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Li JY, Zuo LP, Xu J, Sun CY. Clinical applications of circulating tumor DNA in hematological malignancies: From past to the future. Blood Rev 2024:101237. [PMID: 39261219 DOI: 10.1016/j.blre.2024.101237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 08/26/2024] [Accepted: 08/27/2024] [Indexed: 09/13/2024]
Abstract
Liquid biopsy, particularly circulating tumor DNA (ctDNA), has drawn a lot of attention as a non- or minimal-invasive detection approach for clinical applications in patients with cancer. Many hematological malignancies are well suited for serial and repeated ctDNA surveillance due to relatively high ctDNA concentrations and high loads of tumor-specific genetic and epigenetic abnormalities. Progress of detecting technology in recent years has improved sensitivity and specificity significantly, thus broadening and strengthening the potential utilities of ctDNA including early diagnosis, prognosis estimation, treatment response evaluation, minimal residual disease monitoring, targeted therapy selection, and immunotherapy surveillance. This manuscript reviews the detection methodologies, clinical application and future challenges of ctDNA in hematological malignancies, especially for lymphomas, myeloma and leukemias.
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Affiliation(s)
- Jun-Ying Li
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of science and Technology, Wuhan, Hubei, China.
| | - Li-Ping Zuo
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of science and Technology, Wuhan, Hubei, China
| | - Jian Xu
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of science and Technology, Wuhan, Hubei, China
| | - Chun-Yan Sun
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of science and Technology, Wuhan, Hubei, China.
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2
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Liu LP, Zong SY, Zhang AL, Ren YY, Qi BQ, Chang LX, Yang WY, Chen XJ, Chen YM, Zhang L, Zou Y, Guo Y, Zhang YC, Ruan M, Zhu XF. Early Detection of Molecular Residual Disease and Risk Stratification for Children with Acute Myeloid Leukemia via Circulating Tumor DNA. Clin Cancer Res 2024; 30:1143-1151. [PMID: 38170574 DOI: 10.1158/1078-0432.ccr-23-2589] [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: 08/25/2023] [Revised: 11/07/2023] [Accepted: 12/29/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE Patient-tailored minimal residual disease (MRD) monitoring based on circulating tumor DNA (ctDNA) sequencing of leukemia-specific mutations enables early detection of relapse for pre-emptive treatment, but its utilization in pediatric acute myelogenous leukemia (AML) is scarce. Thus, we aim to examine the role of ctDNA as a prognostic biomarker in monitoring response to the treatment of pediatric AML. EXPERIMENTAL DESIGN A prospective longitudinal study with 50 children with AML was launched, and sequential bone marrow (BM) and matched plasma samples were collected. The concordance of mutations by next-generation sequencing-based BM-DNA and ctDNA was evaluated. In addition, progression-free survival (PFS) and overall survival (OS) were estimated. RESULTS In 195 sample pairs from 50 patients, the concordance of leukemia-specific mutations between ctDNA and BM-DNA was 92.8%. Patients with undetectable ctDNA were linked to improved OS and PFS versus detectable ctDNA in the last sampling (both P < 0.001). Patients who cleared their ctDNA post three cycles of treatment had similar PFS compared with persistently negative ctDNA (P = 0.728). In addition, patients with >3 log reduction but without clearance in ctDNA were associated with an improved PFS as were patients with ctDNA clearance (P = 0.564). CONCLUSIONS Thus, ctDNA-based MRD monitoring appears to be a promising option to complement the overall assessment of pediatric patients with AML, wherein patients with continuous ctDNA negativity have the option for treatment de-escalation in subsequent therapy. Importantly, patients with >3 log reduction but without clearance in ctDNA may not require an aggressive treatment plan due to improved survival, but this needs further study to delineate.
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Affiliation(s)
- Li-Peng Liu
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Su-Yu Zong
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Ao-Li Zhang
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Yuan-Yuan Ren
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Ben-Quan Qi
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Li-Xian Chang
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Wen-Yu Yang
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Xiao-Juan Chen
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Yu-Mei Chen
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Li Zhang
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Yao Zou
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Ye Guo
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Ying-Chi Zhang
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Min Ruan
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Xiao-Fan Zhu
- Division of Pediatric Blood Diseases Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
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George NG, Rishi B, Singh A, Vishmaya S, Kumar R, Kushwaha N, Kaur M, Bhardwaj R, Jain A, Jain A, Chaudhry S, Misra A. Early prognosis prediction in acute myeloid and acute lymphoid leukemia patients using cell-free DNA concentration ratios. Front Mol Biosci 2024; 10:1333943. [PMID: 38317776 PMCID: PMC10840420 DOI: 10.3389/fmolb.2023.1333943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 12/29/2023] [Indexed: 02/07/2024] Open
Abstract
Background: Cell-free DNA (cfDNA) is a promising biomarker for disease prediction in many cancers, including acute leukemia (acute myeloid leukemia [AML] and acute lymphoblastic leukemia [ALL]). This study investigated the role of cfDNA in predicting relapse or unfavorable outcomes in acute leukemia patients upon initial diagnosis. Methods: Paired peripheral blood samples of 25 patients with ALL and AML were compared at baseline and induction/follow-up and clinically correlated with clinicopathological and outcome variables according to the risk category. cfDNA was isolated using commercial cfDNA extraction kits. The probability of poor outcomes in high-risk groups and a cut-off value for risk stratification minimal residual disease (MRD) positivity and outcome prediction were derived. Results: Twenty-five patients diagnosed with AML and ALL were risk-stratified based on NCI risk stratification, and of these 25 patients, 4 patients were of standard risk (SR) and 1 patient was of intermediate risk (IR), while a majority of patients (80%) were of high risk (HR). Of these, four HR patients passed away. The ratio of cfDNA reduction at baseline and the end of induction was a strong predictor of poor outcomes in high-risk patients, regardless of the MRD status. A cfDNA ratio score of 2.6 or higher at diagnosis/remission predicted poor outcomes, with higher accuracy than conventional MRD detection by flow cytometry. Conclusion: A higher cfDNA ratio at diagnosis/remission or at baseline predicts poor outcomes in acute leukemia patients. This pilot study suggests that cfDNA ratio scoring may be a useful tool for predicting prognosis in acute leukemia patients, regardless of the MRD status.
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Affiliation(s)
| | - Bhavika Rishi
- ICMR‐National Institute of Pathology, New Delhi, India
| | - Amitabh Singh
- Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India
| | - Sree Vishmaya
- Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India
| | - Rakesh Kumar
- ICMR‐National Institute of Pathology, New Delhi, India
| | | | - Manpreet Kaur
- ICMR‐National Institute of Pathology, New Delhi, India
| | | | - Ankur Jain
- Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India
| | - Aditi Jain
- Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India
| | - Sumita Chaudhry
- Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India
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Jansko-Gadermeir B, Leisch M, Gassner FJ, Zaborsky N, Dillinger T, Hutter S, Risch A, Melchardt T, Egle A, Drost M, Larcher-Senn J, Greil R, Pleyer L. Myeloid NGS Analyses of Paired Samples from Bone Marrow and Peripheral Blood Yield Concordant Results: A Prospective Cohort Analysis of the AGMT Study Group. Cancers (Basel) 2023; 15:2305. [PMID: 37190237 PMCID: PMC10136651 DOI: 10.3390/cancers15082305] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 04/10/2023] [Accepted: 04/11/2023] [Indexed: 05/17/2023] Open
Abstract
Background: Next generation sequencing (NGS) has become indispensable for diagnosis, risk stratification, prognostication, and monitoring of response in patients with myeloid neoplasias. Guidelines require bone marrow evaluations for the above, which are often not performed outside of clinical trials, indicating a need for surrogate samples. Methods: Myeloid NGS analyses (40 genes and 29 fusion drivers) of 240 consecutive, non-selected, prospectively collected, paired bone marrow/peripheral blood samples were compared. Findings: Very strong correlation (r = 0.91, p < 0.0001), high concordance (99.6%), sensitivity (98.8%), specificity (99.9%), positive predictive value (99.8%), and negative predictive value (99.6%) between NGS analyses of paired samples was observed. A total of 9/1321 (0.68%) detected mutations were discordant, 8 of which had a variant allele frequency (VAF) ≤ 3.7%. VAFs between peripheral blood and bone marrow samples were very strongly correlated in the total cohort (r = 0.93, p = 0.0001) and in subgroups without circulating blasts (r = 0.92, p < 0.0001) or with neutropenia (r = 0.88, p < 0.0001). There was a weak correlation between the VAF of a detected mutation and the blast count in either the peripheral blood (r = 0.19) or the bone marrow (r = 0.11). Interpretation: Peripheral blood samples can be used to molecularly classify and monitor myeloid neoplasms via NGS without loss of sensitivity/specificity, even in the absence of circulating blasts or in neutropenic patients.
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Affiliation(s)
- Bettina Jansko-Gadermeir
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- Laboratory of Immunological and Molecular Cancer Research (LIMCR), 5020 Salzburg, Austria
- Laboratory for Molecular Cytology (MZL), 5020 Salzburg, Austria
- Department of Biosciences and Medical Biology, Allergy-Cancer-BioNano Research Centre, University of Salzburg, 5020 Salzburg, Austria
| | - Michael Leisch
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
| | - Franz J. Gassner
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- Laboratory of Immunological and Molecular Cancer Research (LIMCR), 5020 Salzburg, Austria
| | - Nadja Zaborsky
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- Laboratory of Immunological and Molecular Cancer Research (LIMCR), 5020 Salzburg, Austria
| | - Thomas Dillinger
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Laboratory for Molecular Cytology (MZL), 5020 Salzburg, Austria
| | - Sonja Hutter
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Laboratory for Molecular Cytology (MZL), 5020 Salzburg, Austria
| | - Angela Risch
- Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- Department of Biosciences and Medical Biology, Allergy-Cancer-BioNano Research Centre, University of Salzburg, 5020 Salzburg, Austria
| | - Thomas Melchardt
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
| | - Alexander Egle
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- Laboratory of Immunological and Molecular Cancer Research (LIMCR), 5020 Salzburg, Austria
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
| | - Manuel Drost
- Assign Data Management and Biostatistics GmbH, 6020 Innsbruck, Austria
| | | | - Richard Greil
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- Laboratory of Immunological and Molecular Cancer Research (LIMCR), 5020 Salzburg, Austria
- Laboratory for Molecular Cytology (MZL), 5020 Salzburg, Austria
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
| | - Lisa Pleyer
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- Laboratory of Immunological and Molecular Cancer Research (LIMCR), 5020 Salzburg, Austria
- Laboratory for Molecular Cytology (MZL), 5020 Salzburg, Austria
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
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Chianese U, Papulino C, Megchelenbrink W, Tambaro FP, Ciardiello F, Benedetti R, Altucci L. Epigenomic machinery regulating pediatric AML: clonal expansion mechanisms, therapies, and future perspectives. Semin Cancer Biol 2023; 92:84-101. [PMID: 37003397 DOI: 10.1016/j.semcancer.2023.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 03/07/2023] [Accepted: 03/27/2023] [Indexed: 04/03/2023]
Abstract
Acute myeloid leukemia (AML) is a heterogeneous disease with a genetic, epigenetic, and transcriptional etiology mainly presenting somatic and germline abnormalities. AML incidence rises with age but can also occur during childhood. Pediatric AML (pAML) accounts for 15-20% of all pediatric leukemias and differs considerably from adult AML. Next-generation sequencing technologies have enabled the research community to "paint" the genomic and epigenomic landscape in order to identify pathology-associated mutations and other prognostic biomarkers in pAML. Although current treatments have improved the prognosis for pAML, chemoresistance, recurrence, and refractory disease remain major challenges. In particular, pAML relapse is commonly caused by leukemia stem cells that resist therapy. Marked patient-to-patient heterogeneity is likely the primary reason why the same treatment is successful for some patients but, at best, only partially effective for others. Accumulating evidence indicates that patient-specific clonal composition impinges significantly on cellular processes, such as gene regulation and metabolism. Although our understanding of metabolism in pAML is still in its infancy, greater insights into these processes and their (epigenetic) modulation may pave the way toward novel treatment options. In this review, we summarize current knowledge on the function of genetic and epigenetic (mis)regulation in pAML, including metabolic features observed in the disease. Specifically, we describe how (epi)genetic machinery can affect chromatin status during hematopoiesis, leading to an altered metabolic profile, and focus on the potential value of targeting epigenetic abnormalities in precision and combination therapy for pAML. We also discuss the possibility of using alternative epidrug-based therapeutic approaches that are already in clinical practice, either alone as adjuvant treatments and/or in combination with other drugs.
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Affiliation(s)
- Ugo Chianese
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", 80138 Naples, Italy.
| | - Chiara Papulino
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", 80138 Naples, Italy.
| | - Wout Megchelenbrink
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", 80138 Naples, Italy; Princess Máxima Center, Heidelberglaan 25, 3584 CS, Utrecht, the Netherlands.
| | - Francesco Paolo Tambaro
- Bone Marrow Transplant Unit, Pediatric Oncology Department AORN Santobono Pausilipon, 80129, Naples Italy.
| | - Fortunato Ciardiello
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", 80138 Naples, Italy.
| | - Rosaria Benedetti
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", 80138 Naples, Italy.
| | - Lucia Altucci
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", 80138 Naples, Italy; Biogem Institute of Molecular and Genetic Biology, 83031 Ariano Irpino, Italy; IEOS, Institute for Endocrinology and Oncology "Gaetano Salvatore" (IEOS), 80131 Naples, Italy.
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