Central Nervous System Involvement By Mantle Cell Lymphoma

Background: While extranodal involvement by mantle cell lymphoma (MCL) is relatively common, involvement of the central nervous system (CNS) is rare (<5% of cases), with limited treatment options. We report the outcomes of 36 patients (pts) with CNS involvement compared to 72 matched control MCL pts without CNS involvement. Methods: MCL pts with CNS involvement seen at Mayo Clinic between 1/1995-9/2020 were identified using the Mayo Data Explorer tool. CNS involvement was defined by tissue biopsy confirmed CNS MCL, CSF analysis demonstrating lymphoma cells, and/or neuroimaging findings compatible with CNS involvement. A 2:1 control group of MCL pts without CNS involvement, matched by age (+/- 2 years) and year of diagnosis (+/- 1 year), was selected among all MCL cases. Medical records were reviewed for baseline characteristics, treatment modalities, and outcomes. Kaplan-Meier method was used for time to event analysis. Wilcoxon test was used to compare continuous variables and Chi square test was used for categorical variables. Results: Out of 1,753 pts with MCL, 36 (2%) had evidence of CNS involvement, including 4 pts with CNS involvement at initial MCL diagnosis. Baseline characteristics of pts with CNS involvement (CNS MCL group) and those without CNS involvement (control group) are shown in Table 1. At MCL diagnosis, non-CNS extranodal involvement was seen in 30 (83%) pts in the CNS MCL group (24 pts with 1 site and 6 pts with ≥ 2 sites), with bone marrow being the most common extranodal site of involvement (n=24, 67%). For the control group, 54 (75%) pts had extranodal involvement (44 pts with 1 site and 10 pts with ≥ 2 sites), and bone marrow was also the most common extranodal site of involvement (n=50, 69%). Notably, advanced stage disease (stage 3-4) was more commonly seen in the CNS MCL group (n=32, 97%) than in the control group (n=59, 83%) (p=0.04) at MCL diagnosis. Blastoid variant was present in a higher proportion of pts in the CNS MCL group (n=11, 31%) compared to the control group (n=8, 11%) (p=0.02). The CNS MCL group also presented with a higher median serum LDH at diagnosis (239 U/L [range 153-1901] vs. 187 U/L [range 124-588], p=0.02), and higher Ki-67 (40% [range 15-100] vs. 30% [range 10-90], p=0.04) compared to the control group. The most common frontline treatment regimen was anthracycline-based therapies (i.e. R-CHOP, Nordic regimen, R-hyperCVAD) for both groups (58% in CNS MCL group and 56% in control group). 14 (39%) pts in the CNS MCL group underwent autologous stem cell transplant in CR1 vs. 31 pts (43%) in the control group. Similar use of rituximab maintenance was seen in both groups (31% in CNS MCL group and 25% in control group). Median total lines of therapy from initial MCL diagnosis was 3 (range 1-9) in CNS MCL group and 2 (range 1-9) in the control group. The median follow-up from MCL diagnosis was 134 months (95% CI:119-163) for the entire cohort. Median OS from MCL diagnosis was 50.3 months (95% CI: 20.9-71.1) for the CNS MCL group compared to 97.1 months (95% CI: 82.6-192.7; p=<0.001) for the control group (Figure 1). Median time from MCL diagnosis to CNS involvement was 25 months (range 0-167). Median OS from CNS involvement was 4.7 months (95% CI: 2.3-6.7). At last follow up, 31 (86%) pts were deceased from the CNS MCL group, compared to 38 (52%) pts in the control group. For the CNS MCL group, the causes of death were CNS lymphoma in 10 (32%) pts, systemic lymphoma in 9 (29%) pts, treatment-related complication in 7 (23%) pts, and other/unknown in 5 (16%) pts. For the control group, the causes of death were systemic lymphoma in 15 (39%) pts, treatment-related in 2 (5%) pts, and other/unknown in 21 (55%) pts. Conclusion: In pts with MCL, CNS involvement is associated with worse outcomes as evident by a shorter median OS from initial MCL diagnosis (50 months vs. 97 months). Involvement of the CNS by lymphoma is an important contributor for the shorter OS as suggested by the median OS of only 5 months from CNS involvement. Advanced stage, blastoid variant, elevated LDH, and elevated Ki67 at MCL diagnosis were features more commonly seen in the CNS MCL cohort. Validation of risk factors at initial MCL diagnosis associated with CNS involvement and exploring the role of CNS prophylaxis are important topics for further investigation. Figure 1 Figure 1. Disclosures Paludo: Karyopharm: Research Funding. Wang: Novartis: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; MorphoSys: Research Funding; InnoCare: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding. Bennani: Purdue Pharma: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Vividion: Other: Advisory Board; Kymera: Other: Advisory Board; Verastem: Other: Advisory Board. Nowakowski: Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene, NanoString Technologies, MorphoSys: Research Funding. Witzig: Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding. Habermann: Seagen: Other: Data Monitoring Committee; Tess Therapeutics: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding.

p53 Is a Crucial Regulator of Hemogenic Endothelial Cell Differentiation from Human Induced Pluripotent Stem Cells

De novo generation of hematopoietic stem cells (HSCs) from human induced pluripotent stem cells (hiPSCs) could provide a virtually unlimited supply of autologous HSCs for clinical transplantation, and offer various approaches that enable gene therapy, drug discovery, disease modeling, and in vitro modeling of human hematopoietic development. However, the derivation of long-term self-renewing HSCs from hiPSCs in culture remains elusive. The tumor suppressor protein p53 plays important roles in normal and malignant hematopoiesis, and Trp53-deficient mice exhibit increased number of HSCs. Although activation of p53 is known to promote differentiation of hPSCs and hPSCs recurrently acquire TP53 dominant negative mutations, its role in hematopoietic differentiation of hiPSCs has not been explored. To differentiate hiPSCs into hematopoietic stem and progenitor cells (HSPCs), we used embryoid body (EB) formation method to first differentiate hiPSCs into hemogenic endothelial (HE) cells that express the CD34 highCD144 +CD73 -CD184 -CD43 -CD235a - cell-surface markers. HE cells were then transferred onto a Matrigel-coated plate to undergo endothelial-to-hematopoietic transition (EHT) to generate HSPCs that express the CD34 midCD45 mid cell-surface markers. Developed HSPCs were functionally evaluated by colony forming assay. We observed that the expression of CDKN1A, a p53 target gene, was upregulated in hiPSC-derived EBs and HSPCs over the course of differentiation. To investigate the role of p53 in the generation of HSPCs from hiPSCs, we genetically deleted TP53 in hiPSCs followed by hematopoietic differentiation. While TP53 deletion increased the growth of EBs, it resulted in severe impairment of differentiation into HE cells and overall production of HSPCs that can form colonies. During HE differentiation from hiPSCs, TP53-deficient EBs showed significant reduction of endothelial-lineage gene expression, such as ETV2, CDH5, and PECAM1, as well as expression of RUNX1, a master transcription factor required for HE specification. These results indicate the indispensable role of p53 in HE differentiation from hiPSCs. We then examined the effect of p53 activation on HE differentiation from hiPSCs by pharmacological activation of p53 in hiPSC-derived cells. Transient activation of p53 by Nutlin-3, a small molecule that inhibits the p53-HDM2 interaction and protects p53 from proteasomal degradation, only during HE differentiation but not during EHT significantly promoted HSPC generation as compared to the vehicle treated control. Our findings shed light on the importance of selecting hiPSC lines that retain normal p53 activity for HE differentiation, and provide an approach to promote hematopoietic differentiation of hiPSCs by transiently activating p53 during HE differentiation. Disclosures Kanaujiya: Synthego: Other: Scientific Advisory; eGenesis: Other: Scientific Advisory.

Genomic Drivers of Large B-Cell Lymphoma Resistance to CD19 CAR-T Therapy

Introduction: Anti-CD-19 chimeric antigen receptor-reprogrammed autologous T cells are breakthrough immunotherapies for heavily pretreated patients with aggressive B-cell lymphomas; however, across CAR-19 products, ~60% of patients do not achieve remission or relapse and unfortunately typically progress and rapidly die. Factors associated with impaired response to CAR-19 include inflammatory markers such as interferon signaling and clinical factors such as the need for bridging therapy and high pre-CAR-19 tumor burden, but cell-intrinsic driver of CAR-19 resistance remain largely undefined. Methods: To characterize the genomic mechanisms involved in diffuse large B cell lymphoma (DLBCL) resistance to CAR-19, we interrogated whole genome sequencing (WGS) from 28 relapsed/refractory (r/r) aggressive lymphoma patients treated with axicabtagene ciloleucel (axi-cel). The median coverage was 44.8X. To increase statistical power of analyses, we included also 50 newly diagnosed DLBCL patients from the Pan-Cancer Analysis of Whole Genomes (PCAWG). Results: As reported in other series, neither double hit cytogenetics nor MYC-BCL2 double expression associated with CAR-19 resistance, despite their negative predictive power for newly diagnosed DLBCL patients. Chapuy and LymphGen classification algorithms also demonstrated no prognostic significance. Among known mutated driver genes, only TP53 was significantly enriched in our cohort in comparison to the PCAWG cohort (p=0.002), but it did not predict poor CAR-19 outcome. Among other genes known to be involved in DLBCL pathogenesis, only mutations in NFKBIA or MYC, associated with worse PFS (p=0.04, p=0.025 respectively). Next, we identified 12 single base substitution (SBS) mutational signatures detected in our cohort of r/r lymphomas, four of which are caused by exposure to distinct chemotherapies (Landau et al., 2020, Nat Comm). The melphalan-related signature (SBS-MM1) was identified in 4 out 5 patients who received high dose melphalan followed by autologous stem cell transplant, and 75% of patients exposed to platinum had evidence of one of the three known platinum signatures. Across different SBS signatures, only presence of APOBEC (SBS2 and SBS13) associated with worse PFS with 4/5 patients progressing (p=0.03). We compared newly diagnosed and r/r DLBCL by GISTIC2.0 copy number variation (CNV) analysis, revealing three gene deletions significantly enriched in our r/r cohort: TP53, RHOA and RB1. Interestingly, the deletions involving RHOA and RB1 both independently predicted poor outcome (p=0.0007 and p=0.05 respectively) with 5/5 and 6/8 patients progressing respectively. The third, involving TP53 (46.4% of patients), had no prognostic impact but reflected the high-risk nature of the heavily pretreated tumors. WGS allows detailed identification of structural variants and complex events. Indeed, we found evidence of chromothripsis, a catastrophic event in which one or more chromosomes are shattered and aberrantly reassembles generating multiple aneuploidies, in 39.3% of r/r DLBCL. This strongly associated with poor CAR-19 outcome, with 9/11 affected cases experiencing early progression (p=0.041). Finally, reduced expression (n=3) or genomic alteration (n=3) of CD19 did not associate with poor outcome. We found one case, with durable response, containing a sub-clonal mutation in CD19 (L174V) at baseline, previously reported as associated with CAR-19 resistance. In line with recent evidence, these findings indicate that antigen-mediated tumor killing is not the only mechanism of tumor eradication, and CD19-independent resistance mechanisms predominate. Conclusions: Leveraging the high resolution of WGS, we observed that markers of genomic complexity (chromothripsis and APOBEC) and specific genomic alterations (RHOA and RB1 deletion) associate with resistance to CAR-19 immunotherapy for aggressive B-cell lymphomas. Fifteen out of sixteen patients (93.8%) who relapsed on CAR-19 contained at least one of the described genomic alterations. Recent data demonstrate that an immunosuppressed TME leads to CAR-19 failure in patients, and animal studies show activation of host T cells by CAR-T cells. Combining these findings with these genomics findings, successful CAR-19 therapy must overcome the immune-exhausted tumor microenvironment to mobilize the host immune system and eliminate the tumor. Figure 1 Figure 1. Disclosures Jain: Takeda: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Kite/Gilead: Consultancy, Honoraria. Faramand: Novartis: Research Funding; Kite/Gilead: Research Funding. Landgren: Amgen: Research Funding; Janssen: Research Funding; Amgen: Honoraria; Celgene: Research Funding; Janssen: Other: IDMC; Janssen: Honoraria; Takeda: Other: IDMC; GSK: Honoraria. Locke: Iovance Biotherapeutics: Consultancy, Other: Scientific Advisory Role; Gerson Lehrman Group: Consultancy; Calibr: Consultancy, Other: Scientific Advisory Role; Janssen: Consultancy, Other: Scientific Advisory Role; Umoja: Consultancy, Other; Novartis: Consultancy, Other, Research Funding; Bluebird Bio: Consultancy, Other: Scientific Advisory Role; Allogene Therapeutics: Consultancy, Other: Scientific Advisory Role, Research Funding; Kite, a Gilead Company: Consultancy, Other: Scientific Advisory Role, Research Funding; Takeda: Consultancy, Other; Emerging Therapy Solutions: Consultancy; EcoR1: Consultancy; Cowen: Consultancy; Wugen: Consultancy, Other; Legend Biotech: Consultancy, Other; GammaDelta Therapeutics: Consultancy, Other: Scientific Advisory Role; Cellular Biomedicine Group: Consultancy, Other: Scientific Advisory Role; BMS/Celgene: Consultancy, Other: Scientific Advisory Role; Amgen: Consultancy, Other: Scientific Advisory Role; Moffitt Cancer Center: Patents & Royalties: field of cellular immunotherapy. Maura: Medscape: Consultancy, Honoraria; OncLive: Honoraria. Davila: Precigen: Research Funding.

Primary Progression on Frontline Therapy for Diffuse Large B-Cell Lymphoma Is Associated with a Poor Outcome Despite Subsequent CD19 Targeted CAR T-Cell Therapy

Introduction: Between 50-80% of patients with diffuse large B-cell lymphoma (DLBCL) are cured by frontline (1L) R-CHOP immunochemotherapy. Ultra-high risk (UHR) features for poor overall survival (OS) include: progression through the frontline therapy (primary progression, PP), presence of a MYC translocation (MYC-R+), and a high or high-intermediate National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) (Costa, Am. J. Hematol., 2017). We aim to explore the role of these UHR factors in the outcomes of DLBCL patients receiving standard of care (SOC) anti-CD19 CAR T-cell therapy. Methods: This is a retrospective single-center study of relapsed/refractory (R/R) DLBCL patients treated with either axicabtagene ciloleucel (axi-cel) or tisagenlecleucel (tisa-cel) as SOC at Moffitt Cancer Center according to the FDA label as of March 2021, or who were treated on the expanded access programs (EAP) for axi-cel (NCT03153462) and tisa-cel (NCT03601442) for the provision of CAR T when products fell outside of manufacturing specifications (OOS). We excluded patients who had received prior therapy for indolent B-cell lymphomas (iNHL). We defined patients with primary treatment failure (PTF) as: PP, residual disease after 1L therapy (RD), or early relapse within 6 months of 1L therapy (ER). For patients with PTF, we calculated the number of UHR features (0 to 3): MYC status, NCCN-IPI, and PP. Kaplan-Meier survival curves were used to compare progression free survival (PFS) and overall survival (OS) starting from the date of CAR T-cell infusion, with statistical significance determined using the log-rank test at the P<0.05 threshold. Results: A total of 187 R/R DLBCL patients received SOC or EAP CAR T-cell therapy, of which 116 had DLBCL with no prior therapy for iNHL and were included in this analysis. PTF occurred in 75 patients (65%), of which 30 (40%) patients had primary progression as the failure pattern, 23 (30.7%) patients had MYC-R detected by FISH, and 37 (49.3%) patients had intermediate-high/high NCCN-IPI scores at the time of PTF. The median follow up was 10.05 months. Of the 75 patients with PTF, 69 received axi-cel and 6 received tisa-cel. Main 1L therapies were R-CHOP in 59 (78.6%) cases and DA-EPOCH-R in 14 (18.7%). The median lines of therapy prior to CAR T-cell therapy was 3 (range 2-6 lines). The number of UHR features was associated with a shorter OS after CAR T-cell therapy. The OS for patients with 2-3 and 0-1 UHR were 5.3 months (95% CI, 3.7 to 15.13 months) and not reached, respectively (P=0.005; Figure 1A). In terms of PTF patterns, PP was associated with worse PFS and OS after CAR T-cell therapy compared to other patterns (RD/ER) (PP, mPFS 3.1 months vs RD/ER, mPFS not reached; p<0.001; PP, median OS 5.63 months vs RD/ER, mOS not reached, P<0.001; Figure 1B). Patients with PTF and MYC-R+ had no difference in PFS (P=0.51) but a shorter OS after CAR T-cell therapy compared to those without an identified MYC translocation (P=0.05). Patients with intermediate-high or high NCCN-IPI at time of PTF had similar PFS (P=0.75) and OS (P=0.34) to patients with intermediate-low or low NCCN-IPI. Conclusion: Patients with DLBCL who experience PP to frontline immunochemotherapy had shorter PFS and OS after subsequent CAR T-cell therapy compared to other PTF patterns. R/R DLBCL patients with PP represent a poor prognosis subgroup, even with CAR T-cell therapy. It will be important to determine if patients with primary progression have increased benefit from CAR T-cell therapy if it is provided at first relapse rather than after 2 or more prior lines of therapy. Our study suggests that mechanisms of tumor resistance to CAR T-cell therapy may be present in some patients from the time of upfront therapy. Figure 1 Figure 1. Disclosures Chavez: AstraZeneca: Research Funding; Merk: Research Funding; ADC Therapeutics: Consultancy, Research Funding; BMS: Speakers Bureau; MorphoSys, Bayer, Karyopharm, Kite, a Gilead Company, Novartis, Janssen, AbbVie, TeneoBio, and Pfizer: Consultancy; MorphoSys, AstraZeneca, BeiGene, Genentech, Kite, a Gilead Company, and Epizyme: Speakers Bureau. Shah: Pfizer: Consultancy, Other: Expenses; Incyte: Research Funding; Acrotech/Spectrum: Honoraria; BeiGene: Consultancy, Honoraria; Kite, a Gilead Company: Consultancy, Honoraria, Other: Expenses, Research Funding; Pharmacyclics/Janssen: Honoraria, Other: Expenses; Precision Biosciences: Consultancy; Amgen: Consultancy; Novartis: Consultancy, Other: Expenses; Servier Genetics: Other; Jazz Pharmaceuticals: Research Funding; Bristol-Myers Squibb/Celgene: Consultancy, Other: Expenses; Adaptive Biotechnologies: Consultancy. Nishihori: Karyopharm: Research Funding; Novartis: Research Funding. Lazaryan: Kadmon: Consultancy; Avrobio: Membership on an entity's Board of Directors or advisory committees; Humanigen: Membership on an entity's Board of Directors or advisory committees. Davila: Precigen: Research Funding. Locke: Wugen: Consultancy, Other; Umoja: Consultancy, Other; Cowen: Consultancy; EcoR1: Consultancy; Takeda: Consultancy, Other; Novartis: Consultancy, Other, Research Funding; Legend Biotech: Consultancy, Other; Janssen: Consultancy, Other: Scientific Advisory Role; Kite, a Gilead Company: Consultancy, Other: Scientific Advisory Role, Research Funding; Iovance Biotherapeutics: Consultancy, Other: Scientific Advisory Role; GammaDelta Therapeutics: Consultancy, Other: Scientific Advisory Role; Cellular Biomedicine Group: Consultancy, Other: Scientific Advisory Role; Calibr: Consultancy, Other: Scientific Advisory Role; BMS/Celgene: Consultancy, Other: Scientific Advisory Role; Bluebird Bio: Consultancy, Other: Scientific Advisory Role; Amgen: Consultancy, Other: Scientific Advisory Role; Allogene Therapeutics: Consultancy, Other: Scientific Advisory Role, Research Funding; Emerging Therapy Solutions: Consultancy; Gerson Lehrman Group: Consultancy; Moffitt Cancer Center: Patents & Royalties: field of cellular immunotherapy. Gaballa: Adaptive Biotechnologies: Research Funding; Epizyme: Consultancy, Research Funding; TG therapeutics: Consultancy, Speakers Bureau; Beigene: Consultancy; ADC Therapeutics: Consultancy. Jain: Kite/Gilead: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria.

Myeloablative Fractionated Busulfan Conditioning Regimen with Sorafenib in Patients with AML: Results of Phase I Clinical Trial

Background: Myeloablative conditioning can be given safely to older patients by administering busulfan over a longer period (fractionated busulfan regimen) than the standard four-day regimen. (Popat, et al Lancet Haematology 2018). This longer conditioning regimen duration allows the addition of oral targeted agents like sorafenib, which may be synergistic with conditioning chemotherapy and thus further improve disease control. Therefore, we added sorafenib to fludarabine and fractionated busulfan regimen (f-bu) in a phase 1 dose-finding trial studying 4 different doses of sorafenib with f-bu (NCT03247088). Here we report the results of this trial. Methods: Between 3/2018 and 6/2021, 24 patients with AML aged 18 to 70 years with adequate organ function and 8/8-HLA matched related or unrelated donors were enrolled prospectively. The dose of sorafenib was varied among the four values 200, 400, 600, and 800 mg administered from day -24 to -5. Dose-limiting toxicity (DLT) was defined as grade 3 or higher regimen-related non-hematologic, non-infectious, non-GVHD toxicity occurring between day -24 and day 3. The Bayesian Model Averaging Continual Reassessment Method (BMA-CRM) with target DLT probability 0.30 was used to choose doses for successive cohorts of 3 patients. The first cohort was treated at the lowest sorafenib dose 200, with all successive cohorts' doses chosen adaptively by the BMA-CRM. The doses and schedules of busulfan and fludarabine were fixed, with f-Bu dose targeting an area under the concentration vs time curve (AUC) of 20,000 ± 12% μmol.min given over 3 weeks. The first two doses of busulfan (80 mg/m2 IV each) were administered on days -20 and -13 on an outpatient basis. The last four Bu doses were calculated to give a total course AUC of 20,000 ± 12% μmol.min and were given as inpatient following each dose of Flu 40 mg/m2 on days -6 through -3. GVHD prophylaxis was post-transplant cyclophosphamide (PTCy) 50mg/kg on days 3 and 4 and tacrolimus. Recipients of unrelated donor grafts also received MMF. All patients were eligible to receive post-transplant maintenance sorafenib after engraftment. Results: The median age was 52 years (range, 30-70). Disease status was CR in 16 (66.6%) patients, CRi in 5 (20.8%), and advanced in 3 (12.5%). Adverse risk karyotype was present in 10 (41.7%) patients. MRD was present in 13 (54.2%). 9 (38%) had mutated flt3. The donor was unrelated in 14 (58%), and peripheral blood stem cells were the graft source in 21(87.5%). Due to the absence of DLTs, the BMA-CRM assigned 200mg, 400mg, 600mg, and 800mg of sorafenib, respectively, to the first 4 cohorts, and the next 4 cohorts were given 800mg. Only 2 dose-limiting skin toxicities were seen, one in cohort 3 with 600mg of sorafenib and the second in cohort 6 with 800mg of sorafenib. 800mg was the final recommended phase 2 dose. The median follow-up in 20 surviving patients was 7.6 months and 1-year progression free survival was 89% (95% CI 75-100%). Other outcomes are summarized in Table 1. Conclusion: Sorafenib can be safely added to the fractionated busulfan regimen. Early data on efficacy appear promising, with an 89% PFS at 1 year of follow up. Figure 1 Figure 1. Disclosures Popat: Bayer: Research Funding; Abbvie: Research Funding; Novartis: Research Funding; Incyte: Research Funding. Hosing: Nkarta Therapeutics: Membership on an entity's Board of Directors or advisory committees. Rezvani: Bayer: Other: Scientific Advisory Board ; AvengeBio: Other: Scientific Advisory Board ; Navan Technologies: Other: Scientific Advisory Board; GSK: Other: Scientific Advisory Board ; Virogin: Other: Scientific Advisory Board ; Affimed: Other: License agreement and research agreement; education grant, Patents & Royalties, Research Funding; Pharmacyclics: Other: Educational grant, Research Funding; Caribou: Other: Scientific Advisory Board; GemoAb: Other: Scientific Advisory Board ; Takeda: Other: License agreement and research agreement, Patents & Royalties. Qazilbash: Bristol-Myers Squibb: Other: Advisory Board; Biolline: Research Funding; Amgen: Research Funding; Oncopeptides: Other: Advisory Board; NexImmune: Research Funding; Angiocrine: Research Funding; Janssen: Research Funding. Daver: Daiichi Sankyo: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; ImmunoGen: Consultancy, Research Funding; Astellas: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Gilead Sciences, Inc.: Consultancy, Research Funding; Trillium: Consultancy, Research Funding; Glycomimetics: Research Funding; Abbvie: Consultancy, Research Funding; Hanmi: Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; FATE Therapeutics: Research Funding; Sevier: Consultancy, Research Funding; Novimmune: Research Funding; Trovagene: Consultancy, Research Funding; Novartis: Consultancy; Jazz Pharmaceuticals: Consultancy, Other: Data Monitoring Committee member; Dava Oncology (Arog): Consultancy; Celgene: Consultancy; Syndax: Consultancy; Shattuck Labs: Consultancy; Agios: Consultancy; Kite Pharmaceuticals: Consultancy; SOBI: Consultancy; STAR Therapeutics: Consultancy; Karyopharm: Research Funding; Newave: Research Funding. Ravandi: Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; AstraZeneca: Honoraria; Novartis: Honoraria; Xencor: Honoraria, Research Funding; Taiho: Honoraria, Research Funding; Astex: Honoraria, Research Funding; AbbVie: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Prelude: Research Funding; Syros Pharmaceuticals: Consultancy, Honoraria, Research Funding. Shpall: Magenta: Consultancy; Bayer HealthCare Pharmaceuticals: Honoraria; Magenta: Honoraria; Adaptimmune: Consultancy; Novartis: Consultancy; Navan: Consultancy; Novartis: Honoraria; Takeda: Patents & Royalties; Affimed: Patents & Royalties; Axio: Consultancy. Mehta: CSLBehring: Research Funding; Kadmon: Research Funding; Syndax: Research Funding; Incyte: Research Funding.

Follicular Lymphoma Tumor-Cell Transcriptional Programs Associate with Distinct Somatic Alterations and Tumor-Immune Microenvironments

Background: Follicular lymphoma (FL) exhibits significant clinical, cellular, molecular, and genetic heterogeneity. Our understanding of FL biology and molecular classifications of FL, to date, has largely been driven by pathologic classification (Grade 1-3b), genetic classification (m7-FLIPI), or gene expression profiling (IR-1/2; Huet-23), along with limited studies on small cohorts or targeted panels. In order to further understand the biological underpinnings and complexity of FL, large-scale and integrated whole exome sequencing (WES) and RNA sequencing (RNAseq) studies are needed. Using a highly-annotated cohort of 93 FL tumors with matched RNAseq, WES, and CyTOF data, we have explored the transcriptomic signature of purified FL B cells and identified unique molecular subsets that are defined by distinct pathway activation, immune content, and genomic signatures. Methods: Frozen cell suspensions from 93 untreated FL (Grade 1-3b) patients' tumor biopsies, enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE, were used for the study. DNA was isolated from whole tumor cell suspensions, and RNA was isolated from both whole tumor and B cell-enriched cell suspensions. RNAseq and WES were performed in the Mayo Clinic Genome Analysis Core. RNAseq and WES data were processed using a standard pipeline and novel driver genes were identified using Chasm+ driver analysis. Copy number variants were identified from WES data using GISTIC 2.0. NMF clustering and single sample gene set testing for B cell lineage and tumor microenvironment (TME) signatures were performed in R using the NMF and singscore packages. Results: Unsupervised clustering of RNAseq data identified three distinct expression programs which separated patient B cell samples into 3 groups: Group 1 (G1, n=20), Group 2 (G2, n=24), Group 3 (G3, n=43). While no clinical attributes were defined by any single group, G1 consisted of cases that had less aggressive characteristics (63% Stage I-II, 79% FLIPI 0-1). To identify unique transcriptional pathways driving the three expression programs, we scored gene level contributions to NMF expression programs and employed gene set enrichment analysis. This revealed significant pathway association with type-I IFN signaling (G1), DNA repair and stress response (G2), and epigenetic modulation (G3) as differentiating programs between the 3 groups (FDR q<0.001). VIPER master regulator activity inferencing revealed that these pathways were likely being controlled by differential activity in NF-kB, IRFs, STAT1, BCL6, and FOXO1. Each program significantly enriched for, but were not defined by, portions of specific germinal center programs, such as pre-memory (G1), light-zone-to-dark-zone transition (G2), and a pre-light-zone intermediate (G3). We next assessed the connection between B cell programs and the tumor microenvironment (TME) using available paired CyTOF data on 67 cases, which revealed an active TME in G1, with an abundance of CD8 T cell and NK cell populations, a wide variety of immune content in G2 that consisted mostly of Tfh and myeloid cells, and a poorly populated immune compartment in G3 compared to G1 and G2. Finally, somatic driver mutations and copy number alterations from WES were identified and associated with the three clusters. The three groups distinguished themselves by significant enrichment of copy number alterations (TNFAIP3-loss , 1q23-gain, 1q32-gain) in G2, while 10q-loss and mutations in BCL2 and chromatin modifiers (KMT2D and CREBBP) enriched in G3. G1, overall, had lower alteration burden and had weak associations with any specific alterations, suggesting an alternative mechanism for driving the G1 program. Conclusion: In this study, we have identified three unique FL tumor B cell groups, defined by specific transcriptional programs. Pathways such as inflammation, DNA damage response, and chromatin modification contribute most to the differences between B cell samples and group membership. Additionally, each program associated with specific genetic events as well as TME composition, highlighting potential drivers of these B cell states. This study improves the understanding of the mechanisms driving FL tumors and motivates further investigation into transcriptional consequences of genetic events as well as potential tumor intrinsic factors that may influence the TME. 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. Rimsza: NanoString Technologies: Other: Fee-for-service contract. Link: MEI: Consultancy; Genentech/Roche: Consultancy, Research Funding; Novartis, Jannsen: Research Funding. Habermann: Tess Therapeutics: Other: Data Monitoring Committee; Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. King: Celgene/BMS: Research Funding. Cerhan: Genentech: Research Funding; Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Novak: Celgene/BMS: Research Funding.