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Geelen IGP, Gullaksen SE, Ilander MM, Olssen-Strömberg U, Mustjoki S, Richter J, Blijlevens NMA, Smit WM, Gjertsen BT, Gedde-Dahl T, Markevärn B, Koppes MMA, Westerweel PE, Hjorth-Hansen H, Janssen JJWM. Switching from imatinib to nilotinib plus pegylated interferon-α2b in chronic phase CML failing to achieve deep molecular response: clinical and immunological effects. Ann Hematol 2023; 102:1395-1408. [PMID: 37119314 DOI: 10.1007/s00277-023-05199-1] [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: 06/20/2022] [Accepted: 03/23/2023] [Indexed: 05/01/2023]
Abstract
In order to improve molecular response for a discontinuation attempt in chronic myeloid leukemia (CML) patients in chronic phase, who had not achieved at least a molecular response <0.01% BCR-ABL1IS (MR4.0) after at least 2 years of imatinib therapy, we prospectively evaluated whether they could attain MR4.0 after a switch to a combination of nilotinib and 9 months of pegylated interferon-α2b (PegIFN). The primary endpoint of confirmed MR4.0 at month 12 (a BCR-ABL1IS level ≤ 0.01% both at 12 and 15 months) was reached by 44% (7/16 patients, 95% confidence interval (CI): 23- 67%) of patients, with 81% (13/16 patients, 95% CI: 57-93%) of patients achieving an unconfirmed MR4.0. The scheduled combination was completed by 56% of the patients, with premature discontinuations, mainly due to mood disturbances after the introduction of PegIFN, questioning the feasibility of the combination of nilotinib and PegIFN for this patient population and treatment goal. A comprehensive clinical substudy program was implemented to characterize the impact of the treatment changes on the immunological profile. This trial was registered at www.clinicaltrials.gov as #NCT01866553.
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Affiliation(s)
- Inge G P Geelen
- Department of Internal Medicine / Hematology, Albert Schweitzer Hospital, Dordrecht, The Netherlands.
| | - Stein-Erik Gullaksen
- Centre of Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Internal Medicine, Hematology section, Helse Bergen, Bergen, Norway
| | - Mette M Ilander
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer center, Helsinki, Finland
| | | | - Satu Mustjoki
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Johan Richter
- Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
| | | | - Willem M Smit
- Department of Hematology, Medical Spectrum Twente, Enschede, The Netherlands
| | - Bjorn T Gjertsen
- Centre of Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Internal Medicine, Hematology section, Helse Bergen, Bergen, Norway
| | - Tobias Gedde-Dahl
- Department of Hematology, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Berit Markevärn
- Department of Hematology, Umeå University Hospital, Umeå, Sweden
| | - Malika M A Koppes
- Department of Hematology, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Peter E Westerweel
- Department of Internal Medicine / Hematology, Albert Schweitzer Hospital, Dordrecht, The Netherlands
| | - Henrik Hjorth-Hansen
- Department of Hematology, St Olavs Hospital, Trondheim, Norway
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Jeroen J W M Janssen
- Department of Hematology, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
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2
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Pasic I, Ren AH, Nampoothiri RV, Prassas I, Lipton JH, Mattsson J, Diamandis EP, Michelis FV. Multiplex proteomics using proximity extension assay for the identification of protein biomarkers predictive of acute graft-vs.-host disease in allogeneic hematopoietic cell transplantation. Clin Chem Lab Med 2023; 61:1005-1014. [PMID: 36655501 DOI: 10.1515/cclm-2022-0916] [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: 09/14/2022] [Accepted: 01/04/2023] [Indexed: 01/20/2023]
Abstract
OBJECTIVES Allogeneic hematopoietic cell transplantation (HCT) is associated with acute graft-vs.-host disease (aGVHD). The presented study applied a novel multiplex antibody-based proximity extension assay (PEA) proteomic platform that can detect thousands of serum proteins simultaneously for the identification of potential biomarkers of aGVHD. METHODS Serum samples from 28 patients who underwent allogeneic HCT for acute myeloid leukemia (AML) were analyzed; 17 were diagnosed with grade II-IV aGVHD while 11 patients were not. Samples collected on day -6, day 0, +14, +30, +60 and +90 post-HCT were analyzed for the relative concentrations of 552 proteins. The concentration of each protein from baseline to the closest time point before onset of aGVHD, or to the latest time point in control patients, was documented. RESULTS Individualized analysis identified 26 proteins demonstrating ≥3-fold increase at aGVHD onset compared to baseline, eliminating proteins with a similar increase in controls. Another approach used paired t-testing and logistic regression that identified a four-marker panel, including SLAMF7, IL-1ra, BTN3A2 and DAB2, where individual log-likelihood ratios ranged from 3.99 to 8.15 (logistic regression, p=0.004-0.046). When combined, the four-marker panel demonstrated an area under the curve (AUC) of 0.90 (95% CI: 0.78-1.00; p=0.0006) with high negative predictive value of 81.8% and positive predictive value of 86.7%. All four markers play a physiological role in immune regulation. Among these, three were also present in the individualized analysis (SLAMF7, IL-1ra and BTN3A2). CONCLUSIONS We conclude that serum proteins identified using multiplex proteomics, particularly SLAMF7, IL-1ra, BTN3A2 and DAB2, may potentially predict aGVHD.
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Affiliation(s)
- Ivan Pasic
- Hans Messner Allogeneic Transplant Program, Princess Margaret Hospital Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Annie H Ren
- Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Ram Vasudevan Nampoothiri
- Hans Messner Allogeneic Transplant Program, Princess Margaret Hospital Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Ioannis Prassas
- Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, ON, Canada
| | - Jeffrey H Lipton
- Hans Messner Allogeneic Transplant Program, Princess Margaret Hospital Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jonas Mattsson
- Hans Messner Allogeneic Transplant Program, Princess Margaret Hospital Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Medicine, University of Toronto, Toronto, ON, Canada.,Gloria and Seymour Epstein Chair in Cell Therapy and Transplantation, Princess Margaret Hospital Cancer Centre, Toronto, ON, Canada
| | - Eleftherios P Diamandis
- Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, ON, Canada.,Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, ON, Canada.,Department of Clinical Biochemistry, University Health Network, Toronto, ON, Canada
| | - Fotios V Michelis
- Hans Messner Allogeneic Transplant Program, Princess Margaret Hospital Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Medicine, University of Toronto, Toronto, ON, Canada
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Mehra N, Varmeziar A, Chen X, Kronick O, Fisher R, Kota V, Mitchell CS. Cross-Domain Text Mining to Predict Adverse Events from Tyrosine Kinase Inhibitors for Chronic Myeloid Leukemia. Cancers (Basel) 2022; 14:4686. [PMID: 36230609 PMCID: PMC9563938 DOI: 10.3390/cancers14194686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/04/2022] [Accepted: 09/23/2022] [Indexed: 12/02/2022] Open
Abstract
Tyrosine kinase inhibitors (TKIs) are prescribed for chronic myeloid leukemia (CML) and some other cancers. The objective was to predict and rank TKI-related adverse events (AEs), including under-reported or preclinical AEs, using novel text mining. First, k-means clustering of 2575 clinical CML TKI abstracts separated TKIs by significant (p < 0.05) AE type: gastrointestinal (bosutinib); edema (imatinib); pulmonary (dasatinib); diabetes (nilotinib); cardiovascular (ponatinib). Next, we propose a novel cross-domain text mining method utilizing a knowledge graph, link prediction, and hub node network analysis to predict new relationships. Cross-domain text mining of 30+ million articles via SemNet predicted and ranked known and novel TKI AEs. Three physiology-based tiers were formed using unsupervised rank aggregation feature importance. Tier 1 ranked in the top 1%: hematology (anemia, neutropenia, thrombocytopenia, hypocellular marrow); glucose (diabetes, insulin resistance, metabolic syndrome); iron (deficiency, overload, metabolism), cardiovascular (hypertension, heart failure, vascular dilation); thyroid (hypothyroidism, hyperthyroidism, parathyroid). Tier 2 ranked in the top 5%: inflammation (chronic inflammatory disorder, autoimmune, periodontitis); kidney (glomerulonephritis, glomerulopathy, toxic nephropathy). Tier 3 ranked in the top 10%: gastrointestinal (bowel regulation, hepatitis, pancreatitis); neuromuscular (autonomia, neuropathy, muscle pain); others (secondary cancers, vitamin deficiency, edema). Results suggest proactive TKI patient AE surveillance levels: regular surveillance for tier 1, infrequent surveillance for tier 2, and symptom-based surveillance for tier 3.
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Affiliation(s)
- Nidhi Mehra
- Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, USA
| | - Armon Varmeziar
- Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, USA
| | - Xinyu Chen
- Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, USA
| | - Olivia Kronick
- Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, USA
| | - Rachel Fisher
- Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, USA
| | - Vamsi Kota
- Division of Hematology and Oncology, Georgia Cancer Center, Augusta University, Augusta, GA 30912, USA
| | - Cassie S. Mitchell
- Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia Institute of Technology, Emory University School of Medicine, Atlanta, GA 30332, USA
- Center for Machine Learning, Georgia Institute of Technology, Atlanta, GA 30332, USA
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Breccia M, Scalzulli E, Pepe S, Colafigli G, Bisegna ML, Capriata M, Martelli M. Emerging concepts for assessing and predicting treatment-free remission in chronic myeloid leukemia patients. Expert Rev Hematol 2021; 15:25-32. [PMID: 34894984 DOI: 10.1080/17474086.2022.2018296] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION In chronic myeloid leukemia (CML) patients who have reached a deep and sustained reduction of residual disease can attempt a discontinuation. The 'treatment-free remission' (TFR) has become a real long-term endpoint for 30-40% of chronic phase patients. AREAS COVERED In this review, we focus our attention on possible prognostic features who can predict the success of tyrosine kinase inhibitors discontinuation and how we can assess the minimal residual disease (MRD) during the TFR phase. Broad research was made on Medline, Embase and archives from EHA and ASH congresses. EXPERT OPINION Median duration of TKI therapy and of deep molecular response are the main prognostic factors identified in most trials and real-life experiences on discontinuation. Immunological pathways have been proposed as possible control on successful TFR as also early molecular response dynamics. Appropriate molecular monitoring by RQ-PCR in the TFR phase has been proposed by several international recommendations and digital droplet PCR (ddPCR) seems to have a possible role in the future for a better identification of candidate to this possible therapeutic strategy.
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Affiliation(s)
- Massimo Breccia
- Department of Translational and precision medicine-Az., Policlinico Umberto I-Sapienza University, Rome, Italy
| | - Emilia Scalzulli
- Department of Translational and precision medicine-Az., Policlinico Umberto I-Sapienza University, Rome, Italy
| | - Sara Pepe
- Department of Translational and precision medicine-Az., Policlinico Umberto I-Sapienza University, Rome, Italy
| | - Gioia Colafigli
- Department of Translational and precision medicine-Az., Policlinico Umberto I-Sapienza University, Rome, Italy
| | - Maria Laura Bisegna
- Department of Translational and precision medicine-Az., Policlinico Umberto I-Sapienza University, Rome, Italy
| | - Marcello Capriata
- Department of Translational and precision medicine-Az., Policlinico Umberto I-Sapienza University, Rome, Italy
| | - Maurizio Martelli
- Department of Translational and precision medicine-Az., Policlinico Umberto I-Sapienza University, Rome, Italy
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Castagnetti F, Binotto G, Capodanno I, Billio A, Calistri E, Cavazzini F, Crugnola M, Gozzini A, Gugliotta G, Krampera M, Lucchesi A, Merli A, Miggiano MC, Minotto C, Poggiaspalla M, Salvucci M, Scappini B, Tiribelli M, Trabacchi E, Rosti G, Galimberti S, Bonifacio M. Making Treatment-Free Remission (TFR) Easier in Chronic Myeloid Leukemia: Fact-Checking and Practical Management Tools. Target Oncol 2021; 16:823-838. [PMID: 34661826 PMCID: PMC8613078 DOI: 10.1007/s11523-021-00831-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/20/2021] [Indexed: 11/24/2022]
Abstract
In chronic-phase chronic myeloid leukemia (CML), tyrosine kinase inhibitors (TKIs) are the standard of care, and treatment-free remission (TFR) following the achievement of a stable deep molecular response (DMR) has become, alongside survival, a primary goal for virtually all patients. The GIMEMA CML working party recently suggested that the possibility of achieving TFR cannot be denied to any patient, and proposed specific treatment policies according to the patient's age and risk. However, other international recommendations (including 2020 ELN recommendations) are more focused on survival and provide less detailed suggestions on how to choose first and subsequent lines of treatment. Consequently, some grey areas remain. After literature review, a panel of Italian experts discussed the following controversial issues: (1) early prediction of DMR and TFR: female sex, non-high disease risk score, e14a2 transcript and early MR achievement have been associated with stable DMR, but the lack of these criteria is not sufficient to exclude any patient from TFR; (2) criteria for first and subsequent line therapy choice: a number of patient and drug characteristics have been proposed to make a personalized decision; (3) monitoring of residual disease after discontinuation: after the first 6 months, the frequency of molecular tests can be reduced based on MR4.5 persistence and short turnaround time; (4) prognosis of TFR: therapy and DMR duration are important to predict TFR; although immunological control of CML plays a role, no immunological predictive phenotype is currently available. This guidance is intended as a practical tool to support physicians in decision making.
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Affiliation(s)
- Fausto Castagnetti
- Istituto di Ematologia "Seràgnoli", IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
- Dipartimento di Medicina Specialistica, Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy.
| | - Gianni Binotto
- Hematology and Clinical Immunology Unit, University of Padua, Padua, Italy
| | - Isabella Capodanno
- Hematology Unit, Azienda Unità Sanitaria Locale-IRCCS, Reggio Emilia, Italy
| | - Atto Billio
- Hematology and Bone Marrow Transplantation, Ospedale di Bolzano, Bolzano, Italy
| | | | | | - Monica Crugnola
- Hematology Unit and BMT, Azienda Ospedaliero Universitaria, Parma, Italy
| | - Antonella Gozzini
- Department of Cellular Therapies and Transfusion Medicine, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Gabriele Gugliotta
- Istituto di Ematologia "Seràgnoli", IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Mauro Krampera
- Section of Hematology and Bone Marrow Transplant Unit, Department of Medicine, University of Verona, Verona, Italy
| | - Alessandro Lucchesi
- Hematology Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| | - Anna Merli
- Hematology Unit, Ospedale Infermi Rimini, AUSL Romagna, Rimini, Italy
| | | | - Claudia Minotto
- Medical Oncology and Onco-Hematology Unit, AULSS 3 Serenissima distretto di Dolo-Mirano, Venice, Italy
| | - Monica Poggiaspalla
- Hematology Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| | - Marzia Salvucci
- Hematology Unit, Oncology and Hematology Department, Ospedale Civico, Ravenna, Italy
| | - Barbara Scappini
- Hematology Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Mario Tiribelli
- Division of Hematology and BMT, Department of Medical Area, University of Udine, Udine, Italy
| | - Elena Trabacchi
- Hematology Unit and BMT Center, Ospedale G. Saliceto, Piacenza, Italy
| | - Gianantonio Rosti
- Scientific Direction, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, FC, Italy
| | - Sara Galimberti
- Section of Hematology, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Massimiliano Bonifacio
- Section of Hematology and Bone Marrow Transplant Unit, Department of Medicine, University of Verona, Verona, Italy
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Identification of Immunological Parameters as Predictive Biomarkers of Relapse in Patients with Chronic Myeloid Leukemia on Treatment-Free Remission. J Clin Med 2020; 10:jcm10010042. [PMID: 33375572 PMCID: PMC7795332 DOI: 10.3390/jcm10010042] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 12/11/2020] [Accepted: 12/23/2020] [Indexed: 01/11/2023] Open
Abstract
BCR-ABL is an aberrant tyrosine kinase responsible for chronic myeloid leukemia (CML). Tyrosine kinase inhibitors (TKIs) induce a potent antileukemic response mostly based on the inhibition of BCR-ABL, but they also increase the activity of Natural Killer (NK) and CD8+ T cells. After several years, patients may interrupt treatment due to sustained, deep molecular response. By unknown reasons, half of the patients relapse during treatment interruption, whereas others maintain a potent control of the residual leukemic cells for several years. In this study, several immunological parameters related to sustained antileukemic control were analyzed. According to our results, the features more related to poor antileukemic control were as follows: low levels of cytotoxic cells such as NK, (Natural Killer T) NKT and CD8±TCRγβ+ T cells; low expression of activating receptors on the surface of NK and NKT cells; impaired synthesis of proinflammatory cytokines or proteases from NK cells; and HLA-E*0103 homozygosis and KIR haplotype BX. A Random Forest algorithm predicted 90% of the accuracy for the classification of CML patients in groups of relapse or non-relapse according to these parameters. Consequently, these features may be useful as biomarkers predictive of CML relapse in patients that are candidates to initiate treatment discontinuation.
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