Price-Troska, Tammy

Abstract Although extensively studied, the exact mechanism by which TGF-β mediates T-cell inhibition is not entirely clear. When we examined the effect of TGF-β on the phenotype and function of T cells, we noted that CD70 was significantly up-regulated by TGF-β. This surprising finding led us to explore the underlying mechanism by which TGF-β upregulates CD70 expression on T cells and to define the function of CD70+ cells in B-cell NHL. Interestingly, we observed that TGF-β preferentially induced CD70 expression on effector memory T cells while it predominantly up-regulated Foxp3 on naïve T cells. CD70 induction is Smad3-dependent and involves Stat5 signaling. CD70+ T cells were highly susceptible to TGF-β-mediated apoptosis and that transfection of Jurkat cells with the CD70 gene led to a significantly reduced survival. TGF-β-induced CD70+ T cells had a diminished response to immune stimulation associated with downregulation of co-stimulatory molecules CD27 and CD28. CD70-expressing T cells from biopsy specimens of patients with B-cell NHL failed to produce cytokines and displayed no signal transduction when stimulated. CD70-expressing T cells were highly represented in follicular NHL biopsy specimens and increased numbers of CD70+ cells correlated with an inferior patient outcome. These novel findings not only revealed a biological role for a TGF-β/CD70 axis in mediating immune inhibition, but also may lead to therapeutic approaches in patients with B-cell NHL.

Abstract Background: Multiple mechanisms exist for the positive selection of genes involved in oncogenesis such as gene amplification and transcriptional deregulation associated with chromosome translocations. Here we describe the case of a myeloma cell line that over time acquired extra copies of a derivative chromosome 4 involved in the t(4;14). These changes occurred over time both in vitro (in the generated JMW myeloma cell lines) as well as in vivo from extramedullary myeloma samples collected from the patient at various time points. In the case of the t(4;14)(p16;q32) 30% can be unbalanced translocations, always with loss of the der(14) and consequent loss of the FGFR3 gene expression, suggesting an indispensable role for MMSET located in the der(4). Results: We performed serial analysis on patient samples obtained at 9, 10 and 12 mos from diagnosis, along with a time course analysis of the cell line. At diagnosis the patient tumor cells displayed a complex clinical karyotype subsequently characterized by hypodiploidy, a t(4;14)(p16;q32), 13 monosomy and 17p13.1-. The remaining chromosome 13 and 17 were involved in an unbalanced reciprocal translocation. Notably, over time the cell line duplicated the total chromosome number becoming near-tetraploid. At the time of diagnosis, FISH analysis was performed on the patient sample revealing the translocation t(4;14)(p16.3:q32) in nearly all cells. The t(4;14) was also present in the stable cell line. It was noted that the patient cells exhibited more than one fusion signal per cell for the t(4;14) by FISH. As the disease progresses both in vitro and in vivo, the number of t(4;14)(p16.3:q32) fusion signals detected per cell increased with time suggesting a positive selection of the derivative chromosomes of the translocation. We further analyzed the t(4;14) in the JMW cells by FISH using MMSET/VH, and FGFR3/CH probe combinations. The full-length (MMSET/FGFR3+VH/CH) probe was used to detect the total number of fusions in the JMW cells. At the time of analysis (cell line passage #23), the majority of the cells (69%) had 6 fusion signals per cell while 23% had 5 fusions and 8% of the cells had 4 fusions. We found that most of the cells (88%) displayed 4 fusion signals detected using the MMSET/VH probes. In parallel studies using the FGFR3/CH probes, 61% of the cells had 2 fusion signals and 39% with 1 fusion signal. It is evident that the tumor cells display positive selection of the derivative chromosome der(4) of the t(4;14)(p16.3;q32), accompanied by an increased dosage of the target gene (MMSET) upregulated by the translocation. Conclusion: We present evidence for the amplification of the translocated chromosome in multiple myeloma, which we have termed “trans-amplicons”. Trans-amplicons may provide a selective growth and survival advantage to the myeloma tumor cells in an analogous manner to amplicons of DNA segments, but with much more powerful transcriptional consequences. Importantly, the evolution of genomic instability exemplified by the “trans-amplicons” in the patient cells was paralleled in vitro in the JMW cells.

Abstract Background: The p53 tumor suppressor gene has a common sequence polymorphism that results in either proline or arginine at amino-acid position 72. The Pro72 and Arg72 variants have been reported to differ in its functional activity. The Arg72 variant induces apoptosis more efficiently than Pro72 variant by its greater ability to localize to the mitochondria and increase the release of cytochrome c into the cytoplasm. In addition, recent studies have demonstrated that Arg72 variant was a better suppressor of cellular transformation, an activity believed to rely on the pro-apoptotic function of p53. Moreover, the Pro72 variant has been associated with a higher incidence of tumors. Aim: To evaluate the effect of the polymorphic variants of codon 72 and clinical outcome in patients with plasma cell malignancies. Patients and Methods: We analyzed 79 patients with plasma cell malignancies seen at Mayo Clinic between 2000 and 2003. Genomic DNA was extracted from CD138+ sorted plasma cell from bone marrow aspirates. PCR amplification of codon 72 and posterior sequencing was used for the analysis. Results: A total of 79 patients were analyzed. Thirty-four patients (34%) were heterozygous for p53, 57 (59%) homozygous for Arginine and 6 (6%) homozygous for Proline. The distribution among disorders was as follow, 52 patients had MM, 14 patients with SMM and 13 with MGUS. Among patient with MM 25% were Pro/Arg heterozygous, 71 % were Arg/Arg homozygous and 3.8% Pro/Pro homozygous. Survival data among MM patients and genotype were analyzed to Kaplan- Meier method. No significant differences were found among patients who carried homozygous (72R) or heterozygous genotype and overall survival. We exclude the analysis in MGUS and SMM for a low number of patients available. Conclusions: These findings indicate that codon 72 arginine p53 may not be associated with a prolonged survival in patients with Multiple Myeloma, but further study is needed to assess whether this polymorphism is associated with progression of MGUS to MM, age of onset, clinical manifestations, response to treatment etc.

Abstract Hyperdiploid (>48 chromosomes) multiple myeloma (H-MM) and high hyperdiploid (>50 chromosomes) acute lymphoblastic leukemia (H-ALL) are characterized by aneuploidy and multiple recurrent trisomies (chromosome 3,5,7,9,11,15,19 for H-MM and chromosomes X,4,6,10,14,17,18,21 for H-ALL). Little is known about the oncogenic events, consequences of the trisomies and reasons for the different recurrent trisomies. In an attempt to answer these questions, we undertook a combined gene expression and network/pathway analysis approach. Gene expression data was generated using the Affymetrix U133A chip (Affymetrix, Santa Clara, Ca) for 53 H-MM and 37 non-hyperdiploid MM (NH-MM) cases using CD138-enriched plasma-cell RNA. Gene expression data using the same chip for ALL was obtained from previous published data (Ross ME et al Blood2004; 104: 3679–3687). Analysis was performed using Genespring 7 (Agilent Technologies, Palo Alto, CA). By comparing the median expression of all genes on each chromosome between H-MM/H-ALL and their non-hyperdiploid counterparts (NH-MM and NH-ALL) for the 23 chromosomes (excluding Y), one can clearly identify the commonly trisomic chromosomes in H-ALL and H-MM. However, the relationship of gene expression was highly variable for H-MM and NH-MM as compared to H-ALL and NH-ALL which tended to have expression ratios close to 1 for the non-trisomic chromosomes. Sixty-nine percent of the differentially expressed genes generated by ANOVA analysis (p<0.001) in H-ALL were on the commonly trisomic chromosomes and were upregulated whereas the corresponding figure in H-MM is 40%. These similarities and differences probably reflect both an overall gene dosage effect and the different complexities of the karyotypes of H-MM and H-ALL compared to NH-MM and NH-ALL respectively (MM karyotypes are more complex, hence difference between H and NH-MM is greater and less confined to the trisomic chromosomes). We next performed network analysis using a curated web-based software (MetaCore, GeneGo Inc, St Joseph, MI) using the 2 sets of differentially expressed genes. Majority of genes differentially expressed in H-MM are involved in mRNA translation/protein synthesis whereas the genes differentially expressed in H-ALL were mainly involved in signal transduction. Therefore the transcriptional program that characterize the difference between H and NH-MM/ALL seem to recapitulate normal cellular function: protein synthesis in the mature secretory plasma cells and signal transduction in response to cytokines in a differentiating early-B cell. However, due to the concurrent deregulation of many genes on these trisomic chromosomes, these and other cellular programs are deregulated resulting in malignant transformation. We also intersected the 2 lists of differentially expressed genes to find genes that are up- or downregulated in both H-MM and H-ALL relative to the NH tumors. Thirteen genes including interferon response genes (TNFSF10, MX1, ZNF185) and transcription factors like RUNX1 were upregulated, whereas 13 genes including a cancer testis antigen gene (MAGED4) were downregulated in both H-MM and H-ALL. These genes may point to common oncogenic mechanisms.

Abstract Chromosome 13 (Δ13) abnormalities are found in greater than 50% of patients with Multiple Myeloma (MM). MM is most commonly defined by chromosome 13 monosomy or 13q loss (85%). Interstitial deletions comprise the remaining 15%. Many studies have revealed that Δ13 in MM are associated with poor survival and reduced response to therapy. Genes mapping to chromosome 13 may be involved in pathogenesis and/or progression of the disease due to loss of function from gene mutation or from epigenetic effects such as haploinsufficiency. In this study, array-based comparative genomic hybridization coupled with microarray technology (aCGH) is used to detect gene copy number loss on chromosome 13 from nine MM patient samples. Whole genome long-oligo microarrays constructed by Agilent Technologies were used which contain 40,000 genes that span the human genome with an average spatial resolution of ~75 kb. Using genomic DNA isolated from MM patients with interstitial deletions on chromosome 13, DNA was amplified, labeled and hybridized with a differentially labeled normal DNA reference to determine gene/genomic copy number changes. Arrays were analyzed to search for the minimum region of loss based upon single copy loss for a series of nearby mapping transcripts. A common region of loss of 2.2 Mb, at 13q14.2 was detected. Additionally, we investigated the correlation between genomic copy number change and the expression level for MM patients in the13q region. From an independent gene expression data set whose expression measurements were conducted with Affymetrix HG-U133A v2 microarrays, data was selected that corresponded to the samples used for current aCGH. Expression values from MM samples were divided by the mean expression values from 12 normal bone marrow samples for each gene and the resulting values were treated as surrogate ratios between MM and normal samples. Probes from both microarrays were then aligned according to their chromosomal positions and merged if their chromosomal positions overlapped. Composite chromosomal maps were generated that displayed the expression levels and copy number changes. The maps were used to differentiate chromosomal regions in 13q where copy number changes and expression levels show high correlation and regions where such correlation was not observed. Although the number of probes sampled in the expression microarray was much smaller than those in aCGH microarray, a chromosomal region of great interest, that encompasses 13q14.2, arose naturally from this analysis. Although the mechanism by which loss of 13q effects tumorigenesis in MM could be a haploinsufficiency model, we are not ruling out the presence of a tumor suppressor gene in this region. We are evaluating candidate tumor suppressor genes in the region for loss of function by mutational analysis and hypermethylation studies.

Abstract Hyperdiploid MM (H-MM), characterized by recurrent trisomies constitute about 50% of MM, yet very little is known about its pathogenesis and oncogenic mechanisms. Studies in leukemia and solid tumors have shown gene dosage effect of aneuploidy on gene expression. To determine the possible gene dosage effect and deregulated cellular program in H-MM we undertook a gene expression study of CD138-enriched plasma-cell RNA from 53 hyperdiploid and 37 non-hyperdiploid MM (NH-MM) patients using the Affymetrix U133A chip (Affymetrix, Santa Clara, CA). Gene expression data was analyzed using GeneSpring 7 (Agilent Technologies, Palo Alto, CA). Genes differentially expressed between H-MM and NH-MM were obtained by t-test (p<0.01). The majority of the differentially expressed genes (57%) were under-expressed in H-MM. Genes located on the commonly trisomic chromosomes were mostly (but not always) over-expressed in H-MM and constitute 76% of over-expressed genes. Chromosome 1 contained the most differentially expressed genes (17%) followed by chromosome 12 (9%), and 19 (8%). To examine the relationship of gene copy number to gene expression, we examined the expression of genes on chromosomes 9 and 15 in subjects with 2 copies (15 normal control and 20 NH-MM) and 3 copies (12 H-MM) of each chromosome as detected by interphase FISH. We then derived a ratio of the mean expression of each gene on these chromosomes between patients with 3 copies and 2 copies of the chromosome. If a simple relationship exists between gene expression and gene copy number, one would expect the ratio of expression of most genes on these two chromosomes to be about 1.5 in H-MM compared to NH-MM. However, many genes have ratios either higher than 2 or lower than 0.5. Furthermore, when the heterogeneity of cells with underlying trisomies is taken into consideration by correcting the ratio for the number of cells with trisomies, the actual ratio is always lower than the expected ratio. When the expression of genes on a chromosome was compressed to a median value, this value was always higher in the trisomic chromosomes for H-MM compared to NH-MM. The data suggests that although gene dosage influence gene expression, the relationship is complex and some genes are more gene dosage dependent than others. Amongst the differentially expressed genes with known function, 33% are involved in mRNA translation/protein synthesis. Of note, 37 of the top 100 differentially expressed genes are involved in these processes. In particular, 60 ribosomal protein (RP) genes are significantly (p<0.05) upregulated in H-MM. This signature in H-MM is not associated with increase proliferation as measured by PCLI. This predominant signature suggests that deregulated protein synthesis may be important for the biology of H-MM. Many of these RPs are involved in the synthesis of product of oncogenic pathways (e.g. MYC, NF-KB pathways) and may mediate the growth and survival of tumor cells. It is therefore possible that these tumor cells may be sensitive to the disruption of mRNA translation/protein synthesis. Targeting the mTOR pathway with rapamycin may therefore be useful for treatment of H-MM.

Abstract Activation of NFkB has been noted in late B-cell malignancies, but no genetic basis for this activation has been shown except for rare mutations of the NFkB pathway in lymphoma and none have been described in MM. Bortezomib, highly tumoricidal in a subset of MM patients, inhibits NFkB suggesting it’s role as a therapeutic target. Here we show for the first time the critical importance of mutations that dysregulate this potential survival pathway in human myeloma cell lines (HMCL) and new diagnosis MM patients. We performed high-density oligonucleotide array CGH (Agilent 44k) on CD138+ selected MM cells from 68 patients and 42 unique HMCL. Initially we focused on small loci, bi-allelically deleted, as markers for inactivation of potential tumor suppressor genes. We next developed FISH probes for the identified loci to confirm the bi-allelic deletions seen by aCGH. We next sequenced all samples with monoallelic deletions, and additional unselected patients, and identified additional inactivating mutations. Multiple novel tumor suppressor genes (TSG) were identified and validated, whose loss of function (both in patients and HMCL) leads to activation of the non-canonical NFkB pathway including: TRAF2 (9q34), TRAF3 (14q32), BIRC2/BIRC3 (11q22) and CYLD (16q12). Functional studies showed that HMCL with deletion or mutations in these genes have markedly increased NFkB2 p52/p100 ratios relative to other HMCL (and for BIRC2/BIRC3 relative to an isogenic line that retains one copy of BIRC2/BIRC3), indicating genetic activation of the non-canonical NFkB pathway. Reintroduction of deleted TSG into HMCL inhibited cell growth and resulted in cell death (see data on abstract by J. Keats et al). We next focused our analysis (of combined aCGH and GEP data) on positive regulators of this pathway. Rare IgH translocations of NIK have recently been identified in MM. By aCGH we identified amplification and rearrangements of NIK. We identified dysregulated expression of TNF family receptors that activate the non-canonical pathway: CD40 (translocation), TACI (amplification) and LTBR. All of the HMCL with these mutations also showed increased NFkB2 p52/p100 ratios, consistent with activation of the non-canonical NFkB. These mutations correlate with a gene expression profile of NFkB activation that is detected in one half of patients. In summary, we have determined for the first time the genetic basis for constitutive NFkB activation - present in 19/42 HMCL, and we estimate in at least one quarter of newly diagnosed patients (approximately one half of those with evidence of NFkB activation by GEP). We propose a mechanism in which positive (TACI, CD40, LTBR) and negative regulators (TRAF2, TRAF3, BIRC2/BIRC3, CYLD) of the pathway converge on NIK to mediate the processing of NFKB2 p100 to p52. The preponderance of genetic evidence suggests that drugs that target the non-canonical NFkB pathway, will be most effective in treating the 50% of MM patients with NFkB activation.

Abstract The use of high-resolution aCGH allows for whole genome screening for copy number changes even in tumors that rarely produce metaphase spreads. The aim of this study was to characterize the aCGH findings in B-CLL, lung MALT lymphoma, Waldenström’s Macroglobulinemia (WM), Multiple Myeloma (MM) and human myeloma cell lines (HMCLs). This study includes 301 B-cell malignancy samples (19 B-CLL, 19 MALT, 20 WM, 48 HMCLs and 195 MM) and an additional 76 melanoma samples. We found MM to have the highest number of abnormalities per karyotype, with 15.8±7.5 (mean ± SD) and 20.6±17.0 in hyperdiploid (H) and non-hyperdiploid MM (NH), respectively. The remaining diseases have a significantly lower number of abnormalities: 5.5±4.5 in B-CLL, 3.5±1.96 in MALT and 4±3.5 in WM. Aneuploidy and biallelic deletions were rare events in these three diseases. B-CLL has two highly recurrent abnormalities involving 11q22-q23 (29%) and 13q14.3 (33%). A minimal deleted region (MDR) of ∼108Kb was identified at 11q comprising ACAT1, NPAT and ATM. In 13q, a 280Kb MDR was recognized, including TRIM13, KCNRG, mir-15a and mir-16. The subgroup of MALT patients with t(11;18) had very few abnormalities and the majority are a consequence of unbalanced translocations (MALT, BIRC2 and BIRC3 deletions). In the remaining MALT samples, trisomy 3 and 18q gain were the most common abnormalities (31% each). The 6q16.3-q26 deletion was the most common abnormality in WM (45%). In 4 of 9 patients with 6q deletion there was an associated 6p gain. The same observation was found in 2 of 3 patients with 8p loss and concomitant 8q gain. Interestingly, 6p and 8q gain were not identified in patients without 6q and 8p deletions. Deletion of 17p was the most common recurrent abnormality observed in our panel of B-cell cancers, being identified in MM, WM and B-CLL. In B-CLL and WM, small mono and biallelic deletions of the NF-kB negative regulators, TRAF3 and NFKBIA, were identified, suggesting a potential involvement of this pathway in the pathogenesis of these diseases. Hierarchical clustering of the aCGH data in MM identified 3 distinct groups, NH-MM, H-MM and MM with deletions of chromosome 13 and 14. Interestingly, MGUS and SMM were more commonly clustered with H-MM. Several sub-clusters were observed in the H-MM group, the most prominent being made up exclusively of patients from TC class D1. This cluster was characterized by the presence of trisomy 11 and 21. The 11q13 TC group clustered and was highly associated with 11q amplifications due to unbalanced t(11;14). The 6q deletion defined a cluster with WM, MM and Melanoma patient with that abnormality. In the case of B-CLL and MALT, the only identifiable clusters were observed in cases with 13q loss and trisomy 3, respectively. These results highlight both, the common and unique aCGH findings in several B-cell cancers. By hierarchical clustering, MM was significantly divergent from the rest of the B-cell diseases. Due to the limited number of abnormalities in B-CLL/MALT/WM, the clustering of these groups was exclusively based on the common abnormalities. The use of aCGH has refined the MDRs of 11q and 13q in B-CLL. Additionally, the identification of deletions affecting the NF-kB pathway in B-CLL and WM has prompted us to hypothesize on the importance of constitutive NF-κB activation in these diseases.

Abstract Regulatory T-cells (TREG) are the gateway to immune function and typically regulate immune cell activation. Cytokines, including interleukin-2 (IL-2), induce T-cell differentiation and promote a regulatory phenotype. Once activated via the IL-2 receptor (IL-2R), a cascade of events in T-cells initiate signal transducer and activator of transcription 5 (STAT5) and Forkhead box P3 (FOXP3) activation which appear to function as important regulators of this immunologic pathway and promote the development and function of TREG cells. In non-Hodgkin lymphoma (NHL), we have found that intratumoral TREG cells are increased in number and suppress immune function. In previous work, we have found that TREG cells inhibit T-cell proliferation, suppress cytokine production and limit effector cell cytotoxicity. We have also shown that increased serum levels of soluble sIL-2Rα is a prognostic factor in NHL and that sIL-2Rα can bind to IL-2 and promote its signaling thereby increasing TREG cell numbers. In this study, we developed a strategy to inhibit the binding of IL-2 to sIL-2Rα with the goal of suppressing the induction of FOXP3 and decreasing TREG cell numbers. To do this, we developed peptides designed to disrupt the interaction between IL2 and sILRα. In collaboration with CMDBioscienceSM, we developed and analyzed 22 peptide compounds derived by structure-based computational design. Initially, we screened each peptide at increasing concentrations using an ELISA assay to test the inhibition of IL-2/IL-2Rα binding by the solubilized peptide. Candidate peptides were then further tested using upregulation of pSTAT5 and FOXP3 in T-cells measured by flow cytometry as a measure of inhibition of IL-2 signaling. The peptides were developed according to different design hypotheses and grouped into different families; the screening ELISA results indicated 4 promising peptides that inhibited IL2/IL2Rα binding (up to 100% inhibition; max peptide concentration of 100uM). These peptides were then used to determine their effect on STAT5 and FOXP3 expression. A lead candidate peptide consistently reduced the expression of FOXP3 and STAT5 expression compared to cells not exposed to peptide. Use of the peptide to disrupt IL-2 signaling inhibited the development of cells with a TREG phenotype. We conclude that structure-based peptide design can be used to identify novel peptide inhibitors that block IL-2/IL-2Rα signaling and inhibit STAT5 and FOXP3 upregulation. These peptides could be used as new therapeutic agents to limit immune suppression by TREG cells and promote a more effective anti-tumor immune response in NHL. Disclosures No relevant conflicts of interest to declare.

The outcomes of lymphoma patients treated with PD1 inhibitors (PD1i) vary significantly across different histologies with objective responses rates that are around 70% in classical Hodgkin lymphoma, but significantly lower, around 10%, in indolent non-Hodgkin lymphomas (iNHL). This may be due in part to the inability of PD1i to restore the function of exhausted T-cells (Tex) in the tumor microenvironment (TME). PD1 is expressed on various T-cell subsets, including effector cells and Tex. In this study we sought to identify markers of exhaustion beyond PD1 that define T-cell subsets with high reactivation potential in marginal zone lymphoma (MZL). To define different stages of exhaustion in MZL, we developed and validated a mass cytometry (CyTOF) panel which integrates T-cell markers of lineage, differentiation, activation, suppression, cytokine production and transcription factors associated with exhaustion. We analyzed 35 MZL spleens obtained at diagnosis and 6 reactive spleens. We identified a population of CD8 cells in MZL that express TIM3 without PD1, compose 1.5% (range 0.14-4.88%) of total CD8 cells and expand with activation through the TCR (6.2% of CD8, range 0.6-14.2%). Prolonged cytokine exposure has been shown to induce exhaustion in healthy T-cells, and so to determine whether PD1-TIM3+ cells are Tex, we treated healthy donor T-cells with activating beads and IL12 and analyzed them by flow cytometry. We showed that PD1-TIM3+ cells expand with repetitive activation and IL12 treatment suggesting that they are Tex. Since Tex have been shown to have a distinct transcription profile compared to functional effector T-cells, we analyzed the expression of several transcription factors (TFs) that are upregulated in Tex by CyTOF and compared them to other subsets of T-cells. PD1-TIM3+ cells expressed higher levels of Eomes, Tbet, TOX and Helios compared to activated effector cells, confirming that they are Tex, but lower levels levels of the same TFs compared to PD1+TIM3+ cells, consistent with a less severely exhausted phenotype. To characterize the function of PD1-TIM3+ cells, we manually gated on subsets of CD8+ non-naïve cells that were stained with the CyTOF panel and compared the different subsets. We showed that PD1-TIM3+ cells arise from effector cells, maintain their polyfunctionality by producing cytokines and chemokines and have a unique cytokine production profile, including perforin, granzyme B and proinflammatory cytokines, such as IL17A. Importantly, PD1-TIM3+ cells produced higher levels of most cytokines compared to more severely Tex expressing both PD1 and TIM3 (Fig 1). We then performed tSNE analysis where similar objects are modeled by nearby points. We determined that PD1-TIM3+ cells cluster together, suggesting that they are phenotypically homogeneous cells in terms of function and expression of activation markers and are significantly different from PD1+TIM3+ cells (Fig 2). We finally blocked PD1 or TIM3 and analyzed the effect of each antibody blockade on function. We showed that TIM3 blockade was able to restore the production of most cytokines to higher degrees than PD1 blockade. In addition, TIM3 blockade led to upregulation of CD28, which is critical for the rescue of Tex through costimulation, while PD1 blockade did not. We then analyzed the clinical outcomes of all 34 MZL patients. The frequency of PD1-TIM3+ cells was lower among observed patients who failed to achieve an event-free survival (EFS) of 12 months (EFS12) (0.8% vs 1.7%, p=0.02) and among treated patients that failed an EFS of 24 months (EFS24) (0.9 vs 1.7%, p=0.03), when compared to patients that reached these endpoints. Higher levels of PD1-TIM3+ cells were also associated with a trend towards improved overall survival (OS). Five-year OS was 88% vs. 69% in patients with PD1-TIM3+ levels >2% and <2% of total CD8 cells respectively (p=0.1) (Fig 3). Our study provides insights into the mechanisms of failure of PD1i in MZL and identifies a novel population of Tex with high reactivation potential which is clinically relevant and could serve as a target for future immunotherapies in iNHL. Disclosures Anagnostou: American Society of Hematology, Mayo Clinic/Iowa Lymphoma SPORE, Mayo Clinic Immune Monitoring Core, Mayo Clinic Hematology Small Grant: Research Funding. Novak:Celgene Coorperation: Research Funding. Ansell:Mayo Clinic Rochester: Employment; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding.