RESUMEN
Recent advances in molecular diagnostics have markedly expanded our understanding of the genetic underpinnings of lymphomas and catalysed a transformation in not just how we classify lymphomas, but also how we treat, target, and monitor affected patients. Reflecting these advances, the World Health Organization Classification, International Consensus Classification, and National Comprehensive Cancer Network guidelines were recently updated to better integrate these molecular insights into clinical practice. We summarise here the molecular biomarkers of lymphomas with an emphasis on biomarkers that have well-supported prognostic and predictive utility, as well as emerging biomarkers that show promise for clinical practice. These biomarkers include: (1) diagnostic entity-defining genetic abnormalities [e.g., B-cell acute lymphoblastic leukaemia (B-ALL) with KMT2A rearrangement]; (2) molecular alterations that guide patients' prognoses (e.g., TP53 loss frequently conferring worse prognosis); (3) mutations that serve as the targets of, and often a source of acquired resistance to, small molecular inhibitors (e.g., ABL1 tyrosine kinase inhibitors for B-ALL BCR::ABL1, hindered by ABL1 kinase domain resistance mutations); (4) the growing incorporation of molecular measurable residual disease (MRD) in the management of lymphoma patients (e.g., molecular complete response and sequencing MRD-negative criteria in multiple myeloma). Altogether, our review spans the spectrum of lymphoma types, from the genetically defined subclasses of precursor B-cell lymphomas to the highly heterogeneous categories of small and large cell mature B-cell lymphomas, Hodgkin lymphomas, plasma cell neoplasms, and T/NK-cell lymphomas, and provides an expansive summary of our current understanding of their molecular pathology.
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Linfoma de Células B , Linfoma , Humanos , Pronóstico , Linfoma/diagnóstico , Linfoma/genética , Linfoma/patología , Linfoma de Células B/diagnóstico , MutaciónRESUMEN
Stroma-leukemia interactions mediated by CXCR4, CD44, VLA4, and their respective ligands contribute to therapy resistance in FLT3-ITD-mutated acute myelogenous leukemia (AML). We conducted a phase 1 study with the combination of sorafenib (a FLT3-ITD inhibitor), plerixafor (a SDF-1/CXCR4 inhibitor), and G-CSF (that cleaves SDF-1, CD44, and VLA4). Twenty-eight patients with relapsed/refractory FLT3-ITD-mutated AML were enrolled from December 2010 to December 2013 at three dose levels of sorafenib (400, 600, and 800 mg twice daily) and G-CSF and plerixafor were administered every other day for seven doses starting on day one. Sorafenib 800 mg twice daily was selected for the expansion phase. While no dose-limiting toxicities (DLT) were encountered in the four-week DLT window, hand-foot syndrome and rash were seen beyond the DLT window, which required dose reductions in most patients. The response rate was 36% (complete response (CR) = 4, complete remission with incomplete platelet recovery (CRp) = 4, complete remission with incomplete hematologic recovery (CRi) = 1, and partial response (PR) = 1) for the intention to treat population. Treatment resulted in 58.4 and 47 mean fold mobilization of blasts and CD34 /38- stem/progenitor cells, respectively, to the circulation. Expression of the adhesion molecules CXCR4, CD44, and VLA4 on circulating leukemia cells correlated negatively with the mobilization of CD34+/38-, CD34+/38-/123+ "progenitor" cells (all P ≤ .002). Mass cytometry analysis of sequential samples from two patients demonstrated resistance emerging early on from sub-clones with persistent Akt and/or ERK signaling. In conclusion, the strategy of combined inhibition of FLT3 kinase and stromal adhesive interactions has promising activity in relapsed/refractory, FLT3-ITD-mutated AML, which warrants further evaluation in the front-line setting.
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Protocolos de Quimioterapia Combinada Antineoplásica/administración & dosificación , Leucemia Mieloide Aguda , Mutación , Tirosina Quinasa 3 Similar a fms , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Protocolos de Quimioterapia Combinada Antineoplásica/efectos adversos , Bencilaminas , Ciclamas , Supervivencia sin Enfermedad , Femenino , Factor Estimulante de Colonias de Granulocitos/administración & dosificación , Factor Estimulante de Colonias de Granulocitos/efectos adversos , Compuestos Heterocíclicos/administración & dosificación , Compuestos Heterocíclicos/efectos adversos , Humanos , Leucemia Mieloide Aguda/sangre , Leucemia Mieloide Aguda/tratamiento farmacológico , Leucemia Mieloide Aguda/genética , Leucemia Mieloide Aguda/mortalidad , Masculino , Persona de Mediana Edad , Sorafenib/administración & dosificación , Sorafenib/efectos adversos , Tasa de Supervivencia , Tirosina Quinasa 3 Similar a fms/sangre , Tirosina Quinasa 3 Similar a fms/genéticaRESUMEN
The classification and risk stratification of myeloid neoplasms, including acute myeloid leukemia, myelodysplastic syndromes, myelodysplastic syndromes/myeloproliferative neoplasms, and myeloproliferative neoplasms, have increasingly been guided by molecular genetic abnormalities. Gene expression analysis and next-generation sequencing have led to the ever increasing discovery of somatic gene mutations in myeloid neoplasms. Mutations have been identified in genes involved in epigenetic modification, RNA splicing, transcription factors, DNA repair, and the cohesin complex. These new somatic/acquired gene mutations have refined the classification of myeloid neoplasms and have been incorporated into the 2016 update of the World Health Organization (WHO) classification and the National Comprehensive Cancer Network guidelines. They have also been helpful in the development of new targeted therapeutic agents. In the present review, we describe the clinical utility of recently identified, clinically important gene mutations in myeloid neoplasms, including those incorporated in the 2016 update of the WHO classification.
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Leucemia Mieloide/genética , Mutación , Síndromes Mielodisplásicos/genética , Trastornos Mieloproliferativos/genética , Enfermedad Aguda , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Leucemia Mieloide/diagnóstico , Leucemia Mieloide/tratamiento farmacológico , Terapia Molecular Dirigida , Síndromes Mielodisplásicos/diagnóstico , Síndromes Mielodisplásicos/tratamiento farmacológico , Trastornos Mieloproliferativos/diagnóstico , Trastornos Mieloproliferativos/tratamiento farmacológico , Pronóstico , Organización Mundial de la SaludRESUMEN
BACKGROUND: Next generation sequencing based tumor tissue genotyping involves complex workflow and a relatively longer turnaround time. Semiconductor based next generation platforms varied from low throughput Ion PGM to high throughput Ion Proton and Ion S5XL sequencer. In this study, we compared Ion PGM and Ion Proton, with a new Ion S5XL NGS system for workflow scalability, analytical sensitivity and specificity, turnaround time and sequencing performance in a clinical laboratory. METHODS: Eighteen solid tumor samples positive for various mutations as detected previously by Ion PGM and Ion Proton were selected for study. Libraries were prepared using DNA (range10-40ng) from micro-dissected formalin-fixed, paraffin-embedded (FFPE) specimens using the Ion Ampliseq Library Kit 2.0 for comprehensive cancer (CCP), oncomine comprehensive cancer (OCP) and cancer hotspot panel v2 (CHPv2) panel as per manufacturer's instructions. The CHPv2 were sequenced using Ion PGM whereas CCP and OCP were sequenced using Ion Proton respectively. All the three libraries were further sequenced individually (S540) or multiplexed (S530) using Ion S5XL. For S5XL, Ion chef was used to automate template preparation, enrichment of ion spheres and chip loading. Data analysis was performed using Torrent Suite 4.6 software on board S5XL and Ion Reporter. A limit of detection and reproducibility studies was performed using serially diluted DLD1 cell line. RESULTS: A total of 241 variant calls (235 single nucleotide variants and 6 indels) expected in the studied cohort were successfully detected by S5XL with 100% and 97% concordance with Ion PGM and Proton, respectively. Sequencing run time was reduced from 4.5 to 2.5 hours with output range of 3-5 GB (S530) and 8-9.3Gb (S540). Data analysis time for the Ion S5XL is faster 1 h (S520), 2.5 h (S530) and 5 h (S540) chip, respectively as compared to the Ion PGM (3.5-5 h) and Ion Proton (8h). A limit detection of 5% allelic frequency was established along with high inter-run reproducibility. CONCLUSION: Ion S5XL system simplified workflow in a clinical laboratory, was feasible for running smaller and larger panels on the same instrument, had a shorter turnaround time, and showed good concordance for variant calls with similar sensitivity and reproducibility as the Ion PGM and Proton.