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Ottaiano A, Ianniello M, Santorsola M, Ruggiero R, Sirica R, Sabbatino F, Perri F, Cascella M, Di Marzo M, Berretta M, Caraglia M, Nasti G, Savarese G. From Chaos to Opportunity: Decoding Cancer Heterogeneity for Enhanced Treatment Strategies. BIOLOGY 2023; 12:1183. [PMID: 37759584 PMCID: PMC10525472 DOI: 10.3390/biology12091183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 08/24/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023]
Abstract
Cancer manifests as a multifaceted disease, characterized by aberrant cellular proliferation, survival, migration, and invasion. Tumors exhibit variances across diverse dimensions, encompassing genetic, epigenetic, and transcriptional realms. This heterogeneity poses significant challenges in prognosis and treatment, affording tumors advantages through an increased propensity to accumulate mutations linked to immune system evasion and drug resistance. In this review, we offer insights into tumor heterogeneity as a crucial characteristic of cancer, exploring the difficulties associated with measuring and quantifying such heterogeneity from clinical and biological perspectives. By emphasizing the critical nature of understanding tumor heterogeneity, this work contributes to raising awareness about the importance of developing effective cancer therapies that target this distinct and elusive trait of cancer.
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Affiliation(s)
- Alessandro Ottaiano
- Istituto Nazionale Tumori di Napoli, IRCCS “G. Pascale”, Via M. Semmola, 80131 Naples, Italy; (M.S.); (F.P.); (M.C.); (M.D.M.); (G.N.)
| | - Monica Ianniello
- AMES, Centro Polidiagnostico Strumentale srl, Via Padre Carmine Fico 24, 80013 Casalnuovo Di Napoli, Italy; (M.I.); (R.R.); (R.S.); (G.S.)
| | - Mariachiara Santorsola
- Istituto Nazionale Tumori di Napoli, IRCCS “G. Pascale”, Via M. Semmola, 80131 Naples, Italy; (M.S.); (F.P.); (M.C.); (M.D.M.); (G.N.)
| | - Raffaella Ruggiero
- AMES, Centro Polidiagnostico Strumentale srl, Via Padre Carmine Fico 24, 80013 Casalnuovo Di Napoli, Italy; (M.I.); (R.R.); (R.S.); (G.S.)
| | - Roberto Sirica
- AMES, Centro Polidiagnostico Strumentale srl, Via Padre Carmine Fico 24, 80013 Casalnuovo Di Napoli, Italy; (M.I.); (R.R.); (R.S.); (G.S.)
| | - Francesco Sabbatino
- Oncology Unit, Department of Medicine, Surgery and Dentistry, University of Salerno, 84081 Baronissi, Italy;
| | - Francesco Perri
- Istituto Nazionale Tumori di Napoli, IRCCS “G. Pascale”, Via M. Semmola, 80131 Naples, Italy; (M.S.); (F.P.); (M.C.); (M.D.M.); (G.N.)
| | - Marco Cascella
- Istituto Nazionale Tumori di Napoli, IRCCS “G. Pascale”, Via M. Semmola, 80131 Naples, Italy; (M.S.); (F.P.); (M.C.); (M.D.M.); (G.N.)
| | - Massimiliano Di Marzo
- Istituto Nazionale Tumori di Napoli, IRCCS “G. Pascale”, Via M. Semmola, 80131 Naples, Italy; (M.S.); (F.P.); (M.C.); (M.D.M.); (G.N.)
| | - Massimiliano Berretta
- Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy;
| | - Michele Caraglia
- Department of Precision Medicine, University of Campania “L. Vanvitelli”, Via Luigi De Crecchio 7, 80138 Naples, Italy;
| | - Guglielmo Nasti
- Istituto Nazionale Tumori di Napoli, IRCCS “G. Pascale”, Via M. Semmola, 80131 Naples, Italy; (M.S.); (F.P.); (M.C.); (M.D.M.); (G.N.)
| | - Giovanni Savarese
- AMES, Centro Polidiagnostico Strumentale srl, Via Padre Carmine Fico 24, 80013 Casalnuovo Di Napoli, Italy; (M.I.); (R.R.); (R.S.); (G.S.)
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2
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van den Bosch T, Vermeulen L, Miedema DM. Quantitative models for the inference of intratumor heterogeneity. COMPUTATIONAL AND SYSTEMS ONCOLOGY 2022. [DOI: 10.1002/cso2.1034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Affiliation(s)
- Tom van den Bosch
- Laboratory for Experimental Oncology and Radiobiology Center for Experimental and Molecular Medicine Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism Amsterdam University Medical Centers Amsterdam The Netherlands
- Oncode Institute Amsterdam The Netherlands
| | - Louis Vermeulen
- Laboratory for Experimental Oncology and Radiobiology Center for Experimental and Molecular Medicine Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism Amsterdam University Medical Centers Amsterdam The Netherlands
- Oncode Institute Amsterdam The Netherlands
| | - Daniël M. Miedema
- Laboratory for Experimental Oncology and Radiobiology Center for Experimental and Molecular Medicine Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism Amsterdam University Medical Centers Amsterdam The Netherlands
- Oncode Institute Amsterdam The Netherlands
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3
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van Dijk E, van den Bosch T, Lenos KJ, El Makrini K, Nijman LE, van Essen HFB, Lansu N, Boekhout M, Hageman JH, Fitzgerald RC, Punt CJA, Tuynman JB, Snippert HJG, Kops GJPL, Medema JP, Ylstra B, Vermeulen L, Miedema DM. Chromosomal copy number heterogeneity predicts survival rates across cancers. Nat Commun 2021; 12:3188. [PMID: 34045449 PMCID: PMC8160133 DOI: 10.1038/s41467-021-23384-6] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 04/14/2021] [Indexed: 12/20/2022] Open
Abstract
Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.
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Affiliation(s)
- Erik van Dijk
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Tom van den Bosch
- LEXOR, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Oncode Institute, Amsterdam, The Netherlands
| | - Kristiaan J Lenos
- LEXOR, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Oncode Institute, Amsterdam, The Netherlands
| | - Khalid El Makrini
- LEXOR, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Oncode Institute, Amsterdam, The Netherlands
| | - Lisanne E Nijman
- LEXOR, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Oncode Institute, Amsterdam, The Netherlands
| | - Hendrik F B van Essen
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Nico Lansu
- Oncode Institute, Amsterdam, The Netherlands
- Hubrecht institute-KNAW and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Michiel Boekhout
- Oncode Institute, Amsterdam, The Netherlands
- Center for Molecular Medicine, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Joris H Hageman
- Oncode Institute, Amsterdam, The Netherlands
- Center for Molecular Medicine, University Medical Centre Utrecht, Utrecht, The Netherlands
| | | | - Cornelis J A Punt
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jurriaan B Tuynman
- Department of Surgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Hugo J G Snippert
- Oncode Institute, Amsterdam, The Netherlands
- Center for Molecular Medicine, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Geert J P L Kops
- Oncode Institute, Amsterdam, The Netherlands
- Hubrecht institute-KNAW and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jan Paul Medema
- LEXOR, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Oncode Institute, Amsterdam, The Netherlands
| | - Bauke Ylstra
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Louis Vermeulen
- LEXOR, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
- Oncode Institute, Amsterdam, The Netherlands.
| | - Daniël M Miedema
- LEXOR, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
- Oncode Institute, Amsterdam, The Netherlands.
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Garlaschi S, Fochesato A, Tovo A. Upscaling Statistical Patterns from Reduced Storage in Social and Life Science Big Datasets. ENTROPY (BASEL, SWITZERLAND) 2020; 22:E1084. [PMID: 33286853 PMCID: PMC7597173 DOI: 10.3390/e22101084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 09/17/2020] [Accepted: 09/23/2020] [Indexed: 11/16/2022]
Abstract
Recent technological and computational advances have enabled the collection of data at an unprecedented rate. On the one hand, the large amount of data suddenly available has opened up new opportunities for new data-driven research but, on the other hand, it has brought into light new obstacles and challenges related to storage and analysis limits. Here, we strengthen an upscaling approach borrowed from theoretical ecology that allows us to infer with small errors relevant patterns of a dataset in its entirety, although only a limited fraction of it has been analysed. In particular we show that, after reducing the input amount of information on the system under study, by applying our framework it is still possible to recover two statistical patterns of interest of the entire dataset. Tested against big ecological, human activity and genomics data, our framework was successful in the reconstruction of global statistics related to both the number of types and their abundances while starting from limited presence/absence information on small random samples of the datasets. These results pave the way for future applications of our procedure in different life science contexts, from social activities to natural ecosystems.
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Affiliation(s)
- Stefano Garlaschi
- Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università degli studi di Padova, Via Marzolo 8, 35131 Padova, Italy;
| | - Anna Fochesato
- Fondazione The Microsoft Research—University of Trento, Centre for Computational and Systems Biology (COSBI), Piazza Manifattura 1, 38068 Rovereto, Italy;
- Dipartimento di Matematica, Università degli studi di Trento, Via Sommarive 14, 38123 Povo, Italy
| | - Anna Tovo
- Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università degli studi di Padova, Via Marzolo 8, 35131 Padova, Italy;
- Dipartimento di Matematica “Tullio Levi-Civita”, Università degli studi di Padova, Via Trieste 63, 35121 Padova, Italy
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Assessing Cell Activities rather than Identities to Interpret Intra-Tumor Phenotypic Diversity and Its Dynamics. iScience 2020; 23:101061. [PMID: 32361272 PMCID: PMC7195534 DOI: 10.1016/j.isci.2020.101061] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 03/02/2020] [Accepted: 04/09/2020] [Indexed: 12/26/2022] Open
Abstract
Despite advances in single-cell and molecular techniques, it is still unclear how to best quantify phenotypic heterogeneity in cancer cells that evolved beyond normal, known classifications. We present an approach to phenotypically characterize cells based on their activities rather than static classifications. We validated the detectability of specific activities (epithelial-mesenchymal transition, glycolysis) in single cells, using targeted RT-qPCR analyses and in vitro inductions. We analyzed 50 established activity signatures as a basis for phenotypic description in public data and computed cell-cell distances in 28,513 cells from 85 patients and 8 public datasets. Despite not relying on any classification, our measure correlated with standard diversity indices in populations of known structure. We identified bottlenecks as phenotypic diversity reduced upon colorectal cancer initiation. This suggests that focusing on what cancer cells do rather than what they are can quantify phenotypic diversity in universal fashion, to better understand and predict intra-tumor heterogeneity dynamics. Cells categorized as having the same identity can perform different activities Single-cell expression data can be used to infer the activities cells take part in Activity profiles provide a basis to measure phenotypic cell-cell divergence Cell activity can quantify intra-tumor heterogeneity more fully than identity
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Berry NK, Scott RJ, Rowlings P, Enjeti AK. Clinical use of SNP-microarrays for the detection of genome-wide changes in haematological malignancies. Crit Rev Oncol Hematol 2019; 142:58-67. [PMID: 31377433 DOI: 10.1016/j.critrevonc.2019.07.016] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 07/18/2019] [Accepted: 07/18/2019] [Indexed: 12/17/2022] Open
Abstract
Single nucleotide polymorphism (SNP) microarrays are commonly used for the clinical investigation of constitutional genomic disorders; however, their adoption for investigating somatic changes is being recognised. With increasing importance being placed on defining the cancer genome, a shift in technology is imperative at a clinical level. Microarray platforms have the potential to become frontline testing, replacing or complementing standard investigations such as FISH or karyotype. This 'molecular karyotype approach' exemplified by SNP-microarrays has distinct advantages in the investigation of several haematological malignancies. A growing body of literature, including guidelines, has shown support for the use of SNP-microarrays in the clinical laboratory to aid in a more accurate definition of the cancer genome. Understanding the benefits of this technology along with discussing the barriers to its implementation is necessary for the development and incorporation of SNP-microarrays in a clinical laboratory for the investigation of haematological malignancies.
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Affiliation(s)
- Nadine K Berry
- Department of Haematology, Calvary Mater Hospital, Newcastle, New South Wales, Australia; School of Biomedical Sciences and Pharmacy, University of Newcastle, New South Wales, Australia; Department of Molecular Medicine, NSW Health Pathology, Newcastle, New South Wales, Australia.
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, New South Wales, Australia; Department of Molecular Medicine, NSW Health Pathology, Newcastle, New South Wales, Australia
| | - Philip Rowlings
- Department of Haematology, Calvary Mater Hospital, Newcastle, New South Wales, Australia; School of Medicine and Public Health, University Newcastle, New South Wales, Australia
| | - Anoop K Enjeti
- Department of Haematology, Calvary Mater Hospital, Newcastle, New South Wales, Australia; School of Medicine and Public Health, University Newcastle, New South Wales, Australia
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