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Dakal TC, Dhakar R, Beura A, Moar K, Maurya PK, Sharma NK, Ranga V, Kumar A. Emerging methods and techniques for cancer biomarker discovery. Pathol Res Pract 2024; 262:155567. [PMID: 39232287 DOI: 10.1016/j.prp.2024.155567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 08/24/2024] [Accepted: 08/28/2024] [Indexed: 09/06/2024]
Abstract
Modern cancer research depends heavily on the identification and validation of biomarkers because they provide important information about the diagnosis, prognosis, and response to treatment of the cancer. This review will provide a comprehensive overview of cancer biomarkers, including their development phases and recent breakthroughs in transcriptomics and computational techniques for detecting these biomarkers. Blood-based biomarkers have great potential for non-invasive tumor dynamics and treatment response monitoring. These include circulating tumor DNA, exosomes, and microRNAs. Comprehensive molecular profiles are provided by multi-omic technologies, which combine proteomics, metabolomics, and genomes to support the identification of biomarkers and the targeting of therapeutic interventions. Genetic changes are detected by next-generation sequencing, and patterns of protein expression are found by protein arrays and mass spectrometry. Tumor heterogeneity and clonal evolution can be understood using metabolic profiling and single-cell studies. It is projected that the use of several biomarkers-genetic, protein, mRNA, microRNA, and DNA profiles, among others-will rise, enabling multi-biomarker analysis and improving individualised treatment plans. Biomarker identification and patient outcome prediction are further improved by developments in AI algorithms and imaging techniques. Robust biomarker validation and reproducibility require cooperation between industry, academia, and doctors. Biomarkers can provide individualized care, meet unmet clinical needs, and enhance patient outcomes despite some obstacles. Precision medicine will continue to take shape as scientific research advances and the integration of biomarkers with cutting-edge technologies continues to offer a more promising future for personalized cancer care.
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Affiliation(s)
- Tikam Chand Dakal
- Genome and Computational Biology Lab, Department of Biotechnology, Mohanlal Sukhadia University, Udaipur, Rajasthan 313001, India.
| | - Ramgopal Dhakar
- Deparment of Life Science, Mewar University, Chittorgarh, Rajasthan 312901, India
| | - Abhijit Beura
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India
| | - Kareena Moar
- Department of Biochemistry, Central University of Haryana, Mahendergarh, Haryana 123031, India
| | - Pawan Kumar Maurya
- Department of Biochemistry, Central University of Haryana, Mahendergarh, Haryana 123031, India
| | - Narendra Kumar Sharma
- Deparment of Bioscience and Biotechnology, Banasthali Vidyapith, Tonk, Rajasthan 304022, India
| | - Vipin Ranga
- DBT-NECAB, Assam Agriculture University, Jorhat, Assam 785013, India
| | - Abhishek Kumar
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India; Manipal Academy of Higher Education (MAHE) Manipal, Karnataka, India.
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Chong Y, Chang J, Zhao W, He Y, Li Y, Zhang H, Qi C. Synthesis and evaluation of novel 18 F-labeled quinazoline derivatives with low lipophilicity for tumor PET imaging. J Labelled Comp Radiopharm 2018; 61:42-53. [PMID: 28833405 DOI: 10.1002/jlcr.3538] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 07/14/2017] [Accepted: 07/31/2017] [Indexed: 01/06/2023]
Abstract
Four novel 18 F-labeled quinazoline derivatives with low lipophilicity, [18 F]4-(2-fluoroethoxy)-6,7-dimethoxyquinazoline ([18 F]I), [18 F]4-(3-((4-(2-fluoroethoxy)-7-methoxyquinazolin-6-yl)oxy)propyl)morpholine ([18 F]II), [18 F]4-(2-fluoroethoxy)-7-methoxy-6-(2-methoxyethoxy)quinazoline ([18 F]III), and [18 F]4-(2-fluoroethoxy)-6,7-bis(2-methoxyethoxy)quinazoline ([18 F]IV), were synthesized via a 2-step radiosynthesis procedure with an overall radiochemical yield of 10% to 38% (without decay correction) and radiochemical purities of >98%. The lipophilicity and stability of labeled compounds were tested in vitro. The log P values of the 4 radiotracers ranged from 0.52 to 1.07. We then performed ELISA to measure their affinities to EGFR-TK; ELISA assay results indicated that each inhibitor was specifically bounded to EGFR-TK in a dose-dependent manner. The EGFR-TK autophosphorylation IC50 values of [18 F]I, [18 F]II, [18 F]III, and [18 F]IV were 7.732, 0.4698, 0.1174, and 0.1176 μM, respectively. All labeled compounds were evaluated via cellular uptake and blocking studies in HepG2 cell lines in vitro. Cellular uptake and blocking experiment results indicated that [18 F]I and [18 F]III had excellent cellular uptake at 120-minute postinjection in HepG2 carcinoma cells (51.80 ± 3.42%ID/mg protein and 27.31 ± 1.94%ID/mg protein, respectively). Additionally, biodistribution experiments in S180 tumor-bearing mice in vivo indicated that [18 F]I had a very fast clearance in blood and a relatively high uptake ratio of tumor to blood (4.76) and tumor to muscle (1.82) at 60-minute postinjection. [18 F]III had a quick clearance in plasma, and its highest uptake ratio of tumor to muscle was 2.55 at 15-minute postinjection. These experimental results and experiences were valuable for the further exploration of novel radiotracers of quinazoline derivatives.
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Affiliation(s)
- Yan Chong
- Key Laboratory of Radiopharmaceuticals, College of Chemistry, Beijing Normal University, Beijing, People's Republic of China
| | - Jin Chang
- Key Laboratory of Radiopharmaceuticals, College of Chemistry, Beijing Normal University, Beijing, People's Republic of China
| | - Wenwen Zhao
- Key Laboratory of Radiopharmaceuticals, College of Chemistry, Beijing Normal University, Beijing, People's Republic of China
| | - Yong He
- Key Laboratory of Radiopharmaceuticals, College of Chemistry, Beijing Normal University, Beijing, People's Republic of China
| | - Yuqiao Li
- Key Laboratory of Radiopharmaceuticals, College of Chemistry, Beijing Normal University, Beijing, People's Republic of China
| | - Huabei Zhang
- Key Laboratory of Radiopharmaceuticals, College of Chemistry, Beijing Normal University, Beijing, People's Republic of China
| | - Chuanmin Qi
- Key Laboratory of Radiopharmaceuticals, College of Chemistry, Beijing Normal University, Beijing, People's Republic of China
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Chan SC, Cheng NM, Hsieh CH, Ng SH, Lin CY, Yen TC, Hsu CL, Wan HM, Liao CT, Chang KP, Wang JJ. Multiparametric imaging using 18F-FDG PET/CT heterogeneity parameters and functional MRI techniques: prognostic significance in patients with primary advanced oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiotherapy. Oncotarget 2017; 8:62606-62621. [PMID: 28977973 PMCID: PMC5617533 DOI: 10.18632/oncotarget.15904] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Accepted: 02/20/2017] [Indexed: 01/22/2023] Open
Abstract
Background In this study, PET heterogeneity was combined with functional MRI techniques to refine the prediction of prognosis in patients with oropharyngeal or hypopharyngeal squamous cell carcinoma (OHSCC). Methods A total of 124 patients with primary advanced OHSCC who underwent pretreatment 18F-FDG PET/CT, dynamic contrast-enhanced MR imaging (DCE-MRI), and diffusion-weighted MR imaging (DWI) were enrolled. Conventional and heterogeneity parameters from 18F-FDG PET as well as perfusion parameters from DCE-MRI and diffusion parameter from DWI of primary tumors were analyzed in relation to recurrence-free survival (RFS) and overall survival (OS). Results Multivariate analysis identified hypopharyngeal tumors (P = 0.038), alcohol drinking (P = 0.006), Ktrans ≤ 0.5512 (P = 0.017), and Kep ≤ 0.8872 (P = 0.005) as adverse prognostic factors for RFS. Smoking (p = 0.009), Ktrans ≤ 0.5512 (P = 0.0002), Kep ≤ 0.8872 (P = 0.004), and the PET heterogeneity parameter uniformity ≤ 0.00381 (P = 0.028) were independent predictors of poor OS. The combination of PET uniformity with DCE-MRI parameters and smoking allowed distinguishing four prognostic groups, with 3-year OS rates of 100%, 76.6%, 57.4%, and 7.1%, respectively (P < 0.0001). This prognostic system appeared superior to both the TNM staging system (P = 0.186) and the combination of conventional PET parameters with DCE-MRI (P = 0.004). Conclusions Multiparametric imaging based on PET heterogeneity and DCE-MRI parameters combined with clinical risk factors is superior to the concomitant use of functional MRI coupled with conventional PET parameters. This approach may improve the prognostic stratification of OHSCC patients.
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Affiliation(s)
- Sheng-Chieh Chan
- Department of Nuclear Medicine, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan.,Molecular Imaging Center, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Nai-Ming Cheng
- Molecular Imaging Center, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan.,Department of Nuclear Medicine, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Chia-Hsun Hsieh
- Department of Internal Medicine, Division of Medical Oncology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Shu-Hang Ng
- Department of Diagnostic Radiology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan.,Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan
| | - Chien-Yu Lin
- Department of Radiation Oncology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Tzu-Chen Yen
- Molecular Imaging Center, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan.,Department of Nuclear Medicine, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Cheng-Lung Hsu
- Department of Internal Medicine, Division of Medical Oncology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Hung-Ming Wan
- Department of Internal Medicine, Division of Medical Oncology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Chun-Ta Liao
- Department of Otorhinolaryngology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Kai-Ping Chang
- Department of Otorhinolaryngology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Jiun-Jie Wang
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan
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O'Connor JPB, Aboagye EO, Adams JE, Aerts HJWL, Barrington SF, Beer AJ, Boellaard R, Bohndiek SE, Brady M, Brown G, Buckley DL, Chenevert TL, Clarke LP, Collette S, Cook GJ, deSouza NM, Dickson JC, Dive C, Evelhoch JL, Faivre-Finn C, Gallagher FA, Gilbert FJ, Gillies RJ, Goh V, Griffiths JR, Groves AM, Halligan S, Harris AL, Hawkes DJ, Hoekstra OS, Huang EP, Hutton BF, Jackson EF, Jayson GC, Jones A, Koh DM, Lacombe D, Lambin P, Lassau N, Leach MO, Lee TY, Leen EL, Lewis JS, Liu Y, Lythgoe MF, Manoharan P, Maxwell RJ, Miles KA, Morgan B, Morris S, Ng T, Padhani AR, Parker GJM, Partridge M, Pathak AP, Peet AC, Punwani S, Reynolds AR, Robinson SP, Shankar LK, Sharma RA, Soloviev D, Stroobants S, Sullivan DC, Taylor SA, Tofts PS, Tozer GM, van Herk M, Walker-Samuel S, Wason J, Williams KJ, Workman P, Yankeelov TE, Brindle KM, McShane LM, Jackson A, Waterton JC. Imaging biomarker roadmap for cancer studies. Nat Rev Clin Oncol 2017; 14:169-186. [PMID: 27725679 PMCID: PMC5378302 DOI: 10.1038/nrclinonc.2016.162] [Citation(s) in RCA: 737] [Impact Index Per Article: 92.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.
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Affiliation(s)
- James P B O'Connor
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Eric O Aboagye
- Department of Surgery and Cancer, Imperial College, London, UK
| | - Judith E Adams
- Department of Clinical Radiology, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Hugo J W L Aerts
- Department of Radiation Oncology, Harvard Medical School, Boston, MA
| | - Sally F Barrington
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - Ambros J Beer
- Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany
| | - Ronald Boellaard
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands
| | - Sarah E Bohndiek
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Michael Brady
- CRUK and EPSRC Cancer Imaging Centre, University of Oxford, Oxford, UK
| | - Gina Brown
- Radiology Department, Royal Marsden Hospital, London, UK
| | - David L Buckley
- Division of Biomedical Imaging, University of Leeds, Leeds, UK
| | | | | | | | - Gary J Cook
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - Nandita M deSouza
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | - John C Dickson
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Caroline Dive
- Clinical and Experimental Pharmacology, CRUK Manchester Institute, Manchester, UK
| | | | - Corinne Faivre-Finn
- Radiotherapy Related Research Group, University of Manchester, Manchester, UK
| | - Ferdia A Gallagher
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Fiona J Gilbert
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | | | - Vicky Goh
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - John R Griffiths
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Ashley M Groves
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Steve Halligan
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Adrian L Harris
- CRUK and EPSRC Cancer Imaging Centre, University of Oxford, Oxford, UK
| | - David J Hawkes
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Otto S Hoekstra
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
| | - Erich P Huang
- Biometric Research Program, National Cancer Institute, Bethesda, MD
| | - Brian F Hutton
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Edward F Jackson
- Department of Medical Physics, University of Wisconsin, Madison, WI
| | - Gordon C Jayson
- Institute of Cancer Sciences, University of Manchester, Manchester, UK
| | - Andrew Jones
- Medical Physics, The Christie Hospital NHS Foundation Trust, Manchester, UK
| | - Dow-Mu Koh
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | | | - Philippe Lambin
- Department of Radiation Oncology, University of Maastricht, Maastricht, Netherlands
| | - Nathalie Lassau
- Department of Imaging, Gustave Roussy Cancer Campus, Villejuif, France
| | - Martin O Leach
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | - Ting-Yim Lee
- Imaging Research Labs, Robarts Research Institute, London, Ontario, Canada
| | - Edward L Leen
- Department of Surgery and Cancer, Imperial College, London, UK
| | - Jason S Lewis
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Yan Liu
- EORTC Headquarters, EORTC, Brussels, Belgium
| | - Mark F Lythgoe
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Prakash Manoharan
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Ross J Maxwell
- Northern Institute for Cancer Research, Newcastle University, Newcastle, UK
| | - Kenneth A Miles
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Bruno Morgan
- Cancer Studies and Molecular Medicine, University of Leicester, Leicester, UK
| | - Steve Morris
- Institute of Epidemiology and Health, University College London, London, UK
| | - Tony Ng
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - Anwar R Padhani
- Paul Strickland Scanner Centre, Mount Vernon Hospital, London, UK
| | - Geoff J M Parker
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Mike Partridge
- CRUK and EPSRC Cancer Imaging Centre, University of Oxford, Oxford, UK
| | - Arvind P Pathak
- Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Andrew C Peet
- Institute of Cancer and Genomics, University of Birmingham, Birmingham, UK
| | - Shonit Punwani
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Andrew R Reynolds
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK
| | - Simon P Robinson
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | | | - Ricky A Sharma
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Dmitry Soloviev
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Sigrid Stroobants
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Daniel C Sullivan
- Department of Radiology, Duke University School of Medicine, Durham, NC
| | - Stuart A Taylor
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Paul S Tofts
- Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Gillian M Tozer
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
| | - Marcel van Herk
- Radiotherapy Related Research Group, University of Manchester, Manchester, UK
| | - Simon Walker-Samuel
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | | | - Kaye J Williams
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Paul Workman
- CRUK Cancer Therapeutics Unit, The Institute of Cancer Research, London, UK
| | - Thomas E Yankeelov
- Institute of Computational Engineering and Sciences, The University of Texas, Austin, TX
| | - Kevin M Brindle
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Lisa M McShane
- Biometric Research Program, National Cancer Institute, Bethesda, MD
| | - Alan Jackson
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - John C Waterton
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
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Chan SC, Chang KP, Fang YHD, Tsang NM, Ng SH, Hsu CL, Liao CT, Yen TC. Tumor heterogeneity measured on F-18 fluorodeoxyglucose positron emission tomography/computed tomography combined with plasma Epstein-Barr Virus load predicts prognosis in patients with primary nasopharyngeal carcinoma. Laryngoscope 2016; 127:E22-E28. [PMID: 27435352 DOI: 10.1002/lary.26172] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Revised: 05/31/2016] [Accepted: 06/09/2016] [Indexed: 11/10/2022]
Abstract
OBJECTIVES/HYPOTHESIS Plasma Epstein-Barr virus (EBV) DNA concentrations predict prognosis in patients with nasopharyngeal carcinoma (NPC). Recent evidence also indicates that intratumor heterogeneity on F-18 fluorodeoxyglucose positron emission tomography (18 F-FDG PET) scans is predictive of treatment outcomes in different solid malignancies. Here, we sought to investigate the prognostic value of heterogeneity parameters in patients with primary NPC. STUDY DESIGN Retrospective cohort study. METHODS We examined 101 patients with primary NPC who underwent pretreatment 18 F-FDG PET/computed tomography. Circulating levels of EBV DNA were measured in all participants. The following PET heterogeneity parameters were collected: histogram-based heterogeneity parameters, second-order texture features (uniformity, contrast, entropy, homogeneity, dissimilarity, inverse difference moment), and higher-order (coarseness, contrast, busyness, complexity, strength) texture features. RESULTS The median follow-up time was 5.14 years. Total lesion glycolysis (TLG), tumor heterogeneity measured by histogram-based parameter skewness, and the majority of second-order or higher-order texture features were significantly associated with overall survival (OS) and/or recurrence-free survival (RFS). In multivariate analysis, age (P =.005), EBV DNA load (P = .0002), and uniformity (P = .001) independently predicted OS. Only skewness retained the independent prognostic significance for RFS. Tumor stage, standardized uptake value, or TLG did not show an independent association with survival endpoints. The combination of uniformity, EBV DNA load, and age resulted in a more reliable prognostic stratification (P < .001). CONCLUSIONS Tumor heterogeneity is superior to traditional PET parameters for predicting outcomes in primary NPC. The combination of uniformity with EBV DNA load can improve prognostic stratification in this clinical entity. LEVEL OF EVIDENCE 4 Laryngoscope, 127:E22-E28, 2017.
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Affiliation(s)
- Sheng-Chieh Chan
- Department of Nuclear Medicine, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan.,Molecular Imaging Center and Department of Nuclear Medicine, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Kai-Ping Chang
- Department of Otorhinolaryngology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Yu-Hua Dean Fang
- Department of Biomedical Engineering, National Cheng Kung University, Tainan, Taiwan
| | - Ngan-Ming Tsang
- Department of Radiation Oncology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Shu-Hang Ng
- Department of Diagnostic Radiology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Cheng-Lung Hsu
- Division of Medical Oncology, Department of Internal Medicine, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Chun-Ta Liao
- Department of Otorhinolaryngology, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Tzu-Chen Yen
- Molecular Imaging Center and Department of Nuclear Medicine, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan.,Department of Nuclear Medicine, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
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Diagnostic accuracy of (18)F-FDG PET/CT compared with that of contrast-enhanced MRI of the breast at 3 T. Eur J Nucl Med Mol Imaging 2015; 42:1656-1665. [PMID: 26121928 DOI: 10.1007/s00259-015-3099-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2015] [Accepted: 05/28/2015] [Indexed: 10/23/2022]
Abstract
PURPOSE To compare the diagnostic accuracy of prone (18)F-FDG PET/CT with that of contrast-enhanced MRI (CE-MRI) at 3 T in suspicious breast lesions. To evaluate the influence of tumour size on diagnostic accuracy and the use of maximum standardized uptake value (SUVMAX) thresholds to differentiate malignant from benign breast lesions. METHODS A total of 172 consecutive patients with an imaging abnormality were included in this IRB-approved prospective study. All patients underwent (18)F-FDG PET/CT and CE-MRI of the breast at 3 T in the prone position. Two reader teams independently evaluated the likelihood of malignancy as determined by (18)F-FDG PET/CT and CE-MRI independently. (18)F-FDG PET/CT data were qualitatively evaluated by visual interpretation. Quantitative assessment was performed by calculation of SUVMAX. Sensitivity, specificity, diagnostic accuracy, area under the curve and interreader agreement were calculated for all lesions and for lesions <10 mm. Histopathology was used as the standard of reference. RESULTS There were 132 malignant and 40 benign lesions; 23 lesions (13.4%) were <10 mm. Both (18)F-FDG PET/CT and CE-MRI achieved an overall diagnostic accuracy of 93%. There were no significant differences in sensitivity (p = 0.125), specificity (p = 0.344) or diagnostic accuracy (p = 1). For lesions <10 mm, diagnostic accuracy deteriorated to 91% with both (18)F-FDG PET/CT and CE-MRI. Although no significant difference was found for lesions <10 mm, CE-MRI at 3 T seemed to be more sensitive but less specific than (18)F-FDG PET/CT. Interreader agreement was excellent (κ = 0.85 and κ = 0.92). SUVMAX threshold was not helpful in differentiating benign from malignant lesions. CONCLUSION (18)F-FDG PET/CT and CE-MRI at 3 T showed equal diagnostic accuracies in breast cancer diagnosis. For lesions <10 mm, diagnostic accuracy deteriorated, but was equal for (18)F-FDG PET/CT and CE-MRI at 3 T. For lesions <10 mm, CE-MRI at 3 T seemed to be more sensitive but less specific than (18)F-FDG PET/CT. Quantitative assessment using an SUVMAX threshold for differentiating benign from malignant lesions was not helpful in breast cancer diagnosis.
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O'Farrell AC, Shnyder SD, Marston G, Coletta PL, Gill JH. Non-invasive molecular imaging for preclinical cancer therapeutic development. Br J Pharmacol 2014; 169:719-35. [PMID: 23488622 DOI: 10.1111/bph.12155] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2012] [Revised: 01/02/2013] [Accepted: 02/10/2013] [Indexed: 12/18/2022] Open
Abstract
Molecular and non-invasive imaging are rapidly emerging fields in preclinical cancer drug discovery. This is driven by the need to develop more efficacious and safer treatments, the advent of molecular-targeted therapeutics, and the requirements to reduce and refine current preclinical in vivo models. Such bioimaging strategies include MRI, PET, single positron emission computed tomography, ultrasound, and optical approaches such as bioluminescence and fluorescence imaging. These molecular imaging modalities have several advantages over traditional screening methods, not least the ability to quantitatively monitor pharmacodynamic changes at the cellular and molecular level in living animals non-invasively in real time. This review aims to provide an overview of non-invasive molecular imaging techniques, highlighting the strengths, limitations and versatility of these approaches in preclinical cancer drug discovery and development.
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Affiliation(s)
- A C O'Farrell
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
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Morphological, functional and metabolic imaging biomarkers: assessment of vascular-disrupting effect on rodent liver tumours. Eur Radiol 2010; 20:2013-26. [PMID: 20182730 DOI: 10.1007/s00330-010-1743-5] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2009] [Revised: 01/06/2010] [Accepted: 01/14/2010] [Indexed: 12/16/2022]
Abstract
OBJECTIVES To evaluate effects of a vascular-disrupting agent on rodent tumour models. METHODS Twenty rats with liver rhabdomyosarcomas received ZD6126 intravenously at 20 mg/kg, and 10 vehicle-treated rats were used as controls. Multiple sequences, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) with the microvascular permeability constant (K), were acquired at baseline, 1 h, 24 h and 48 h post-treatment by using 1.5-T MRI. [(18)F]fluorodeoxyglucose micro-positron emission tomography ((18)F-FDG microPET) was acquired pre- and post-treatment. The imaging biomarkers including tumour volume, enhancement ratio, necrosis ratio, apparent diffusion coefficient (ADC) and K from MRI, and maximal standardised uptake value (SUV(max)) from FDG microPET were quantified and correlated with postmortem microangiography and histopathology. RESULTS In the ZD6126-treated group, tumours grew slower with higher necrosis ratio at 48 h (P < 0.05), corresponding well to histopathology; tumour K decreased from 1 h until 24 h, and partially recovered at 48 h (P < 0.05), parallel to the evolving enhancement ratios (P < 0.05); ADCs varied with tumour viability and perfusion; and SUV(max) dropped at 24 h (P < 0.01). Relative K of tumour versus liver at 48 h correlated with relative vascular density on microangiography (r = 0.93, P < 0.05). CONCLUSIONS The imaging biomarkers allowed morphological, functional and metabolic quantifications of vascular shutdown, necrosis formation and tumour relapse shortly after treatment. A single dose of ZD6126 significantly diminished tumour blood supply and growth until 48 h post-treatment.
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Abstract
Theragnostics is a treatment strategy that combines therapeutics with diagnostics. It associates both a diagnostic test that identifies patients most likely to be helped or harmed by a new medication, and targeted drug therapy based on the test results. Bioinformatics, genomics, proteomics, and functional genomics are molecular biology tools essential for the progress of molecular theragnostics. These tools generate the genetic and protein information required for the development of diagnostic assays. Theragnostics includes a wide range of subjects, including personalized medicine, pharmacogenomics, and molecular imaging to develop efficient new targeted therapies with adequate benefit/risk to patients and a better molecular understanding of how to optimize drug selection. Furthermore, theragnostics aims to monitor the response to the treatment, to increase drug efficacy and safety. In addition, theragnostics could eliminate the unnecessary treatment of patients for whom therapy is not appropriate, resulting in significant drug cost savings for the healthcare system. However, the introduction of theragnostic tests into routine health care requires both a demonstration of cost-effectiveness and the availability of appropriate accessible testing systems. This review reports validation studies in oncology and infectious diseases that have demonstrated the benefits of such approach in well-defined subpopulations of patients, moving the field from the drug development process toward clinical practice and routine application. Theragnostics may change the usual business model of pharmaceutical companies from the classic blockbuster model toward targeted therapies.
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