DOCSLIB.ORG

Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome James P.B

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome James P.B Published OnlineFirst November 24, 2014; DOI: 10.1158/1078-0432.CCR-14-0990 Review Clinical Cancer Research Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome James P.B. O'Connor1,2, Chris J. Rose1, John C. Waterton1,3, Richard A.D. Carano4, Geoff J.M. Parker1, and Alan Jackson1 Abstract Tumors exhibit genomic and phenotypic heterogeneity, than another and can identify subregions with differing biol- which has prognostic significance and may influence response ogy. In this article, we review the image analysis methods to therapy. Imaging can quantify the spatial variation in archi- currently used to quantify spatial heterogeneity within tumors. tecture and function of individual tumors through quantifying We discuss how analysis of intratumor heterogeneity can pro- basic biophysical parameters such as CT density or MRI signal vide benefit over more simple biomarkers such as tumor size relaxation rate; through measurements of blood flow, hypoxia, and average function. We consider how imaging methods can metabolism, cell death, and other phenotypic features; and be integrated with genomic and pathology data, instead of through mapping the spatial distribution of biochemical path- being developed in isolation. Finally, we identify the challenges ways and cell signaling networks using PET, MRI, and other that must be overcome before measurements of intratumoral emerging molecular imaging techniques. These methods can heterogeneity can be used routinely to guide patient care. Clin establish whether one tumor is more or less heterogeneous Cancer Res; 21(2); 1–9. Ó2014 AACR. Introduction extent varies between preclinical cancer models and between patients (12). Allowing for these differences, some common Malignant tumors are biologically complex and exhibit sub- themes emerge. First, intratumor heterogeneity can be dynamic. stantial spatial variation in gene expression, biochemistry, histo- For example, variations in tumor pO fluctuate over minutes to pathology, and macroscopic structure. Cancerous cells not only 2 hours (5, 6). Second, intratumor heterogeneity tends to increase as undergo clonal evolution from a single progenitor cell into more tumors grow (7, 13). Third, established spatial heterogeneity aggressive and therapy-resistant cells, but also exhibit branched frequently indicates poor clinical prognosis (14), in part due to evolution, whereby each tumor develops and preserves multiple resistant subpopulations of cells driving resistance to therapy distinct subclonal populations (1). This genetic heterogeneity (3, 15). Finally, intratumor heterogeneity may increase or decrease (1, 2), combined with spatial variation in environmental stres- following efficacious anticancer therapy (11, 16), depending on sors, leads to regional differences in stromal architecture (3), the imaging test used and the underlying tumor biology (17). oxygen consumption (4, 5), glucose metabolism (4), and growth Imaging depicts spatial heterogeneity in tumors. However, factor expression (6). Consequently, tumor subregions develop, while imaging is central to diagnosis, staging, response assess- each with spatially distinct patterns of blood flow (7, 8), vessel ment, and recurrence detection in routine oncologic practice, permeability (9), cell proliferation (10), cell death (11), and other most clinical radiology and research studies only measure tumor features. size or average parameter values, such as median blood flow (18). Spatial heterogeneity is found between different tumors within In doing so, spatially rich information is discarded. There has been individual patients (intertumor heterogeneity) and within each considerable effort to use more sophisticated analyses to either lesion in an individual (intratumor heterogeneity). Intratumor quantify overall tumor spatial complexity or identify the tumor heterogeneity is near ubiquitous in malignant tumors, but the subregions that may drive disease transformation, progression, and drug resistance (11, 19). 1CRUK-EPSRC Cancer Imaging Centre in Cambridge and Manchester, In this review, we highlight the strengths and weaknesses of University of Manchester, Manchester, United Kingdom. 2Department methods that measure intratumor spatial heterogeneity (Fig. 1 of Radiology, Christie Hospital, Manchester, United Kingdom. 3R&D fi and Table 1). We evaluate evidence that heterogeneity analyses Personalised Healthcare and Biomarkers, AstraZeneca, Maccles eld, fi United Kingdom. 4Biomedical Imaging Department, Genentech, Inc., provide any clinical bene t over simple "average value" measure- South San Francisco, California. ments. We discuss how imaging, genomic, and pathology bio- Note: Supplementary data for this article are available at Clinical Cancer markers of intratumor heterogeneity relate to one another. Final- Research Online (http://clincancerres.aacrjournals.org/). ly, we identify the hurdles to translating image biomarkers of Corresponding Author: James P.B. O'Connor, University of Manchester, spatial heterogeneity into clinical practice. Stopford Building, Oxford Road, Manchester M13 9PT, United Kingdom. Phone: 44-1614463896; Fax: 44-1612755145; E-mail: james.o'[email protected] Qualitative Assessment of Heterogeneity doi: 10.1158/1078-0432.CCR-14-0990 Radiologists use qualitative descriptors to describe adverse Ó2014 American Association for Cancer Research. spatial features and functional heterogeneity on clinical scans. www.aacrjournals.org OF1 Downloaded from clincancerres.aacrjournals.org on September 25, 2021. © 2014 American Association for Cancer Research. Published OnlineFirst November 24, 2014; DOI: 10.1158/1078-0432.CCR-14-0990 O'Connor et al. AB C Clinical radiology Imaging science: current Imaging science: future Size (1D or 2D) Tumor function Intratumoral heterogeneity and complexity 20 Histograms 15 (e.g., mode, skew, 10 Figure 1. kurtosis, nth centile, 5 Quantifying intratumoral standard deviation) 0 heterogeneity: the example liver metastasis from a patient with a colonic primary tumor can be measured in several different ways. A, most clinical assessment of tumors Texture analysis is size based. B, functional imaging (e.g., box counting) methods can measure tumor pathophysiology but tend to derive average parameter values, such as median Ktrans. C, some intratumoral heterogeneity methods quantify overall complexity of a distribution RECIST: 1D DCE-MRI Partitioning (histograms) or spatial arrangement WHO: 2D (e.g., median K trans) (e.g., enhancing fraction) of data (texture analysis). Other methods identify tumor subregions using a priori assumptions (partitioning) or data-driven approaches (multispectral analysis). Multispectral analysis (e.g., size of cluster, change within cluster) © 2014 American Association for Cancer Research For example, when assessing pulmonary nodules on CT (20) and Voxels: Considerations for Quantifying breast lumps on X-ray mammography (21), spiculation implies Heterogeneity greater risk of malignancy compared with well-circumscribed lesions. Indeed, spiculate morphology is part of the BI-RADS Imaging modalities measure biophysical signals in tissues and (Breast Imaging Reporting and Data System) lexicon that classifies spatially encode these signals to create clinical images or param- breast lesions as "radiologically malignant" (22). eter maps composed of three-dimensional picture elements called Identifying a tumor "hot spot" is also commonplace in cancer voxels. Heterogeneity analyses combine data from many voxels. radiology. The maximum standardized uptake value (SUVmax) Several issues arise when interpreting these data. derived from 18F-FDG PET-CT imaging is an established proxy for First, some voxels suffer from partial volume averaging (typ- identifying abnormal glucose metabolism, based on identifying ically at interface with nontumor tissue). Second, there is inev- the one or more voxels with greatest abnormality. Measuring itable compromise between having sufficient numbers of voxels fi SUVmax is simple and reproducible (23, 24) and can be performed to perform the analysis versus suf ciently large voxels to over- on clinical work stations. The presence of abnormal glycolysis in come noise and keep imaging times practical (29). Most methods part of a tumor using SUVmax is used widely to stage and monitor of analysis require hundreds to thousands of voxels for robust response in several malignant tumors (25). In glioma, regional application. Third, many studies of tumor spatial heterogeneity high values of tracer uptake (18F-FDG and 11C-methionine) have have used standard clinical data from protocols dictated by been used to grade tumors using targeted biopsy (26). clinical rather than research needs. In some cases, sections of Perfusion CT and MRI methods use "hot spot" analysis to tumor were omitted when noncontiguous tumor sampling was identify tumor regions with the most abnormal vascular features. used (30), which may confound three-dimensional spatial anal- Specialist neuro-oncology centers use dynamic contrast-enhanced yses (31). Fourth, some calculated voxel values, such as apparent trans MRI (DCE-MRI) or dynamic susceptibility contrast MRI (DSC- diffusion coefficient (ADC), contrast transfer coefficient (K ), MRI) in patients with high-grade glioma (HGG) to map relative and blood flow, are derived from multiple images obtained over cerebral blood volume (rCBV; ref. 27) based on the rationale that time. The estimation errors associated with motion vary for "more vascular" regions correspond to
Load more

Recommended publications
  • Intratumor Heterogeneity: Novel Approaches for Resolving Genomic Architecture and Clonal Evolution Ravi G
    Published OnlineFirst June 8, 2017; DOI: 10.1158/1541-7786.MCR-17-0070 Review Molecular Cancer Research Intratumor Heterogeneity: Novel Approaches for Resolving Genomic Architecture and Clonal Evolution Ravi G. Gupta and Robert A. Somer Abstract High-throughput genomic technologies have revealed a full mutational landscape of tumors could help reconstruct remarkably complex portrait of intratumor heterogeneity in their phylogenetic trees and trace the subclonal origins of cancer and have shown that tumors evolve through a reiterative therapeutic resistance, relapsed disease, and distant metastases, process of genetic diversification and clonal selection. This the major causes of cancer-related mortality. Real-time assess- discovery has challenged the classical paradigm of clonal ment of the tumor subclonal architecture, however, remains dominance and brought attention to subclonal tumor cell limited by the high rate of errors produced by most genome- populations that contribute to the cancer phenotype. Dynamic wide sequencing methods as well as the practical difficulties evolutionary models may explain how these populations grow associated with serial tumor genotyping in patients. This review within the ecosystem of tissues, including linear, branching, focuses on novel approaches to mitigate these challenges using neutral, and punctuated patterns. Recent evidence in breast bulk tumor, liquid biopsies, single-cell analysis, and deep cancer favors branching and punctuated evolution driven by sequencing techniques. The origins of intratumor heterogene- genome instability as well as nongenetic sources of heteroge- ity and the clinical, diagnostic, and therapeutic consequences neity, such as epigenetic variation, hierarchal tumor cell orga- in breast cancer are also explored. Mol Cancer Res; 15(9); 1127–37. nization, and subclonal cell–cell interactions.
    [Show full text]
  • Intra-Tumor Heterogeneity from a Cancer Stem Cell Perspective Pramudita R
    Prasetyanti and Medema Molecular Cancer (2017) 16:41 DOI 10.1186/s12943-017-0600-4 REVIEW Open Access Intra-tumor heterogeneity from a cancer stem cell perspective Pramudita R. Prasetyanti1,2 and Jan Paul Medema1,2,3* Abstract Tumor heterogeneity represents an ongoing challenge in the field of cancer therapy. Heterogeneity is evident between cancers from different patients (inter-tumor heterogeneity) and within a single tumor (intra-tumor heterogeneity). The latter includes phenotypic diversity such as cell surface markers, (epi)genetic abnormality, growth rate, apoptosis and other hallmarks of cancer that eventually drive disease progression and treatment failure. Cancer stem cells (CSCs) have been put forward to be one of the determining factors that contribute to intra-tumor heterogeneity. However, recent findings have shown that the stem-like state in a given tumor cell is a plastic quality. A corollary to this view is that stemness traits can be acquired via (epi)genetic modification and/or interaction with the tumor microenvironment (TME). Here we discuss factors contributing to this CSC heterogeneity and the potential implications for cancer therapy. Keywords: Tumor heterogeneity, Cancer stem cell, Stemness, Tumor microenvironment Background tumor and microenvironment heterogeneity determine A tumor is a heterogeneous population of cells, containing the fitness of the tumor and as such, are likely to be transformed cancer cells, supportive cells and tumor- crucial factors in treatment success. infiltrating cells. This intra-tumor heterogeneity is further Two models have been proposed to account for hetero- enhanced by clonal variation and microenvironmental geneity within a tumor. In the clonal evolution model, influences on cancer cells, which also do not represent a stochastic mutations in individual tumor cells serve as homogeneous set of cells.
    [Show full text]
  • A Population Genetics Perspective on the Determinants of Intra-Tumor Heterogeneity☆
    BBACAN-88143; No. of pages: 18; 4C: 2, 6, 8, 9, 10 Biochimica et Biophysica Acta xxx (2017) xxx–xxx Contents lists available at ScienceDirect Biochimica et Biophysica Acta journal homepage: www.elsevier.com/locate/bbacan A population genetics perspective on the determinants of intra-tumor heterogeneity☆ Zheng Hu, Ruping Sun, Christina Curtis ⁎ Departments of Medicine and Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA article info abstract Article history: Cancer results from the acquisition of somatic alterations in a microevolutionary process that typically occurs Received 16 December 2016 over many years, much of which is occult. Understanding the evolutionary dynamics that are operative at differ- Received in revised form 1 March 2017 ent stages of progression in individual tumors might inform the earlier detection, diagnosis, and treatment of can- Accepted 2 March 2017 cer. Although these processes cannot be directly observed, the resultant spatiotemporal patterns of genetic Available online xxxx variation amongst tumor cells encode their evolutionary histories. Such intra-tumor heterogeneity is pervasive not only at the genomic level, but also at the transcriptomic, phenotypic, and cellular levels. Given the implica- tions for precision medicine, the accurate quantification of heterogeneity within and between tumors has be- come a major focus of current research. In this review, we provide a population genetics perspective on the determinants of intra-tumor heterogeneity and approaches to quantify genetic diversity. We summarize evi- dence for different modes of evolution based on recent cancer genome sequencing studies and discuss emerging evolutionary strategies to therapeutically exploit tumor heterogeneity.
    [Show full text]
  • Heterogeneity in Breast Cancer and the Problem of Relevance of findings
    53 Mini review Heterogeneity in breast cancer and the problem of relevance of findings ∗ M. Aubele a, and M. Werner b these events has not been established. Furthermore, the a GSF – National Research Center for Environment relationship between histological progression and ge- and Health, Institute of Pathology, Neuherberg, netic events in breast cancer is not yet well defined. Germany This review discusses the cytogenetic and molecular b Technische Universität München, Klinikum rechts genetic findings published within the last years, the der Isar, Institute of Pathology, Munich, Germany problem of correlating molecular-biological data with histology, and, consequently, the difficulties in devel- Received 15 August 1999 oping a model for breast cancer progression. Accepted 16 November 1999 Many attempts are made to identify critical genetic events re- 2. Evidences for intratumoural heterogeneity sponsible for the development and progression of breast can- cer. There is increasing evidence that breast cancer is a het- Intratumour phenotypic heterogeneity is one of the erogeneous disease, both, phenotypically as well as with re- characteristics of breast carcinoma, and genetic mech- spect to its molecular biologically. It is, therefore, extremely anisms are likely to contribute to it [39]. Heteroge- difficult to establish a diagnostically and prognostically rel- neous molecular findings in different parts of a tumour evant tumourigenesis model. Emerging new techniques such may reflect concomitant or successive clonal develop- as microarrays, will provide us with a wealth of additional ment. No studies have yet been carried out to make a data over the next years. The precise sampling of tumour ma- comprehensive analysis of known genetic alterations.
    [Show full text]
  • The Role of Tumour Heterogeneity and Clonal Cooperativity in Metastasis, Immune Evasion and Clinical Outcome Deborah R
    Caswell and Swanton BMC Medicine (2017) 15:133 DOI 10.1186/s12916-017-0900-y REVIEW Open Access The role of tumour heterogeneity and clonal cooperativity in metastasis, immune evasion and clinical outcome Deborah R. Caswell1* and Charles Swanton1,2 Abstract Background: The advent of rapid and inexpensive sequencing technology allows scientists to decipher heterogeneity within primary tumours, between primary and metastatic sites, and between metastases. Charting the evolutionary history of individual tumours has revealed drivers of tumour heterogeneity and highlighted its impact on therapeutic outcomes. Discussion: Scientists are using improved sequencing technologies to characterise and address the challenge of tumour heterogeneity, which is a major cause of resistance to therapy and relapse. Heterogeneity may fuel metastasis through the selection of rare, aggressive, somatically altered cells. However, extreme levels of chromosomal instability, which contribute to intratumour heterogeneity, are associated with improved patient outcomes, suggesting a delicate balance between high and low levels of genome instability. Conclusions: We review evidence that intratumour heterogeneity influences tumour evolution, including metastasis, drug resistance, and the immune response. We discuss the prevalence of tumour heterogeneity, and how it can be initiated and sustained by external and internal forces. Understanding tumour evolution and metastasis could yield novel therapies that leverage the immune system to control emerging tumour neo-antigens.
    [Show full text]
  • Tumor Heterogeneity: a Central Foe in the War on Cancer Jane De Lartigue, Phd
    Feature New Therapies Tumor heterogeneity: a central foe in the war on cancer Jane de Lartigue, PhD major challenge to effective cancer treat- develop – the clonal evolution model and the cancer ment is the astounding level of heteroge- stem cell (CSC) model (Figure 1). neity that tumors display on many different Afronts. Here, we discuss how a deeper appreciation of The clonal evolution model this heterogeneity and its impact is driving research As cells divide, they randomly acquire mutations as a efforts to better understand and tackle it and a radi- result of DNA damage. The clonal evolution model cal rethink of treatment paradigms. posits that cancer develops as the result of a multi- step accumulation of a series of “driver” mutations A complex and dynamic disease that confer a promalignant advantage to the cell and The nonuniformity of cancer has long been appre- ultimately fuel a cancerous hallmark. ciated, reflected most visibly in the variation of This evolution can occur in a linear fashion, response to the same treatment across patients with whereby the emergence of a new driver mutation the same type of tumor (inter-tumor heterogene- conveys such a potent evolutionary advantage that it ity). The extent of tumor heterogeneity is being fully outcompetes all previous clones. There is limited evi- realized only now, with the advent of next-genera- dence for linear evolution in most advanced human tion sequencing technologies. Even within the same cancers; instead, they are thought to evolve predom- tumor, there can be significant heterogeneity from inantly through a process of branching evolution, in cell to cell (intra-tumor heterogeneity), yielding which multiple clones can diverge in parallel from a substantial complexity in cancer.
    [Show full text]
  • Cancer Stem Cells in Glioblastoma
    Downloaded from genesdev.cshlp.org on October 1, 2021 - Published by Cold Spring Harbor Laboratory Press REVIEW Cancer stem cells in glioblastoma Justin D. Lathia,1,2 Stephen C. Mack,3 Erin E. Mulkearns-Hubert,1 Claudia L.L. Valentim,3 and Jeremy N. Rich2,3 1Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195, USA; 2Department of Molecular Medicine, Cleveland Clinic, Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio 44195, USA; 3Department of Stem Cell Biology and Regenerative Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195, USA Tissues with defined cellular hierarchies in development tumors will develop resistance to overcome initially effec- and homeostasis give rise to tumors with cellular hierar- tive therapies that poison driving oncogenes. chies, suggesting that tumors recapitulate specific tissues Glioblastoma (GBM; World Health Organization grade and mimic their origins. Glioblastoma (GBM) is the IV glioma) is the most prevalent and lethal primary in- most prevalent and malignant primary brain tumor and trinsic brain tumor (Stupp et al. 2009). Unlike other solid contains self-renewing, tumorigenic cancer stem cells tumor cell types, GBM widely invades the surrounding (CSCs) that contribute to tumor initiation and thera- brain but rarely metastasizes to other organs. While halt- peutic resistance. As normal stem and progenitor cells ing steps to fight GBM are being made using targeted participate in tissue development and repair, these de- therapies (e.g., bevacizumab) or immunotherapies, GBM velopmental programs re-emerge in CSCs to support the therapy remains focused on achieving maximal surgi- development and progressive growth of tumors.
    [Show full text]
  • Future Medical Applications of Single-Cell Sequencing in Cancer Nicholas Navin*1,2 and James Hicks3
    Navin and Hicks Genome Medicine 2011, 3:31 http://genomemedicine.com/content/3/5/31 REVIEW Future medical applications of single-cell sequencing in cancer Nicholas Navin*1,2 and James Hicks3 Abstract thus complicate the inter- and intra-tumor comparisons, which are the basis of molecular classification methods. Advances in whole genome amplication and next- In addition, solid tumors are often composed of generation sequencing methods have enabled genomic multiple clonal subpopulations [1-3], and this analyses of single cells, and these techniques are now heterogeneity further confounds the analysis of clinical beginning to be used to detect genomic lesions in samples. Single-cell genomic methods have the capacity individual cancer cells. Previous approaches have been to resolve complex mixtures of cells in tumors. When unable to resolve genomic dierences in complex multiple clones are present in a tumor, molecular assays mixtures of cells, such as heterogeneous tumors, despite reflect an average signal of the population, or, the importance of characterizing such tumors for alternatively, only the signal from the dominant clone, cancer treatment. Sequencing of single cells is likely to which may not be the most malignant clone present in improve several aspects of medicine, including the early the tumor. is becomes particularly important as detection of rare tumor cells, monitoring of circulating molecular assays are employed for directing targeted tumor cells (CTCs), measuring intratumor heterogeneity, therapy, as in the use of ERBB2 (Her2-neu) gene and guiding chemotherapy. In this review we discuss amplification to identify patients likely to respond to the challenges and technical aspects of single-cell Herceptin (trastuzumab) treatment in breast cancer, sequencing, with a strong focus on genomic copy where 5% to 30% of all patients have been reported to number, and discuss how this information can be used exhibit such genetic heterogeneity [4-7].
    [Show full text]
  • A Deep Convolutional Neural Network for Segmentation of Whole-Slide
    www.nature.com/bjc ARTICLE AI Applied to Cancer A deep convolutional neural network for segmentation of whole-slide pathology images identifies novel tumour cell- perivascular niche interactions that are associated with poor survival in glioblastoma Amin Zadeh Shirazi 1,2, Mark D. McDonnell 2, Eric Fornaciari3, Narjes Sadat Bagherian4, Kaitlin G. Scheer 1, Michael S. Samuel 1,5, Mahdi Yaghoobi6, Rebecca J. Ormsby 7, Santosh Poonnoose 7,8, Damon J. Tumes 1 and Guillermo A. Gomez 1 BACKGROUND: Glioblastoma is the most aggressive type of brain cancer with high-levels of intra- and inter-tumour heterogeneity that contribute to its rapid growth and invasion within the brain. However, a spatial characterisation of gene signatures and the cell types expressing these in different tumour locations is still lacking. METHODS: We have used a deep convolutional neural network (DCNN) as a semantic segmentation model to segment seven different tumour regions including leading edge (LE), infiltrating tumour (IT), cellular tumour (CT), cellular tumour microvascular proliferation (CTmvp), cellular tumour pseudopalisading region around necrosis (CTpan), cellular tumour perinecrotic zones (CTpnz) and cellular tumour necrosis (CTne) in digitised glioblastoma histopathological slides from The Cancer Genome Atlas (TCGA). Correlation analysis between segmentation results from tumour images together with matched RNA expression data was performed to identify genetic signatures that are specific to different tumour regions. RESULTS: We found that spatially resolved gene signatures were strongly correlated with survival in patients with defined genetic mutations. Further in silico cell ontology analysis along with single-cell RNA sequencing data from resected glioblastoma tissue samples showed that these tumour regions had different gene signatures, whose expression was driven by different cell types in the regional tumour microenvironment.
    [Show full text]
  • Heterogeneity in Cancer Stem Cells
    Cancer Letters 357 (2015) 63–68 Contents lists available at ScienceDirect Cancer Letters journal homepage: www.elsevier.com/locate/canlet Mini-review Heterogeneity in cancer stem cells Anxin Wang a,b,c,1, Lisha Chen a,b,c,1, Chunlin Li a,b,c, Yimin Zhu a,* a Key Laboratory for Nano-Bio Interface Research, Suzhou Key Laboratory for Nanotheranostics, Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou 215123, China b Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China c University of Chinese Academy of Sciences, Beijing 100049, China ARTICLE INFO ABSTRACT Article history: Accumulating evidence suggests that cancer stem cells (CSCs) are heterogeneous populations and their Received 30 September 2014 phenotypes are unstable. A number of intrinsic and extrinsic mechanisms contribute to CSC phenotypic Received in revised form 18 November variation. The existence of various CSC subpopulations which would lead to a rapid relapse after primary 2014 treatments might pose a problem for CSC targeted therapeutics. In order to develop more effective ap- Accepted 18 November 2014 proaches to cancer therapeutics, more CSC-related surface markers or targeting molecules, as well as some novel targeting strategies should be explored. This review summarized the origin and performance of Keywords: heterogeneity in CSCs and discussed their therapeutic implications. Cancer stem cell Heterogeneity © 2014 Elsevier Ireland Ltd. All rights reserved. Surface marker Targeting therapy Introduction which cause heterogeneous in macroscopic feature, microscope ap- pearance and clinical outcomes, define the heterogeneity of CSCs In the past two decades, significant progress has been made in [20].
    [Show full text]
  • Tumor Heterogeneity: a Great Barrier in the Age of Cancer Immunotherapy
    cancers Review Tumor Heterogeneity: A Great Barrier in the Age of Cancer Immunotherapy Nader El-Sayes 1,†, Alyssa Vito 1,† and Karen Mossman 2,* 1 Department of Biochemistry and Biomedical Sciences, McMaster Immunology Research Centre, McMaster University, Hamilton, ON L8S 4K1, Canada; [email protected] (N.E.-S.); [email protected] (A.V.) 2 Department of Medicine, McMaster Immunology Research Centre, McMaster University, Hamilton, ON L8S 4K1, Canada * Correspondence: [email protected] † These authors contributed equally to this publication. Simple Summary: Despite great advances in cancer therapy, tumor heterogeneity continues to be a great barrier for the successful treatment of cancer. It has long been established that tumor heterogeneity is prevelant in most cancer patients and is a major driver of acquired resistance to all forms of cancer therapy. In the case of immunotherapy, the response of the immune system against specific tumor antigens can drive selective pressure towards antigen-negative cells, which is a common cause of relapse in the clinic. In this review we summarize the mechanisms in which tumor heterogeity can arise. Furthermore, we discuss recent advances in the field of oncology that can be used to better identify, study, and overcome tumor heterogeneity. Abstract: Throughout the history of oncology research, tumor heterogeneity has been a major hurdle for the successful treatment of cancer. As a result of aberrant changes in the tumor microenvironment such as high mutational burden, hypoxic conditions and abnormal vasculature, several malignant subpopulations often exist within a single tumor mass. Therapeutic intervention can also increase Citation: El-Sayes, N.; Vito, A.; selective pressure towards subpopulations with acquired resistance.
    [Show full text]
  • UNDERSTANDING CANCER: Tumour Heterogeneity
    PIP Digest UNDERSTANDING CANCER: Tumour Heterogeneity The genetic diversity or ‘heterogeneity’ of cancer makes it a complex and challenging disease. This PIP Digest explains what the concept of tumour heterogeneity means for cancer treatment. Key Concepts • Intratumour heterogeneity • Clonal evolution • Cancer stem cells Related PIP Digests • Understanding Cancer: Epigenetics 101 • Understanding Cancer: Cancer Biomarker Basics • Clinical Trials: Precision Medicine and Clinical Trials “Every individual specimen of cancer is its own individual specimen of cancer. We have not encountered in our history a disease where every single instance of the disease is its own instance of the disease. That is a unique thing about cancer." -- Siddhartha Mukherjee (2017) For a very long time, cancer was considered a mass of fast-growing cells with similar mutations that could respond if only researchers could fine an effective treatment. Over time, though, researchers discovered that cancer not only varies between patients (interpatient heterogeneity), but that there is variation within one person’s tumours (intertumour heterogeneity) and even within a single tumour (intratumour heterogeneity). Tumour heterogeneity describes differences in cancer cells’ shape and structure (morphology), gene expression, metabolism, and capacity to move, proliferate, and metastasize. For example, prostate cancer has been described as “multi-focal.” This means that men with prostate cancer often have multiple tumours, each of which evolves independently and has different mutations. These variations greatly affect clinical care. A single biopsy or tissue sample cannot reveal the variability among and within tumours. A treatment plan made on partial information will likely fail to eradicate the cancer. 1 PIP Digest Tumour Heterogeneity From: https://www.ous-research.no/lothe/?k=lothe%2Fcancer+type&aid=14844 The heterogeneity of tumours is the key reason why effective cancer treatment is so challenging.
    [Show full text]