Search

Current prognostic scoring systems based on clinicopathologic variables are inadequate in predicting the survival and treatment response of extranodal natural killer/T-cell lymphoma (ENKTL) patients undergoing nonanthracyline-based treatment. We aimed to construct a classifier based on single-nucleotide polymorphisms (SNPs) for improving predictive accuracy and guiding clinical decision making. Data from 722 patients with ENKTL from international centers were analyzed. A 7-SNP–based classifier was constructed using LASSO Cox regression in the training cohort (n = 336) and further validated in the internal testing cohort (n = 144) and in 2 external validation cohorts (n = 142 and n = 100). The 7-SNP–based classifier showed good prognostic predictive efficacy in the training cohort and the 3 validation cohorts. Patients with high- and low-risk scores calculated by the classifier exhibited significantly different progression-free survival (PFS) and overall survival (OS) (all P < .001). The 7-SNP–based classifier was further proved to be an independent prognostic factor by multivariate analysis, and its predictive accuracy was significantly better than clinicopathological risk variables. Application of the 7-SNP–based classifier was not affected by sample types. Notably, chemotherapy combined with radiotherapy significantly improved PFS and OS vs radiotherapy alone in high-risk Ann Arbor stage I patients, whereas there was no statistical difference between the 2 therapeutic modalities among low-risk patients. A nomogram was constructed comprising the classifier and clinicopathological variables; it showed remarkably better predictive accuracy than either variable alone. The 7-SNP–based classifier is a complement to existing risk-stratification systems in ENKTL, which could have significant implications for clinical decision making for patients with ENKTL.

Current prognostic scoring systems based on clinicopathologic variables are inadequate in predicting the survival and treatment response of extranodal natural killer/T-cell lymphoma (ENKTL) patients undergoing nonanthracyline-based treatment. We aimed to construct a classifier based on single-nucleotide polymorphisms (SNPs) for improving predictive accuracy and guiding clinical decision making. Data from 722 patients with ENKTL from international centers were analyzed. A 7-SNP–based classifier was constructed using LASSO Cox regression in the training cohort (n = 336) and further validated in the internal testing cohort (n = 144) and in 2 external validation cohorts (n = 142 and n = 100). The 7-SNP–based classifier showed good prognostic predictive efficacy in the training cohort and the 3 validation cohorts. Patients with high- and low-risk scores calculated by the classifier exhibited significantly different progression-free survival (PFS) and overall survival (OS) (all P< .001). The 7-SNP–based classifier was further proved to be an independent prognostic factor by multivariate analysis, and its predictive accuracy was significantly better than clinicopathological risk variables. Application of the 7-SNP–based classifier was not affected by sample types. Notably, chemotherapy combined with radiotherapy significantly improved PFS and OS vs radiotherapy alone in high-risk Ann Arbor stage I patients, whereas there was no statistical difference between the 2 therapeutic modalities among low-risk patients. A nomogram was constructed comprising the classifier and clinicopathological variables; it showed remarkably better predictive accuracy than either variable alone. The 7-SNP–based classifier is a complement to existing risk-stratification systems in ENKTL, which could have significant implications for clinical decision making for patients with ENKTL.

High dose Cyclophosphamide (Cy) and Vinorelbine Cyclophosphamide (Vino-Cy) are stem cell (SC) mobilisation options for patients with multiple myeloma (MM). We present a comparison of mobilisation outcomes using these regimens.

DNA alterations have been extensively reported in multiple myeloma (MM); however, they cannot yet fully explain all the biological and molecular abnormalities in MM, which remains to this day an incurable disease with eventual emergence of refractory disease. Recent years have seen abnormalities at the RNA levels being reported to possess potential biological relevance in cancers. ADAR1-mediated A-to-I editing is an important posttranscriptional mechanism in human physiology, and the biological implication of its abnormality, especially at the global level, is underexplored in MM. In this study, we define the biological implications of A-to-I editing and how it contributes to MM pathogenesis. Here, we identified that the MM transcriptome is aberrantly hyperedited because of the overexpression of ADAR1. These events were associated with patients’ survival independent of 1q21 amplifications and could affect patients’ responsiveness to different treatment regimes. Our functional assays established ADAR1 to be oncogenic, driving cellular growth and proliferation in an editing-dependent manner. In addition, we identified NEIL1 (base-excision repair gene) as an essential and a ubiquitously edited ADAR1 target in MM. The recoded NEIL1 protein showed defective oxidative damage repair capacity and loss-of-function properties. Collectively, our data demonstrated that ADAR1-mediated A-to-I editing is both clinically and biologically relevant in MM. These data unraveled novel insights into MM molecular pathogenesis at the global RNA level.

DNA alterations have been extensively reported in multiple myeloma (MM); however, they cannot yet fully explain all the biological and molecular abnormalities in MM, which remains to this day an incurable disease with eventual emergence of refractory disease. Recent years have seen abnormalities at the RNA levels being reported to possess potential biological relevance in cancers. ADAR1-mediated A-to-I editing is an important posttranscriptional mechanism in human physiology, and the biological implication of its abnormality, especially at the global level, is underexplored in MM. In this study, we define the biological implications of A-to-I editing and how it contributes to MM pathogenesis. Here, we identified that the MM transcriptome is aberrantly hyperedited because of the overexpression of ADAR1. These events were associated with patients' survival independent of 1q21 amplifications and could affect patients' responsiveness to different treatment regimes. Our functional assays established ADAR1 to be oncogenic, driving cellular growth and proliferation in an editing-dependent manner. In addition, we identified NEIL1 (base-excision repair gene) as an essential and a ubiquitously edited ADAR1 target in MM. The recoded NEIL1 protein showed defective oxidative damage repair capacity and loss-of-function properties. Collectively, our data demonstrated that ADAR1-mediated A-to-I editing is both clinically and biologically relevant in MM. These data unraveled novel insights into MM molecular pathogenesis at the global RNA level.

Immunohistochemistry (IHC) provides clinically useful information on protein expression in cancer cells. However, quantification of colocalizing signals using conventional IHC and visual scores is challenging. Here we describe the application of quantitative immunofluorescence in angioimmunoblastic T-cell lymphoma (AITL), a peripheral T-cell lymphoma characterized by cellular heterogeneity that impedes IHC interpretation and quantification. A multiplexed immunofluorescence (IF) panel comprising T- and B-lymphocyte markers along with T-follicular helper (TFH) markers was validated for appropriate cellular localization in sections of benign tonsillar tissue and tested in two samples of AITL, using a Vectra microscope for spectral imaging and InForm software for analysis. We measured the percentage positivity of the TFHmarkers, BCL6 and PD1, in AITL CD4-positive cells to be approximately 26% and 45%, with 12% coexpressing both markers. The pattern is similar to CD4 cells within the germinal center of normal tonsils and clearly distinct from extragerminal CD4 cells. This study demonstrates the feasibility of automated and quantitative imaging of a multiplexed panel of cellular markers in formalin-fixed, paraffin-embedded tissue sections of a cellularly heterogenous lymphoma. Multiplexed IF allows the simultaneous scoring of markers in malignant and immune cell populations and could potentially increase accuracy for establishment of diagnostic thresholds.

Immunohistochemistry (IHC) provides clinically useful information on protein expression in cancer cells. However, quantification of colocalizing signals using conventional IHC and visual scores is challenging. Here we describe the application of quantitative immunofluorescence in angioimmunoblastic T-cell lymphoma (AITL), a peripheral T-cell lymphoma characterized by cellular heterogeneity that impedes IHC interpretation and quantification. A multiplexed immunofluorescence (IF) panel comprising T- and B-lymphocyte markers along with T-follicular helper (TFH) markers was validated for appropriate cellular localization in sections of benign tonsillar tissue and tested in two samples of AITL, using a Vectra microscope for spectral imaging and InForm software for analysis. We measured the percentage positivity of the TFHmarkers, BCL6 and PD1, in AITL CD4-positive cells to be approximately 26% and 45%, with 12% coexpressing both markers. The pattern is similar to CD4 cells within the germinal center of normal tonsils and clearly distinct from extragerminal CD4 cells. This study demonstrates the feasibility of automated and quantitative imaging of a multiplexed panel of cellular markers in formalin-fixed, paraffin-embedded tissue sections of a cellularly heterogenous lymphoma. Multiplexed IF allows the simultaneous scoring of markers in malignant and immune cell populations and could potentially increase accuracy for establishment of diagnostic thresholds.

Multiple Myeloma (MM) is the second most common hematologic malignancy and remains incurable. Daratumumab (dara) is a potent anti-CD38 monoclonal antibody used for MM treatment, but responses are heterogeneous, and resistance is inevitable. There is hence an urgent need for identification of biomarkers to predict responses and in-depth characterisation of mechanisms of resistance.

Introduction

Background:

Background:

Introduction

The WHO defines three categories of NK cell malignancies; extra nodal NK/T cell lymphoma (NKTCL), aggressive NK cell leukemia, and the provisional entity chronic lymphoproliferative disorder of NK cells (CLPD‐NK). Although the flow cytometric (FC) phenotype of CLPD‐NK has been described, studies on FC phenotype of NKTCL are limited. To the best of our knowledge ours is the first study to compare the phenotype of NKTCL, CLPD‐NK, reactive NK lymphocytosis (RNKL), and normal NK cells using eight color (8C) FC. Specimens analyzed using the Euroflow8C NK Lymphoproliferative Disorder (NKLPD) panel between 2011 and 2014 were identified from our database. All samples were analyzed on the FACSCantoII cytometer. NK cells were identified as CD45+, smCD3−, CD19−, CD56+ and normal T‐cells served as internal controls. The majority of NKTCL were CD56 bright, CD16 dim, CD57−, and CD94+. CLPD‐NK and RNKL were predominantly CD56+ or dim with positive expression of CD16 and CD57 and weak CD94 expression. Antigen based statistical analyses showed robust division of samples along the NKTCL/normal CD56 bright NK cell and CLPD‐NK/RNKL/normal CD56 positive NK cell groups. It was concluded that FC can reliably distinguish NKTCL from CLPD‐NK, normal NK cells of CD56+ phenotype, and RNKL. It was proposed that the typical phenotype for NKTCL is: CD56 bright, CD16 dim with positive CD2, CD7, CD94, HLADR, CD25, CD26, and absent CD57. This resembles the phenotype of the CD56 bright immunoregulatory subset of NK cells which we therefore hypothesize is the cell of origin of NKTCL. © 2017 International Clinical Cytometry Society

ABSTRACTBackground: Neuropathy is a common adverse effect of bortezomib. Isolated central nervous system (CNS) relapse in MM remains exceedingly rare and carries a dismal prognosis. We present an unusual case of bortezomib related neuropathy masking a CNS relapse of MM. Case presentation: A 57-year-old female was diagnosed with standard-risk MM with clinical and cytogenetic features not typically associated with CNS involvement. She was treated with 4 cycles of bortezomib/cyclophosphamide/dexamethasone (VCD) and achieved a VGPR, after which she underwent an autologous stem cell transplant (ASCT) followed by bortezomib maintenance. Six months after ASCT she developed symptoms suggestive of peripheral neuropathy which was attributed to bortezomib. However the symptoms persisted despite discontinuation of bortezomib. Imaging and cerebrospinal fluid analysis subsequently confirmed a CNS relapse. Discussion: CNS involvement in MM (CNS-MM) is uncommon and is considered an aggressive disease. Recently published literature has reported biomarkers with prognostic potential. However, isolated CNS relapse is even less common; an event which carries a very poor prognosis. Given the heterogeneous neurologic manifestations associated with MM, clinical suspicion may be masked by confounding factors such as bortezomib-based therapy. The disease may further remain incognito if the patient does not exhibit any of the high risk features and biomarkers associated with CNS involvement. Conclusion: In the era of proteasome inhibitor (PtdIns)/immunomodulator (IMID)-based therapy for MM which carries neurologic adverse effects, it is prudent to consider CNS relapse early. This case further highlights the need for more robust biomarkers to predict CNS relapse and use of newer novel agents which demonstrate potential for CNS penetration.

Although combination therapy is the standard of care for relapsed/refractory non-Hodgkin’s lymphoma (RR-NHL), combination treatment chosen for an individual patient is empirical, and response rates remain poor in individuals with chemotherapy-resistant disease. Here, we evaluate an experimental-analytic method, quadratic phenotypic optimization platform (QPOP), for prediction of patient-specific drug combination efficacy from a limited quantity of biopsied tumor samples. In this prospective study, we enrolled 71 patients with RR-NHL (39 B cell NHL and 32 NK/T cell NHL) with a median of two prior lines of treatment, at two academic hospitals in Singapore from November 2017 to August 2021. Fresh biopsies underwent ex vivo testing using a panel of 12 drugs with known efficacy against NHL to identify effective single and combination treatments. Individualized QPOP reports were generated for 67 of 75 patient samples, with a median turnaround time of 6 days from sample collection to report generation. Doublet drug combinations containing copanlisib or romidepsin were most effective against B cell NHL and NK/T cell NHL samples, respectively. Off-label QPOP-guided therapy offered at physician discretion in the absence of standard options (n= 17) resulted in five complete responses. Among patients with more than two prior lines of therapy, the rates of progressive disease were lower with QPOP-guided treatments than with conventional chemotherapy. Overall, this study shows that the identification of patient-specific drug combinations through ex vivo analysis was achievable for RR-NHL in a clinically applicable time frame. These data provide the basis for a prospective clinical trial evaluating ex vivo–guided combination therapy in RR-NHL.

Background

Background and aims:

Background

Introduction

Introduction

Background

Xu: Proteona Pte Ltd: Current Employment. Scolnick: Proteona Pte Ltd: Current holder of individual stocks in a privately-held company. Huo: Proteona Pte Ltd: Ended employment in the past 24 months. Lovci: Proteona Pte Ltd: Current Employment. Chng: Amgen: Honoraria, Research Funding; Abbvie: Honoraria; Janssen: Honoraria, Research Funding; Novartis: Honoraria; Celgene: Honoraria, Research Funding.

Ooi: Jansen: Honoraria; Teva Pharmaceuticals: Honoraria; GSK: Honoraria; Abbvie: Honoraria; Amgen: Honoraria. Chng: Sanofi: Honoraria; Abbvie: Honoraria; Takeda: Honoraria; Amgen: Honoraria; BMS/Celgene: Honoraria, Research Funding; Johnson and Johnson: Honoraria, Research Funding; Pfizer: Honoraria.

Chng: Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria; Abbvie: Honoraria.everolimus palbociclib for diffuse large B cell lymphoma and rhomidepsin Bortezomib for extra nodal NK T cell lymphoma

Scolnick: Proteona Pte Ltd: Current holder of individual stocks in a privately-held company. Huo: Proteona Pte Ltd: Ended employment in the past 24 months. Xu: Proteona Pte Ltd: Current Employment. Chng: Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria; Abbvie: Honoraria.

No relevant conflicts of interest to declare.

Jeyasekharan: Turbine Ltd: Consultancy; Janssen: Consultancy, Research Funding; AstraZeneca: Consultancy, Research Funding; Perkin Elmer: Other: travel funding ; MSD: Consultancy.

No relevant conflicts of interest to declare.

Lewis: AstraZeneca: Consultancy, Honoraria; Novartis: Patents & Royalties: Conference attendance; Janssen: Honoraria, Patents & Royalties: Conference attendance; Roche: Consultancy, Honoraria. Villa: Janssen: Honoraria; Gilead: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Seattle Genetics: Honoraria; Celgene: Honoraria; Lundbeck: Honoraria; Roche: Honoraria; NanoString Technologies: Honoraria. Bobillo: F. Hoffmann-La Roche Ltd: Consultancy, Speakers Bureau; Gilead: Speakers Bureau. Ekstroem Smedby: Takeda: Consultancy; Janssen Cilag: Research Funding. Savage: Merck: Consultancy, Honoraria, Other: Institutional clinical trial funding; BMS: Consultancy, Honoraria, Other: Institutional clinical trial funding; AbbVie: Consultancy, Honoraria; Roche: Research Funding; Takeda: Other: Institutional clinical trial funding; Servier: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Astra-Zeneca: Consultancy, Honoraria; Beigene: Other: Institutional clinical trial funding; Genentech: Research Funding. Eyre: Beigene: Honoraria, Research Funding; Incyte: Consultancy; Secura Bio: Consultancy, Honoraria; Janssen: Honoraria; Gilead/KITE: Honoraria, Other: Travel support for conferences, Research Funding, Speakers Bureau; Loxo Oncology: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Honoraria, Other: Travel to conferences; AstraZeneca: Honoraria, Research Funding; Roche: Consultancy, Honoraria. Cwynarski: Incyte: Consultancy, Speakers Bureau; Gilead: Consultancy, Speakers Bureau; Atara: Consultancy; Celgene: Consultancy; Takeda: Consultancy, Other: travel to scientific conferences, Speakers Bureau; Kite, a Gilead Company: Consultancy, Other: travel to scientific conferences, Speakers Bureau; Janssen: Consultancy, Other: travel to scientific conferences; Roche: Consultancy, Other: travel to scientific conferences, Speakers Bureau; BMS/Celgene: Other: travel to scientific conferences. Stewart: Teva: Honoraria; Sandoz: Honoraria; Amgen: Honoraria; AstraZeneca: Honoraria; Novartis: Honoraria; Celgene: Honoraria; Gilead: Honoraria; Abbvie: Honoraria; Janssen: Honoraria; Roche: Honoraria. Bishton: Gilead: Honoraria, Other: Travel grants; AbbVie: Honoraria, Other: Travel grants; Celgene/BMS: Honoraria, Other: travel grants; Celltrion: Honoraria, Other: Travel grants; Takeda.: Honoraria, Other: Travel grants . Fox: F. Hoffmann-La Roche Ltd: Consultancy, Membership on an entity's Board of Directors or advisory committees. Joffe: Epizyme: Consultancy; AstraZeneca: Consultancy. Eloranta: Janssen Pharmaceutical NV: Other: NV. Sehn: Genmab: Consultancy; Novartis: Consultancy; Debiopharm: Consultancy. Manos: Bristol-Myers Squibb: Other: Travel and meetings. Hawkes: Specialised Therapeutics: Consultancy; Gilead: Membership on an entity's Board of Directors or advisory committees; Merck Sharpe Dohme: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Antigene: Membership on an entity's Board of Directors or advisory committees; Regeneron: Speakers Bureau; Bristol Myers Squib/Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck KgA: Research Funding; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Travel and accommodation expenses, Research Funding, Speakers Bureau; Janssen: Speakers Bureau. Minson: Novartis: Research Funding; Hoffman La Roche: Research Funding. Dickinson: Celgene: Research Funding; Amgen: Honoraria; Takeda: Research Funding; Gilead Sciences: Consultancy, Honoraria, Speakers Bureau; MSD: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Other: travel, accommodation, expenses, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau. Øvlisen: Abbvie: Other: Travel expenses. Gregory: Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel fees, Speakers Bureau; Janssen: Consultancy; Novartis: Consultancy. Ku: Roche: Consultancy; Antegene: Consultancy; Genor Biopharma: Consultancy. Talaulikar: Roche: Honoraria, Research Funding; Jansenn: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; EUSA Pharma: Honoraria, Research Funding. Maurer: Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Genentech: Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Nanostring: Research Funding. El-Galaly: Abbvie: Other: Speakers fee; ROCHE Ltd: Ended employment in the past 24 months. Cheah: Roche: Consultancy, Honoraria, Other: advisory and travel expenses, Research Funding; Janssen: Consultancy, Honoraria, Other: advisory; MSD: Consultancy, Honoraria, Other: advisory, Research Funding; Gilead: Consultancy, Honoraria, Other: advisory; Ascentage pharma: Consultancy, Honoraria, Other: advisory; Beigene: Consultancy, Honoraria, Other: advisory; AbbVie: Research Funding; Celgene: Research Funding; AstraZeneca: Consultancy, Honoraria, Other: advisory; Loxo/Lilly: Consultancy, Honoraria, Other: advisory; TG Therapeutics: Consultancy, Honoraria, Other: advisory.

No relevant conflicts of interest to declare.

Introduction:

No relevant conflicts of interest to declare.

Introduction:

Jeyasekharan: PerkinElmer: Other: Collaboration; Merck Sharp & Dohme: Honoraria; Janssen: Research Funding; AstraZeneca: Other: Collaboration.

Chng: Takeda: Consultancy, Honoraria, Other: Travel, accommodation, expenses; Janssen: Consultancy, Honoraria, Other: Travel, accommodation, expenses, Research Funding; Amgen: Consultancy, Honoraria, Other: Travel, accommodation, expenses; Aslan: Research Funding; Merck: Research Funding; Celgene: Consultancy, Honoraria, Other: Travel, accommodation, expenses, Research Funding.

Jeyasekharan: AstraZeneca: Other: Collaboration; Merck Sharp & Dohme: Honoraria; Janssen: Research Funding; PerkinElmer: Other: Collaboration. Bishton:Gilead: Research Funding; Abbvie: Research Funding; Roche: Research Funding; Takeda: Other: travel support to ASH.

Background/Objective:

Introduction

BACKGROUND/OBJECTIVE: