Clinical Validation of MCL35 in Mantle Cell Lymphoma Patients ≥65 Years Receiving Bendamustine-Rituximab

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.

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Evaluation of the International Prognostic Index for Chronic Lymphocytic Leukemia (CLL-IPI) and Validation of a Proposed Novel Risk Model (BALL Score) in Real-World Relapsed/Refractory (R/R) CLL Patients Receiving Idelalisib and Rituximab

Blood ◽

10.1182/blood-2019-126717 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 5485-5485

Author(s):

Massimo Gentile ◽

Gianluigi Reda ◽

Francesca Romana Mauro ◽

Paolo Sportoletti ◽

Luca Laurenti ◽

...

Keyword(s):

High Risk ◽

Risk Stratification ◽

Board Of Directors ◽

Research Funding ◽

Advisory Board ◽

Low Risk ◽

Intermediate Risk ◽

Advisory Committees ◽

Scientific Advisory Board ◽

Scientific Advisory

The CLL-IPI score, which combines genetic, biochemical, and clinical parameters, represents a simple worldwide model able to refine risk stratification for CLL patients. This score, developed in the era of chemo-immunotherapy, has not been gauged extensively in R/R-CLL patients treated with novel targeted agents, such as BCR and BCL2 inhibitors. Soumerai et al (Lancet Hematol 2019) assembled a novel risk model for OS in the setting of R/R-CLL receiving targeted therapies in clinical trials. This model, consisting of four accessible markers (β2M, LDH, Hb, and time from initiation of last therapy; BALL score), is able to cluster 3 groups of CLL patients with significantly different OS. This multicenter, observational retrospective study aimed to validate the proposed Soumerai (BALL) and/or CLL-IPI scores for R/R-CLL real-world patients treated with idelalisib and rituximab (IDELA-R). The primary objectives were to determine whether: i) the CLL-IPI retains its prognostic power also in R/R patients treated with IDELA-R; ii) the BALL score is of prognostic value for IDELA-treated R/R-CLL patients, and iii) the BALL score is predictive of PFS. This study, sponsored by Gilead (ISR#IN-IT-312-5339), included CLL patients collected from 12 Italian centers, who received IDELA-R (idelalisib 150 mg b.i.d. and a total of 8 rituximab infusions intravenously) outside clinical trials as salvage therapy with available data for the calculation of the CLL-IPI and BALL scores at the time of treatment start. OS was estimated for all subgroups of both scores. Additionally, risk-specific PFS was assessed. Kaplan-Meier curve, log-rank test, and Cox regression analyses were performed. The prognostic accuracy of the predictive model was assessed by Harrell's C-index. Overall, 120 CLL patients were included in this analysis. The majority of patients were Binet stage B and C (94.2%). The median age was 75 years and 83 cases (69.2%) were male. The median number of previous therapies was 3 (range 1-9) Baseline patient features are listed in Table 1. After a median follow-up of 1.6 years (1 month to 5.8 years), 33 patients had died and 39 experienced an event (death or progression). CLL-IPI scoring (115/120 evaluable cases) indicated that 6 patients (5.2%) were classified as low-risk, 24 (20.9%) as intermediate-risk, 58 (50.4%) as high-risk, and 27 (23.5%) as very high-risk. Stratification of patients according to the CLL-IPI score did not allow prediction of significant differences in OS. Thus, low-risk patients had a 2-year OS probability of 75% (HR=1), with an intermediate-risk of 68% (HR=2.9, 95%CI 0.37-23.3, P=0.3), high-risk of 83% (HR=1.58, 95%CI 0.2-12.5, P=0.66), and very high-risk of 63% (HR=5.9, 95%CI 0.78-45.2, P=0.86). Next, we tested a modified CLL-IPI by assigning a more balanced score to the original CLL-IPI variables (Soumerai et al, Leukemia Lymphoma 2019), partially overlapping previous results. Specifically, modified CLL-IPI high-risk group showed a significantly different OS as compared with intermediate- and low-risk groups. However, differently from the original report no difference was observed between low- and intermediate-risk). According to the BALL score (120/120 evaluable cases), 33 patients (27.5%) were classified as low-risk, 68 (56.7%) as intermediate-risk, and 19 (15.8%) as high-risk. Stratification of patients according to the BALL score predicted significant differences in terms of OS. Thus, low-risk patients had a 2-year OS probability of 92% (HR=1), intermediate-risk of 76% (HR=5.47, 95%CI 1.3-23.7, P=0.023), and high-risk of 54% (HR=15.1, 95%CI 3.4-67, P<0.0001) (Figure 1). Harrell's C-statistic was 0.68 (P<0.001) for predicting OS. To note, BALL score failed to significantly stratify patients in terms of PFS. As for Soumerai et al (Leukemia Lymphoma 2019), the original CLL-IPI score did not retain discriminative power in term of OS in R/R-CLL patients receiving IDELA-R. The modified CLL-IPI failed to stratify low- and intermediate-risk groups, likely due to the number of cases analysed in the current cohort and the heterogeneous IDELA-containing regimens included in the Soumerai study (Soumerai et al, Leukemia Lymphoma 2019). The CLL-IPI was designed for CLL patients treated with first-line chemo-immunotherapy. Herein, we confirm the prognostic power of the BALL score in this real-world series for OS, while losing the predictive impact of patient outcomes in terms of PFS. Disclosures Mauro: Gilead: Consultancy, Research Funding; Jannsen: Consultancy, Research Funding; Shire: Consultancy, Research Funding; Abbvie: Consultancy, Research Funding; Roche: Consultancy, Research Funding. Coscia:Abbvie: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Karyopharm Therapeutics: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Varettoni:ABBVIE: Other: travel expenses; Roche: Consultancy; Janssen: Consultancy; Gilead: Other: travel expenses. Rossi:Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Honoraria, Other: Scientific advisory board; Janseen: Honoraria, Other: Scientific advisory board; Roche: Honoraria, Other: Scientific advisory board; Astra Zeneca: Honoraria, Other: Scientific advisory board. Gaidano:AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sunesys: Consultancy, Honoraria; Astra-Zeneca: Consultancy, Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

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Conventional Immunochemotherapy (R-CHOEP) Vs High-Dose Immunochemotherapy (R-MegaCHOEP) in Younger Patients with High-Risk Aggressive B-Cell Lymphoma: 10-Year Long-Term Follow-up of a German Lymphoma Alliance (GLA) Study

Blood ◽

10.1182/blood-2019-123637 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1589-1589

Author(s):

Fabian Frontzek ◽

Marita Ziepert ◽

Maike Nickelsen ◽

Bettina Altmann ◽

Bertram Glass ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Advisory Board ◽

High Dose ◽

Advisory Committees ◽

Scientific Advisory Board ◽

Scientific Advisory

Introduction: The R-MegaCHOEP trial showed that dose-escalation of conventional chemotherapy necessitating autologous stem cell transplantation (ASCT) does not confer a survival benefit for younger patients (pts) with high-risk aggressive B-cell lymphoma in the Rituximab era (Schmitz et al., Lancet Oncology 2012; 13, 1250-1259). To describe efficacy and toxicity over time and document the long-term risks of relapse and secondary malignancy we present the 10-year follow-up of this study. Methods: In the randomized, prospective phase 3 trial R-MegaCHOEP younger pts aged 18-60 years with newly diagnosed, high-risk (aaIPI 2-3) aggressive B-cell lymphoma were assigned to 8 cycles of CHOEP (cyclophosphamide, doxorubcine, vincristine, etoposide, prednisone) or 4 cycles of dose-escalated high-dose therapy (HDT) necessitating repetitive ASCT both combined with Rituximab. Both arms were stratified according to aaIPI, bulky disease, and center. Primary endpoint was event-free survival (EFS). All analyses were calculated for the intention-to-treat population. This follow-up report includes molecular data based on immunohistochemistry (IHC) and fluorescent in situ hybridization (FISH) for MYC (IHC: 31/92 positive [40-100%], FISH: 14/103 positive), BCL2 (IHC: 65/89 positive [50-100%], FISH: 23/111 positive) and BCL6 (IHC: 52/86 positive [30-100%], FISH: 34/110 positive) and data on cell of origin (COO) classification according to the Lymph2CX assay (GCB: 53/88; ABC: 24/88; unclassified: 11/88). Results: 130 pts had been assigned to R-CHOEP and 132 to R-MegaCHOEP. DLBCL was the most common lymphoma subtype (~80%). 73% of pts scored an aaIPI of 2 and 27% an aaIPI of 3. 60% of pts had an initial lymphoma bulk and in 40% more than 1 extranodal site was involved. After a median observation time of 111 months, EFS at 10 years was 57% (95% CI 47-67%) in the R-CHOEP vs. 51% in the R-MegaCHOEP arm (42-61%) (hazard ratio 1.3, 95% CI 0.9-1.8, p=0.228), overall survival (OS) after 10 years was 72% (63-81%) vs. 66% (57-76%) respectively (p=0.249). With regard to molecular characterization, we were unable to detect a significant benefit for HDT/ASCT in any subgroup analyzed. In total, 16% of pts (30 pts) relapsed after having achieved a complete remission (CR). 23% of all relapses (7 pts) showed an indolent histology (follicular lymphoma grade 1-3a) and 6 of these pts survived long-term. In contrast, of 23 pts (77%) relapsing with aggressive DLBCL or unknown histology 18 pts died due to lymphoma or related therapy. The majority of relapses occurred during the first 3 years after randomization (median time: 22 months) while after 5 years we detected relapses only in 5 pts (3% of all 190 pts prior CR). 11% of pts were initially progressive (28 pts) among whom 71% (20 pts) died rapidly due to lymphoma. Interestingly, the remaining 29% (8 pts) showed a long-term survival after salvage therapy (+/- ASCT); only 1 pt received allogeneic transplantation. The frequency of secondary malignancies was very similar in both treatment arms (9% vs. 8%) despite the very high dose of etoposide (total 4g/m2)in the R-MegaCHOEP arm. We observed 2 cases of AML and 1 case of MDS per arm. In total 70 pts (28%) have died: 30 pts due to lymphoma (12%), 22 pts therapy-related (11 pts due to salvage therapy) (9%), 8 pts of secondary neoplasia (3%), 5 pts due to concomitant disease (2%) and 5 pts for unknown reasons. Conclusions: This 10-year long-term follow-up of the R-MegaCHOEP trial confirms the very encouraging outcome of young high-risk pts following conventional chemotherapy with R-CHOEP. High-dose therapy did not improve outcome in any subgroup analysis including molecular high-risk groups. Relapse rate was generally low. Pts with aggressive relapse showed a very poor long-term outcome while pts with indolent histology at relapse survived long-term. Secondary malignancies occurred; however, they were rare with no excess leukemias/MDS following treatment with very high doses of etoposide and other cytotoxic agents. Supported by Deutsche Krebshilfe. Figure Disclosures Nickelsen: Roche Pharma AG: Membership on an entity's Board of Directors or advisory committees, Other: Travel Grants; Celgene: Membership on an entity's Board of Directors or advisory committees, Other: Travel Grant; Janssen: Membership on an entity's Board of Directors or advisory committees. Hänel:Amgen: Honoraria; Celgene: Other: advisory board; Novartis: Honoraria; Takeda: Other: advisory board; Roche: Honoraria. Truemper:Nordic Nanovector: Consultancy; Roche: Research Funding; Mundipharma: Research Funding; Janssen Oncology: Consultancy; Takeda: Consultancy, Research Funding; Seattle Genetics, Inc.: Research Funding. Held:Roche: Consultancy, Other: Travel support, Research Funding; Amgen: Research Funding; Acrotech: Research Funding; MSD: Consultancy; Bristol-Myers Squibb: Consultancy, Other: Travel support, Research Funding. Dreyling:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: scientific advisory board, Research Funding, Speakers Bureau; Bayer: Consultancy, Other: scientific advisory board, Speakers Bureau; Celgene: Consultancy, Other: scientific advisory board, Research Funding, Speakers Bureau; Mundipharma: Consultancy, Research Funding; Gilead: Consultancy, Other: scientific advisory board, Speakers Bureau; Novartis: Other: scientific advisory board; Sandoz: Other: scientific advisory board; Janssen: Consultancy, Other: scientific advisory board, Research Funding, Speakers Bureau; Acerta: Other: scientific advisory board. Viardot:Kite/Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; F. Hoffmann-La Roche Ltd: Honoraria, Membership on an entity's Board of Directors or advisory committees. Rosenwald:MorphoSys: Consultancy. Lenz:Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; AstraZeneca: Consultancy, Honoraria, Research Funding; Agios: Research Funding; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Bayer: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Roche: Employment, Honoraria, Research Funding, Speakers Bureau; BMS: Consultancy. Schmitz:Novartis: Honoraria; Gilead: Honoraria; Celgene: Equity Ownership; Riemser: Consultancy, Honoraria.

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The Genomic Landscape of Plasmablastic Lymphoma (PBL) - an L.L.M.P.P. Project

Blood ◽

10.1182/blood-2021-153441 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 1326-1326

Author(s):

Jasper Wong ◽

Brett Collinge ◽

Laura K Hilton ◽

Susana Ben-Neriah ◽

Graham W. Slack ◽

...

Keyword(s):

Gene Expression ◽

Clinical Trial ◽

B Cell ◽

Gene Expression Profiling ◽

Board Of Directors ◽

Cell Fate ◽

Expression Profiling ◽

Research Funding ◽

Advisory Committees ◽

Genomic Landscape

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..

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Validation of the EMC92/SKY92 Signature in HOVON-87/Nmsg-18: Gene Expression Based Prognostication Is Applicable in Elderly Patients with Newly Diagnosed Multiple Myeloma

Blood ◽

10.1182/blood.v126.23.2967.2967 ◽

2015 ◽

Vol 126 (23) ◽

pp. 2967-2967

Author(s):

Mark van Duin ◽

Rowan Kuiper ◽

Martin van Vliet ◽

Annemiek Broijl ◽

Leonie de Best ◽

...

Keyword(s):

Gene Expression ◽

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Univariate Analysis ◽

Low Risk ◽

Advisory Committees ◽

Hazard Ratios ◽

Risk Patients ◽

Standard Risk

Abstract Improved prognostication is required for multiple myeloma (MM). So far, marker development has been based on clinical trials with a study population predominantly younger than 65 years. However, the median age of newly diagnosed MM patients is 66 years old. Based on gene expression profiles of the HOVON-65/GMMG-HD4 dataset, we previously developed the EMC92 prognostic signature, consisting of 92 probe sets for improved prognostication in MM. The EMC92 was validated in the MRC-IX, TT2, TT3 and APEX datasets. These studies were mostly aimed at younger patients with a median age of 57 years. The EMC92 signature was subsequently developed for clinical use as part of the MMprofiler, and termed the SKY92 signature. To assess the validity of the SKY92 signature in older MM patients, we used the HOVON-87/NMSG-18 study, in which induction therapy with melphalan, prednisone and thalidomide, followed by thalidomide maintenance, was compared with melphalan, prednisone and lenalidomide, followed by lenalidomide maintenance (MPT-T vs. MPR-R). The median age of all patients included in this trial was 73 years, with 34% of patients 76 years or older. The median follow up of the patients still alive was 39 months. Of 143 patients both gene expression profiling and clinical data were available (median age 73; 30% ≥76; n=83 MPT-T; n=60 MPR-R). The MMprofiler was used to obtain SKY92 scores, classifying a patient as high risk or standard risk (MMprofiler- CE IVD assay, performed according to the manufacturers' instructions for use at the SkylineDx reference lab, Rotterdam, The Netherlands). The association between survival and the SKY92 signature was evaluated using Cox regression analysis. Kaplan-Meier curves were constructed for visualization. Using the SKY92 signature 22/143 patients were identified as high risk (15.4%). The median overall survival (OS) for high risk patients was 21 months, compared to 53 months for standard risk patients (hazard ratio (HR): 2.9 (95% confidence interval (CI): 1.6-5.4; p=5.6 x 10-4)). The median progression free survival (PFS) in the high risk and standard risk groups were 12 months and 23 months, respectively (HR: 2.2 (95% CI: 1.4-3.7; p=1.2 x 10-3)). In this subset of 143 patients, deletion of 17p (del17p) and gain of 1q (gain1q) were also adversely associated with OS in a univariate analysis. Including SKY92, del(17p) and gain(1q) in a multivariate model demonstrated that SKY92 and del(17p) remained significantly associated with OS (subset of 143 (n=101) with all data known; Table 1). We previously developed the combination of ISS with SKY92: low risk (ISS I-SKY92 standard risk (SR)), intermediate-low (ISS II-SKY92 SR), intermediate-high (ISS III-SKY92 SR) and high risk (ISS I-III, SKY92 high risk; Kuiper et al., ASH 2014, #3358). The Cox model for this combined marker has a p-value for the likelihood ratio test of p=3 x 10-3 for OS (Figure 2) and p=0.016 for PFS. In conclusion, the SKY92 signature (MMprofiler) is a useful prognostic marker to identify a high-risk subgroup in the elderly population. Figure 1. Performance of the SKY92 signature in the HOVON-87/NMSG-18 study. Red line indicates high risk patients (n=22), blue line indicates standard risk patients (n=121). PFS (A); OS (B). Figure 1. Performance of the SKY92 signature in the HOVON-87/NMSG-18 study. Red line indicates high risk patients (n=22), blue line indicates standard risk patients (n=121). PFS (A); OS (B). Table 1. SKY92 in relation to FISH markers in the HOVON-87/NMSG-18 (Hazard ratios (HR), 95% confidence intervals (CI) and p-values (2-sided; p) for Cox proportional hazards analysis). The multivariate analysis (bottom) was performed using the markers significant in the univariate analysis (top). Bold: p<0.05, pos: positive, neg: negative and na: not available. Table 1. SKY92 in relation to FISH markers in the HOVON-87/NMSG-18 (Hazard ratios (HR), 95% confidence intervals (CI) and p-values (2-sided; p) for Cox proportional hazards analysis). The multivariate analysis (bottom) was performed using the markers significant in the univariate analysis (top). Bold: p<0.05, pos: positive, neg: negative and na: not available. Figure 2. Combining ISS with SKY92. Groups are defined in the text. Hazard ratios of the individual groups are given relative to the low risk group. Figure 2. Combining ISS with SKY92. Groups are defined in the text. Hazard ratios of the individual groups are given relative to the low risk group. Disclosures Kuiper: SkylineDx: Employment. van Vliet:SkylineDx: Employment. Broijl:Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. de Best:SkylineDx: Employment. van Beers:SkylineDx: Employment. Bosman:SkylineDx: Employment. Dumee:SkylineDx: Employment. van den Bosch:SkylineDx: Employment. Waage:Amgen: Research Funding; Celgene: Research Funding; Janssen: Research Funding. Zweegman:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Sonneveld:Celgene: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Karyopharm: Research Funding; SkylineDx: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Research Funding.

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Use of Gene Expression Profiling May Predict Clinical Outcomes in Newly Diagnosed Multiple Myeloma Patients in a Standard of Care Setting

Blood ◽

10.1182/blood.v126.23.5390.5390 ◽

2015 ◽

Vol 126 (23) ◽

pp. 5390-5390

Author(s):

Catherine M Claussen ◽

Tammy Chuang ◽

Jatin Shah ◽

Hans Lee ◽

Nina Shah ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Clinical Outcomes ◽

Expression Profiling ◽

Research Funding ◽

Complete Response ◽

Low Risk ◽

Newly Diagnosed ◽

Advisory Committees ◽

Risk Patients

Abstract Introduction: Multiple myeloma (MM) is characterized by malignant plasma cell (PC) proliferation. Gene expression profiling (GEP) of CD138+ bone marrow PC has emerged as a new way to identify patients with worse clinical outcomes so that an individualized treatment approach can be undertaken in the clinic. The majority of data with GEP come from clinical trials. We aimed to evaluate the use of GEP in a standard clinical setting. Methods: We retrospectively searched our database of newly diagnosed MM patients with GEP completed prior to initial treatment. 35MM patients from April 2014 until June 2015 were identified and included in our analysis. GEP was performed through MyPRS® (Signal Genetics, Little Rock, AR). Fisher's exact test was used to evaluate the associations between complete response status and other categorical variables. The Wilcoxon rank sum test was used to evaluate the difference in continuous variables between patients that achieved a complete remission after 6 months of initial treatment and those who did not. Responses were assessed using IMWG criteria. Results: Median age was 60 (38-76). Patients presented with lytic lesions (60%), anemia (80%), kidney dysfunction (11%) and hypercalcemia (20%). All patients with known initial therapy were treated with bortezomib (n=29) or carfilzomib (n=1) based therapy. 10 patients had upfront autologous stem cell transplant. 18 patients had available response at 6 months. 37% (n=13) of patients were characterized as high risk by GEP, of which 46% (n=6) had the proliferation (PR) subtype. Most low risk patients had hyperdiploidy (HY) subtype (n=12, 55%). Patients with high risk GEP presented more often with complex karyotypes whereas low risk GEP patients most often had normal or hyperdiploid karyotypes. FISH abnormalities that are usually present in high risk myeloma were also present in patients classified as GEP low risk (Table 1). At 6 months after diagnosis, lower baseline total protein, serum M-spike, serum free light chain ratio and serum kappa light chain levels were significantly associated with achieving a stringent complete response (sCR) (p<0.05). High risk patients were more likely to achieve a CR (n= 6/10, 60%) than low risk patients (n=5/16, 31%) at 6 months. Despite this, high risk patients seemed more likely to lose CR and relapse or die. Within one year of diagnosis, one patient relapsed after achieving a VGPR (high risk, PR subtype) and one patient died due to MM progressive disease after achieving an sCR (high risk, CD-1 subtype) (Table 1). Conclusion: In a standard clinical setting, GEP seems to identify MM patients that are at higher risk of adverse clinical outcomes early after diagnosis. GEP may be an adjunct to cytogenetics/FISH in MM risk stratification, as high risk FISH abnormalities were also found in low risk GEP patients. Larger studies with longer follow up may help address the particular role of GEP in the individualized treatment of MM. Figure 1. Figure 1. Disclosures Orlowski: Array BioPharma: Consultancy, Research Funding; Acetylon: Membership on an entity's Board of Directors or advisory committees; Onyx Pharmaceuticals: Consultancy, Research Funding; Spectrum Pharmaceuticals: Research Funding; Celgene: Consultancy, Research Funding; Genentech: Consultancy; Millennium Pharmaceuticals: Consultancy, Research Funding; Forma Therapeutics: Consultancy; BioTheryX, Inc.: Membership on an entity's Board of Directors or advisory committees; Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Research Funding.

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A Phase 1 Trial of MEC (Mitoxantrone, Etoposide, Cytarabine) in Combination with Ixazomib (MLN9708) for Relapsed/ Refractory Acute Myeloid Leukemia (AML)

Blood ◽

10.1182/blood.v128.22.4065.4065 ◽

2016 ◽

Vol 128 (22) ◽

pp. 4065-4065

Author(s):

Anjali S. Advani ◽

Brenda Cooper ◽

Paul Elson ◽

Sudipto Mukherjee ◽

Jaime Fensterl ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profiling ◽

Board Of Directors ◽

Dose Escalation ◽

Expression Profiling ◽

Research Funding ◽

Overall Response Rate ◽

Response Rate ◽

Advisory Committees ◽

Grade 3

Abstract Proteasome inhibitors (PIs) capitalize on the constitutive activation of NF-KB in AML cells and increase chemosensitivity to anthracyclines and cytarabine. We combined the second generation PI, ixazomib, with the standard AML salvage regimen of MEC (mitoxantrone, etoposide, cytarabine). The primary objectives of this study were to determine the dose limiting toxicity (DLT), maximum tolerated dose (MTD), and phase 2 dose of ixazomib in combination with MEC in relapsed/ refractory (R/R) AML. Secondary objectives included evaluating the efficacy of this combination and correlating response to the gene expression profile and CD74 expression, which may identify a subset of leukemias in which NF-KB is operative with increased sensitivity to PI (Attar et al. CCR 2008; 14: 1446-54). Methods: Patients (pts) were treated at Cleveland Clinic and University Hospitals of Cleveland from Oct 2014 to present. An IND was approved by the FDA, and the protocol was approved by each institutional review board. Eligibility: age 18-70 yrs, R/R AML, and cardiac ejection fraction ≥ 45%. The fraction of blasts positive for CD74 was assessed by flow cytometry. Samples were stored for gene expression profiling pre- and post-treatment (at the time of response assessment). Pts received MEC: mitoxantrone (8 mg/ m2), etoposide (80 mg/m2), and cytarabine (1000 mg/m2) intravenous (IV) Days 1-6. Ixazomib, provided by Takeda, was given orally on Days 1, 4, 8, and 11 and was dose escalated using a standard 3x3 design. Dose levels (DLs): 1 (1.0 mg), 2 (2.0 mg), 3 (3.0 mg), 4 (3.7 mg). An additional 18 pts were to be treated at the MTD. One cycle of treatment was administered. Response was assessed by bone marrow aspirate/ biopsy by Day 45 and complete remission (CR) was defined by IWG criteria (Cheson 2006). Toxicities were graded according to NCI CTCAE v 4.03. Toxicities secondary to neutropenia or sepsis were not considered DLTs. DLTs included: (1) ≥ Grade 4 non-hematologic toxicity (NHT) with the exception of nausea, vomiting/ alopecia and drug-related fevers; (2) any ≥ Grade 3 neurologic toxicity; (3) grade 4 platelet or neutrophil count 50 days beyond the start of chemotherapy and not related to leukemia; (4) any Grade 4 NHT > grade 2 by 45 days beyond the start of chemotherapy. Grade 2, 3, and 4 hyperbilirubinemia were redefined as 1.5-< 10x upper limits of normal (ULN), 10-20 x ULN, and > 20 x ULN. Results: Of 23 pts enrolled, 22 are evaluable. The median age was 58 yrs (range 31-70), 12 (52%) were male and the median baseline WBC was 2.56 K/ uL (range 0.1-62.9). The median time from initial diagnosis to registration was 7.1 months (range 1.4-36.8) and 7 pts (30%) had a history of an antecedent hematologic disorder. Thirteen pts were in 1st relapse and 10 pts were refractory to their last therapy. One pt had received a prior allogeneic hematopoietic cell transplant (AHCT), 7 pts had FLT3 ITD mutations and 7/ 21 pts (33%) had adverse cytogenetics per CALGB 8461 criteria at the time of relapse. At DL1, 1 DLT occurred (grade 4 thrombocytopenia), so this DL was expanded to 6 pts. At DL2, 2 pts developed Grade 4 thrombocytopenia; therefore, the MTD of ixazomib was 1.0 mg. The most common grade 3-5 NHTs in the dose escalation phase were febrile neutropenia (100%), hypoalbuminemia (25%), hypokalemia (42%), hypotension (33%), and respiratory failure (33%). No adverse events in the dose escalation phase were attributed to ixazomib alone. The overall response rate was 55% [CR/ CR with incomplete count recovery (CRi)], and 9 pts proceeded to AHCT. Five of these 9 pts remain alive with a median follow-up of 12.8 months. Five pts had CD74 expression performed. Two pts had high levels of CD74 expression (> 80%); and both achieved CRi. Myeloid mutation panel data was available in 14 pts. Previous data has demonstrated the number of mutations in DNTMT3A, TP53, ASXL1, and NRAS (0, 1, >1) is associated with a worse response to salvage therapy (Advani et al, abstract 3825, ASH 2015). Seven pts had at least one of these mutations and 6 of the 7 achieved CR/ CRi. Conclusions: The combination of MEC and ixazomib was well-tolerated and produced an overall response rate of 55% in patients with relapsed/ refractory AML irrespective of molecular mutation status. The combination is safe with a similar toxicity profile to MEC alone. CD74 expression may represent a biomarker for response to this therapy. Results from gene expression profiling will be complete by the time of the meeting and will be presented. Disclosures Mukherjee: Novartis: Consultancy, Honoraria, Research Funding; Ariad: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Caimi:Genentech: Speakers Bureau; Gilead: Consultancy; Roche: Research Funding; Novartis: Consultancy. Maciejewski:Alexion Pharmaceuticals Inc: Consultancy, Honoraria, Speakers Bureau; Apellis Pharmaceuticals Inc: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Speakers Bureau. Sekeres:Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees.

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Multicenter Analysis of Treatment and Outcomes for Patient with TP53 Mutated AML in the Era of Novel Therapies; Significant Impact of Allogeneic Stem Cell Transplantation on Survival

Blood ◽

10.1182/blood-2021-147639 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 797-797

Author(s):

Talha Badar ◽

Mark R. Litzow ◽

Rory M. Shallis ◽

Jan Philipp Bewersdorf ◽

Antoine Saliba ◽

...

Keyword(s):

Stem Cell ◽

High Risk ◽

Stem Cell Transplantation ◽

Board Of Directors ◽

Research Funding ◽

Univariate Analysis ◽

Advisory Board ◽

Novel Therapies ◽

Advisory Committees ◽

Tp53 Mutations

Abstract Background: TP53 mutations occur in 10-20% of patients with AML, constitute high-risk disease as per ELN criteria, and confer poorer prognosis. Venetoclax combination therapies and CPX-351 were recently approved for AML treatment and lead to improved outcomes in subsets of high-risk AML, however the most effective approach for treatment of TP53-mutated (m) AML remains unclear. In this study we explored the clinical outcome of TP53m AML patients treated over the last 8 years as novel therapies have been introduced to our therapeutic armamentarium. Methods: We conducted a multicenter observational study in collaboration with 4 U.S. academic centers and analyzed clinical characteristics and outcome of 174 TP53m AML patients diagnosed between March 2013 and February 2021. Mutation analysis was performed on bone marrow specimens using 42, 49, 199, or 400 gene targeted next generation sequencing (NGS) panels. Patients with an initial diagnosis of AML were divided into 4 groups (GP) based on the progressive use of novel therapies in clinical trials and their approvals as AML induction therapy during different time periods: 2013-2017 (GP1, n= 37), 2018-2019 (GP2, n= 53), 2019-2020 (GP3, n= 48) and 2020-2021 (GP4, n= 36) to analyze difference in outcome. Results: Baseline characteristics were not significantly different across different GP, as shown in Table 1. Median age of patients was 68 (range [R], 18-83), 65 (R, 29-88), 69 (R, 37-90) and 70 (R, 51-97) years in GP1-4, respectively (p=0.40). The percentage of patients with de novo AML/secondary AML/therapy-related AML in GP1-4 was 40/40/20, 36/29/24, 37.5/37.5/25 and 28/52/20, respectively (p=0.82). The proportion of patients with complex cytogenetics (CG) was 92%, 89%, 96% and 94% in GP1-4, respectively (p=0.54). The median TP53m variant allele frequency (VAF) was 48% (range [R], 5-94), 42% (R, 5-91), 45% (R, 10-94) and 60% (R, 8-82) in GP1-4, respectively (p=0.38). Four (11%), 13 (24.5%), 10 (21%) and 9 (25%) patients had multiple TP53 mutations in GP1-4, respectively (p=0.33). The proportion of patients who received 3+7 (30%, 16%, 6% & 8%; p=0.01), HMA only (11%, 18%, 2% & 8%; p=0.06), venetoclax-based (2.5%, 12%, 48%, & 61%; p <0.01) and CPX-351 induction (16%, 40%, 28% & 5%; p<0.001) were varied in GP1-4, respectively. The rate of CR/CRi was 22%, 26%, 28% and 18% in GP1-4, respectively (p=0.63). Treatment related mortality during induction was observed in 3%, 7%, 10% and 17% of patients in GP1-4, respectively (p=0.18). Overall, 28 (16%) patients received allogeneic hematopoietic stem cell transplantation (alloHCT) after induction/consolidation: 22%, 15%, 17% and 11% in GP1-4, respectively (p=0.67). In subset analysis, there was no difference in the rate of CR/CRi with venetoclax-based regimens vs. others (39% vs 61%, p=0.18) or with CPX-351 vs. others (25% vs 75%, p=0.84). The median progression-free survival was 7.7, 7.0, 5.1 and 6.6 months in GP1-4, respectively (p=0.60, Fig 1A). The median overall survival (OS) was 9.4, 6.1, 4.0 and 8.0 months in GP1-4, respectively (p=0.29, Fig 1B). In univariate analysis for OS, achievement of CR/CRi (p<0.001) and alloHCT in CR1 (p<0.001) associated with favorable outcome, whereas complex CG (p=0.01) and primary refractory disease (p<0.001) associated with poor outcome. Multiple TP53 mutations (p=0.73), concurrent ASXL1m (p=0.86), extra-medullary disease (p=0.92), ≥ 3 non-TP53m mutations (p=0.72), TP53m VAF ≥ 40% vs. < 40% (p=0.25), induction with CPX-351 vs. others (p=0.59) or venetoclax-based regimen vs. others (p=0.14) did not show significance for favorable or poor OS in univariate analysis. In multivariable analysis, alloHCT in CR1 (hazard ratio [HR]=0.28, 95% CI: 0.15-0.53; p=0.001) retained an association with favorable OS and complex CG (HR 4.23, 95%CI: 1.79-10.0; p=0.001) retained an association with dismal OS. Conclusion: We present the largest experience with TP53m AML patients analyzed by NGS. Although outcomes were almost universally dismal, alloHCT appears to improve the long-term survival in a subset of these patients. Effective therapies are warranted to successfully bridge patients to alloHCT and to prolong survival for transplant ineligible patients. Figure 1 Figure 1. Disclosures Badar: Pfizer Hematology-Oncology: Membership on an entity's Board of Directors or advisory committees. Litzow: Omeros: Other: Advisory Board; Pluristem: Research Funding; Actinium: Research Funding; Amgen: Research Funding; Jazz: Other: Advisory Board; AbbVie: Research Funding; Astellas: Research Funding; Biosight: Other: Data monitoring committee. Shallis: Curis: Divested equity in a private or publicly-traded company in the past 24 months. Goldberg: Celularity: Research Funding; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Aprea: Research Funding; Arog: Research Funding; DAVA Oncology: Honoraria; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Research Funding; Prelude Therapeutics: Research Funding; Aptose: Consultancy, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Atallah: BMS: Honoraria, Speakers Bureau; Takeda: Consultancy, Research Funding; Amgen: Consultancy; Abbvie: Consultancy, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Research Funding. Foran: revolution medicine: Honoraria; gamida: Honoraria; bms: Honoraria; pfizer: Honoraria; novartis: Honoraria; takeda: Research Funding; kura: Research Funding; h3bioscience: Research Funding; OncLive: Honoraria; servier: Honoraria; aptose: Research Funding; actinium: Research Funding; abbvie: Research Funding; trillium: Research Funding; sanofi aventis: Honoraria; certara: Honoraria; syros: Honoraria; taiho: Honoraria; boehringer ingelheim: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding.

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Identification of Two CAR T-Cell Populations Associated with Complete Response or Progressive Disease in Adult Lymphoma Patients Treated with Axi-Cel

Blood ◽

10.1182/blood-2019-130815 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 779-779 ◽

Cited By ~ 2

Author(s):

Zinaida Good ◽

Jay Y. Spiegel ◽

Bita Sahaf ◽

Meena B. Malipatlolla ◽

Matthew J. Frank ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Board Of Directors ◽

Research Funding ◽

Advisory Board ◽

Advisory Committees ◽

Car T Cells ◽

Scientific Advisory Board ◽

Car T ◽

Scientific Advisory

Axicabtagene ciloleucel (Axi-cel) is an autologous anti-CD19 chimeric antigen receptor (CAR) T-cell therapy approved for the treatment of relapsed or refractory diffuse large B-cell lymphoma (r/r DLBCL). Long-term analysis of the ZUMA-1 phase 1-2 clinical trial showed that ~40% of Axi-cel patients remained progression-free at 2 years (Locke et al., Lancet Oncology 2019). Those patients who achieved a complete response (CR) at 6 months generally remained progression-free long-term. The biological basis for achieving a durable CR in patients receiving Axi-cel remains poorly understood. Here, we sought to identify CAR T-cell intrinsic features associated with CR at 6 months in DLBCL patients receiving commercial Axi-cel at our institution. Using mass cytometry, we assessed expression of 33 surface or intracellular proteins relevant to T-cell function on blood collected before CAR T cell infusion, on day 7 (peak expansion), and on day 21 (late expansion) post-infusion. To identify cell features that distinguish patients with durable CR (n = 11) from those who developed progressive disease (PD, n = 14) by 6 months following Axi-cel infusion, we performed differential abundance analysis of multiparametric protein expression on CAR T cells. This unsupervised analysis identified populations on day 7 associated with persistent CR or PD at 6 months. Using 10-fold cross-validation, we next fitted a least absolute shrinkage and selection operator (lasso) model that identified two clusters of CD4+ CAR T cells on day 7 as potentially predictive of clinical outcome. The first cluster identified by our model was associated with CR at 6 months and had high expression of CD45RO, CD57, PD1, and T-bet transcription factor. Analysis of protein co-expression in this cluster enabled us to define a simple gating scheme based on high expression of CD57 and T-bet, which captured a population of CD4+ CAR T cells on day 7 with greater expansion in patients experiencing a durable CR (mean±s.e.m. CR: 26.13%±2.59%, PD: 10.99%±2.53%, P = 0.0014). In contrast, the second cluster was associated with PD at 6 months and had high expression of CD25, TIGIT, and Helios transcription factor with no CD57. A CD57-negative Helios-positive gate captured a population of CD4+ CAR T cells was enriched on day 7 in patients who experienced progression (CR: 9.75%±2.70%, PD: 20.93%±3.70%, P = 0.016). Co-expression of CD4, CD25, and Helios on these CAR T cells highlights their similarity to regulatory T cells, which could provide a basis for their detrimental effects. In this exploratory analysis of 25 patients treated with Axi-cel, we identified two populations of CD4+ CAR T cells on day 7 that were highly associated with clinical outcome at 6 months. Ongoing analyses are underway to fully characterize this dataset, to explore the biological activity of the populations identified, and to assess the presence of other populations that may be associated with CAR-T expansion or neurotoxicity. This work demonstrates how multidimensional correlative studies can enhance our understanding of CAR T-cell biology and uncover populations associated with clinical outcome in CAR T cell therapies. This work was supported by the Parker Institute for Cancer Immunotherapy. Figure Disclosures Muffly: Pfizer: Consultancy; Adaptive: Research Funding; KITE: Consultancy. Miklos:Celgene: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Kite-Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; AlloGene: Membership on an entity's Board of Directors or advisory committees; Precision Bioscience: Membership on an entity's Board of Directors or advisory committees; Miltenyi Biotech: Membership on an entity's Board of Directors or advisory committees; Becton Dickinson: Research Funding; Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno: Membership on an entity's Board of Directors or advisory committees. Mackall:Vor: Other: Scientific Advisory Board; Roche: Other: Scientific Advisory Board; Adaptimmune LLC: Other: Scientific Advisory Board; Glaxo-Smith-Kline: Other: Scientific Advisory Board; Allogene: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Apricity Health: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Unum Therapeutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Obsidian: Research Funding; Lyell: Consultancy, Equity Ownership, Other: Founder, Research Funding; Nektar: Other: Scientific Advisory Board; PACT: Other: Scientific Advisory Board; Bryologyx: Other: Scientific Advisory Board.

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Ninety Percent Sustained Complete Response (CR) Rate Projected 4 Years after Onset of CR in Gene Expression Profiling (GEP)-Defined Low-Risk Multiple Myeloma (MM) Treated with Total Therapy 3 (TT3): Basis for GEP-Risk-Adapted TT4 and TT5

Blood ◽

10.1182/blood.v112.11.162.162 ◽

2008 ◽

Vol 112 (11) ◽

pp. 162-162 ◽

Cited By ~ 5

Author(s):

Bart Barlogie ◽

Elias J. Anaissie ◽

John D. Shaughnessy ◽

Frits van Rhee ◽

Mauricio Pineda-Roman ◽

...

Keyword(s):

Gene Expression ◽

High Risk ◽

Gene Expression Profiling ◽

Expression Profiling ◽

Complete Response ◽

Low Risk ◽

Event Free Survival ◽

Free Survival ◽

Response Onset ◽

Dose Dense

Abstract We have previously reported on the remarkable activity of the TT3 program that incorporated both bortezomib (V) and thalidomide (T) into the up-front management of 303 patients. TT3 consisted of 2 cycles each of induction prior to and of dose-reduced consolidation therapy with VTD-PACE (cisplatin, doxorubicin, cyclophosphamide, etoposide) after melphalan 200mg/m2 (M200)-based tandem transplants, followed by maintenance therapy for 3 years with VTD and, in later stages, VRD (substituting T for lenalidomide, R). Characteristics included a median age of 59yr (range, 33–75yr), B2M >=4mg/L in 37%, albumin <3.5g/dL in 26%, ISS stages II and III in 33% and 21%, cytogenetic abnormalities (CA) in 33% and gene expression profiling (GEP)-defined high-risk MM in 15% of the 275 patients with such data. With a median follow-up of 39 months, 4-yr overall survival (OS) and event-free survival (EFS) estimates were 78% and 71%, respectively, including 84% and 77% among the 85% with GEP-defined low-risk MM contrasting with 43% and 33% in the remainder with high-risk MM (both p<0.0001). Near-CR and CR, attained in 86% and 63%, were sustained at 4 years from response onset in 78% and 87%, which pertained to 83% and 90% with low-risk MM but to only 44% and 57% with high-risk MM (all p <0.0001). These results were corroborated in a TT3 extension trial (TT3E) that enrolled 175 additional patients, comprising higher proportions of CA (42%) and GEP-defined high-risk MM (21%). Two-year estimates of OS and EFS are 85% and 85%, with 94% and 92% in low-risk patients versus 61% and 62% in high-risk MM (p=0.0001, p=0.0003); the 2-yr estimate of remaining in CR is 93% including 100% in low-risk and 77% in high-risk MM (p=0.01). Multivariate analysis of features linked to OS in TT3 included GEP-defined high-risk, CA, B2M and LDH elevation, collectively accounting for 41% of outcome variability by R2 statistics; the corresponding R2 values for EFS and n-CR duration were 38% and 39%. Compared to the predecessor trial, TT2, that evaluated the role of T in a randomized trial design in 668 patients, TT3 data were superior for OS (p=0.08), EFS (<0.0001), n-CR duration (p<0.0001) and CR duration (p=0.0002). In the low-risk subgroup, EFS (p=0.0001), n-CR duration (p<0.0001) and CR duration (Figure 1a; p=0.0002) all were superior in TT3 versus TT2; whereas, in the high-risk MM group, outcomes remained poor also with TT3 despite superior EFS (Figure 1b; p=0.03). Based on these data, we have now started a GEP-risk-based algorithm of assigning separate therapies to good-risk (TT4) and poor-risk MM (TT5). As the TT3 results for low-risk are difficult to improve upon, TT4 randomizes patients between standard TT3 and TT3-LITE that employs only 1 cycle each of induction and consolidation (with anticipated further improvement in compliance) and 4-day-fractionated M50×4 to enable the addition of VTD and thus exploit synergistic drug interactions to occur. In order to sustain tolerable effective therapies for at least 3 years and prevent recurrence from previous drug-free or insufficiently effective phases in TT3, TT5 for high-risk MM employs less dose-intense and more dose-dense highly synergistic combination therapy, utilizing M10-VTD-PACE for induction, M80 (in 4 daily fractions of M20) plus VRD-PACE tandem transplants, separated by 2 cycles of M20 (in 4 daily fractions of M5) plus VTD-PACE, and followed by 2 years of monthly alternating R-VD and M-VD. Figure 1a: Superior CR duration with TT3 v TT2 in GEP-low-risk MM: Figure 1a:. Superior CR duration with TT3 v TT2 in GEP-low-risk MM: Figure 1b: Superior event-free survival with TT3 v TT2 in GEP-high-risk MM: Figure 1b:. Superior event-free survival with TT3 v TT2 in GEP-high-risk MM:

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High Risk Multiple Myeloma Demonstrates Marked Spatial Genomic Heterogeneity Between Focal Lesions and Random Bone Marrow; Implications for Targeted Therapy and Treatment Resistance

Blood ◽

10.1182/blood.v126.23.20.20 ◽

2015 ◽

Vol 126 (23) ◽

pp. 20-20 ◽

Cited By ~ 5

Author(s):

Niels Weinhold ◽

Shweta S. Chavan ◽

Christoph Heuck ◽

Owen W Stephens ◽

Ruslana Tytarenko ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Advisory Board ◽

Driver Mutations ◽

University Of Arkansas ◽

Medical Sciences ◽

Clonal Heterogeneity ◽

Advisory Committees ◽

Site Specific

Abstract Introduction: Recent next generation sequencing studies have defined the mutation spectrum in multiple myeloma (MM) and uncovered significant intra-clonal heterogeneity, showing that clinically relevant mutations are often only present in sub-clones. Longitudinal analyses demonstrated that tumor clones under therapeutic pressure behave in a "Darwinian" fashion, with shifting dominance of tumor clones over time. Recently, stratification of clonal substructures in distinct areas of the tumor bulk has been shown for multiple cancer types. So far, spatial genomic heterogeneity has not been systematically analyzed in MM. This stratification in space is becoming increasingly important as we begin to understand the contribution of Focal Lesions (FL) to tumor progression and emergence of drug resistance in MM. We have recently shown that high numbers of FL are associated with gene expression profiling (GEP) defined high risk (HR). A comparison of GEP data of 170 paired random bone marrow (RBM) and FL aspirates showed differences in risk signatures, supporting the concept of spatial clonal heterogeneity. In this study we have extended the analysis by performing whole exome sequencing (WES) and genotyping on paired RBM and FL in order to gain further insight into spatial clonal heterogeneity in MM and to find site-specific single nucleotide variant (SNV) spectra and copy number alterations (CNA), which contribute to disease progression and could form the basis of adaptation of the tumor to therapeutic pressure. Materials and Methods: We included 50 Total Therapy MM patients for whom paired CD138-enriched RBMA and FL samples were available. Leukapheresis products were used as controls. For WES we applied the Agilent qXT kit and a modified Agilent SureSelect Clinical Research Exome bait design additionally covering the immunoglobulin heavy chain locus and sequences located within 1Mb of the MYC locus. Paired-End sequencing to a minimum average coverage of 120x was performed on an Illumina HiSeq 2500. Sequencing data were aligned to the Ensembl GRCh37/hg19 human reference using BWA. Somatic variants were identified using MuTect. For detection of CNA we analyzed Illumina HumanOmni 2.5 bead chip data with GenomeStudio. Subclonal reconstruction was performed using PhyloWGS. Mutational signatures were investigated using SomaticSignatures. The GEP70 risk signature was calculated as described previously. Informed consent in accordance with the Declaration of Helsinki was obtained for all cases included in this study. Results: Analyzing RBM and FL WES data, we detected between 100 and 200 somatic SNVs in covered regions, with approximately 30% of them being non-synonymous, and less than 5% stop gained or splice site variants. A comparison of paired RBM and FL WES data showed different extents of spatial heterogeneity. Some pairs had very similar mutation profiles with up to 90% shared variants, whereas others demonstrated marked heterogeneity of point mutations. We did not detect differences in mutational signatures between RBM and FL using the 'SomaticSignatures' package. We found site-specific driver mutations with high variant allele frequencies, indicating replacement of other clones in these areas. For example we observed a clonal KRAS mutation exclusively in the RBM, whereas a NRAS variant was only identified in the paired FL. The same holds true for large-scale CNAs (>1 Mb). We identified a case in which the high risk CNAs gain(1q) and del(17p) were only detectable in the FL. Further examples for site-specific CNAs were a del(10q21) and a gain(4q13) detected in FLs only. As a prominent pattern, we observed outgrowth of sub-clonal RBM CNAs as clonal events in the FL. Based on mutation and CNA data we identified different forms of spatial evolution, including parallel, linear and branching patterns. Of note, a stratified analysis by GEP70-defined risk showed that a more pronounced spatial genomic heterogeneity of SNVs and CNAs was associated with HR disease. Conclusion: We show that spatial heterogeneity in clonal substructure exists in MM and that it is more pronounced in HR. The existence of site-specific HR CNAs and driver mutations highlights the importance of heterogeneity analyses for targeted treatment strategies, thereby facilitating optimal personalized MM medicine. Disclosures Weinhold: University of Arkansas for Medical Sciences: Employment; Janssen Cilag: Other: Advisory Board. Chavan:University of Arkansas for Medical Sciences: Employment. Heuck:Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment; Foundation Medicine: Honoraria. Stephens:University of Arkansas for Medical Sciences: Employment. Tytarenko:University of Arkansas for Medical Sciences: Employment. Bauer:University of Arkansas for Medical Sciences: Employment. Peterson:University of Arkansas for Medical Sciences: Employment. Ashby:University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Johann:University of Arkansas for Medical Sciences: Employment. Johnson:University of Arkansas for Medical Sciences: Employment. Yaccoby:University of Arkansas for Medical Sciences: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Zangari:Novartis: Research Funding; Onyx: Research Funding; Millennium: Research Funding; University of Arkansas for Medical Sciences: Employment. Schinke:University of Arkansas for Medical Sciences: Employment. Thanendrarajan:University of Arkansas for Medical Sciences: Employment. Davies:Millenium: Consultancy; Onyx: Consultancy; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment; Janssen: Consultancy. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:University of Arkansas for Medical Sciences: Employment; MMRF: Honoraria; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Weismann Institute: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

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