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AbstractBackgroundWhile parenchymal hepatic metastases were previously considered a contraindication to cytoreductive surgery (CRS) and heated intraperitoneal chemotherapy (HIPEC), liver resection (LR) is increasingly performed with CRS/HIPEC.MethodsPatients from the US HIPEC Collaborative (2000–2017) with invasive appendiceal or colorectal adenocarcinoma undergoing primary, curative intent CRS/HIPEC with CC0‐1 resection were included. LR was defined as a formal parenchymal resection. Primary endpoints were postoperative complications and overall survival (OS).ResultsA total of 658 patients were included. About 83 (15%) underwent LR of colorectal (58%) or invasive appendiceal (42%) metastases. LR patients had more complications (81% vs. 60%; p = .001), greater number of complications (2.3 vs. 1.5; p < .001) per patient and required more reoperations (22% vs. 11%; p = .007) and readmissions (39% vs. 25%; p = .014) than non‐LR patients. LR patients had decreased OS (2‐year OS 62% vs. 79%, p < .001), even when accounting for peritoneal carcinomatosis index and histology type. Preoperative factors associated with decreased OS on multivariable analysis in LR patients included age < 60 years (HR, 3.61; 95% CI, 1.10–11.81), colorectal histology (HR, 3.84; 95% CI, 1.69–12.65), and multiple liver tumors (HR, 3.45; 95% CI, 1.21–9.85) (all p < .05). When assigning one point for each factor, there was an incremental decrease in 2‐year survival as the risk score increased from 0 to 3 (0: 100%; 1: 91%; 2: 58%; 3: 0%).ConclusionsAs CRS/HIPEC + LR has become more common, we created a simple risk score to stratify patients considered for CRS/HIPEC + LR. These data aid in striking the balance between an increased perioperative complication profile with the potential for improvement in OS.

Abstract Purpose: T-cell immunoglobulin and ITIM domain (TIGIT), a member of the immune checkpoint family, is important in normal T-cell biology. However, the phenotypical profile and clinical relevance of TIGIT in follicular lymphoma is largely unknown. Experimental Design: Biopsy specimens from a cohort of 82 patients with follicular lymphoma were analyzed using mass cytometry to explore the phenotype and biological and clinical significance of TIGIT+ T cells. Results: TIGIT is highly expressed on intratumoral T cells and its expression alters T-cell phenotype in follicular lymphoma. TIGIT is abundantly expressed on Treg cells, resulting in an enhanced suppressive property. TIGIT expression on non-Treg/TFH T cells defines a population that exhibits an exhausted phenotype. Clinically, increased numbers of TIGIT+ T cells are associated with inferior patient outcomes and poor survival. We observe that anti–PD-1 therapy with pembrolizumab alters the phenotype of TIGIT+ T subsets and identifies a role for CD28 expression on TIGIT+ T cells in treatment response. Conclusions: The current study provides a comprehensive analysis of the phenotypic profile of intratumoral TIGIT+ T subsets and their prognostic relevance in follicular lymphoma. Inhibition of TIGIT signaling may be an additional mechanism to prevent T-cell suppression and exhaustion in B-cell lymphoma.

AbstractBackgroundVariations in care have been demonstrated both within and among institutions in many clinical settings. By standardizing perioperative practices, Enhanced Recovery After Surgery (ERAS) pathways reduce variation in perioperative care. We sought to characterize the variation in cytoreductive surgery (CRS)/heated intraperitoneal chemotherapy (HIPEC) perioperative practices among experienced US medical centers.MethodsData from the US HIPEC Collaborative represents a retrospective multi‐institutional cohort study of CRS and CRS/HIPEC procedures performed from 12 major academic institutions. Patient characteristics and perioperative practices were reported and compared. Institutional variation was analyzed using hierarchical mixed‐effects linear (continuous outcomes) or logistic (binary outcomes) regression models.ResultsA total of 2372 operations were included. CRS/HIPEC was performed most commonly for appendiceal histologies (64.2%). The rate of complications (overall 56.3%, range: 31.8‐70.9) and readmissions (overall 20.6%, range: 8.9‐33.3) varied by institution (P < .001). Institution‐level variation in perioperative practice patterns existed among measured ERAS pathway process/outcomes (P < .001). The percentages of variation with each process/outcome measure attributable solely to institutional practices ranged from 0.6% to 66.6%.ConclusionsSignificant variation exists in the perioperative care of patients undergoing CRS/HIPEC at major US academic institutions. These findings provide a strong rationale for the investigation of best practices in CRS/HIPEC patients.

Cytoreductive surgery (CRS) with or without hyperthermic intraperitoneal chemotherapy (HIPEC) is associated with improved survival for patients with colorectal peritoneal metastases (CR-PM). However, the role of neoadjuvant chemotherapy (NAC) prior to CRS-HIPEC is poorly understood. A retrospective review of adult patients with CR-PM who underwent CRS+/-HIPEC from 2000–2017 was performed. Among 298 patients who underwent CRS+/-HIPEC, 196 (65.8%) received NAC while 102 (34.2%) underwent surgery first (SF). Patients who received NAC had lower peritoneal cancer index score (12.1 + 7.9 vs. 14.3 + 8.5, p = 0.034). There was no significant difference in grade III/IV complications (22.4% vs. 16.7%, p = 0.650), readmission (32.3% vs. 23.5%, p = 0.114), or 30-day mortality (1.5% vs. 2.9%, p = 0.411) between groups. NAC patients experienced longer overall survival (OS) (median 32.7 vs. 22.0 months, p = 0.044) but similar recurrence-free survival (RFS) (median 13.8 vs. 13.0 months, p = 0.456). After controlling for confounding factors, NAC was not independently associated with improved OS (OR 0.80) or RFS (OR 1.04). Among patients who underwent CRS+/-HIPEC for CR-PM, the use of NAC was associated with improved OS that did not persist on multivariable analysis. However, NAC prior to CRS+/-HIPEC was a safe and feasible strategy for CR-PM, which may aid in the appropriate selection of patients for aggressive cytoreductive surgery.

40 Background: Postoperative complications (POCs) are associated with worse oncologic outcomes in various cancer histologies. The impact of POCs on the survival of patients with appendiceal or colorectal cancer after cytoreductive surgery/heated intraperitoneal chemotherapy (CRS/HIPEC) is unknown. Methods: US HIPEC Collaborative (2000-17) was reviewed for patients who underwent CCR0/1 CRS/HIPEC for appendiceal/colorectal cancer. Analysis was stratified by non-invasive appendiceal neoplasm vs invasive appendiceal/colorectal adenocarcinoma. POCs were grouped into infectious, cardiopulmonary, thromboembolic and intestinal dysmotility. Primary outcomes were 3-yr overall survival (OS) and recurrence-free survival (RFS). Results: Of 1304 pts, median age was 55 yrs, 41% were male (n = 537), 33% had non-invasive appendiceal (n = 426) and 67% had invasive appendiceal/colorectal adenocarcinoma (n = 878). In the non-invasive appendiceal cohort, POCs were identified in 55% (n = 233) and OS and RFS did not differ between patients who experienced a complication and those who did not (OS 94 vs 94% p = 0.26; RFS 68 vs 60% p = 0.15). In the invasive appendiceal/colorectal adenocarcinoma cohort, however, POCs (63%; n = 555) were associated with decreased OS (59 vs 74% p < 0.001) and RFS (32 vs 42% p < 0.001). Infectious POCs were most common (35%; n = 196). On MV analysis accounting for gender, PCI and incomplete resection (CCR1), infectious POCs in particular were associated with decreased OS compared to no complication (HR 2.08 95%CI 1.48-2.93 p < 0.01) or other types of complications (HR 1.7 95%CI 1.28-2.25 p < 0.01). This association persisted for infectious POCs and reduced RFS (HR 1.61 95%CI 1.23-2.10 p < 0.01). Conclusions: Postoperative complications are associated with decreased OS and RFS after CRS/HIPEC for invasive histology, but not for an indolent disease like non-invasive appendiceal neoplasm. Of all complication types, infectious complications are the main driver for this association. The exact mechanism is not known, but may be immunologic. Efforts must target best practices and standardized prevention strategies to minimize infectious POCs.

37 Background: While parenchymal hepatic metastases were previously considered a contraindication to cytoreductive surgery(CRS) and heated intraperitoneal chemotherapy(HIPEC), liver resection(LR) is increasingly performed concomitantly with CRS/HIPEC. As this practice continues to expand, identification of preoperative factors associated with poor outcomes is paramount. Methods: Patients from the US HIPEC Collaborative(2000-2017) with invasive appendiceal or colorectal adenocarcinoma undergoing primary, curative intent CRS/HIPEC with CC0-1 resection were included. LR was defined as a formal parenchymal resection. Primary endpoints were postoperative complications and overall survival(OS). Results: 658 patients were included. Average age was 54 years and 45% were male; 83 (15%) underwent liver resection of colorectal (58%) or invasive appendiceal (42%) metastases. Liver resection patients had more complications (81 vs 60%; p = 0.001), greater number of complications (2.3 vs 1.5; p < 0.001), and required more reoperations (22 vs 11%; p = 0.007) and readmissions (39 vs 25%; p = 0.014) than non-liver resection patients. Liver resection patients had decreased OS (2-year OS 62% vs 79%, p < 0.001), which persisted on multivariable Cox regression when accounting for PCI and histology type. Preoperative factors associated with decreased OS on multivariable analysis in patients undergoing liver resection included age < 60 years (HR:3.61), colorectal histology (HR:3.84), and multiple liver tumors (HR:3.45) (all p < 0.05). When assigning one point for each factor, there was an incremental decrease in 2-yr survival as the risk score increased from 0 to 3 (0: 100%; 1: 91%; 2: 58%; 3: 0%; p < 0.001). Conclusions: As concurrent liver resection with CRS/HIPEC has become more common, we created a simple risk score to stratify patients considered for CRS/HIPEC with liver resection. These data aid in striking the balance between an increased perioperative complication profile with the potential for improvement in overall survival.

184 Background: Patient age is often a significant factor in preoperative selection for major abdominal surgery. Its association with postoperative outcomes in patients undergoing cytoreductive surgery(CRS) and hyperthermic intraperitoneal chemotherapy(HIPEC) remains ill-defined. Methods: The US HIPEC Collaborative database(2000-2017) was reviewed for patients who underwent a CCR0/1 CRS/HIPEC. Age was categorized into < 65 or >65yrs. Primary outcomes were postoperative major complications, readmission, 30-day mortality, and non-home discharge(NHD). Analysis was stratified by disease histology: non-invasive(appendiceal LAMN/HAMN), and invasive(appendiceal/colorectal adenocarcinoma). Results: Of 1090pts identified, 22% were >65yrs(n = 240), 59% were female(n = 646), 25% had non-invasive(n = 276) and 51% had invasive(n = 555) histology. Median PCI was 13(IQR7-20). Patients >65yrs had a higher rate of major complications(37vs26%, p = 0.02), readmission(28vs22%,p = 0.05), 30-day mortality(3vs1%,p = 0.02), and NHD(12vs5%,p < 0.01) compared to those < 65yrs. On multivariable analysis accounting for extent of disease as measured by PCI, for non-invasive histology, age >65yrs was an independent predictor for NHD(OR:2.54,95%CI:1.08-5.99,p = 0.03), but not major complications. For invasive histology, even when accounting for PCI, age >65yrs was an independent predictor for both NHD(OR:2.54,95%CI:1.08-5.98,p = 0.03) and major complications(OR:2.04,95%CI:1.16-3.59,p = 0.05). Age was not associated with hospital readmission or 30-day mortality for any histology. Conclusions: Regardless of histology, patients >65yrs are nearly at three-fold increased risk for non-home discharge after CRS/HIPEC. For invasive histology, age >65yrs is also associated with increased major complication rates, but the procedure seems to be better tolerated when performed for indolent biology. These data inform preoperative counseling and risk stratification. Early planning for discharge disposition in this high-risk population can potentially translate to cost savings.

Introduction: Current classifications of low-grade B-cell lymphomas (LGL), including splenic marginal zone lymphomas (SMZL), nodal marginal zone lymphomas (NMZL), and Lymphoplasmacytic lymphomas (LPL) are based on a mixture of clinical features and morphologic, immunophenotypic, and genetic findings from the tumor biopsy specimen. While this approach to classification makes pathologic diagnosis more precise, the corresponding clinical impact for the timing and choice of treatment is limited, and differentiating between cases can be challenging. Although LGL are considered indolent and the 10-year overall survival (OS) is about 80%, 70% of cases will eventually require treatment and approximately 30% of patients display a more aggressive phenotype and have a poor prognosis. Consequently, further investigations into the driving genetic, biological, and immune mechanisms of LGL are essential for early identification of high-risk patients and design of personalized treatments. Materials and Methods: RNA-seq was performed on 63 newly diagnosed LGL patient samples from the Mayo Clinic/University of Iowa Lymphoma SPORE: SMZL (N=48), NMZL (N=6), LPL (N=5), MALT (N=2), and BCL (N=2) as well as 5 normal memory B cell controls (CD19+CD27+). For identification of biologic clusters, filtered RNA-seq data was analyzed using the Non-negative Matrix Factorization (NMF) clustering tool from the Broad Institute against the normal samples. Each cluster was analyzed for differential gene expression. This analysis generated cluster-specific T values for each gene. Genes that were significantly associated with a cluster (FDR<0.05) were analyzed for genetic ontology. Cibersort was used to deconvolute the tumor microenvironment (TME). We performed whole exome sequencing (WES) analyses on 60/63 matched LGL to characterize mutations and copy number alterations. Results: WES revealed the presence of previously reported mutations in genes such as MYD88, SPEN, NOTCH, and KLF2 as well as copy number alterations 7q31.2, BCL6, TNFAIP3, and BCL2. NMF clustering of RNA-seq data resulted in a best fit of 5 clusters, named LGL1 through LGL4 and "Normals". Pathologic subtypes were not exclusive to a specific cluster. Differential RNA expression analysis resulted in gene sets that were differentially expressed in each cluster. A cluster signature of the top 1% of associated genes (N=94) was created for each. LGL1 genes were associated with higher BCR signaling. LGL2 was characterized by regulatory dysfunction, particularly concerning mitochondrial integrity. LGL3 genes were associated with high TME and NOTCH and STAT signaling components. Specifically, LGL3 was associated with high CD8+ T-cell and M2 macrophage TME presence. LGL4 was distinguished by the presence of aggressive genetic programs related to B-cell activation such as NF-kB and IRF4. Consequently, LGL4 patients had significantly poorer rates of event-free survival (EFS) (P=0.029) and OS (P=0.006) when compared against the other groups. The top 1% gene signature (N=94) was next validated against an independent cohort of 84 LGL samples with gene expression data (SMZL [N=34], NZML [N=24], and LPL [N=24]). A similar cluster pattern emerged, with pathological subtypes distributing across LGL classifications based on respective transcriptomic signatures. Association of DNA variants within each cluster was also analyzed, but due to the low frequency of genomic variants detected in LGL, nothing was significantly associated. However, we did see an enrichment of BCL2, BCL6, and TNFAIP3 alterations in LGL4 and an overall lower driver gene mutation frequency in LGL2. Conclusions: Gaining a greater understanding of LGL based on their genetic, biologic, and immune profiles will establish a valuable platform for clinicians to identify high-risk cases and make better therapeutic decisions. Using a large cohort of well-annotated cases we identify novel clusters of LGL that present unique genomic and clinical profiles. Our study lays the groundwork for a precision therapy approach in LGL in which DNA or RNA profiles can be used to identify patients early in treatment who may not benefit from the current standard of care and who would benefit from closer monitoring and targeted agents. Disclosures Anagnostou: American Society of Hematology, Mayo Clinic/Iowa Lymphoma SPORE, Mayo Clinic Immune Monitoring Core, Mayo Clinic Hematology Small Grant: Research Funding. Ansell:Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment. Cerhan:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; NanoString: Research Funding. Novak:Celgene Coorperation: Research Funding.

Introduction Waldenstrom macroglobulinemia (WM) is a rare, incurable, indolent non-Hodgkin lymphoma that is preceded by an IgM monoclonal gammopathy of undetermined significance (IgM MGUS). In recent years, better understanding of the pathobiology of WM and IgM MGUS has strengthened the hypothesis that they may represent different stages of the same disease. Studying the relationship between these two conditions is the essential first step to understanding the mechanisms driving the malignant transformation from IgM MGUS to WM. Recently long non-coding RNAs (lncRNAs) have garnered significant recognition for their roles in the regulation of gene expression and cellular function. lncRNA can regulate gene expression of neighboring protein-coding genes through multiple mechanisms such as by recruiting chromatin modifiers and increasing accessibility of genes to transcription proteins, or by directly binding to enhancers or promoters. Here we present the first analysis of the lncRNA expression profile in patients with WM compared to IgM MGUS. Methods Twenty-one patients with untreated WM (n=14) and IgM MGUS (n=7) seen at Mayo Clinic were included in this analysis. Malignant cells were isolated from bone marrow samples using CD19 and CD38 positive selection. Total RNA was extracted and sequencing was performed using the Illumina HiSeq4000 NGS platform. Differentially expressed lncRNAs in WM compared to IgM MGUS were defined as log2 fold change (FC) > 1.0 (upregulated) or < -1.0 (downregulated) and a false discovery rate (FDR) < 0.05. The nearest gene to each lncRNA was also identified and their gene expression was detected. Using the Ingenuity Pathway Analysis software and taking into account the transcriptional expression and known function of these genes, a correlation between cell function and disease analysis was performed. Results A total of 119 lncRNAs were differently expressed between WM and IgM MGUS (17 transcripts were upregulated in WM, while 102 were downregulated in WM). Sixteen unique genes were identified as the nearest gene to 17 upregulated lncRNAs, while 18 genes were identified as the nearest genes to the top 18 downregulated lncRNAs in WM compared to IgM MGUS. Several of the upregulated lncRNA in WM were in proximity to known oncogenes. The well-known oncogenic lncRNA PVT1 was found to be upregulated in WM compared to IgM MGUS (log2 FC 1.35, FRD 0.04). PVT1 is overexpressed in several malignancies and associated with inhibition of apoptosis and increased cell proliferation. PVT1 is in close proximity to MYC and co-expression of PVT1-MYC has been described in multiple cancers. PVT1 also potentiate MYC amplification by increasing MYC protein stability, therefore promoting malignant cell growth. The lncRNA TCB1D27, also upregulated in WM compared to IgM MGUS, is located in close proximity to the oncogene TNFRSF13B (TACI), which was found to be overexpressed in WM patients (log2 FC 1.61, FDR <0.001). TACI is a receptor for BLyS/BAFF, which modulates the development of normal B-cells and plays a role in various B-cell malignancies. In fact, BLyS/BAFF level is known to be increased in WM and to promote survival and proliferation of WM B cells. The upregulated lncRNA RP11-25K21.1 in WM is located in close proximity to the oncogene FCGR2B (CD32B), which was also upregulated in WM compared to IgM MGUS (log2 FC 1.59, FDR 0.001). Overexpression of CD32B was previously shown to be associated with inferior outcomes in DLBCL and FL patients, presumably secondary to an increased internalization and clearance of rituximab due to increased CD32B expression on malignant cells. Several other upregulated lncRNAs in WM compared to IgM MGUS are also in proximity of other oncogenes such as PCED1B, POLD3, CLLU1, and SMAD7. Finally, we considered the expression of the nearest genes and their reported cell function and association with diseases. Several genes that are known to have a role in the cell proliferation and/or neoplasm development were noted to be upregulated in WM (figure 1). Conclusion We present the first report of lncRNAs expression in WM and IgM MGUS in addition to a concurrent analysis of the gene expression of the nearest protein-coding genes. Several known oncogenes are in proximity of overexpressed lncRNAs in WM compared to IgM MGUS that could indicate potential implications in the pathobiology of these diseases and the mechanism driving the malignant transformation to WM. Disclosures Paludo: Celgene: Research Funding; Celgene: Research Funding; Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding. Dasari:The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Kapoor:Celgene: Honoraria; Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding. Ailawadhi:Amgen: Consultancy, Research Funding; Pharmacyclics: Research Funding; Takeda: Consultancy; Janssen: Consultancy, Research Funding; Cellectar: Research Funding; Celgene: Consultancy. Gertz:Amyloidosis Foundation: Research Funding; i3Health: Other: Development of educational programs and materials; Medscape: Consultancy, Speakers Bureau; Ionis/Akcea: Consultancy; Celgene: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Teva: Speakers Bureau; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Springer Publishing: Patents & Royalties; International Waldenstrom Foundation: Research Funding. Novak:Celgene Coorperation: Research Funding. Ansell:Affimed: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding.

Introduction: New Diffuse Large B-cell (DLBCL) treatments remain a clinical need despite the success of rituximab combined with CHOP chemotherapy (RCHOP), which results in durable responses in 60-70% of patients. Those refractory to, or who relapse following, first-line therapy have a very poor outcome, with only 20% surviving beyond 5 years. Rationally-targeted frontline strategies are needed, especially for those with high-risk disease. Significant advances have been made in the genomic classification of DLBCL, but none have impacted the design of phase III trials for untreated DLBCL patients. Building on new genetic profiling studies to personalize clinical treatment, an NCI initiative, could allow clinicians to add targeted therapies to the RCHOP backbone based on individual tumor signatures. The phase II ECOG-ACRIN1412 trial, which compared RCHOP combined with lenalidomide (R2CHOP) versus RCHOP showed significantly superior event free survival (EFS) and overall survival benefits for those treated with R2CHOP. Herein, we report the profile of a high-risk ABC/non-GCB subset of DLBCL driven by genomic alterations in inflammatory genes that are susceptible to front-line R2CHOP, but continue to experience poor outcome with RCHOP alone. Methods: We studied a total of 196 DLBCL patients. 47 were treated with R2CHOP from an investigator-initiated, open-label, single-arm phase II study (NCT00670358). 149 were newly diagnosed DLBCL cases treated with RCHOP, or R-immunochemotherapy (herein called RCHOP), and followed prospectively through the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic SPORE that served as a contemporary cohort. Patients from each treatment group were divided based on their event free survival at 24 months (EFS24). DNA alterations within these populations were identified through whole exome sequencing (WES). Variants were analyzed for their presence in EFS24 achievement or failure groups in both RCHOP and R2CHOP. Both tumor and germline sequencing was performed for 47/47 R2CHOP cases and 49/149 RCHOP cases. Gene expression data from the PanCan panel of 730 B-cell-related genes was analyzed to determine gene expression profiles characteristic of the high-risk/R2CHOP-profile on 59 available non-GCB DLBCL cases (45 RCHOP; 14 R2CHOP). A two-sided comparative marker analysis T statistic test was applied to assess what genes displayed differential expression based on achieving EFS24 in both R2CHOP and RCHOP populations. Positive values represented associations with achieving EFS24 and negative values were associated with cases of EFS24 failure. Results: Three genes were enriched in the RCHOP cases that failed EFS24 but achieved EFS24 with R2CHOP among non-GCB patients: PIM1, SPEN, and MYD88 (L265P), herein referred to as Responder Alterations. In R2CHOP cases, patients with a Responder Alteration had a better overall EFS (P = 0.051) compared to wild type patients. In contrast, RCHOP treated patients with a Responder Alteration in their tumor had a significantly worse overall EFS (P = 0.0004) compared to patients without a mutation. Together, PIM1, SPEN, or MYD88 (L265P) mutations were present in 38.0% (30/79) of all non-GCB cases. Collective R2CHOP and RCHOP EFS24 differential gene expression T values were significantly different for 18 previously-defined signatures. The R2CHOP cases that achieved EFS24 were enriched for genes involved in cell cycle, JAK-STAT, cytokine signaling, and NF-κB pathways based on these signatures and ontology analyses. Lastly, cases with WES and PanCan data were analyzed together to observe differential gene expression patterns between cases with and without signature mutations. These data suggest that R2CHOP disrupts tumors reliant on IRF4, NF-κB, and STAT transcription factors, leading to a loss of proliferative feedback systems. Conclusions: Our combined analysis of DNA and RNA across R2CHOP and RCHOP treatment cohorts identifies a high-risk non-GCB phenotype that encompasses approximately 38% of non-GCB patients, is capable of sustaining JAK-STAT and NF-κB signaling, and is sensitive to R2CHOP. Our study lays the groundwork for a precision therapy approach in DLBCL in which DNA or RNA profiles can be used to identify patients early in treatment who may not benefit from the current standard of care, RCHOP, and who would benefit from the addition of lenalidomide or other targeted agents. Disclosures Gandhi: Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Ansell:LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding. Cerhan:Celgene: Research Funding; NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees. Nowakowski:Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding; NanoString: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees. Novak:Celgene Coorperation: Research Funding.