U, Dhar R. Increased heterogeneity in expression of genes associated with cancer progression and drug resistance. Transl Oncol 2024; 41:101879. [PMID: 38262110 PMCID: PMC10832509 DOI: 10.1016/j.tranon.2024.101879] [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: 10/27/2023] [Revised: 12/16/2023] [Accepted: 12/29/2023] [Indexed: 01/25/2024] Open
Abstract
Fluctuations in the number of regulatory molecules and differences in timings of molecular events can generate variation in gene expression among genetically identical cells in the same environmental condition. This variation, termed as expression noise, can create differences in metabolic state and cellular functions, leading to phenotypic heterogeneity. Expression noise and phenotypic heterogeneity have been recognized as important contributors to intra-tumor heterogeneity, and have been associated with cancer growth, progression, and therapy resistance. However, how expression noise changes with cancer progression in actual cancer patients has remained poorly explored. Such an analysis, through identification of genes with increasing expression noise, can provide valuable insights into generation of intra-tumor heterogeneity, and could have important implications for understanding immune-suppression, drug tolerance and therapy resistance. In this work, we performed a genome-wide identification of changes in gene expression noise with cancer progression using single-cell RNA-seq data of lung adenocarcinoma patients at different stages of cancer. We identified 37 genes in epithelial cells that showed an increasing noise trend with cancer progression, many of which were also associated with cancer growth, EMT and therapy resistance. We found that expression of several of these genes was positively associated with expression of mitochondrial genes, suggesting an important role of mitochondria in generation of heterogeneity. In addition, we uncovered substantial differences in sample-specific noise profiles which could have implications for personalized prognosis and treatment.
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Affiliation(s)
- Anwesha Bose
- Department of Bioscience and Biotechnology, Indian Institute of Technology (IIT) Kharagpur, India
| | - Subhasis Datta
- Department of Bioscience and Biotechnology, Indian Institute of Technology (IIT) Kharagpur, India
| | - Rakesh Mandal
- Department of Bioscience and Biotechnology, Indian Institute of Technology (IIT) Kharagpur, India
| | - Upasana Ray
- Department of Bioscience and Biotechnology, Indian Institute of Technology (IIT) Kharagpur, India
| | - Riddhiman Dhar
- Department of Bioscience and Biotechnology, Indian Institute of Technology (IIT) Kharagpur, India.
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4
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Sharma NK, Bahot A, Sekar G, Bansode M, Khunteta K, Sonar PV, Hebale A, Salokhe V, Sinha BK. Understanding Cancer's Defense against Topoisomerase-Active Drugs: A Comprehensive Review. Cancers (Basel) 2024; 16:680. [PMID: 38398072 PMCID: PMC10886629 DOI: 10.3390/cancers16040680] [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: 01/25/2024] [Accepted: 02/02/2024] [Indexed: 02/25/2024] Open
Abstract
In recent years, the emergence of cancer drug resistance has been one of the crucial tumor hallmarks that are supported by the level of genetic heterogeneity and complexities at cellular levels. Oxidative stress, immune evasion, metabolic reprogramming, overexpression of ABC transporters, and stemness are among the several key contributing molecular and cellular response mechanisms. Topo-active drugs, e.g., doxorubicin and topotecan, are clinically active and are utilized extensively against a wide variety of human tumors and often result in the development of resistance and failure to therapy. Thus, there is an urgent need for an incremental and comprehensive understanding of mechanisms of cancer drug resistance specifically in the context of topo-active drugs. This review delves into the intricate mechanistic aspects of these intracellular and extracellular topo-active drug resistance mechanisms and explores the use of potential combinatorial approaches by utilizing various topo-active drugs and inhibitors of pathways involved in drug resistance. We believe that this review will help guide basic scientists, pre-clinicians, clinicians, and policymakers toward holistic and interdisciplinary strategies that transcend resistance, renewing optimism in the ongoing battle against cancer.
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Affiliation(s)
- Nilesh Kumar Sharma
- Cancer and Translational Research Centre Dr. D.Y. Patil Biotechnology & Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune 411033, Maharashtra, India; (N.K.S.); (A.B.); (G.S.); (M.B.); (K.K.); (P.V.S.); (A.H.); (V.S.)
| | - Anjali Bahot
- Cancer and Translational Research Centre Dr. D.Y. Patil Biotechnology & Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune 411033, Maharashtra, India; (N.K.S.); (A.B.); (G.S.); (M.B.); (K.K.); (P.V.S.); (A.H.); (V.S.)
| | - Gopinath Sekar
- Cancer and Translational Research Centre Dr. D.Y. Patil Biotechnology & Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune 411033, Maharashtra, India; (N.K.S.); (A.B.); (G.S.); (M.B.); (K.K.); (P.V.S.); (A.H.); (V.S.)
| | - Mahima Bansode
- Cancer and Translational Research Centre Dr. D.Y. Patil Biotechnology & Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune 411033, Maharashtra, India; (N.K.S.); (A.B.); (G.S.); (M.B.); (K.K.); (P.V.S.); (A.H.); (V.S.)
| | - Kratika Khunteta
- Cancer and Translational Research Centre Dr. D.Y. Patil Biotechnology & Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune 411033, Maharashtra, India; (N.K.S.); (A.B.); (G.S.); (M.B.); (K.K.); (P.V.S.); (A.H.); (V.S.)
| | - Priyanka Vijay Sonar
- Cancer and Translational Research Centre Dr. D.Y. Patil Biotechnology & Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune 411033, Maharashtra, India; (N.K.S.); (A.B.); (G.S.); (M.B.); (K.K.); (P.V.S.); (A.H.); (V.S.)
| | - Ameya Hebale
- Cancer and Translational Research Centre Dr. D.Y. Patil Biotechnology & Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune 411033, Maharashtra, India; (N.K.S.); (A.B.); (G.S.); (M.B.); (K.K.); (P.V.S.); (A.H.); (V.S.)
| | - Vaishnavi Salokhe
- Cancer and Translational Research Centre Dr. D.Y. Patil Biotechnology & Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune 411033, Maharashtra, India; (N.K.S.); (A.B.); (G.S.); (M.B.); (K.K.); (P.V.S.); (A.H.); (V.S.)
| | - Birandra Kumar Sinha
- Mechanistic Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC 27709, USA
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5
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Yousef A, Ghobrial L, Diamandis EP. Tumor heterogeneity: how could we use it to achieve better clinical outcomes? Diagnosis (Berl) 2024; 11:25-30. [PMID: 37817292 DOI: 10.1515/dx-2023-0108] [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: 08/16/2023] [Accepted: 09/17/2023] [Indexed: 10/12/2023]
Abstract
Differences in tumors related to location, tissue type, and histological subtype have been well documented for decades. Tumors are also molecularly very diverse. In this short review we describe the current classification schemes for tumor heterogeneity. We enlist the various drivers of tumor heterogeneity generation and comment on their clinical significance. New molecular techniques promise to assess tumor heterogeneity at affordable cost, so that these techniques can soon enter the clinic. While tumor heterogeneity currently represents a major unfavorable barrier in the field of oncology, it may also be a key in revolutionizing cancer diagnosis and treatment. Information regarding tumor heterogeneity has the potential to provide more thorough prognostic information, guide more efficacious combination treatment regimens, and lead to the development of novel therapeutic strategies and identification of new targets. For these gains to be realized, assessment of tumor heterogeneity needs to be incorporated into current diagnostic protocols but standardized and reproducible assessment methods are required. Fortunately, when these advances are realized, tumor heterogeneity has the potential to improve clinical outcomes.
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Affiliation(s)
| | - Lucianna Ghobrial
- School of Medicine, and Department of Public Health, King's College London, London, UK
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6
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Biswas A, Sahoo S, Riedlinger GM, Ghodoussipour S, Jolly MK, De S. Transcriptional state dynamics lead to heterogeneity and adaptive tumor evolution in urothelial bladder carcinoma. Commun Biol 2023; 6:1292. [PMID: 38129585 PMCID: PMC10739805 DOI: 10.1038/s42003-023-05668-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 12/04/2023] [Indexed: 12/23/2023] Open
Abstract
Intra-tumor heterogeneity contributes to treatment failure and poor survival in urothelial bladder carcinoma (UBC). Analyzing transcriptome from a UBC cohort, we report that intra-tumor transcriptomic heterogeneity indicates co-existence of tumor cells in epithelial and mesenchymal-like transcriptional states and bi-directional transition between them occurs within and between tumor subclones. We model spontaneous and reversible transition between these partially heritable states in cell lines and characterize their population dynamics. SMAD3, KLF4 and PPARG emerge as key regulatory markers of the transcriptional dynamics. Nutrient limitation, as in the core of large tumors, and radiation treatment perturb the dynamics, initially selecting for a transiently resistant phenotype and then reconstituting heterogeneity and growth potential, driving adaptive evolution. Dominance of transcriptional states with low PPARG expression indicates an aggressive phenotype in UBC patients. We propose that phenotypic plasticity and dynamic, non-genetic intra-tumor heterogeneity modulate both the trajectory of disease progression and adaptive treatment response in UBC.
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Affiliation(s)
- Antara Biswas
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ, USA.
| | | | - Gregory M Riedlinger
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ, USA
| | - Saum Ghodoussipour
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ, USA
| | | | - Subhajyoti De
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ, USA.
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7
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Brisset M, Mehlen P, Meurette O, Hollande F. Notch receptor/ligand diversity: contribution to colorectal cancer stem cell heterogeneity. Front Cell Dev Biol 2023; 11:1231416. [PMID: 37860822 PMCID: PMC10582728 DOI: 10.3389/fcell.2023.1231416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/21/2023] [Indexed: 10/21/2023] Open
Abstract
Cancer cell heterogeneity is a key contributor to therapeutic failure and post-treatment recurrence. Targeting cell subpopulations responsible for chemoresistance and recurrence seems to be an attractive approach to improve treatment outcome in cancer patients. However, this remains challenging due to the complexity and incomplete characterization of tumor cell subpopulations. The heterogeneity of cells exhibiting stemness-related features, such as self-renewal and chemoresistance, fuels this complexity. Notch signaling is a known regulator of cancer stem cell (CSC) features in colorectal cancer (CRC), though the effects of its heterogenous signaling on CRC cell stemness are only just emerging. In this review, we discuss how Notch ligand-receptor specificity contributes to regulating stemness, self-renewal, chemoresistance and cancer stem cells heterogeneity in CRC.
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Affiliation(s)
- Morgan Brisset
- Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Cancer Research, The University of Melbourne, Melbourne, VIC, Australia
- Cancer Cell Death Laboratory, Centre de Recherche en Cancérologie de Lyon, INSERM U1052-CNRS UMR5286, Centre Léon Bérard, Université de Lyon, Lyon, France
| | - Patrick Mehlen
- Cancer Cell Death Laboratory, Centre de Recherche en Cancérologie de Lyon, INSERM U1052-CNRS UMR5286, Centre Léon Bérard, Université de Lyon, Lyon, France
| | - Olivier Meurette
- Cancer Cell Death Laboratory, Centre de Recherche en Cancérologie de Lyon, INSERM U1052-CNRS UMR5286, Centre Léon Bérard, Université de Lyon, Lyon, France
| | - Frédéric Hollande
- Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Cancer Research, The University of Melbourne, Melbourne, VIC, Australia
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8
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Pérez-Aliacar M, Ayensa-Jiménez J, Doblaré M. Modelling cell adaptation using internal variables: Accounting for cell plasticity in continuum mathematical biology. Comput Biol Med 2023; 164:107291. [PMID: 37586203 DOI: 10.1016/j.compbiomed.2023.107291] [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: 05/04/2023] [Revised: 07/20/2023] [Accepted: 07/28/2023] [Indexed: 08/18/2023]
Abstract
Cellular adaptation is the ability of cells to change in response to different stimuli and environmental conditions. It occurs via phenotypic plasticity, that is, changes in gene expression derived from changes in the physiological environment. This phenomenon is important in many biological processes, in particular in cancer evolution and its treatment. Therefore, it is crucial to understand the mechanisms behind it. Specifically, the emergence of the cancer stem cell phenotype, showing enhanced proliferation and invasion rates, is an essential process in tumour progression. We present a mathematical framework to simulate phenotypic heterogeneity in different cell populations as a result of their interaction with chemical species in their microenvironment, through a continuum model using the well-known concept of internal variables to model cell phenotype. The resulting model, derived from conservation laws, incorporates the relationship between the phenotype and the history of the stimuli to which cells have been subjected, together with the inheritance of that phenotype. To illustrate the model capabilities, it is particularised for glioblastoma adaptation to hypoxia. A parametric analysis is carried out to investigate the impact of each model parameter regulating cellular adaptation, showing that it permits reproducing different trends reported in the scientific literature. The framework can be easily adapted to any particular problem of cell plasticity, with the main limitation of having enough cells to allow working with continuum variables. With appropriate calibration and validation, it could be useful for exploring the underlying processes of cellular adaptation, as well as for proposing favourable/unfavourable conditions or treatments.
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Affiliation(s)
- Marina Pérez-Aliacar
- Mechanical Engineering Department, School of Engineering and Architecture, University of Zaragoza, C/ Maria de Luna, Zaragoza, 50018, Spain; Engineering Research Institute of Aragón (I3A), University of Zaragoza, C/ Mariano Esquillor, Zaragoza, 50018, Spain.
| | - Jacobo Ayensa-Jiménez
- Engineering Research Institute of Aragón (I3A), University of Zaragoza, C/ Mariano Esquillor, Zaragoza, 50018, Spain; Aragón Health Research Institute (IISAragón), Avda. San Juan Bosco, Zaragoza, 50009, Spain.
| | - Manuel Doblaré
- Engineering Research Institute of Aragón (I3A), University of Zaragoza, C/ Mariano Esquillor, Zaragoza, 50018, Spain; Aragón Health Research Institute (IISAragón), Avda. San Juan Bosco, Zaragoza, 50009, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBERBBN), Avda. Monforte de Lemos, Madrid, 28029, Spain; Nanjing Tech University, South Puzhu Road, Nanging, 211800, China.
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9
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Chen Z, Lau KS. Advances in Mapping Tumor Progression from Precancer Atlases. Cancer Prev Res (Phila) 2023; 16:439-447. [PMID: 37167978 PMCID: PMC10523872 DOI: 10.1158/1940-6207.capr-22-0473] [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: 01/27/2023] [Revised: 03/22/2023] [Accepted: 04/11/2023] [Indexed: 05/13/2023]
Abstract
Tissue profiling technologies present opportunities for understanding transition from precancerous lesions to malignancy, which may impact risk stratification, prevention, and even cancer treatment. A human precancer atlas building effort is ongoing to tackle the significant challenge of decoding the heterogeneity among cells, specimens, and patients. Here, we discuss the findings resulting from atlases built across precancer types, including those found in colon, breast, lung, stomach, cervix, and skin, using bulk, single-cell, and spatial profiling strategies. We highlight two main themes that emerge across precancer types: the ordering of molecular events that occur during tumor progression and the fluctuation of microenvironmental response during precancer progression. We further highlight the key challenges of data integration across large cohorts of patients, and the need for computational tools to reliably annotate and quality control high-volume, high-dimensional data.
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Affiliation(s)
- Zhengyi Chen
- Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Program in Chemical and Physical Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Ken S. Lau
- Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Program in Chemical and Physical Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
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Gunnarsson EB, Foo J, Leder K. Statistical inference of the rates of cell proliferation and phenotypic switching in cancer. J Theor Biol 2023; 568:111497. [PMID: 37087049 PMCID: PMC10372878 DOI: 10.1016/j.jtbi.2023.111497] [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: 09/26/2022] [Revised: 02/21/2023] [Accepted: 04/12/2023] [Indexed: 04/24/2023]
Abstract
Recent evidence suggests that nongenetic (epigenetic) mechanisms play an important role at all stages of cancer evolution. In many cancers, these mechanisms have been observed to induce dynamic switching between two or more cell states, which commonly show differential responses to drug treatments. To understand how these cancers evolve over time, and how they respond to treatment, we need to understand the state-dependent rates of cell proliferation and phenotypic switching. In this work, we propose a rigorous statistical framework for estimating these parameters, using data from commonly performed cell line experiments, where phenotypes are sorted and expanded in culture. The framework explicitly models the stochastic dynamics of cell division, cell death and phenotypic switching, and it provides likelihood-based confidence intervals for the model parameters. The input data can be either the fraction of cells or the number of cells in each state at one or more time points. Through a combination of theoretical analysis and numerical simulations, we show that when cell fraction data is used, the rates of switching may be the only parameters that can be estimated accurately. On the other hand, using cell number data enables accurate estimation of the net division rate for each phenotype, and it can even enable estimation of the state-dependent rates of cell division and cell death. We conclude by applying our framework to a publicly available dataset.
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Affiliation(s)
- Einar Bjarki Gunnarsson
- Department of Industrial and Systems Engineering, University of Minnesota, Twin Cities, MN 55455, USA; School of Mathematics, University of Minnesota, Twin Cities, MN 55455, USA.
| | - Jasmine Foo
- School of Mathematics, University of Minnesota, Twin Cities, MN 55455, USA
| | - Kevin Leder
- Department of Industrial and Systems Engineering, University of Minnesota, Twin Cities, MN 55455, USA
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11
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Sadee W, Wang D, Hartmann K, Toland AE. Pharmacogenomics: Driving Personalized Medicine. Pharmacol Rev 2023; 75:789-814. [PMID: 36927888 PMCID: PMC10289244 DOI: 10.1124/pharmrev.122.000810] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 03/18/2023] Open
Abstract
Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.
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Affiliation(s)
- Wolfgang Sadee
- Department of Cancer Biology and Genetics, College of Medicine, The Ohio State University, Columbus Ohio (W.S., A.E.T.); Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida (D.W.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania (K.H.); Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California (W.S.); and Aether Therapeutics, Austin, Texas (W.S.)
| | - Danxin Wang
- Department of Cancer Biology and Genetics, College of Medicine, The Ohio State University, Columbus Ohio (W.S., A.E.T.); Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida (D.W.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania (K.H.); Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California (W.S.); and Aether Therapeutics, Austin, Texas (W.S.)
| | - Katherine Hartmann
- Department of Cancer Biology and Genetics, College of Medicine, The Ohio State University, Columbus Ohio (W.S., A.E.T.); Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida (D.W.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania (K.H.); Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California (W.S.); and Aether Therapeutics, Austin, Texas (W.S.)
| | - Amanda Ewart Toland
- Department of Cancer Biology and Genetics, College of Medicine, The Ohio State University, Columbus Ohio (W.S., A.E.T.); Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida (D.W.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania (K.H.); Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California (W.S.); and Aether Therapeutics, Austin, Texas (W.S.)
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12
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Cararo Lopes E, Sawant A, Moore D, Ke H, Shi F, Laddha S, Chen Y, Sharma A, Naumann J, Guo JY, Gomez M, Ibrahim M, Smith TL, Riedlinger GM, Lattime EC, Trooskin S, Ganesan S, Su X, Pasqualini R, Arap W, De S, Chan CS, White E. Integrated metabolic and genetic analysis reveals distinct features of human differentiated thyroid cancer. Clin Transl Med 2023; 13:e1298. [PMID: 37317665 PMCID: PMC10267429 DOI: 10.1002/ctm2.1298] [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: 03/10/2023] [Revised: 05/22/2023] [Accepted: 05/27/2023] [Indexed: 06/16/2023] Open
Abstract
BACKGROUND Differentiated thyroid cancer (DTC) affects thousands of lives worldwide each year. Typically, DTC is a treatable disease with a good prognosis. Yet, some patients are subjected to partial or total thyroidectomy and radioiodine therapy to prevent local disease recurrence and metastasis. Unfortunately, thyroidectomy and/or radioiodine therapy often worsen(s) quality of life and might be unnecessary in indolent DTC cases. On the other hand, the lack of biomarkers indicating a potential metastatic thyroid cancer imposes an additional challenge to managing and treating patients with this disease. AIM The presented clinical setting highlights the unmet need for a precise molecular diagnosis of DTC and potential metastatic disease, which should dictate appropriate therapy. MATERIALS AND METHODS In this article, we present a differential multi-omics model approach, including metabolomics, genomics, and bioinformatic models, to distinguish normal glands from thyroid tumours. Additionally, we are proposing biomarkers that could indicate potential metastatic diseases in papillary thyroid cancer (PTC), a sub-class of DTC. RESULTS Normal and tumour thyroid tissue from DTC patients had a distinct yet well-defined metabolic profile with high levels of anabolic metabolites and/or other metabolites associated with the energy maintenance of tumour cells. The consistency of the DTC metabolic profile allowed us to build a bioinformatic classification model capable of clearly distinguishing normal from tumor thyroid tissues, which might help diagnose thyroid cancer. Moreover, based on PTC patient samples, our data suggest that elevated nuclear and mitochondrial DNA mutational burden, intra-tumour heterogeneity, shortened telomere length, and altered metabolic profile reflect the potential for metastatic disease. DISCUSSION Altogether, this work indicates that a differential and integrated multi-omics approach might improve DTC management, perhaps preventing unnecessary thyroid gland removal and/or radioiodine therapy. CONCLUSIONS Well-designed, prospective translational clinical trials will ultimately show the value of this integrated multi-omics approach and early diagnosis of DTC and potential metastatic PTC.
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Affiliation(s)
- Eduardo Cararo Lopes
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
- Department of Molecular Biology and BiochemistryRutgers UniversityPiscatawayNew JerseyUSA
| | - Akshada Sawant
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
| | - Dirk Moore
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
- Department of Biostatistics and EpidemiologyRutgers School of Public HealthPiscatawayNew JerseyUSA
| | - Hua Ke
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
| | - Fuqian Shi
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
| | - Saurabh Laddha
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
| | - Ying Chen
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
| | - Anchal Sharma
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
| | - Jake Naumann
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
| | - Jessie Yanxiang Guo
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
- Department of MedicineRobert Wood Johnson Medical SchoolRutgers UniversityNew BrunswickNew JerseyUSA
- Department of Chemical BiologyRutgers Ernest Mario School of PharmacyPiscatawayNew JerseyUSA
| | - Maria Gomez
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
| | - Maria Ibrahim
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
| | - Tracey L. Smith
- Rutgers Cancer Institute of New JerseyNewarkNew JerseyUSA
- Division of Cancer BiologyDepartment of Radiation OncologyRutgers New Jersey Medical SchoolNewarkNew JerseyUSA
| | | | - Edmund C. Lattime
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
- Department of Surgery, Robert Wood Johnson Medical SchoolRutgers UniversityNew BrunswickNew JerseyUSA
| | - Stanley Trooskin
- Department of Surgery, Robert Wood Johnson Medical SchoolRutgers UniversityNew BrunswickNew JerseyUSA
| | - Shridar Ganesan
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
- Department of MedicineRobert Wood Johnson Medical SchoolRutgers UniversityNew BrunswickNew JerseyUSA
| | - Xiaoyang Su
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
- Department of MedicineRobert Wood Johnson Medical SchoolRutgers UniversityNew BrunswickNew JerseyUSA
| | - Renata Pasqualini
- Rutgers Cancer Institute of New JerseyNewarkNew JerseyUSA
- Division of Cancer BiologyDepartment of Radiation OncologyRutgers New Jersey Medical SchoolNewarkNew JerseyUSA
| | - Wadih Arap
- Rutgers Cancer Institute of New JerseyNewarkNew JerseyUSA
- Division of Hematology/OncologyDepartment of MedicineRutgers New Jersey Medical SchoolNewarkNew JerseyUSA
| | - Subhajyoti De
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
| | - Chang S. Chan
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
- Department of MedicineRobert Wood Johnson Medical SchoolRutgers UniversityNew BrunswickNew JerseyUSA
| | - Eileen White
- Rutgers Cancer Institute of New JerseyNew BrunswickNew JerseyUSA
- Department of Molecular Biology and BiochemistryRutgers UniversityPiscatawayNew JerseyUSA
- Ludwig Princeton Branch, Ludwig Institute for Cancer ResearchPrinceton UniversityPrincetonNew JerseyUSA
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13
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Gruen C, Yang HH, Sassano A, Wu E, Gopalan V, Marie KL, Castro A, Mehrabadi FR, Wu CH, Church I, Needle GA, Smith C, Chin S, Ebersole J, Marcelus C, Fon A, Liu H, Malikic S, Sahinalp C, Carter H, Hannenhalli S, Day CP, Lee MP, Merlino G, Pérez-Guijarro E. Melanoma clonal subline analysis uncovers heterogeneity-driven immunotherapy resistance mechanisms. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.03.535074. [PMID: 37333132 PMCID: PMC10274874 DOI: 10.1101/2023.04.03.535074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Intratumoral heterogeneity (ITH) can promote cancer progression and treatment failure, but the complexity of the regulatory programs and contextual factors involved complicates its study. To understand the specific contribution of ITH to immune checkpoint blockade (ICB) response, we generated single cell-derived clonal sublines from an ICB-sensitive and genetically and phenotypically heterogeneous mouse melanoma model, M4. Genomic and single cell transcriptomic analyses uncovered the diversity of the sublines and evidenced their plasticity. Moreover, a wide range of tumor growth kinetics were observed in vivo , in part associated with mutational profiles and dependent on T cell-response. Further inquiry into melanoma differentiation states and tumor microenvironment (TME) subtypes of untreated tumors from the clonal sublines demonstrated correlations between highly inflamed and differentiated phenotypes with the response to anti-CTLA-4 treatment. Our results demonstrate that M4 sublines generate intratumoral heterogeneity at both levels of intrinsic differentiation status and extrinsic TME profiles, thereby impacting tumor evolution during therapeutic treatment. These clonal sublines proved to be a valuable resource to study the complex determinants of response to ICB, and specifically the role of melanoma plasticity in immune evasion mechanisms.
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14
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Cararo-Lopes E, Sawant A, Moore D, Ke H, Shi F, Laddha S, Chen Y, Sharma A, Naumann J, Guo JY, Gomez M, Ibrahim M, Smith TL, Riedlinger GM, Lattime EC, Trooskin S, Ganesan S, Su X, Pasqualini R, Arap W, De S, Chan CS, White E. Integrated metabolic and genetic analysis reveals distinct features of primary differentiated thyroid cancer and its metastatic potential in humans. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.09.23287037. [PMID: 36945575 PMCID: PMC10029066 DOI: 10.1101/2023.03.09.23287037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Differentiated thyroid cancer (DTC) affects thousands of lives worldwide every year. Typically, DTC is a treatable disease with a good prognosis. Yet, some patients are subjected to partial or total thyroidectomy and radioiodine therapy to prevent local disease recurrence and metastasis. Unfortunately, thyroidectomy and/or radioiodine therapy often worsen(s) the quality of life and might be unnecessary in indolent DTC cases. This clinical setting highlights the unmet need for a precise molecular diagnosis of DTC, which should dictate appropriate therapy. Here we propose a differential multi-omics model approach to distinguish normal gland from thyroid tumor and to indicate potential metastatic diseases in papillary thyroid cancer (PTC), a sub-class of DTC. Based on PTC patient samples, our data suggest that elevated nuclear and mitochondrial DNA mutational burden, intratumor heterogeneity, shortened telomere length, and altered metabolic profile reflect the potential for metastatic disease. Specifically, normal and tumor thyroid tissues from these patients had a distinct yet well-defined metabolic profile with high levels of anabolic metabolites and/or other metabolites associated with the energy maintenance of tumor cells. Altogether, this work indicates that a differential and integrated multi-omics approach might improve DTC management, perhaps preventing unnecessary thyroid gland removal and/or radioiodine therapy. Well-designed, prospective translational clinical trials will ultimately show the value of this targeted molecular approach. TRANSLATIONAL RELEVANCE In this article, we propose a new integrated metabolic, genomic, and cytopathologic methods to diagnose Differentiated Thyroid Cancer when the conventional methods failed. Moreover, we suggest metabolic and genomic markers to help predict high-risk Papillary Thyroid Cancer. Both might be important tools to avoid unnecessary surgery and/or radioiodine therapy that can worsen the quality of life of the patients more than living with an indolent Thyroid nodule.
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15
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Feller G, Khammissa RAG, Ballyram R, Beetge MM, Lemmer J, Feller L. Tumour Genetic Heterogeneity in Relation to Oral Squamous Cell Carcinoma and Anti-Cancer Treatment. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:2392. [PMID: 36767758 PMCID: PMC9915085 DOI: 10.3390/ijerph20032392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/24/2023] [Accepted: 01/26/2023] [Indexed: 06/18/2023]
Abstract
Oral squamous cell carcinoma (SCC) represents more than 90% of all oral cancers and is the most frequent SCC of the head and neck region. It may affect any oral mucosal subsite but most frequently the tongue, followed by the floor of the mouth. The use of tobacco and betel nut, either smoked or chewed, and abuse of alcohol are the main risk factors for oral SCC. Oral SCC is characterized by considerable genetic heterogeneity and diversity, which together have a significant impact on the biological behaviour, clinical course, and response to treatment and on the generally poor prognosis of this carcinoma. Characterization of spatial and temporal tumour-specific molecular profiles and of person-specific resource availability and environmental and biological selective pressures could assist in personalizing anti-cancer treatment for individual patients, with the aim of improving treatment outcomes. In this narrative review, we discuss some of the events in cancer evolution and the functional significance of driver-mutations in carcinoma-related genes in general and elaborate on mechanisms mediating resistance to anti-cancer treatment.
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Affiliation(s)
- Gal Feller
- Department of Radiation Oncology, University of Witwatersrand, Johannesburg and Charlotte Maxeke Academic Hospital, Johannesburg 2193, South Africa
| | - Razia Abdool Gafaar Khammissa
- Department of Periodontics and Oral Medicine, School of Oral Health Sciences, Faculty of Health Sciences, University of Pretoria, Pretoria 0084, South Africa
| | - Raoul Ballyram
- Department of Periodontology and Oral Medicine, Sefako Makgatho Health Sciences University, Pretoria 0204, South Africa
| | - Mia-Michaela Beetge
- Department of Periodontics and Oral Medicine, School of Oral Health Sciences, Faculty of Health Sciences, University of Pretoria, Pretoria 0084, South Africa
| | - Johan Lemmer
- Retired Professor, Silvela Street, Sandton, Johannesburg 2031, South Africa
| | - Liviu Feller
- Retired Professor, Bantry Bay, Cape Town 8005, South Africa
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16
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Lu J, Duan Y, Liu P, He X, Yang Y, Zhang R, Weng L. Identification of tumour-infiltrating myeloid subsets associated with overall survival in lung squamous cell carcinoma. J Pathol 2023; 259:21-34. [PMID: 36178315 PMCID: PMC10100161 DOI: 10.1002/path.6015] [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: 07/13/2022] [Revised: 09/02/2022] [Accepted: 09/28/2022] [Indexed: 11/08/2022]
Abstract
Lung squamous cell carcinoma (LUSC) is a primary subtype of lung cancer with limited therapeutic options and poor prognosis, and tumour-infiltrating myeloid cells (TIMs) are key regulators of LUSC. However, the correlation between the abundance of TIM subtypes and clinical outcomes of LUSC remains unexplored. This study aimed to develop and validate a prognostic model for low- and high-risk patients with LUSC based on myeloid cell microenvironments. TIM markers in the tumoural (T) and stromal (S) regions were quantified using immunohistochemistry for 502 LUSC patients. L1-penalized Cox regression was used to develop a myeloid survival score (MSS) model based on the training cohort, followed by validation in distinct cohorts from multiple centres. RNA sequencing and immunostaining were used to examine the mechanisms of myeloid cells in LUSC progression and predict potential drug targets and therapeutic agents. Of the 12 myeloid markers, CD163T, CD163S, and S100A12T were highly associated with overall survival (OS) in LUSC patients. The MSS of the three myeloid signatures accurately categorized LUSC patients into risk categories, with an observable difference in OS between the training and validation cohorts. Tumours with high MSS were associated with enhanced antioxidative ability and hedgehog signalling and a shift to a more pro-tumorigenic microenvironment, accompanied by a reduced tumour cell immunogenicity and increased CD8+ T cell exhaustion patterns. Additionally, in high-risk patients, potential drug targets and compounds regulating hedgehog signalling were identified. Our study provides the first prognostic myeloid signature for LUSC, which may help advance precision medicine. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Jun Lu
- Department of Oncology, Xiangya Cancer Center, Xiangya Hospital, Central South University, Changsha, PR China.,Hunan Normal University School of Medicine, Changsha, PR China
| | - Yumei Duan
- Cancer Research Institute and School of Basic Medical Sciences, Central South University, Changsha, PR China.,Department of Pathology, Xiangya Hospital, Central South University, Changsha, PR China
| | - Pinbo Liu
- Center of Clinical Pharmacology, Third Xiangya Hospital, Central South University, Changsha, PR China
| | - Xiang He
- Department of Oncology, Xiangya Cancer Center, Xiangya Hospital, Central South University, Changsha, PR China
| | - Yiping Yang
- Center of Clinical Pharmacology, Third Xiangya Hospital, Central South University, Changsha, PR China
| | - Ran Zhang
- Hunan Normal University School of Medicine, Changsha, PR China
| | - Liang Weng
- Department of Oncology, Xiangya Cancer Center, Xiangya Hospital, Central South University, Changsha, PR China.,Key Laboratory of Molecular Radiation Oncology, Hunan Province, Xiangya Hospital, Central South University, Changsha, PR China.,Hunan International Science and Technology Collaboration Base of Precision Medicine for Cancer, Xiangya Hospital, Central South University, Changsha, PR China.,Hunan Provincial Clinical Research Center for Respiratory Diseases, Xiangya Hospital, Central South University, Changsha, PR China.,Institute of Gerontological Cancer Research, National Clinical Research Center for Gerontology, Xiangya Hospital, Central South University, Changsha, PR China.,Xiangya Lung Cancer Center, Xiangya Hospital, Central South University, Changsha, PR China
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17
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Lavia P, Sciamanna I, Spadafora C. An Epigenetic LINE-1-Based Mechanism in Cancer. Int J Mol Sci 2022; 23:ijms232314610. [PMID: 36498938 PMCID: PMC9738484 DOI: 10.3390/ijms232314610] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 11/18/2022] [Accepted: 11/20/2022] [Indexed: 11/24/2022] Open
Abstract
In the last fifty years, large efforts have been deployed in basic research, clinical oncology, and clinical trials, yielding an enormous amount of information regarding the molecular mechanisms of cancer and the design of effective therapies. The knowledge that has accumulated underpins the complexity, multifactoriality, and heterogeneity of cancer, disclosing novel landscapes in cancer biology with a key role of genome plasticity. Here, we propose that cancer onset and progression are determined by a stress-responsive epigenetic mechanism, resulting from the convergence of upregulation of LINE-1 (long interspersed nuclear element 1), the largest family of human retrotransposons, genome damage, nuclear lamina fragmentation, chromatin remodeling, genome reprogramming, and autophagy activation. The upregulated expression of LINE-1 retrotransposons and their protein products plays a key role in these processes, yielding an increased plasticity of the nuclear architecture with the ensuing reprogramming of global gene expression, including the reactivation of embryonic transcription profiles. Cancer phenotypes would thus emerge as a consequence of the unscheduled reactivation of embryonic gene expression patterns in an inappropriate context, triggering de-differentiation and aberrant proliferation in differentiated cells. Depending on the intensity of the stressing stimuli and the level of LINE-1 response, diverse degrees of malignity would be generated.
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Affiliation(s)
- Patrizia Lavia
- Institute of Molecular Biology and Pathology (IBPM), CNR Consiglio Nazionale delle Ricerche, c/o Department of Biology and Biotechnology, Sapienza University of Rome, 00185 Rome, Italy
- Correspondence: or
| | - Ilaria Sciamanna
- Center for Animal Research and Welfare (BENA), ISS Istituto Superiore di Sanità, 00161 Rome, Italy
| | - Corrado Spadafora
- Institute of Translational Pharmacology (IFT), CNR Consiglio Nazionale delle Ricerche, 00133 Rome, Italy
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18
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Warzecha KW, Pudełek M, Catapano J, Madeja Z, Czyż J. Long-Term Fenofibrate Treatment Stimulates the Phenotypic Microevolution of Prostate Cancer Cells In Vitro. Pharmaceuticals (Basel) 2022; 15:1320. [PMID: 36355492 PMCID: PMC9694160 DOI: 10.3390/ph15111320] [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: 09/19/2022] [Revised: 10/19/2022] [Accepted: 10/22/2022] [Indexed: 08/30/2023] Open
Abstract
Fenofibrate is a widely used anti-hyperlipidemic agonist of peroxisome proliferator-activated receptor alpha (PPARα). As a metabolic blocker, fenofibrate interferes with cancer promotion/progression via its misbalancing effects on cellular metabolism. However, the consequences of its long-term application for patients with diagnosed drug-resistant cancers are unknown. We addressed this point by tracing the phenotypic microevolution of naïve and drug-resistant prostate cancer PC3_DCX20 cells that underwent a long-term exposition to 10 μM and 50 μM fenofibrate. Their resistance to fenofibrate, metabolic profile and invasive phenotype were estimated in the control conditions and under fenofibrate-induced stress. Apparently, drug efflux systems are not effective against the cytostatic FF action. However, wtPC3 and PC3_DCX20 cells that survived the long-term 50 μM fenofibrate treatment gave rise to lineages that displayed an increased proliferation rate, lower motility in the control conditions and enhanced fenofibrate resistance. Attenuated fenofibrate bioavailability modified the pattern of PC3 microevolution, as illustrated by phenotypic differences between wtPC3/PC3_DCX20 lineages propagated in the presence of 50 μM and 10 μM fenofibrate. Collectively, our observations indicate that fenofibrate acts as a selective factor that affects prostate cancer microevolution. We also pinpoint potential consequences of long-term exposition of prostate cancer patients to metabolic blockers.
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Affiliation(s)
| | | | | | | | - Jarosław Czyż
- Department of Cell Biology, Faculty of Biochemistry, Biophysics and Biotechnology, Jagiellonian University, ul. Gronostajowa 7, 30-387 Cracow, Poland
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19
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Li J, Li X, Guo Q. Drug Resistance in Cancers: A Free Pass for Bullying. Cells 2022; 11:3383. [PMID: 36359776 PMCID: PMC9654341 DOI: 10.3390/cells11213383] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 10/13/2022] [Accepted: 10/20/2022] [Indexed: 08/13/2023] Open
Abstract
The cancer burden continues to grow globally, and drug resistance remains a substantial challenge in cancer therapy. It is well established that cancerous cells with clonal dysplasia generate the same carcinogenic lesions. Tumor cells pass on genetic templates to subsequent generations in evolutionary terms and exhibit drug resistance simply by accumulating genetic alterations. However, recent evidence has implied that tumor cells accumulate genetic alterations by progressively adapting. As a result, intratumor heterogeneity (ITH) is generated due to genetically distinct subclonal populations of cells coexisting. The genetic adaptive mechanisms of action of ITH include activating "cellular plasticity", through which tumor cells create a tumor-supportive microenvironment in which they can proliferate and cause increased damage. These highly plastic cells are located in the tumor microenvironment (TME) and undergo extreme changes to resist therapeutic drugs. Accordingly, the underlying mechanisms involved in drug resistance have been re-evaluated. Herein, we will reveal new themes emerging from initial studies of drug resistance and outline the findings regarding drug resistance from the perspective of the TME; the themes include exosomes, metabolic reprogramming, protein glycosylation and autophagy, and the relates studies aim to provide new targets and strategies for reversing drug resistance in cancers.
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Affiliation(s)
| | | | - Qie Guo
- The Department of Clinical Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao 266003, China
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20
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Shah UJ, Alsulimani A, Ahmad F, Mathkor DM, Alsaieedi A, Harakeh S, Nasiruddin M, Haque S. Bioplatforms in liquid biopsy: advances in the techniques for isolation, characterization and clinical applications. Biotechnol Genet Eng Rev 2022; 38:339-383. [PMID: 35968863 DOI: 10.1080/02648725.2022.2108994] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Tissue biopsy analysis has conventionally been the gold standard for cancer prognosis, diagnosis and prediction of responses/resistances to treatments. The existing biopsy procedures used in clinical practice are, however, invasive, painful and often associated with pitfalls like poor recovery of tumor cells and infeasibility for repetition in single patients. To circumvent these limitations, alternative non-invasive, rapid and economical, yet sturdy, consistent and dependable, biopsy techniques are required. Liquid biopsy is an emerging technology that fulfills these criteria and potentially much more in terms of subject-specific real-time monitoring of cancer progression, determination of tumor heterogeneity and treatment responses, and specific identification of the type and stages of cancers. The present review first briefly revisits the state-of-the-art technique of liquid biopsy and then proceeds to address in detail, the advances in the potential clinical applications of four major biological agencies present in liquid biopsy samples (circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes and tumor-educated platelets (TEPs)). Finally, the authors conclude with the limitations that need to be addressed in order for liquid biopsy to effectively replace the conventional invasive biopsy methods in the clinical settings.
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Affiliation(s)
- Ushma Jaykamal Shah
- MedGenome Labs Ltd, Kailash Cancer Hospital and Research Center, Vadodara, India
| | - Ahmad Alsulimani
- Medical Laboratory Technology Department, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Faraz Ahmad
- Department of Biotechnology, School of Bio Sciences and Technology (SBST), Vellore Institute of Technology, Vellore, India
| | - Darin Mansor Mathkor
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, Saudi Arabia
| | - Ahdab Alsaieedi
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.,Vaccines and Immunotherapy Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Steve Harakeh
- King Fahd Medical Research Center, and Yousef Abdullatif Jameel Chair of Prophetic Medicine Application, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mohammad Nasiruddin
- MedGenome Labs Ltd, Narayana Health City, Bangalore, India.,Genomics Lab, Orbito Asia Diagnostics, Coimbatore, India
| | - Shafiul Haque
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, Saudi Arabia
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21
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Tri-Reagent Homogenate Is a Suitable Starting Material for UHPLC-MS Lipidomic Analysis. SEPARATIONS 2022. [DOI: 10.3390/separations9100268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background: Transcriptomic and lipidomic dual analyses usually initiate with independent extractive procedures. That entails a difficulty in aligning results from both omics platforms, especially in the case of highly heterogeneous tissues, such as the kidney. Methods: Bligh and Dyer lipid extraction was performed using rat kidney homogenates prepared in PBS or commercially available Tri-reagent used for RNA extraction. Samples were analyzed by ultrahigh performance liquid chromatography-mass spectrometry (UHPLC-MS) lipidomic analysis. Results: Comparison of the lipidome obtained from phosphate-buffered saline (PBS) and Tri-reagent homogenates showed qualitative and quantitative validity of the Tri-reagent homogenate with the exception of ether lipids; the acidic nature of the mix seems to promote the hydrolysis of the ether bond, especially in plasmalogens. We tested several conditions in the sample processing, which allowed to optimize the procedure. Conclusions: Aiming to implement a method that allows the extraction of RNA and lipids from the same tissue homogenate not using external tracers, we here report the use of Tri-reagent homogenates as a suitable starting material for UHPLC-MS lipidomic analysis.
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22
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Stochastic population dynamics of cancer stemness and adaptive response to therapies. Essays Biochem 2022; 66:387-398. [PMID: 36073715 DOI: 10.1042/ebc20220038] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 08/19/2022] [Accepted: 08/22/2022] [Indexed: 02/07/2023]
Abstract
Intratumoral heterogeneity can exist along multiple axes: Cancer stem cells (CSCs)/non-CSCs, drug-sensitive/drug-tolerant states, and a spectrum of epithelial-hybrid-mesenchymal phenotypes. Further, these diverse cell-states can switch reversibly among one another, thereby posing a major challenge to therapeutic efficacy. Therefore, understanding the origins of phenotypic plasticity and heterogeneity remains an active area of investigation. While genomic components (mutations, chromosomal instability) driving heterogeneity have been well-studied, recent reports highlight the role of non-genetic mechanisms in enabling both phenotypic plasticity and heterogeneity. Here, we discuss various processes underlying phenotypic plasticity such as stochastic gene expression, chromatin reprogramming, asymmetric cell division and the presence of multiple stable gene expression patterns ('attractors'). These processes can facilitate a dynamically evolving cell population such that a subpopulation of (drug-tolerant) cells can survive lethal drug exposure and recapitulate population heterogeneity on drug withdrawal, leading to relapse. These drug-tolerant cells can be both pre-existing and also induced by the drug itself through cell-state reprogramming. The dynamics of cell-state transitions both in absence and presence of the drug can be quantified through mathematical models. Such a dynamical systems approach to elucidating patterns of intratumoral heterogeneity by integrating longitudinal experimental data with mathematical models can help design effective combinatorial and/or sequential therapies for better clinical outcomes.
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23
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Biswas A, Ghaddar B, Riedlinger G, De S. Inference on spatial heterogeneity in tumor microenvironment using spatial transcriptomics data. COMPUTATIONAL AND SYSTEMS ONCOLOGY 2022; 2:e21043. [PMID: 36035873 PMCID: PMC9410565 DOI: 10.1002/cso2.1043] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
In the tumor microenvironment (TME), functional interactions among tumor, immune, and stromal cells and the extracellular matrix play key roles in tumor progression, invasion, immune modulation, and response to treatment. Intratumor heterogeneity is ubiquitous not only at the genetic and transcriptomic levels but also in the composition and characteristics of TME. However, quantitative inference on spatial heterogeneity in the TME is still limited. Here, we propose a framework to use network graph-based spatial statistical models on spatially annotated molecular data to gain insights into modularity and spatial heterogeneity in the TME. Applying the framework to spatial transcriptomics data from pancreatic ductal adenocarcinoma samples, we observed significant global and local spatially correlated patterns in the abundance score of tumor cells; in contrast, immune cell types showed dispersed patterns in the TME. Hypoxia, EMT, and inflammation signatures contributed to intra-tumor spatial variations. Spatial patterns in cell type abundance and pathway signatures in the TME potentially impact tumor growth dynamics and cancer hallmarks. Tumor biopsies are integral to the diagnosis and clinical management of cancer patients; our data suggest that owing to intra-tumor non-genetic spatial heterogeneity, individual biopsies may underappreciate the extent of clinically relevant, functional variations across geographic regions within tumors.
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Affiliation(s)
- Antara Biswas
- Rutgers Cancer Institute, Rutgers the State University of New Jersey, New Brunswick, New Jersey, USA
| | - Bassel Ghaddar
- Rutgers Cancer Institute, Rutgers the State University of New Jersey, New Brunswick, New Jersey, USA
| | - Gregory Riedlinger
- Rutgers Cancer Institute, Rutgers the State University of New Jersey, New Brunswick, New Jersey, USA
| | - Subhajyoti De
- Rutgers Cancer Institute, Rutgers the State University of New Jersey, New Brunswick, New Jersey, USA
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Fassler DJ, Torre-Healy LA, Gupta R, Hamilton AM, Kobayashi S, Van Alsten SC, Zhang Y, Kurc T, Moffitt RA, Troester MA, Hoadley KA, Saltz J. Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression. Cancers (Basel) 2022; 14:2148. [PMID: 35565277 PMCID: PMC9105398 DOI: 10.3390/cancers14092148] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 04/09/2022] [Accepted: 04/15/2022] [Indexed: 12/15/2022] Open
Abstract
Tumor-infiltrating lymphocytes (TILs) have been established as a robust prognostic biomarker in breast cancer, with emerging utility in predicting treatment response in the adjuvant and neoadjuvant settings. In this study, the role of TILs in predicting overall survival and progression-free interval was evaluated in two independent cohorts of breast cancer from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS). We utilized machine learning and computer vision algorithms to characterize TIL infiltrates in digital whole-slide images (WSIs) of breast cancer stained with hematoxylin and eosin (H&E). Multiple parameters were used to characterize the global abundance and spatial features of TIL infiltrates. Univariate and multivariate analyses show that large aggregates of peritumoral and intratumoral TILs (forests) were associated with longer survival, whereas the absence of intratumoral TILs (deserts) is associated with increased risk of recurrence. Patients with two or more high-risk spatial features were associated with significantly shorter progression-free interval (PFI). This study demonstrates the practical utility of Pathomics in evaluating the clinical significance of the abundance and spatial patterns of distribution of TIL infiltrates as important biomarkers in breast cancer.
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Affiliation(s)
- Danielle J. Fassler
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA; (D.J.F.); (L.A.T.-H.); (R.G.); (S.K.); (Y.Z.); (T.K.); (R.A.M.)
| | - Luke A. Torre-Healy
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA; (D.J.F.); (L.A.T.-H.); (R.G.); (S.K.); (Y.Z.); (T.K.); (R.A.M.)
| | - Rajarsi Gupta
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA; (D.J.F.); (L.A.T.-H.); (R.G.); (S.K.); (Y.Z.); (T.K.); (R.A.M.)
| | - Alina M. Hamilton
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; (A.M.H.); (S.C.V.A.); (M.A.T.)
| | - Soma Kobayashi
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA; (D.J.F.); (L.A.T.-H.); (R.G.); (S.K.); (Y.Z.); (T.K.); (R.A.M.)
| | - Sarah C. Van Alsten
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; (A.M.H.); (S.C.V.A.); (M.A.T.)
| | - Yuwei Zhang
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA; (D.J.F.); (L.A.T.-H.); (R.G.); (S.K.); (Y.Z.); (T.K.); (R.A.M.)
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA; (D.J.F.); (L.A.T.-H.); (R.G.); (S.K.); (Y.Z.); (T.K.); (R.A.M.)
| | - Richard A. Moffitt
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA; (D.J.F.); (L.A.T.-H.); (R.G.); (S.K.); (Y.Z.); (T.K.); (R.A.M.)
| | - Melissa A. Troester
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; (A.M.H.); (S.C.V.A.); (M.A.T.)
| | - Katherine A. Hoadley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA;
| | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA; (D.J.F.); (L.A.T.-H.); (R.G.); (S.K.); (Y.Z.); (T.K.); (R.A.M.)
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25
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Cancer: More than a geneticist’s Pandora’s box. J Biosci 2022. [DOI: 10.1007/s12038-022-00254-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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26
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Jain P, Bhatia S, Thompson EW, Jolly MK. Population Dynamics of Epithelial-Mesenchymal Heterogeneity in Cancer Cells. Biomolecules 2022; 12:biom12030348. [PMID: 35327538 PMCID: PMC8945776 DOI: 10.3390/biom12030348] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 11/16/2022] Open
Abstract
Phenotypic heterogeneity is a hallmark of aggressive cancer behaviour and a clinical challenge. Despite much characterisation of this heterogeneity at a multi-omics level in many cancers, we have a limited understanding of how this heterogeneity emerges spontaneously in an isogenic cell population. Some longitudinal observations of dynamics in epithelial-mesenchymal heterogeneity, a canonical example of phenotypic heterogeneity, have offered us opportunities to quantify the rates of phenotypic switching that may drive such heterogeneity. Here, we offer a mathematical modeling framework that explains the salient features of population dynamics noted in PMC42-LA cells: (a) predominance of EpCAMhigh subpopulation, (b) re-establishment of parental distributions from the EpCAMhigh and EpCAMlow subpopulations, and (c) enhanced heterogeneity in clonal populations established from individual cells. Our framework proposes that fluctuations or noise in content duplication and partitioning of SNAIL—an EMT-inducing transcription factor—during cell division can explain spontaneous phenotypic switching and consequent dynamic heterogeneity in PMC42-LA cells observed experimentally at both single-cell and bulk level analysis. Together, we propose that asymmetric cell division can be a potential mechanism for phenotypic heterogeneity.
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Affiliation(s)
- Paras Jain
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
| | - Sugandha Bhatia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane 4000, Australia;
- The University of Queensland Diamantina Institute, Faculty of Medicine, The University of Queensland, Woolloongabba 4102, Australia
- Translational Research Institute, Woolloongabba 4102, Australia
| | - Erik W. Thompson
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane 4000, Australia;
- Translational Research Institute, Woolloongabba 4102, Australia
- Correspondence: (E.W.T.); (M.K.J.)
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Correspondence: (E.W.T.); (M.K.J.)
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Carlos-Reyes Á, Romero-Garcia S, Contreras-Sanzón E, Ruiz V, Prado-Garcia H. Role of Circular RNAs in the Regulation of Immune Cells in Response to Cancer Therapies. Front Genet 2022; 13:823238. [PMID: 35186039 PMCID: PMC8847670 DOI: 10.3389/fgene.2022.823238] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 01/11/2022] [Indexed: 12/25/2022] Open
Abstract
Circular RNAs (CircRNAs) are a class of small endogenous noncoding RNA that are formed by means of either the spliceosome or lariat-type splicing. CircRNAs have multiple regulatory functions and have been detected in different cell types, like normal, tumor and immune cells. CircRNAs have been suggested to regulate T cell functions in response to cancer. CircRNAs can enter into T cells and promote the expression of molecules that either trigger antitumoral responses or promote suppression and the consequent evasion to the immune response. Additionally, circRNAs may promote tumor progression and resistance to anticancer treatment in different types of neoplasias. In this minireview we discuss the impact of circRNAs and its function in the regulation of the T-cells in immune response caused by cancer therapies.
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Affiliation(s)
- Ángeles Carlos-Reyes
- Laboratorio de Onco-Inmunobiologia, Departamento de Enfermedades Crónico-Degenerativas, Instituto Nacional de Enfermedades Respiratorias, Mexico, Mexico
| | | | | | - Víctor Ruiz
- Laboratorio de Biología Molecular, Instituto Nacional de Enfermedades Respiratorias, Mexico, Mexico
| | - Heriberto Prado-Garcia
- Laboratorio de Onco-Inmunobiologia, Departamento de Enfermedades Crónico-Degenerativas, Instituto Nacional de Enfermedades Respiratorias, Mexico, Mexico
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Analysis of the Single-Cell Heterogeneity of Adenocarcinoma Cell Lines and the Investigation of Intratumor Heterogeneity Reveals the Expression of Transmembrane Protein 45A (TMEM45A) in Lung Adenocarcinoma Cancer Patients. Cancers (Basel) 2021; 14:cancers14010144. [PMID: 35008313 PMCID: PMC8750076 DOI: 10.3390/cancers14010144] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 12/14/2021] [Accepted: 12/24/2021] [Indexed: 11/25/2022] Open
Abstract
Simple Summary Non-small cell lung cancer (NSCLC) is one of the main causes of cancer-related deaths worldwide. Intratumoral heterogeneity (ITH) is responsible for the majority of difficulties encountered in the treatment of lung-cancer patients. Therefore, the heterogeneity of NSCLC cell lines and primary lung adenocarcinoma was investigated by single-cell mass cytometry (CyTOF). Human NSCLC adenocarcinoma cells A549, H1975, and H1650 were studied at single-cell resolution for the expression pattern of 13 markers: GLUT1, MCT4, CA9, TMEM45A, CD66, CD274, CD24, CD326, pan-keratin, TRA-1-60, galectin-3, galectin-1, and EGFR. The intra- and inter-cell-line heterogeneity of A549, H1975, and H1650 cells were demonstrated through hypoxic modeling. Additionally, human primary lung adenocarcinoma, and non-involved healthy lung tissue were homogenized to prepare a single-cell suspension for CyTOF analysis. The single-cell heterogeneity was confirmed using unsupervised viSNE and FlowSOM analysis. Our results also show, for the first time, that TMEM45A is expressed in lung adenocarcinoma. Abstract Intratumoral heterogeneity (ITH) is responsible for the majority of difficulties encountered in the treatment of lung-cancer patients. Therefore, the heterogeneity of NSCLC cell lines and primary lung adenocarcinoma was investigated by single-cell mass cytometry (CyTOF). First, we studied the single-cell heterogeneity of frequent NSCLC adenocarcinoma models, such as A549, H1975, and H1650. The intra- and inter-cell-line single-cell heterogeneity is represented in the expression patterns of 13 markers—namely GLUT1, MCT4, CA9, TMEM45A, CD66, CD274 (PD-L1), CD24, CD326 (EpCAM), pan-keratin, TRA-1-60, galectin-3, galectin-1, and EGFR. The qRT-PCR and CyTOF analyses revealed that a hypoxic microenvironment and altered metabolism may influence cell-line heterogeneity. Additionally, human primary lung adenocarcinoma and non-involved healthy lung tissue biopsies were homogenized to prepare a single-cell suspension for CyTOF analysis. The CyTOF showed the ITH of human primary lung adenocarcinoma for 14 markers; particularly, the higher expressions of GLUT1, MCT4, CA9, TMEM45A, and CD66 were associated with the lung-tumor tissue. Our single-cell results are the first to demonstrate TMEM45A expression in human lung adenocarcinoma, which was verified by immunohistochemistry.
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Enhanced Detection of Desmoplasia by Targeted Delivery of Iron Oxide Nanoparticles to the Tumour-Specific Extracellular Matrix. Pharmaceutics 2021; 13:pharmaceutics13101663. [PMID: 34683956 PMCID: PMC8539756 DOI: 10.3390/pharmaceutics13101663] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 09/27/2021] [Accepted: 09/30/2021] [Indexed: 01/14/2023] Open
Abstract
Diagnostic imaging of aggressive cancer with a high stroma content may benefit from the use of imaging contrast agents targeted with peptides that have high binding affinity to the extracellular matrix (ECM). In this study, we report the use of superparamagnetic iron-oxide nanoparticles (IO-NP) conjugated to a nonapeptide, CSGRRSSKC (CSG), which specifically binds to the laminin-nidogen-1 complex in tumours. We show that CSG-IO-NP accumulate in tumours, predominantly in the tumour ECM, following intravenous injection into a murine model of pancreatic neuroendocrine tumour (PNET). In contrast, a control untargeted IO-NP consistently show poor tumour uptake, and IO-NP conjugated to a pentapeptide, CREKA that bind fibrin clots in blood vessels show restricted uptake in the angiogenic vessels of the tumours. CSG-IO-NP show three-fold higher intratumoral accumulation compared to CREKA-IO-NP. Magnetic resonance imaging (MRI) T2-weighted scans and T2 relaxation times indicate significant uptake of CSG-IO-NP irrespective of tumour size, whereas the uptake of CREKA-IO-NP is only consistent in small tumours of less than 3 mm in diameter. Larger tumours with significantly reduced tumour blood vessels show a lack of CREKA-IO-NP uptake. Our data suggest CSG-IO-NP are particularly useful for detecting stroma in early and advanced solid tumours.
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Agaimy A. The challenge of undifferentiated malignancies: Phenotype versus genotype! What matters most? Semin Diagn Pathol 2021; 38:117-118. [PMID: 34556375 DOI: 10.1053/j.semdp.2021.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 09/14/2021] [Indexed: 11/11/2022]
Affiliation(s)
- Abbas Agaimy
- Institute of Pathology, Friedrich-Alexander-University Erlangen-Nürnberg, University Hospital, Krankenhausstrasse 8-10, 91054 Erlangen, Germany.
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Stem Cell Theory of Cancer: Origin of Tumor Heterogeneity and Plasticity. Cancers (Basel) 2021; 13:cancers13164006. [PMID: 34439162 PMCID: PMC8394880 DOI: 10.3390/cancers13164006] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 07/29/2021] [Accepted: 08/05/2021] [Indexed: 12/12/2022] Open
Abstract
In many respects, heterogeneity is one of the most striking revelations and common manifestations of a stem cell origin of cancer. We observe heterogeneity in myriad mixed tumors including testicular, lung, and breast cancers. We recognize heterogeneity in diverse tumor subtypes in prostate and kidney cancers. From this perspective, we illustrate that one of the main stem-ness characteristics, i.e., the ability to differentiate into diverse and multiple lineages, is central to tumor heterogeneity. We postulate that cancer subtypes can be meaningless and useless without a proper theory about cancer's stem cell versus genetic origin and nature. We propose a unified theory of cancer in which the same genetic abnormalities, epigenetic defects, and microenvironmental aberrations cause different effects and lead to different outcomes in a progenitor stem cell versus a mature progeny cell. We need to recognize that an all-encompassing genetic theory of cancer may be incomplete and obsolete. A stem cell theory of cancer provides greater universality, interconnectivity, and utility. Although genetic defects are pivotal, cellular context is paramount. When it concerns tumor heterogeneity, perhaps we need to revisit the conventional wisdom of precision medicine and revise our current practice of targeted therapy in cancer care.
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