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Han Z, Shen Z, Pei J, You Q, Zhang Q, Wang L. Transformation of peptides to small molecules in medicinal chemistry: Challenges and opportunities. Acta Pharm Sin B 2024; 14:4243-4265. [PMID: 39525591 PMCID: PMC11544290 DOI: 10.1016/j.apsb.2024.06.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/14/2024] [Accepted: 06/11/2024] [Indexed: 11/16/2024] Open
Abstract
Peptides are native binders involved in numerous physiological life procedures, such as cellular signaling, and serve as ready-made regulators of biochemical processes. Meanwhile, small molecules compose many drugs owing to their outstanding advantages of physiochemical properties and synthetic convenience. A novel field of research is converting peptides into small molecules, providing a convenient portable solution for drug design or peptidomic research. Endowing properties of peptides onto small molecules can evolutionarily combine the advantages of both moieties and improve the biological druggability of molecules. Herein, we present eight representative recent cases in this conversion and elaborate on the transformation process of each case. We discuss the innovative technological methods and research approaches involved, and analyze the applicability conditions of the approaches and methods in each case, guiding further modifications of peptides to small molecules. Finally, based on the aforementioned cases, we summarize a general procedure for peptide-to-small molecule modifications, listing the technological methods available for each transformation step and providing our insights on the applicable scenarios for these methods. This review aims to present the progress of peptide-to-small molecule modifications and propose our thoughts and perspectives for future research in this field.
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Affiliation(s)
- Zeyu Han
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing 210009, China
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Zekai Shen
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing 210009, China
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Jiayue Pei
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing 210009, China
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Qidong You
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing 210009, China
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Qiuyue Zhang
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing 210009, China
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Lei Wang
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Design and Optimization, China Pharmaceutical University, Nanjing 210009, China
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
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Desai N, Chavda V, Singh TRR, Thorat ND, Vora LK. Cancer Nanovaccines: Nanomaterials and Clinical Perspectives. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2401631. [PMID: 38693099 DOI: 10.1002/smll.202401631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 03/30/2024] [Indexed: 05/03/2024]
Abstract
Cancer nanovaccines represent a promising frontier in cancer immunotherapy, utilizing nanotechnology to augment traditional vaccine efficacy. This review comprehensively examines the current state-of-the-art in cancer nanovaccine development, elucidating innovative strategies and technologies employed in their design. It explores both preclinical and clinical advancements, emphasizing key studies demonstrating their potential to elicit robust anti-tumor immune responses. The study encompasses various facets, including integrating biomaterial-based nanocarriers for antigen delivery, adjuvant selection, and the impact of nanoscale properties on vaccine performance. Detailed insights into the complex interplay between the tumor microenvironment and nanovaccine responses are provided, highlighting challenges and opportunities in optimizing therapeutic outcomes. Additionally, the study presents a thorough analysis of ongoing clinical trials, presenting a snapshot of the current clinical landscape. By curating the latest scientific findings and clinical developments, this study aims to serve as a comprehensive resource for researchers and clinicians engaged in advancing cancer immunotherapy. Integrating nanotechnology into vaccine design holds immense promise for revolutionizing cancer treatment paradigms, and this review provides a timely update on the evolving landscape of cancer nanovaccines.
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Affiliation(s)
- Nimeet Desai
- Department of Biomedical Engineering, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502285, India
| | - Vivek Chavda
- Department of Pharmaceutics and Pharmaceutical Technology, L M College of Pharmacy, Ahmedabad, 380009, India
| | | | - Nanasaheb D Thorat
- Limerick Digital Cancer Research Centre (LDCRC), University of Limerick, Castletroy, Limerick, V94T9PX, Ireland
- Department of Physics, Bernal Institute, Castletroy, Limerick, V94T9PX, Ireland
- Nuffield Department of Women's & Reproductive Health, Medical Science Division, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Lalitkumar K Vora
- School of Pharmacy, Queen's University Belfast, 97 Lisburn Road, Belfast, BT9 7BL, UK
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Shankar LK, Schöder H, Sharon E, Wolchok J, Knopp MV, Wahl RL, Ellingson BM, Hall NC, Yaffe MJ, Towbin AJ, Farwell MD, Pryma D, Poussaint TY, Wright CL, Schwartz L, Harisinghani M, Mahmood U, Wu AM, Leung D, de Vries EGE, Tang Y, Beach G, Reeves SA. Harnessing imaging tools to guide immunotherapy trials: summary from the National Cancer Institute Cancer Imaging Steering Committee workshop. Lancet Oncol 2023; 24:e133-e143. [PMID: 36858729 PMCID: PMC10119769 DOI: 10.1016/s1470-2045(22)00742-2] [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: 09/08/2022] [Revised: 11/18/2022] [Accepted: 11/30/2022] [Indexed: 03/02/2023]
Abstract
As the immuno-oncology field continues the rapid growth witnessed over the past decade, optimising patient outcomes requires an evolution in the current response-assessment guidelines for phase 2 and 3 immunotherapy clinical trials and clinical care. Additionally, investigational tools-including image analysis of standard-of-care scans (such as CT, magnetic resonance, and PET) with analytics, such as radiomics, functional magnetic resonance agents, and novel molecular-imaging PET agents-offer promising advancements for assessment of immunotherapy. To document current challenges and opportunities and identify next steps in immunotherapy diagnostic imaging, the National Cancer Institute Clinical Imaging Steering Committee convened a meeting with diverse representation among imaging experts and oncologists to generate a comprehensive review of the state of the field.
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Affiliation(s)
- Lalitha K Shankar
- Clinical Trials Branch, National Cancer Institute, Rockville, MD, USA.
| | - Heiko Schöder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Elad Sharon
- Investigational Drug Branch, National Cancer Institute, Rockville, MD, USA
| | - Jedd Wolchok
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Michael V Knopp
- Department of Radiology, Ohio State University, Columbus, OH, USA
| | - Richard L Wahl
- Department of Radiology, Washington University, St Louis, MO, USA
| | - Benjamin M Ellingson
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Nathan C Hall
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Martin J Yaffe
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Alexander J Towbin
- Department of Radiology and Medical Imaging, Cincinnati Children's Hospital, Cincinnati, OH, USA
| | - Michael D Farwell
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel Pryma
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | - Umar Mahmood
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Anna M Wu
- Department of Immunology & Theranostics, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | | | - Elisabeth G E de Vries
- Department of Medical Oncology, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
| | | | | | - Steven A Reeves
- Coordinating Center for Clinical Trials, National Cancer Institute, Rockville, MD, USA
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Ling T, Zhang L, Peng R, Yue C, Huang L. Prognostic value of 18F-FDG PET/CT in patients with advanced or metastatic non-small-cell lung cancer treated with immune checkpoint inhibitors: A systematic review and meta-analysis. Front Immunol 2022; 13:1014063. [PMID: 36466905 PMCID: PMC9713836 DOI: 10.3389/fimmu.2022.1014063] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/20/2022] [Indexed: 08/30/2023] Open
Abstract
PURPOSE This study aimed to investigate the value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting early immunotherapy response of immune checkpoint inhibitors (ICIs) in patients with advanced or metastatic non-small-cell lung cancer (NSCLC). METHODS A comprehensive search of PubMed, Web of science, Embase and the Cochrane library was performed to examine the prognostic value of 18F-FDG PET/CT in predicting early immunotherapy response of ICIs in patients with NSCLC. The main outcomes for evaluation were overall survival (OS) and progression-free survival (PFS). Detailed data from each study were extracted and analyzed using STATA 14.0 software. RESULTS 13 eligible articles were included in this systematic review. Compared to baseline 18F-FDG PET/CT imaging, the pooled hazard ratios (HR) of maximum and mean standardized uptake values SUVmax, SUVmean, MTV and TLG for OS were 0.88 (95% CI: 0.69-1.12), 0.79 (95% CI: 0.50-1.27), 2.10 (95% CI: 1.57-2.82) and 1.58 (95% CI: 1.03-2.44), respectively. The pooled HR of SUVmax, SUVmean, MTV and TLG for PFS were 1.06 (95% CI: 0.68-1.65), 0.66 (95% CI: 0.48-0.90), 1.50 (95% CI: 1.26-1.79), 1.27 (95% CI: 0.92-1.77), respectively. Subgroup analysis showed that high MTV group had shorter OS than low MTV group in both first line group (HR: 1.97, 95% CI: 1.39-2.79) and undefined line group (HR: 2.11, 95% CI: 1.61-2.77). High MTV group also showed a shorter PFS in first line group (HR: 1.85, 95% CI: 1.28-2.68), and low TLG group had a longer OS in undefined group (HR: 1.37, 95% CI: 1.00-1.86). No significant differences were in other subgroup analysis. CONCLUSION Baseline MTV and TLG may have predictive value and should be prospectively studied in clinical trials. Baseline SUVmax and SUVmean may not be appropriate prognostic markers in advanced or metastatic NSCLC patients treated with ICIs. SYSTEMATIC REVIEW REGISTRATION https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=323906, identifier CRD42022323906.
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Affiliation(s)
- Tao Ling
- Department of Pharmacy, Suqian First Hospital, Suqian, China
| | - Lianghui Zhang
- Department of Oncology, Changzhou Traditional Chinese Medicine Hospital, Changzhou, China
| | - Rui Peng
- Department of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Chao Yue
- Department of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Lingli Huang
- Department of Pharmacy, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
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Liberini V, Mariniello A, Righi L, Capozza M, Delcuratolo MD, Terreno E, Farsad M, Volante M, Novello S, Deandreis D. NSCLC Biomarkers to Predict Response to Immunotherapy with Checkpoint Inhibitors (ICI): From the Cells to In Vivo Images. Cancers (Basel) 2021; 13:4543. [PMID: 34572771 PMCID: PMC8464855 DOI: 10.3390/cancers13184543] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 09/06/2021] [Accepted: 09/08/2021] [Indexed: 12/24/2022] Open
Abstract
Lung cancer remains the leading cause of cancer-related death, and it is usually diagnosed in advanced stages (stage III or IV). Recently, the availability of targeted strategies and of immunotherapy with checkpoint inhibitors (ICI) has favorably changed patient prognosis. Treatment outcome is closely related to tumor biology and interaction with the tumor immune microenvironment (TME). While the response in molecular targeted therapies relies on the presence of specific genetic alterations in tumor cells, accurate ICI biomarkers of response are lacking, and clinical outcome likely depends on multiple factors that are both host and tumor-related. This paper is an overview of the ongoing research on predictive factors both from in vitro/ex vivo analysis (ranging from conventional pathology to molecular biology) and in vivo analysis, where molecular imaging is showing an exponential growth and use due to technological advancements and to the new bioinformatics approaches applied to image analyses that allow the recovery of specific features in specific tumor subclones.
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Affiliation(s)
- Virginia Liberini
- Department of Medical Science, Division of Nuclear Medicine, University of Turin, 10126 Turin, Italy;
- Nuclear Medicine Department, S. Croce e Carle Hospital, 12100 Cuneo, Italy
| | - Annapaola Mariniello
- Thoracic Oncology Unit, Department of Oncology, S. Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy; (A.M.); (M.D.D.); (S.N.)
| | - Luisella Righi
- Pathology Unit, Department of Oncology, S. Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy; (L.R.); (M.V.)
| | - Martina Capozza
- Molecular & Preclinical Imaging Centers, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Italy; (M.C.); (E.T.)
| | - Marco Donatello Delcuratolo
- Thoracic Oncology Unit, Department of Oncology, S. Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy; (A.M.); (M.D.D.); (S.N.)
| | - Enzo Terreno
- Molecular & Preclinical Imaging Centers, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Italy; (M.C.); (E.T.)
| | - Mohsen Farsad
- Nuclear Medicine, Central Hospital Bolzano, 39100 Bolzano, Italy;
| | - Marco Volante
- Pathology Unit, Department of Oncology, S. Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy; (L.R.); (M.V.)
| | - Silvia Novello
- Thoracic Oncology Unit, Department of Oncology, S. Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy; (A.M.); (M.D.D.); (S.N.)
| | - Désirée Deandreis
- Department of Medical Science, Division of Nuclear Medicine, University of Turin, 10126 Turin, Italy;
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The Role of the Immune Metabolic Prognostic Index in Patients with Non-Small Cell Lung Cancer (NSCLC) in Radiological Progression during Treatment with Nivolumab. Cancers (Basel) 2021; 13:cancers13133117. [PMID: 34206545 PMCID: PMC8268031 DOI: 10.3390/cancers13133117] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 06/08/2021] [Accepted: 06/20/2021] [Indexed: 12/15/2022] Open
Abstract
Simple Summary Identifying reliable prognostic biomarkers of progression in the early phases of treatment is crucial in patients undergoing immune checkpoints inhibitors (ICI) administration for advanced non-small cell lung cancer (NSCLC). With this aim, in this study we combined the prognostic power of the degree of systemic inflammation (depicted by peripheral inflammation indexes), the quantification of the metabolically active tumor burden (estimated using 18F-fluorodeoxyglucose positron emission tomography/computed tomography) as well as their combination in NSCLC patients receiving immune checkpoints inhibitors. This combined approach could be used to improve the risk stratification and the subsequent clinical management in NSCLC patients treated with immune checkpoints inhibitors. Abstract An emerging clinical need is represented by identifying reliable biomarkers able to discriminate between responders and non-responders among patients showing imaging progression during the administration of immune checkpoints inhibitors for advanced non-small cell lung cancer (NSCLC). In the present study, we analyzed the prognostic power of peripheral-blood systemic inflammation indexes and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) in this clinical setting. In 45 patients showing radiological progression (defined as RECIST 1.1 progressive disease) during Nivolumab administration, the following lab and imaging parameters were collected: neutrophil-to-lymphocyte ratio (NLR), derived-NLR (dNLR), lymphocyte-to-monocyte ratio (LMR), platelets-to-lymphocyte ratio (PLR), systemic inflammation index (SII), maximum standardized uptake value, metabolic tumor volume (MTV), and total lesion glycolysis (TLG). MTV and SII independently predicted OS. Their combination in the immune metabolic prognostic index (IMPI) allowed the identification of patients who might benefit from immunotherapy continuation, despite radiological progression. The combination of FDG PET/CT volumetric data with SII also approximates the immune-metabolic response with respect to baseline, providing additional independent prognostic insights. In conclusion, the degree of systemic inflammation, the quantification of the metabolically active tumor burden, and their combination might disclose the radiological progression in NSCLC patients receiving Nivolumab.
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Zarogoulidis P, Sardeli C, Christakidis V, Hohenforst-Schmidt W, Huang H, Kosmidis C, Vagionas A, Baka S, Tsakiridis K, Perdikouri EI, Romanidis K, Sapalidis K. PD-L1 and standardized uptake value expression in lung cancer: a possible connection for efficient early lung cancer treatment. Biomark Med 2021; 15:463-466. [PMID: 33733828 DOI: 10.2217/bmm-2020-0485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- Paul Zarogoulidis
- 3rd University General Hospital, 'AHEPA' University Hospital, Thessaloniki, Greece
| | - Chrysanthi Sardeli
- Intensive Care Unit, 'AHEPA' University Hospital, Aristotle University of Thessaloniki, Medical School, Thessaloniki, Greece
| | | | - Wolfgang Hohenforst-Schmidt
- Department of Cardiology/Pulmonology/Intensive Care/Nephrology, Sana Clinic Group Franken,'Hof' Clinics, University of Erlangen, Hof, Germany
| | - Haidong Huang
- Department of Respiratory & Critical Care Medicine, Changhai Hospital, The Second Military Medical University, Shanghai, PR China
| | | | | | - Sofia Baka
- Oncology Department, Interbalkan European Medical Center, Thessaloniki, Greece
| | - Kosmas Tsakiridis
- Thoracic Surgery Department, 'Interbalkan' European Medical Center, Thessaloniki, Greece
| | | | - Konstantinos Romanidis
- Second Department of Surgery, University Hospital of Alexandroupolis, Medical School, Democritus University of Thrace, Alexandroupolis, Greece
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Pleszczyński M. Implementation of the computer tomography parallel algorithms with the incomplete set of data. PeerJ Comput Sci 2021; 7:e339. [PMID: 33816990 PMCID: PMC7959649 DOI: 10.7717/peerj-cs.339] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 11/28/2020] [Indexed: 06/12/2023]
Abstract
Computer tomography has a wide field of applicability; however, most of its applications assume that the data, obtained from the scans of the examined object, satisfy the expectations regarding their amount and quality. Unfortunately, sometimes such expected data cannot be achieved. Then we deal with the incomplete set of data. In the paper we consider an unusual case of such situation, which may occur when the access to the examined object is difficult. The previous research, conducted by the author, showed that the CT algorithms can be used successfully in this case as well, but the time of reconstruction is problematic. One of possibilities to reduce the time of reconstruction consists in executing the parallel calculations. In the analyzed approach the system of linear equations is divided into blocks, such that each block is operated by a different thread. Such investigations were performed only theoretically till now. In the current paper the usefulness of the parallel-block approach, proposed by the author, is examined. The conducted research has shown that also for an incomplete data set in the analyzed algorithm it is possible to select optimal values of the reconstruction parameters. We can also obtain (for a given number of pixels) a reconstruction with a given maximum error. The paper indicates the differences between the classical and the examined problem of CT. The obtained results confirm that the real implementation of the parallel algorithm is also convergent, which means it is useful.
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Belgioia L, Morbelli SD, Corvò R. Prediction of Response in Head and Neck Tumor: Focus on Main Hot Topics in Research. Front Oncol 2021; 10:604965. [PMID: 33489911 PMCID: PMC7821385 DOI: 10.3389/fonc.2020.604965] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 11/26/2020] [Indexed: 11/13/2022] Open
Abstract
Radiation therapy is a cornerstone in the treatment of head and neck cancer patients; actually, their management is based on clinical and radiological staging with all patients at the same stage treated in the same way. Recently the increasing knowledge in molecular characterization of head and neck cancer opens the way for a more tailored treatment. Patient outcomes could be improved by a personalized radiotherapy beyond technological and anatomical precision. Several tumor markers are under evaluation to understand their possible prognostic or predictive value. In this paper we discuss those markers specific for evaluate response to radiation therapy in head and neck cancer for a shift toward a biological personalization of radiotherapy.
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Affiliation(s)
- Liliana Belgioia
- Radiation Oncology Department, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Health Science Department (DISSAL), University of Genoa, Genoa, Italy
| | - Silvia Daniela Morbelli
- Health Science Department (DISSAL), University of Genoa, Genoa, Italy
- Nuclear Medicine Department, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Renzo Corvò
- Radiation Oncology Department, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Health Science Department (DISSAL), University of Genoa, Genoa, Italy
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