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Ott, German

https://orcid.org/0000-0001-7990-6793

Mayo Clinic

Robert Bosch Hospital

Citations 26

Clinical Validation of MCL35 in Mantle Cell Lymphoma Patients ≥65 Years Receiving Bendamustine-Rituximab
Ramsower, Colleen , Mwangi, Raphael , Villa, Diego , McDonnell, Timothy J. , Cohen, Jonathon B. , Robetorye, Ryan S. , Giné, Eva , Cook, James R. , Hill, Brian T. , Ott, German , Reichart, Alexander, Rosenthal, Allison , Maurer, Matthew J. , Feldman, Andrew L. , Habermann, Thomas M. , Campo, Elı́as , Raess, Philipp W. , Scott, David W. , Rimsza, Lisa M.

Blood | November 23, 2021 | Volume: 138 | Issue: Supplement 1 | Pages: 3517-3517

10.1182/blood-2021-151275 Get It

Abstract BACKGROUND: Mantle cell lymphoma (MCL) is a B-cell non-Hodgkin lymphoma with variable clinical outcomes. Commonly used risk stratification tools (Ki67 IHC, MIPI) in newly diagnosed MCL are not frequently used when selecting therapy, resulting in treatment choice being dictated by age and co-morbidities rather than disease biology. The MCL35 risk score was developed as a more reliable measure of proliferation and has been shown to be prognostic and can risk stratify younger transplant eligible MCL patients into three groups with significantly different overall survival (OS; Scott et al. 2017; Holte et al. 2018) but has not been evaluated in older transplant ineligible patients. We report results evaluating the prognostic value of the MCL35 assay in older MCL patients (≥65) treated with frontline bendamustine/rituximab (BR). METHODS: Archived tissue samples from 119 patients age ≥65 years treated with BR from collaborating Lymphoma/Leukemia Molecular Profiling Project (LLMPP) sites and the LEO/MER cohort were collected and analyzed using the MCL35 assay and stratified into three distinct risk groups (low, standard, and high risk). Association between MCL35 proliferation scores and OS were estimated by the Kaplan-Meier method and hazard ratios were calculated. Associations between Ki67, s-MIPI, p53 IHC status, morphology and OS were also evaluated. RESULTS: The MCL35 assay was run on tissue samples from 119 patients. Median patient age was 74 (range 65-93) and 69.5% were male. Ki67 was <30% in 29 patients (24%) and ≥30% in 90 patients (76%). Simplified MIPI (s-MIPI) score was 0-3 in 21 patients (24%), 4-5 in 42 patients (48%) and ≥6 in 25 patients (28%). Thirty-one did not have sufficient data to calculate a s-MIPI score. MCL35 was low risk in 51 patients (43%), standard risk in 39 patients (33%) and high risk in 29 patients (24%). Eleven patients had blastic morphology, 7 had pleomorphic morphology and the remainder were classic morphology (n=56). Of 57 samples with p53 IHC staining 7 (12.3%) were positive. At a median follow up of 33.4 months, 82 patients were alive and 35 had died. Patients with high risk MCL35 score had inferior OS compared to low risk (HR 2.27, 95% CI: 1.03-5.00; p=0.042) while standard risk was not statistically significant compared to low risk (HR 0.87, 95% CI: 0.37-2.0; p=0.740)(Figure 1). Ki67 IHC using a cutoff of ≥ 30% and 10%-29% was not significantly associated with OS compared to Ki67 <10% ( Ki67 ≥ 30% vs. Ki67 < 10%, HR 0.87, 95% CI: 0.12-6.41; p=0.892, Ki67 ≥ 10%-29% vs. Ki67 < 10%, HR 0.32, 95% CI: 0.04-2.83; p=0.303), however high s-MIPI score (≥6) (s-MIPI ≥6 vs. s-MIPI 0-3, HR 3.86, 95% CI 1.20-12.5; p=0.024) and positive p53 IHC (HR: 9.51, 3.26-27.7; p <0.001) were both associated with poor OS. Eighteen cases were blastic/pleomorphic by morphology, 12 of which were in the high-risk group by MCL35, and this subset also had worse survival than classic MCL (p=0.0052). CONCLUSIONS: These results suggest high risk MCL35 score is a prognostic biomarker of poor OS in patients >65 with MCL treated with BR. Conversely, Ki67 was not significantly associated with OS in these patients. Additional clinical validation using a larger sample size from the E1411 study is planned. If similar results are found, the MCL35 assay in combination with s-MIPI and p53 status may have utility in stratifying patients into risk adapted treatment arms in future prospective clinical trial designs. Figure 1 Figure 1. Disclosures Maurer: BMS: Research Funding; Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Villa: Janssen: Honoraria; Gilead: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Seattle Genetics: Honoraria; Celgene: Honoraria; Lundbeck: Honoraria; Roche: Honoraria; NanoString Technologies: Honoraria. Habermann: Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Tess Therapeutics: Other: Data Monitoring Committee; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Cohen: Janssen, Adicet, Astra Zeneca, Genentech, Aptitude Health, Cellectar, Kite/Gilead, Loxo, BeiGene, Adaptive: Consultancy; Genentech, BMS/Celgene, LAM, BioINvent, LOXO, Astra Zeneca, Novartis, M2Gen, Takeda: Research Funding. Hill: Celgene (BMS): Consultancy, Honoraria, Research Funding; Epizyme: Consultancy, Honoraria; Gentenech: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel Support, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; Incyte/Morphysis: Consultancy, Honoraria, Research Funding. Raess: Scopio Labs: Research Funding. Scott: Celgene: Consultancy; NanoString Technologies: Patents & Royalties: Patent describing measuring the proliferation signature in MCL using gene expression profiling.; BC Cancer: Patents & Royalties: Patent describing assigning DLBCL COO by gene expression profiling--licensed to NanoString Technologies. Patent describing measuring the proliferation signature in MCL using gene expression profiling. ; Rich/Genentech: Research Funding; Janssen: Consultancy, Research Funding; Incyte: Consultancy; Abbvie: Consultancy; AstraZeneca: Consultancy. Rimsza: NanoString Technologies: Other: Fee-for-service contract.
The Genomic Landscape of Plasmablastic Lymphoma (PBL) - an L.L.M.P.P. Project
Slack, Graham W. , Farinha, Pedro , Cook, James R. , Ott, German , Rosenwald, Andreas , Amador, Catalina, Greiner, Timothy C. , Weisenburger, Dennis D. , Chan, Wing C. , Beiske, Klaus , Delabie, Jan , Delabie, Jan , Farinha, Pedro , Wong, Jasper , Collinge, Brett , Hilton, Laura K. , Ben‐Neriah, Susana , Salaverría, Itziar , Campo, Elı́as , Jaffe, Elaine S. , Raess, Philipp W. , Song, Joo Y. , Inghirami, Giorgio , Holte, Harald , Fu, Kai, Pittaluga, Stefania , Feldman, Andrew L. , Savage, Kerry J. , Mungall, Andrew J. , Steidl, Christian , Rimsza, Lisa M. , Morin, Ryan D , Scott, David W.

Blood | November 23, 2021 | Volume: 138 | Issue: Supplement 1 | Pages: 1326-1326

10.1182/blood-2021-153441 Get It

Abstract Introduction: Plasmablastic lymphoma (PBL) is an aggressive B-cell lymphoma that predominantly occurs in patients with HIV or other causes of immunodeficiency. Frequent infection by the Epstein-Barr virus (EBV) and MYC translocations have been described as major features contributing to the pathogenesis of PBL. Prior studies examining the genetic landscape of PBL have largely relied on targeted capture-based sequencing approaches. As such, the molecular features of PBL remain to be fully explored. Here, we provide a comprehensive description of the genomic landscape of PBL using whole-genome and whole-exome sequencing to identify commonly perturbed pathways. Method: Archival diagnostic fresh frozen and formalin fixed paraffin embedded tissue biopsies from 58 PBL tumours were accrued from Lymphoma/Leukemia Molecular Profiling Project (LLMPP) sites, including 15 tumours from Ramis-Zaldivar et al., Haematolgica 2021. MYC rearrangements were identified by break-apart fluorescent in situ hybridization (FISH) and rearrangement partner was determined in a subset of tumours from capture or genome sequencing data using structural variant callers Manta, GRIDSS, and Delly. High confidence somatic mutations (SNVs/Indels) were identified in data from whole-genome (n=5) or whole-exome (n=53) sequencing through an ensemble voting approach utilizing four variant callers (Strelka2, Lofreq, Mutect2, SAGE). Mutation frequencies in known lymphoma-related genes were compared to activated B-cell (ABC)-DLBCL (Schmitz et al., NEJM 2018), as the closest tumour entity in terms of putative cell-of-origin differentiation stage, to identify differences in genetic aberrations. Candidate somatic copy number alterations (CNAs) were identified from exome and genome sequencing data, using CopywriteR and ControlFREEC, respectively, and high-confidence CNAs were determined using GISTIC2.0. Results: Within the study cohort, 81% of patients were male with a median age of 59 years (range 11-88). HIV and EBV statuses were available for 47% of patients and 95% of tumours, respectively, with 49% (13/27) of the patients being HIV+ and 69% (38/55) of tumours being EBV+. MYC rearrangement was observed in 60% (35/58) of PBLs, with IGH as the partner gene in 88% (21/24) of tumours. The most frequently mutated genes were STAT3 (38%), TP53 (22%), NRAS (21%), and TET2 (16%), consistent with previous studies, however novel mutations were seen in DUSP2 (21%), KLHL6 (16%), and BHLHE41 (16%). Recurrent CNAs included amplifications in 1q, whole gains of 7, 8q24, 11p12 and deletions affecting 4p16, 5p15, 10q11.22. While the mutational landscapes were similar between samples with and without a MYC translocation, the MYC-translocated PBLs showed more frequent amplification of 1q32.1. When stratifying by EBV status, STAT3 and SOCS1 mutations were more frequent in EBV-positive tumours, whereas TP53, TET2, KRAS, and MMRN2 mutations were associated with EBV-negativity. In comparison to ABC-DLBCL, PBLs were significantly enriched in STAT3 and NRAS mutations, and lacked common mutations affecting the NF-κB pathway (eg. MYD88, CD79B, and NFKBIZ 3' UTR mutations). Mutations in genes that are frequently mutated in ABC-DLBCLs, such as those associated with plasma cell differentiation (eg. PRDM1) or a memory B-cell fate (eg. TBL1XR1), were also not mutated in PBLs. Finally, genetic alterations associated with immune evasion, such as deletion of MHC I and II and mutations in B2M, CIITA, and CD58, were rarely observed. Conclusion: These data present a comprehensive overview of the genomic landscape of PBLs in a large cohort. We show frequent mutations involving the JAK-STAT and MAPK pathways, wherein the genetic landscape can be differentially characterized by EBV status and MYC rearrangement status. We show that PBLs are genetically distinct from ABC-DLBCLs, with absence of mutations in genes affecting the NF-κB pathway, immune evasion, and driving a memory B-cell fate. Disclosures Slack: Seagen: Consultancy, Honoraria. Raess: Scopio Labs: Research Funding. Holte: Gilead: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Nordic: Membership on an entity's Board of Directors or advisory committees; Nanovector: Membership on an entity's Board of Directors or advisory committees, Other: lectures honorarias; Novartis: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Savage: Servier: Consultancy, Honoraria; Roche: Research Funding; BMS: Consultancy, Honoraria, Other: Institutional clinical trial funding; Astra-Zeneca: Consultancy, Honoraria; Merck: Consultancy, Honoraria, Other: Institutional clinical trial funding; AbbVie: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Takeda: Other: Institutional clinical trial funding; Beigene: Other: Institutional clinical trial funding; Genentech: Research Funding. Steidl: Seattle Genetics: Consultancy; Curis Inc.: Consultancy; Bayer: Consultancy; Epizyme: Research Funding; Trillium Therapeutics: Research Funding; AbbVie: Consultancy; Bristol-Myers Squibb: Research Funding. Rimsza: NanoString Technologies: Other: Fee-for-service contract. Morin: Foundation for Burkitt Lymphoma Research: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Epizyme: Patents & Royalties. Scott: Abbvie: Consultancy; AstraZeneca: Consultancy; Rich/Genentech: Research Funding; BC Cancer: Patents & Royalties: Patent describing assigning DLBCL COO by gene expression profiling--licensed to NanoString Technologies. Patent describing measuring the proliferation signature in MCL using gene expression profiling. ; Incyte: Consultancy; Janssen: Consultancy, Research Funding; Celgene: Consultancy; NanoString Technologies: Patents & Royalties: Patent describing measuring the proliferation signature in MCL using gene expression profiling..
Genome-Wide miRNA Expression Profiling of Molecular Subgroups of Peripheral T-cell Lymphoma
Lone, Waseem , Bouska, Alyssa , Sharma, Sunandini , Amador, Catalina, Herek, Tyler A. , Heavican, Tayla B., Yu, Jiayu , Lim, Soon Thye , Ong, Choon Kiat , Slack, Graham W. , Savage, Kerry J. , Rosenwald, Andreas , Ott, German , Cook, James R. , Greiner, Timothy C. , Weisenburger, Dennis D. , Motta, Giovanna , Chan, Wing C. , Iqbal, Javeed , Saumyaranjan, Mallick , Ong, Choon Kiat , Feldman, Andrew L , Weisenburger, Dennis D , Melle, Federica , Savage, Kerry J , Bouska, Alyssa , Iqbal, Javeed , Lone, Waseem G , Feldman, Andrew L. , Rimsza, Lisa M. , McKeithan, Timothy W. , Pileri, Stefano , Vose, Julie M.

Clinical Cancer Research | August 23, 2021 | Volume: 27 | Issue: 21 | Pages: 6039-6053

10.1158/1078-0432.ccr-21-0573 Get It

Abstract Purpose: Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of non–Hodgkin lymphomas with aggressive clinical behavior. We performed comprehensive miRNA profiling in PTCLs and corresponding normal CD4+ Th1/2 and TFH-like polarized subsets to elucidate the role of miRNAs in T-cell lymphomagenesis. Experimental Design: We used nCounter (NanoString Inc) for miRNA profiling and validated using Taqman qRT-PCR (Applied Biosystems, Inc). Normal CD4+ T cells were polarized into effector Th subsets using signature cytokines, and miRNA significance was revealed using functional experiments. Results: Effector Th subsets showed distinct miRNA expression with corresponding transcription factor expression (e.g., BCL6/miR-19b, -106, -30d, -26b, in IL21-polarized; GATA3/miR-155, miR-337 in Th2-polarized; and TBX21/miR-181a, -331-3p in Th1-polarized cells). Integration of miRNA signatures suggested activation of TCR and PI3K signaling in IL21-polarized cells, ERK signaling in Th1-polarized cells, and AKT–mTOR signaling in Th2-polarized cells, validated at protein level. In neoplastic counterparts, distinctive miRNAs were identified and confirmed in an independent cohort. Integrative miRNA–mRNA analysis identified a decrease in target transcript abundance leading to deregulation of sphingolipid and Wnt signaling and epigenetic dysregulation in angioimmunoblastic T-cell lymphoma (AITL), while ERK, MAPK, and cell cycle were identified in PTCL subsets, and decreased target transcript abundance was validated in an independent cohort. Elevated expression of miRNAs (miR-126-3p, miR-145-5p) in AITL was associated with poor clinical outcome. In silico and experimental validation suggest two targets (miR-126→ SIPR2 and miR-145 → ROCK1) resulting in reduced RhoA-GTPase activity and T–B-cell interaction. Conclusions: Unique miRNAs and deregulated oncogenic pathways are associated with PTCL subtypes. Upregulated miRNA-126-3p and miR-145-5p expression regulate RhoA-GTPase and inhibit T-cell migration, crucial for AITL pathobiology.
A Cyclin D1–Dependent Transcriptional Program Predicts Clinical Outcome in Mantle Cell Lymphoma
Demajo, Santiago , Alberó, Robert , Clot, Guillem , Castellano, Giancarlo , Navarro, Alba , Capdevila, Cristina, Enjuanes, Anna , Nadeu, Ferran , Giné, Eva , Pinyol, Magda, Ott, German , Staudt, Louis M. , Rosenwald, Andreas , López‐Guillermo, Armando , Jaffe, Elaine S , Beà, Sílvia , Campo, Elías , Demajo, Santiago , Castellano, Giancarlo , Jaffe, Elaine S. , Scott, David W. , Rimsza, Lisa M. , Beà, Sı́lvia , Campo, Elı́as , Jares, Pedro , Nadeu, Ferran , Albero, Robert

Clinical Cancer Research | October 12, 2020 | Volume: 27 | Issue: 1 | Pages: 213-225

10.1158/1078-0432.ccr-20-2868 Get It

Abstract Purpose: Mantle cell lymphoma (MCL) is characterized by the t(11;14)(q13;q32) translocation leading to cyclin D1 overexpression. Cyclin D1 is a major cell-cycle regulator and also regulates transcription, but the impact of cyclin D1–mediated transcriptional dysregulation on MCL pathogenesis remains poorly understood. The aim of this study was to define a cyclin D1–dependent gene expression program and analyze its prognostic value. Experimental Design: We integrated genome-wide expression analysis of cyclin D1–silenced and overexpressing cells with cyclin D1 chromatin-binding profiles to identify a cyclin D1–dependent transcriptional program in MCL cells. We analyzed this gene program in two MCL series of peripheral blood samples (n = 53) and lymphoid tissues (n = 106) to determine its biological and clinical relevance. We then obtained a simplified signature of this program and evaluated a third series of peripheral blood MCL samples (n = 81) by NanoString gene expression profiling to validate our findings. Results: We identified a cyclin D1–dependent transcriptional program composed of 295 genes that were mainly involved in cell-cycle control. The cyclin D1–dependent gene program was overexpressed in MCL tumors directly proportional to cyclin D1 levels. High expression of this program conferred an adverse prognosis with significant shorter overall survival of the patients. These observations were validated in an independent cohort of patients using a simplified 37-gene cyclin D1 signature. The cyclin D1–dependent transcriptional program was also present in multiple myeloma and breast tumors with cyclin D1 overexpression. Conclusions: We identified a cyclin D1–dependent transcriptional program that is overexpressed in MCL and predicts clinical outcome.
Comprehensive Analyses of Genetic Features Identify Coordinate Signatures in Diffuse Large B-Cell Lymphoma
Kim, Jaegil , Roemer, Margaretha GM, Ziepert, Marita , Li, Amy Jiayue, Lawrence, Mike, Hess, Julian M. , Rosenburg, Mara, Horn, Heike , Novak, Anne J. , Haberman, Thomas M, Golub, Todd R. , Ott, German , Siebert, Reiner , Rosenwald, Andreas , Wulf, Gerald , Pfreundschuh, Michael , Trümper, Lorenz, Chapuy, Bjoern , Dunford, Andrew , Stewart, Chip , Kamburov, Atanas , Roemer, Margaretha G.M. , Lawrence, Mike, Taylor-Weiner, Amaro N , Redd, Robert , Cerhan, James R. , Feldman, Andrew L. , Link, Brian K. , Neuberg, Donna , Monti, Stefano , Rodig, Scott J , Löffler, Markus , Getz, Gad , Shipp, Margaret Ann

Blood | October 10, 2019 | Volume: 126 | Issue: 23 | Pages: 3922-3922

10.1182/blood.v126.23.3922.3922 Get It

Abstract Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous disease characterized by multiple low-frequency alterations including somatic mutations, copy number alterations (CNAs) and chromosomal rearrangements. We sought to identify previously unrecognized low-frequency genetic events, integrate recurrent alterations into comprehensive signatures and associate these signatures with clinical parameters. For these reasons, our multi-institutional international group assembled a cohort of 304 primary DLBCLs from newly diagnosed patients, 87% of whom were uniformly treated with state-of-the-art therapy (rituximab-containing CHOP regimen) and had long term followup. Tumors were subjected to whole exome sequencing with an extended bait set that included custom probes designed to capture recurrent chromosomal rearrangements. In this cohort, 47% of samples had available transcriptional profiling and assignment to associated disease subtypes. Analytical pipelines developed at the Broad Institute were used to detect mutations (MuTect), CNAs (Recapseq+Allelic Capseq) and chromosomal rearrangements (dRanger+Breakpointer) and assess clonality (Absolute). To analyze formalin-fixed paraffin-embedded tumors without paired normals we developed a method which utilized 8334 unrelated normal samples to stringently filter recurrent germline events and artifacts. Significant mutational drivers were identified using the MutSig2CV algorithm and recurrent CNAs were assessed with GISTIC2.0. In addition, we utilized a recently developed algorithm, CLUMPS2, to prioritize somatic mutations which cluster in 3-dimensional protein structure. With this approach, we identified > 90 recurrently mutated genes, 34 focal amplifications and 41 focal deletions, 20 arm-level events and > 200 chromosomal rearrangements in the DLBCL series. Of note, 33% of the mutational drivers were also perturbed by chromosomal rearrangements or CNAs, underscoring the importance of a comprehensive genetic analysis. In the large DLBCL series, we identified several previously unrecognized but potentially targetable alterations including mutations in NOTCH2 (8%) and TET2 (5%). The majority of identified chromosomal rearrangements involved translocations of potent regulatory regions to intact gene coding sequences. The most frequently rearrangements involved Ig regulatory elements which were translocated to BCL2, MYC, BCL6 and several additional genes with known roles in germinal center B-cell biology. After identifying recurrent somatic mutations, CNAs and chromosomal rearrangements, we performed hierarchical clustering and identified subsets of DLBCLs with comprehensive signatures comprised of specific alterations. A large subset of tumors shared recurrent alterations previously associated with follicular lymphoma including mutations of chromatin modifiers such as CREBBP, MLL2, and EZH2 in association with alterations of TNFRSF14 and GNA13 and translocations of BCL2. This cluster was enriched in GCB-type DLBCLs and contained a subset with select genetic alterations associated with an unfavorable outcome. An additional cohort of tumors was characterized by alterations perturbing B-cell differentiation including recurrent BCL6 translocations or alterations of PRDM1. A subset of these DLBCLs had alterations of NOTCH2 and additional pathway components or mutations of MYD88 in association with TNFAIP3, CD70 and EBF1, a master regulator of B-cell differentiation. An additional group of DLBCLs exhibited frequent MYD88 mutations in association with alterations of CD79B, PIM1, TBL1XR1 and ETV6 and BCL2 copy gain; these tumors were highly enriched for ABC-type DLBCLs. This coordinate signature and additional alterations of p53 pathway components were associated with outcome. We explored bases for the identified genetic alterations in DLBCL by performing an in silico mutational signature analysis. The most frequent mutational signatures were those of spontaneous deamination (aging) and AID with rare cases of microsatellite instability. We also assessed the clonality of identified genetic features to define cancer cell fraction and establish the timing of specific genetic events. The comprehensive genetic signatures of clinically annotated DLBCLs provide new insights regarding approaches to targeted therapy. Disclosures Link: Kite Pharma: Research Funding; Genentech: Consultancy, Research Funding. Rodig:Perkin Elmer: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding. Pfreundschuh:Boehringer Ingelheim, Celegene, Roche, Spectrum: Other: Advisory board; Roche: Honoraria; Amgen, Roche, Spectrum: Research Funding. Shipp:Gilead: Consultancy; Sanofi: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees; Bayer: Membership on an entity's Board of Directors or advisory committees, Research Funding.
A Clinicogenetic Risk Model (m7-FLIPI) Prospectively Identifies One-Half of Patients with Early Disease Progression of Follicular Lymphoma after First-Line Immunochemotherapy
Jurinović, Vindi , Horn, Heike , Dreyling, Martin , Rosenwald, Andreas , Ott, German , Friedberg, Jonathan W. , Ansell, Stephen M. , Gascoyne, Randy D. , Weinstock, David M. , Unterhalt, Michael, Weigert, Oliver , Kridel, Robert , Staiger, Annette M. , Szczepanowski, Monika , Klapper, Wolfram , Zelenetz, Andrew D. , Sehn, Laurie H. , Connors, Joseph M. , Klapper, Wolfram , Hoster, Eva

Blood | October 10, 2019 | Volume: 126 | Issue: 23 | Pages: 333-333

10.1182/blood.v126.23.333.333 Get It

Abstract Background: Follicular lymphoma (FL) is the second most common nodal lymphoma worldwide and remains incurable for most patients (pts). FL is recognized to be a highly heterogeneous disease and a subset of pts experience remarkable poor outcome. In a recent study, 19-26% of pts receiving first-line R-CHOP experienced progression of disease (POD) within 24 months after diagnosis and had a 5-year (yr) overall survival (OS) of only 34-50%, as compared to a 5-yr OS of 90-94% for pts without POD within 24 months (Casulo et al., J Clin Oncol 2015). Consequently, event-free survival at 12 (EFS12) and 24 months (EFS24) have been suggested as novel surrogate endpoints for poor overall survival in clinical trials and useful for patient counseling (Maurer et al., ASH 2014). We have previously shown that a clinicogenetic risk model (m7-FLIPI) that includes the mutation status of seven genes (EZH2, ARID1A, MEF2B, EP300, FOXO1, CREBBP, and CARD11), the FL International Prognostic Index (FLIPI), and the Eastern Cooperative Oncology Group (ECOG) performance status, improves risk stratification for failure-free survival (FFS) and OS in pts with FL receiving first-line immunochemotherapy (Pastore et al., Lancet Oncology 2015). An online tool is available at: http://www.glsg.de/m7-flipi. It would be advantageous to determine prognosis prior to front-line therapy rather than after POD. Thus, we aimed to investigate the predictive utility of the m7-FLIPI for early POD. Patients and Methods: Clinical and mutation data were available from two independent cohorts: 151 pts who received R-CHOP and IFN maintenance as part of a randomized trial of the German Low-Grade Lymphoma Study Group (GLSG), and 107 pts from a population-based registry of the British Columbia Cancer Agency (BCCA) who received R-CVP. Among the latter, 93 (87%) received R-maintenance by intention to treat. All pts had symptomatic, advanced stage or bulky disease considered ineligible for curative radiotherapy, and a biopsy specimen obtained </=12 months prior to the initiation of first-line therapy. POD was defined as progression, relapse, or death due to any cause. POD12 and POD24 were defined based on POD status at 12 and 24 months after therapy initiation, respectively. Logistic regression analysis was performed to assess if m7-FLIPI was predictive of early POD using the statistical software R (version 3.1.2). Results: In the GLSG cohort, median age was 57 yrs (range 27-77), 51% had high-risk FLIPI, and 5-yr failure-free survival (FFS) and OS rates were 66% and 83%, respectively (median follow-up for OS 7.7 yrs). In the BCCA cohort, median age was higher (62 yrs, 37-83), but high-risk FLIPI was similarly frequent (50%); 5-yr FFS and OS rates were 58% and 74%, respectively (median follow-up for OS 6.7 yrs). A total of 43 GLSG (28%) and 24 BCCA pts (22%) were classified as high-risk by m7-FLIPI, with a 5-yr OS of 65% and 42%, respectively. In the GLSG cohort, 8 (5%) and 29 pts (19%) had POD within 12 and 24 months, respectively, 4 and 10 pts were censored before POD12 and POD24 (table). High-risk m7-FLIPI pts were significantly more likely to experience early POD with an Odds Ratio (OR) of 20.80 (95% confidence interval (CI) 3.53-395.96; p=0.0052) for POD12 and 6.33 (95% CI 2.67-15.69; p<0.0001) for POD24. Likewise, in the BCCA cohort, 16 (15%) and 28 pts (26%) experienced POD12 and POD24, respectively (table). The OR for high-risk m7-FLIPI pts was 4.69 (95% CI 1.52-14.65; p=0.0068) for POD12, and 5.36 (95% CI 2.03-14.60; p=0.0008) for POD24. In the GLSG and BCCA cohorts, the m7-FLIPI had a sensitivity of 88% and 50%, a specificity of 75% and 82%, a positive predictive value (PPV) of 16 and 33%, and a negative predictive value (NPV) of 96% and 90% to predict POD12. For POD24, sensitivity was 62% and 46%, specificity 79% and 86%, PPV 42% and 54%, and NPV 82% and 82%, respectively. Conclusion: We conclude that patients classified as high-risk m7-FLIPI are highly enriched among those with early progression of disease. However, approximately one-half of patients with progression by 24 months after therapy initiation are classified as low-risk m7-FLIPI. Thus, further efforts are needed to refine the m7-FLIPI and thereby capture additional cases that may benefit from innovative first-line approaches. Table. Population m7-FLIPI N POD12 POD24 GLSG Total 151 8/147* 29/141* High-risk 43 7 18 Low-risk 108 1 11 BCCA Total 107 16/107 28/107 High-risk 24 8 13 Low-risk 83 8 15 *Pts censored were removed Disclosures Ansell: Bristol-Myers Squibb: Research Funding; Celldex: Research Funding.
Reproducing the molecular subclassification of peripheral T-cell lymphoma–NOS by immunohistochemistry
Amador, Catalina , Greiner, Timothy C. , Heavican, Tayla B., Smith, Lynette M. , Galvis, Karen, Lone, Waseem , Bouska, Alyssa , d’Amore, Francesco, Pedersen, Martin Bjerregård , Pileri, Stefano , Rosenwald, Andreas , Ott, German , Mottok, Anja , Lim, Soon Thye , Ong, Choon Kiat , Ondrejka, Sarah L. , Song, Joo Y. , Staudt, Louis M. , Weisenburger, Dennis D. , Chan, Wing C. , Iqbal, Javeed , Song, Joo Y , Ong, Choon Kiat , Bouska, Alyssa , Amador, Catalina , Greiner, Timothy C , Smith, Lynette , Pileri, Stefano , d'Amore, Francesco , Iqbal, Javeed , Agostinelli, Claudio , Feldman, Andrew L. , Savage, Kerry J. , Leval, Laurence de , Gaulard, Philippe , Campo, Elı́as , Jaffe, Elaine S. , Rimsza, Lisa M. , Vose, Julie M. , Lone, Waseem G

Blood | September 27, 2019 | Volume: 134 | Issue: 24 | Pages: 2159-2170

10.1182/blood.2019000779 Get It

One-third of peripheral T-cell lymphomas are “not otherwise specified” (PTCL-NOS), but they have been subdivided into 2 subgroups based on gene expression profiling. Amador and colleagues generated an immunohistochemical algorithm that parallels the molecular separation of PTCL-NOS and provides useful prognostic information.