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Molecular monitoring of tumor-derived alterations has an established role in the surveillance of leukemias, and emerging nucleic acid sequencing technologies are likely to similarly transform the clinical management of lymphomas. Lymphomas are well suited for molecular surveillance due to relatively high cell-free DNA and circulating tumor DNA concentrations, high somatic mutational burden, and the existence of stereotyped variants enabling focused interrogation of recurrently altered regions. Here, we review the clinical scenarios and key technologies applicable for the molecular monitoring of lymphomas, summarizing current evidence in the literature regarding molecular subtyping and classification, evaluation of treatment response, the surveillance of active cellular therapies, and emerging clinical trial strategies. Expected final online publication date for the

Supplemental Table 1. Overall cohort characteristics of AAPC whole exome sequencing cohort (n=102) Supplemental Table 2. Clinical and pathological characteristics of AAPC WES discovery cohort (n=102) Supplemental Table 3. Comparison of numbers of tumors by Gleason grade between the TCGA and AAPC cohorts Supplemental Table 4. Germline pathogenic variants in genes in the DNA repair pathway and list of 20 DNA repair genes assessed in targeted analysis Supplemental Table 5. Alteration file of somatic variants detected in the AAPC WES discovery cohort (n=102) Supplemental Table 6. Focal deletion and amplification peaks and genes located within peaks by GISTIC2.0 analysis of AAPC WES cohort Supplemental Table 7. ERF deletions and mutations in prostate tumors of the Weill Cornell Precision Medicine cohort Supplemental Table 8. Clinical and pathological characteristics of AAPC targeted sequencing extension cohort Supplemental Table 9. List of genes and intronic regions targeted with hybrid capture bait set used for AAPC extension cohort Supplemental Table 10. Alteration file of somatic variants detected in the AAPC extension cohort (n=90) using the targeted sequencing panel Supplemental Table 11. ERF mutation frequencies across published prostate cancer cohorts Supplemental Table 12. Germline ERF variant detected in the AAPC WES cohort Supplemental Table 13. Mutations in cytochrome P450 genes in the AAPC exome discovery cohort Supplemental Table 14. ERF oligonucleotides used for RNA in situ hybridization Supplemental Table 15. Gene sets shERF_VCAP_UP_LnCAP_UP_overlap_UP and shERF_vs_CNTRL.LHSAR_UP Supplemental Table 16. Tumor purity estimates for AAPC exome discovery cohort

Supplemental Methods

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Mastering nuclear fusion, which is an abundant, safe, and environmentally competitive energy, is a great challenge for humanity. Tokamak represents one of the most promising paths toward controlled fusion. Obtaining a high-performance, steady-state, and long-pulse plasma regime remains a critical issue. Recently, a big breakthrough in steady-state operation was made on the Experimental Advanced Superconducting Tokamak (EAST). A steady-state plasma with a world-record pulse length of 1056 s was obtained, where the density and the divertor peak heat flux were well controlled, with no core impurity accumulation, and a new high-confinement and self-organizing regime (Super I-mode = I-mode + e-ITB) was discovered and demonstrated. These achievements contribute to the integration of fusion plasma technology and physics, which is essential to operate next-step devices.

Most relapsed/refractory large B cell lymphoma (r/rLBCL) patients receiving anti-CD19 chimeric antigen receptor (CAR19) T cells relapse. To characterize determinants of resistance, we profiled over 700 longitudinal specimens from two independent cohorts (n = 65 and n = 73) of r/rLBCL patients treated with axicabtagene ciloleucel. A method for simultaneous profiling of circulating tumor DNA (ctDNA), cell-free CAR19 (cfCAR19) retroviral fragments, and cell-free T cell receptor rearrangements (cfTCR) enabled integration of tumor and both engineered and non-engineered T cell effector-mediated factors for assessing treatment failure and predicting outcomes. Alterations in multiple classes of genes are associated with resistance, including B cell identity (PAX5 and IRF8), immune checkpoints (CD274), and those affecting the microenvironment (TMEM30A). Somatic tumor alterations affect CAR19 therapy at multiple levels, including CAR19 T cell expansion, persistence, and tumor microenvironment. Further, CAR19 T cells play a reciprocal role in shaping tumor genotype and phenotype. We envision these findings will facilitate improved chimeric antigen receptor (CAR) T cells and personalized therapeutic approaches.

Implementing cancer precision medicine in the clinic requires assessing the therapeutic relevance of genomic alterations. A main challenge is the systematic interpretation of whole-exome sequencing (WES) data for clinical care. One hundred sixty-five adults with metastatic colorectal and lung adenocarcinomas were prospectively enrolled in the CanSeq study. WES was performed on DNA extracted from formalin-fixed paraffin-embedded tumor biopsy samples and matched blood samples. Somatic and germ-line alterations were ranked according to therapeutic or clinical relevance. Results were interpreted using an integrated somatic and germ-line framework and returned in accordance with patient preferences. At the time of this analysis, WES had been performed and results returned to the clinical team for 165 participants. Of 768 curated somatic alterations, only 31% were associated with clinical evidence and 69% with preclinical or inferential evidence. Of 806 curated germ-line variants, 5% were clinically relevant and 56% were classified as variants of unknown significance. The variant review and decision-making processes were effective when the process was changed from that of a Molecular Tumor Board to a protocol-based approach. The development of novel interpretive and decision-support tools that draw from scientific and clinical evidence will be crucial for the success of cancer precision medicine in WES studies. Genet Med advance online publication 26 January 2017

Background: Characterization of T-cell receptor (TCR) diversity and dynamics is increasingly critical to understanding therapeutic immune responses targeting tumors. Current TCR profiling methods generally require invasive tissue biopsies that capture a single snapshot of immune activity or are limited by the sheer diversity of the circulating TCR repertoire. In theory, T-cells with the greatest turnover could best reflect pivotal immune dynamics from both circulating and tissue-derived compartments, including non-circulating tissue-resident memory T-cells (Trm). To noninvasively capture such responses in the blood, we developed and benchmarked a high-throughput TCR profiling approach using plasma, optimized for the fragmented nature of cfDNA and the non-templated nature of rearranged TCRs. We then applied this method for residual disease monitoring in mature T-cell lymphomas (TCL) without circulating disease and for characterizing immune dynamics after anti-CD19 chimeric antigen receptor (CAR19) T-cell therapy of B-cell lymphomas with axicabtagene ciloleucel. Methods: We developed SABER (Sequence Affinity capture & analysis By Enumeration of cell-free Receptors) as a technique for TCR enrichment and analysis of fragmented rearrangements shed in cfDNA and applied this method using Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq). We used SABER to profile a total of 381 samples (300 cfDNA and 81 PBMC samples) from 75 lymphoma patients and 18 healthy controls. After mapping sequencing reads (hg38) to identify candidate rearrangements within TCR loci, unique cfDNA fragments were resolved by a novel strategy to define consensus of unique molecular identifiers clustered by Levenshtein distances, followed by CDR3-anchoring for enumeration of final receptor clonotypes. SABER thus leverages information from fragmented TCRs, a critical requirement for cfDNA, to make V gene, CDR3, and J gene assignments after deduplication-mediated error-correction. We benchmarked SABER against established amplicon-based TCR-β targeted sequencing (LymphoTrack, Invivoscribe) and repertoire analysis methods (MiXCR; Bolotin et al, 2015 Nature Methods) when considering both cfDNA and PBMC samples from healthy adults and TCL patients. We assessed SABER performance for tracking clonal molecular disease in patients with mature TCLs from both cellular and cell-free circulating compartments (n=9). Malignant TCL clonotypes were identified in tumor specimens using clonoSEQ (Adaptive Biotechnologies). Finally, we evaluated TCR repertoire dynamics over time in 66 DLBCL patients after CAR19 T-cell therapy. Results: SABER demonstrated superior recovery of TCR clonotypes from cfDNA compared to both amplicon sequencing (LymphoTrack, Invivoscribe) and hybrid-capture methods when enumerating receptors using MiXCR (Fig. 1A). When applied to blood samples from TCL patients, SABER identified the malignant clonal TCR-β rearrangement in 8/9 (88.9%) cases, with significantly improved detection in cfDNA (p=0.015, Fig. 1B). Specifically, tumoral TCR clonotype was detectable only in cfDNA in 6 cases (75%), cfDNA-enriched in 1 case (12.5%), and detectable only in PBMCs in 1 case (12.5%). We applied SABER to monitor TCR repertoire dynamics in cfDNA after CAR T-cell therapy of patients with relapsed/refractory DLBCL and observed increased T-cell turnover and repertoire expansion (greater total TCR-β clonotypes) (Fig. 1C). As early as 1-week after CAR19 infusion, TCR repertoire size was significantly correlated both with cellular CAR19 T-cell levels by flow cytometry (p=0.008) as well as with retroviral CAR19 levels in cfDNA (p=2.20e-07) suggesting faithful monitoring of CAR T-cell activity (Fig. 1D). TCR repertoire size one month after infusion was significantly associated with longer progression-free survival (HR 0.246, 95% CI 0.080-0.754, p=0.014). Conclusions: SABER has a favorable profile for cfDNA TCR repertoire capture when compared to existing methods and could thus have potential broad applicability to diverse disease contexts. Given the higher abundance of lymphoma-derived TCRs in cfDNA than intact circulating leukocytes, SABER holds promise for monitoring minimal residual disease in T-cell lymphomas. This approach also holds promise for monitoring T-cell repertoire changes including after CAR T-cell therapy and for predicting therapeutic responses. Disclosures Kurtz: Genentech: Consultancy; Foresight Diagnostics: Other: Ownership; Roche: Consultancy. Kim:Corvus: Research Funding; Eisai: Membership on an entity's Board of Directors or advisory committees, Research Funding; Elorac: Research Funding; Forty Seven Inc: Research Funding; Galderma: Membership on an entity's Board of Directors or advisory committees, Research Funding; Horizon Pharma: Consultancy, Research Funding; Innate Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Kyowa-Kirin Pharma: Research Funding; Medivir: Membership on an entity's Board of Directors or advisory committees; Merck: Research Funding; miRagen: Research Funding; Neumedicine: Consultancy, Research Funding; Portola: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Solingenix: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Trillium: Research Funding. Mackall:Lyell Immunopharma: Consultancy, Current equity holder in private company; BMS: Consultancy; Allogene: Current equity holder in publicly-traded company; Apricity Health: Consultancy, Current equity holder in private company; Nektar Therapeutics: Consultancy; NeoImmune Tech: Consultancy. Miklos:Kite-Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Research Funding; Adaptive Biotech: Consultancy, Other: Travel support, Research Funding; Juno-Celgene-Bristol-Myers Squibb: Consultancy, Other: Travel support, Research Funding; Novartis: Consultancy, Other: Travel support, Research Funding; Allogene Therapeutics Inc.: Research Funding; Pharmacyclics: Consultancy, Other: Travel support, Patents & Royalties, Research Funding; Janssen: Consultancy, Other: Travel support; Miltenyi Biotec: Research Funding. Diehn:Varian Medical Systems: Research Funding; Illumina: Research Funding; Roche: Consultancy; AstraZeneca: Consultancy; RefleXion: Consultancy; BioNTech: Consultancy. Khodadoust:Seattle Genetics: Consultancy; Kyowa Kirin: Consultancy. Alizadeh:Janssen: Consultancy; Genentech: Consultancy; Pharmacyclics: Consultancy; Chugai: Consultancy; Celgene: Consultancy; Gilead: Consultancy; Roche: Consultancy; Pfizer: Research Funding.

8518 Background: Detection of circulating tumor DNA (ctDNA) has prognostic value in lung cancer and could facilitate minimal residual disease (MRD) driven approaches. However, the sensitivity of ctDNA detection is suboptimal due to the background error rates of existing assays. We developed a novel method leveraging multiple mutations on a single cell-free DNA molecule (“phased variants” or PVs) resulting in an ultra-low error profile. Here we develop and apply this approach to improve MRD in localized NSCLC. Methods: To identify the prevalence of PVs, we reanalyzed whole genome sequencing (WGS) from 2,538 tumors and 24 cancer types from the pan-cancer analysis of whole genomes (PCAWG). We applied Phased Variant Enrichment and Detection Sequencing (PhasED-Seq) to track personalized PVs in localized NSCLC. We compared PhasED-Seq to a single nucleotide variant (SNV)-based ctDNA method. Results: In the PCAWG dataset, we found that PVs were common in both lung squamous cell carcinomas (LUSC, median 1,268/tumor; rank 2nd) and adenocarcinomas (LUAD, median 655.5/tumor; rank 3rd). However, PVs did not occur in stereotyped genomic regions. Thus, to leverage PhasED-Seq, we performed tumor/normal WGS to identify PVs, followed by design of personalized panels targeting PVs to allow deep cfDNA sequencing. We performed personalized PhasED-Seq for 5 patients with localized NSCLC. PVs were identified from WGS of tumor FFPE and validated by targeted resequencing in all cases (median 248/case). The background rate of PVs was lower than that of SNVs, even when considering duplex molecules (background: SNVs, 3.8e-5; duplex SNVs, 1.0e-5; PVs, 1.2e-6; P < 0.0001). We next assessed PhasED-Seq for MRD detection in 14 patient plasma samples. Both SNVs and PhasED-Seq had high specificity in healthy control cfDNA (95% and 97% respectively). Using SNVs, ctDNA was detected in 5/14 samples; PhasED-Seq detected all of these with nearly identical tumor fractions (Spearman rho = 0.97). However, PhasED-Seq also detected MRD in an additional 5 samples containing tumor fractions as low as 0.000094% (median 0.0004%). We analyzed serial samples from a patient with stage III LUAD treated with chemoradiotherapy (CRT) and durvalumab. SNV-based ctDNA and PhasED-Seq detected similar MRD levels (0.8%) prior to therapy. However, 3 samples collected during CRT, as well as before and during immunotherapy, were undetectable by SNVs. SNV-based ctDNA then re-emerged at disease recurrence. PhasED-Seq detected MRD in all 3 samples not detected by SNVs with tumor fractions as low as 0.00016%, including prior to immunotherapy (8 months prior to progression). Similar improvements were seen in samples not detected by SNVs from 2 additional patients. Conclusions: Personalized ctDNA monitoring via PVs is feasible and improves MRD detection in localized NSCLC. PhasED-Seq allows clinical studies testing personalized treatment based on MRD.

Renal oncocytomas are benign tumors characterized by a marked accumulation of mitochondria. We report a combined exome, transcriptome, and metabolome analysis of these tumors. Joint analysis of the nuclear and mitochondrial (mtDNA) genomes reveals loss-of-function mtDNA mutations occurring at high variant allele fractions, consistent with positive selection, in genes encoding complex I as the most frequent genetic events. A subset of these tumors also exhibits chromosome 1 loss and/or cyclin D1 overexpression, suggesting they follow complex I loss. Transcriptome data revealed that many pathways previously reported to be altered in renal oncocytoma were simply differentially expressed in the tumor's cell of origin, the distal nephron, compared with other nephron segments. Using a heuristic approach to account for cell-of-origin bias we uncovered strong expression alterations in the gamma-glutamyl cycle, including glutathione synthesis (increased GCLC) and glutathione degradation. Moreover, the most striking changes in metabolite profiling were elevations in oxidized and reduced glutathione as well as γ-glutamyl-cysteine and cysteinyl-glycine, dipeptide intermediates in glutathione biosynthesis, and recycling, respectively. Biosynthesis of glutathione appears adaptive as blockade of GCLC impairs viability in cells cultured with a complex I inhibitor. Our data suggest that loss-of-function mutations in complex I are a candidate driver event in renal oncocytoma that is followed by frequent loss of chromosome 1, cyclin D1 overexpression, and adaptive up-regulation of glutathione biosynthesis.

Purpose Diffuse large B cell (DLBCL)-like post-transplant lymphoproliferative disorder (PTLD) affects up to 10% of thoracic transplant recipients. Although 50% of PTLDs can be related to Epstein-Barr virus (EBV) infection, and high or increasing EBV viral load may precede EBV+ PTLD, preemptive monitoring of EBV titers does not reliably predict PTLD . Consequently, we assessed the utility of circulating tumor DNA (ctDNA), a promising biomarker for many cancers including DLBCL , for early detection of PTLD. Methods We used Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) to analyze diagnostic tumor and plasma samples and matched germline DNA in a cohort of 10 heart and lung transplant recipients who developed PTLD to identify somatic alterations. We compared mutational patterns in PTLD to 173 de novo DLBCL cases. We additionally sequenced serial post-transplant plasma samples preceding diagnosis in 5 patients (2 EBV-, 3 EBV+), and during or after treatment in 8 patients, to determine the dynamics of ctDNA and compared these patterns to clinical outcomes and EBV titers. Results There was no significant difference in mutational burden between patients with PTLD and de novo DLBCL (median PTLD variants: 216, IQR = 79 - 321; median de novo DLBCL variants: 143.5, IQR = 45 - 243.8; p = 0.35), although there was a trend toward greater variant count in EBV- compared to EBV+ PTLD (p = 0.064). The prevalence of alterations in known driver genes was similar between PTLD and de novo DLBCL. Prediagnostic plasma samples were available for 5 cases, and we detected ctDNA in all patients prior to clinical diagnosis (mean lead time = 114 days, maximum lead time 1.5 years). Levels of ctDNA during and after treatment were concordant with EBV titers in EBV+ disease and with clinical response in all patients. Conclusion PTLD patients have detectable ctDNA prior to clinical diagnosis. Development of screening tools utilizing both ctDNA and EBV titers would facilitate early detection of PTLD in the transplant population.

Background Diffuse large B-cell lymphoma (DLBCL) is a genetically and clinically heterogeneous disease. The cell-of-origin (COO) classification subdivides DLBCL into the transcriptionally defined activated B-cell (ABC) and germinal center B-cell (GCB) subtypes. Recently, 2 novel classifiers based on genetic features were independently proposed further unraveling the diversity of DLBCL [Schmitz et al, NEJM2018; Chapuy et al, Nat Med2018]. The concordance between the 2 novel classification systems has not yet been systematically studied. However, both classifiers are largely complementary to COO subtypes, and describe overlapping genotypes. We previously demonstrated the feasibility of COO classification by noninvasive plasma genotyping in a limited gene panel using Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) [Scherer et al, STM2016], and this approach has now been replicated by others. In this study, we take first steps toward a comprehensive non-invasive classification of novel DLBCL genetic subtypes using a limited gene panel. Methods We analyzed genetic profiling of 476 DLBCL patients reported by Schmitz et al (NEJM 2018) as a training set to build 2 classifiers in a limited gene panel applicable to plasma genotyping from CAPP-Seq: (1) A COO classifier (i.e. ABC, GCB and Unclassified); (2) A comprehensive genetic classifier (i.e. EZB, BN2, MCD, N1 and Other as defined in Schmitz et al, NEJM 2018). Features were limited to genetic alterations captured by our plasma genotyping panel, and those with population frequency of at least 10% in at least one genetic subtype. Our final model comprised 100 features: 64 recurrently mutated genes, 26 amplifications, 7 deletions and 3 translocations (BCL2, BCL6 and MYC). After cross-validation in the training set, we applied the 2 classifiers to the dataset from Chapuy et al (Nat Med 2018) as well as pretreatment plasma genotyping data from patients previously reported by our group [Kurtz et al, JCO 2018]. Results We first evaluated our 2 classifiers in a 10-fold cross-validation (CV) framework in the NEJM 2018 dataset of Schmitz et al. Despite modest performance of our GCB/ABC classification, COO labels had the expected significant prognostic associations (Fig. 1A). Overall accuracy of our second classifier to determine novel genetic subtypes was 82% (Fig. 1B). Consistent with the original study, inferred MCD and N1 subtypes had adverse prognosis compared to EZB and BN2 (Fig. 1C). We next applied our classifiers to the Chapuy et al (Nat Med 2018) dataset. Again, consistent with findings by Schmitz et al (NEJM 2018), the EZB subset of GCB cases had inferior outcome compared to non-EZB cases (Fig. 1D). We next examined the cross-correlation between the two classifiers and observed the expected enrichment patterns of ABCs in the MCD subset and enrichment of GCBs in the EZB subset (Fig. 1E). Finally, we applied our classifiers to plasma genotyping data previously reported by our group [Kurtz et al., JCO 2018]. We restricted the analysis to cases with a mean variant allele fraction ≥0.5% (n=68). Similar to the original study, 59% of cases (40/68) were labeled unclassifiable (i.e. Other). We compared the distribution of COO subtypes within the Schmitz genetic clusters. Representation of ABC and GCB within the clusters inferred from Plasma genotyping (Fig. 1F) was similar to the distribution from Tumor genotyping (Fig. 1E). Conclusions We describe 2 new classifiers applicable to noninvasive plasma genotyping data that recapitulate transcriptionally and genetically defined DLBCL subtypes. Using independent datasets, we show the feasibility of classification with a limited feature set with good prediction accuracy and prognostic stratification of defined subtypes. Genotyping of pretreatment plasma samples suggest that comprehensive non-invasive classification of genetic subtypes of DLBCL is achievable. Disclosures Kurtz: Roche: Consultancy. Diehn:BioNTech: Consultancy; Quanticell: Consultancy; Roche: Consultancy; AstraZeneca: Consultancy; Novartis: Consultancy. Alizadeh:Roche: Consultancy; Genentech: Consultancy; Janssen: Consultancy; Pharmacyclics: Consultancy; Gilead: Consultancy; Celgene: Consultancy; Chugai: Consultancy; Pfizer: Research Funding.

Background: Anti-CD19 chimeric antigen receptor (CAR19) T-cells have significant activity in patients with relapsed/refractory DLBCL (rrDLBCL). While the majority of rrDLBCL patients receiving axicabtagene ciloleucel (Axi-cel)achieve complete responses, a significant subset of patients experience disease progression (Locke FL, et al. Lancet Oncol. 2019). Circulating tumor DNA (ctDNA) analysis has demonstrated utility for predicting therapeutic benefit in DLBCL, as well as for detecting emergent resistance mechanisms to targeted therapies. Here we apply cell-free DNA (cfDNA) analysis to patients receiving Axi-cel, to characterize molecular responses, resistance mechanisms, and to track CAR19 cells. Methods: We performed Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) on DNA from germline and plasma samples collected prior to CAR T-cell infusion, multiple time-points post infusion, and, where available, at the time of relapse from 30 patients receiving Axi-cel for rrDLBCL at Stanford University. We designed a novel hybrid-capture panel and analysis pipeline designed to detect both tumor variants, as well as Axi-cel specific recombinant retroviral sequences to quantify CAR19 levels in cfDNA. Tumor variants were identified prior to and following Axi-cel therapy to assess for emergent variants, and Axi-cel specific sequences were quantified. Results: The median follow-up for the 30 patients after Axi-cel infusion was 10 months, with 47% (14/30) of patients experiencing disease progression after Axi-cel therapy. We identified an average of 164.3 SNVs per case (range:1-685) before Axi-cel therapy; the most common coding variants identified at baseline were in MLL2 (29.2%), BCL2 (22.5%), and TP53 (19.3%). When treated as a continuous variable, pretreatment ctDNA levels were prognostic of PFS (HR 2.16, 95% CI 1.11-4.21, P=0.02). Using a previously established ctDNA threshold to stratify disease burden (2.5 log10(hGE/mL); Kurtz et al. JCO 2018), we observed significantly superior PFS in patients with low pretreatment ctDNA levels treated with Axi-cel (Fig. 1A). In the majority of Axi-cel treated patients (62.9%), ctDNA was detectable at day 28, and PFS was significantly longer in patients with undetectable ctDNA at this time-point (Fig. 1B). Multiple putative resistance mechanisms were identified at relapse after Axi-cel, including emergent variants in CD19, HVEM, and TP53, as well as copy number gains in PD-L1 (Fig. 1C). For example, in one patient, a CD19 stop-gain mutation, which was not detected prior to treatment or at the time of the first interim PET scan, emerged at the time of relapse (Fig. 1D). Finally, we found cfDNA evidence for Axi-cel DNA in 74% of patients 28 days after therapy, including in patients without evidence of circulating CAR T-cells in PBMCs. Axi-cel levels in cfDNA as measured by CAPP-Seq were significantly correlated with CAR19 flow cytometry (Pearson r=0.55, P=.015; Fig. 1E). Conclusions: Baseline and interim ctDNA measurements have prognostic significance in DLBCL patients being treated with CAR19 T-cells, and potential emergent resistance mutations, including in CD19, can be identified in patients via cfDNA analysis. Quantification of CAR19 T-cells using cfDNA is significantly correlated with flow cytometric quantification, indicating that these cells can be quantified via cfDNA. Taken together, these data indicate that cfDNA analysis is a powerful tool for predicting response to CAR19 therapy, identifying genomic determinants of resistance and quantifying CAR19 cells, which may in turn inform the next therapeutic steps. Figure 1: A) Kaplan Meier analysis of PFS, with patients stratified based on pre-Axi-cel therapy ctDNA level, above and below a previously established threshold (2.5 log10[haploid Genome Equivalents/mL]). B) A Kaplan Meier plot depicting PFS stratification for patients with detectable versus undetectable ctDNA at day 28 after Axi-cel infusion. C) Oncoprint depicting selected emergent and baseline tumor variants in progressors and non-progressors after Axi-cel therapy. D) Change in mean ctDNA variant allele frequency (VAF) and emergence of a CD19 stop-gain mutation (CD19 pTrpX) at the time of relapse in a patient who initially achieved a CR at day 28 after CAR19 infusion. E) Relationship between CAR19 T-cell quantification by cfDNA and flow cytometry. (ND: Not detected) Disclosures Kurtz: Roche: Consultancy. Chabon:Lexent Bio Inc: Consultancy. Khodadoust:Corvus Pharmaceuticals: Research Funding. Majzner:Xyphos Inc.: Consultancy; Lyell Immunopharma: Consultancy. Mackall:Obsidian: Research Funding; Lyell: Consultancy, Equity Ownership, Other: Founder, Research Funding; Nektar: Other: Scientific Advisory Board; PACT: Other: Scientific Advisory Board; Bryologyx: Other: Scientific Advisory Board; Vor: Other: Scientific Advisory Board; Roche: Other: Scientific Advisory Board; Adaptimmune LLC: Other: Scientific Advisory Board; Glaxo-Smith-Kline: Other: Scientific Advisory Board; Allogene: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Apricity Health: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Unum Therapeutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Diehn:Roche: Consultancy; Quanticell: Consultancy; Novartis: Consultancy; AstraZeneca: Consultancy; BioNTech: Consultancy. Miklos:Miltenyi Biotech: Membership on an entity's Board of Directors or advisory committees; Becton Dickinson: Research Funding; AlloGene: Membership on an entity's Board of Directors or advisory committees; Kite-Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Juno: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Precision Bioscience: Membership on an entity's Board of Directors or advisory committees. Alizadeh:Genentech: Consultancy; Janssen: Consultancy; Pharmacyclics: Consultancy; Gilead: Consultancy; Celgene: Consultancy; Chugai: Consultancy; Roche: Consultancy; Pfizer: Research Funding.

Background: Immunocompromised patients have higher risk for virally-driven lymphomas associated with pathogens including Epstein-Barr Virus (EBV), Kaposi Sarcoma Herpesvirus (KSHV), HTLV-1, and HIV-1. Within this high-risk patient population, early cancer detection remains a critically unmet clinical need. Recently, analysis of viral cell-free DNA (cfDNA) has shown promise as a predictive biomarker for both immune status and cancer risk. In solid organ transplant recipients, immunosuppression is associated with expansion of a circulating family of viruses called Anelloviridae (De Vlaminck I, Cell, 2013). In screening for EBV-driven nasopharyngeal carcinomas (NPC), EBV cfDNA fragment length distributions distinguish normal adults with transient viremia from those with high risk of NPC (Lam WK, PNAS, 2018). We developed VirCAPP-Seq (Viral Cancer Personalized Profiling by Deep Sequencing) as a clinical virome capture approach for enriching and deeply sequencing circulating viral nucleic acids to elucidate virome composition, fragment length distribution, host genome integration sites, and viral polymorphisms. These features of viral cfDNA may clarify patient risk for malignancy and immunosuppression. Method: 180 viral species from 15 families were selected on the basis of 3 criteria: (1) Known oncoviruses (eg, EBV, Human Papillomavirus (HPV), Hepatitis B Virus (HBV)); (2) Commensal viruses associated with immune state (eg, Anelloviridae); (3) Common clinically relevant viruses (Adenovirus, CMV, BK, etc.). Viral reference genomes were segmented into continuous sliding 50mer windows, and compared to hg19 and a pan-viral reference database for homology using BLASTN. Non-unique regions were excluded. Remaining regions were clustered using CD-HIT at 85% homology to minimize redundant probes (figure 1A). We applied VirCAPP-Seq to plasma samples of patients with known levels of EBV viremia. To evaluate possible interactions of VirCAPP-Seq with human probes, we applied the viral panel alone and in combination with a CAPP-Seq lymphoma panel (Kurtz DM, JCO, 2018). Reads were aligned to a composite reference genome consisting of 180 viral reference genomes and hg19. For each targeted virus, plasma (GE) were estimated by computing the ratio of unique viral depth to human depth, and multiplying by the measured plasma DNA concentration and plasma volume. We correlated the sequencing-based GE estimate to viral titers determined by a clinical RT-PCR assay measured in a CLIA laboratory. Viral integration sites were evaluated with Virus-Clip (Ho DW, Oncotarget, 2015). Results: The final VirCAPP-Seq design consists of 2349 target regions across 180 species, spanning 2.097 Mb. A median of 95.9% of each targeted virus was covered by the panel (IQR 85.1% - 99.0%). Sequence-based phylogenetic analysis demonstrated clear relationships between members of each viral family. However, following in silico masking of non-unique regions, these phylogenetic relationships were no longer discernible, demonstrating that our design avoids targeting regions with interspecies ambiguity (figure 1B). Surprisingly, addition of VirCAPP-Seq to a human capture panel did not significantly impact the human on-target rate compared to human-only capture of lymphoma CAPP-Seq targets (Kurtz et al 2018 JCO), suggesting minimal non-specific interaction between viral probes and host DNA (figure 1C). Across EBV-positive samples, VirCAPP-Seq enriched EBV cfDNA a median of 214,000x compared to off-target EBV abundance in human-only capture (IQR 55,100x - 277,600x) (figure 1D). EBV-positive samples achieved a median EBV depth of 1015x (IQR 210x - 2802x) after enrichment. Additionally, viral GE estimates from read counts were highly correlated with viral titer estimates by clinical RT-PCR (r = 0.92, p < 0.001, n=9) (figure 1E). We observed several significant correlations between virome measurements across a range of immunosuppression states and lymphoma subtypes, with details to be presented at the meeting. Conclusions: VirCAPP-Seq enables simultaneous enrichment of clinically relevant viral and host cfDNA from plasma over several orders of magnitude. This framework holds promise for monitoring diverse features of viral cfDNA that capture risks for malignancy and immunosuppression, facilitating personalized diagnostic and therapeutic interventions. Disclosures Kurtz: Roche: Consultancy. Advani:Janssen: Research Funding; Kura: Research Funding; Merck: Research Funding; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cell Medica, Ltd: Consultancy; Kyowa Kirin Pharmaceutical Developments, Inc.: Consultancy; Forty-Seven: Research Funding; Agensys: Research Funding; Bayer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Consultancy, Research Funding; AstraZeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Celmed: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead Sciences, Inc./Kite Pharma, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity Pharma: Research Funding; Millennium: Research Funding; Regeneron: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Stanford University: Employment, Equity Ownership; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees. Diehn:AstraZeneca: Consultancy; BioNTech: Consultancy; Quanticell: Consultancy; Novartis: Consultancy; Roche: Consultancy.

African-American men have the highest incidence and mortality from prostate cancer. Whether a biological basis exists for this disparity remains unclear. Exome sequencing (n=102) and targeted validation (n = 90) of localized primary hormone-naïve prostate cancer in African-American men identified several gene mutations not previously observed in this context, including recurrent loss-of-function mutations in ERF, an ETS transcriptional repressor, in 5% of cases. Analysis of existing prostate cancer cohorts revealed ERF deletions in 3% of primary prostate cancers and mutations or deletions in ERF in 3–5% of lethal castration-resistant prostate cancers. Knockdown of ERF confers increased anchorage-independent growth and generates a gene expression signature associated with oncogenic ETS activation and androgen signaling. Together, these results suggest that ERF is a prostate cancer tumor suppressor gene. More generally, our findings support the application of systematic cancer genomic characterization in settings of broader ancestral diversity to enhance discovery and, eventually, therapeutic applications.

Background : Infectious disease plays a central role in malignancy, with up to one in six cancers having a microbial association (Parkin Int. J. Cancer 2006). Lymphomas in particular are associated with multiple viral pathogens, including Epstein Barr virus (EBV), Kaposi Sarcoma herpesvirus (KSHV), and HIV. Sequencing of cell-free DNA (cfDNA) is an emerging technique in the diagnosis and surveillance of cancer. While studies to date have focused primarily on tumor-associated somatic variants, cfDNA may also provide insight into the infectious and immune state of cancer patients. We examined cfDNA from lymphoma patients of multiple histologic subtypes to characterize viral detection and dynamics. Methods: Plasma from 360 pre-treatment patients with various lymphoma histologies was analyzed along with that of 69 healthy adults. Multiple samples per patient were included when available. All samples underwent deep sequencing with error correction by CAPP-Seq (Newman Nat Biotech 2016). Reads were filtered for homology to the human genome and endogenous retroviruses, mapped to NCBI consensus genomes for human-hosted viral species, and filtered by breadth of genomic coverage. Viral read count was normalized by total sequencing depth to determine viral read fraction (VRF). EBV fragment size was assessed via single-read BLAST alignment length considering reads with expect value < 1E-5. Integration sites were assessed with the VirusClip package (Ho Oncotarget 2015). Results: Patients with most lymphoma histologic subtypes had viral loads not significantly different from those of healthy adults. However, post-transplant lymphoproliferative disorder (PTLD) patients receiving immunosuppression for solid organ transplants had significantly increased total viremia (Fig 1A) and EBV levels (Fig 1B) when compared to healthy adults and non-transplant DLBCL patients. EBER+ classical Hodgkin lymphoma (cHL) displayed no difference in total viremia but had significantly elevated EBV. In an EBV-positive PTLD patient, cfDNA viral levels tracked both clinical viral qPCR and circulating tumor DNA (ctDNA) levels in serial samples leading to diagnosis (Fig 1C). Elevated EBV levels were also present in a subset of non-transplant DLBCL. In a cohort of DLBCL patients treated with frontline R-CHOP-like chemotherapy (n=152), individuals with pre-treatment EBV frequency greater than VRF 1E-7 had significantly higher risk of disease progression at three years (HR 1.8, CI 1.0-3.4, p=0.013) (Fig 1D). Immunosuppression in transplant patients is associated with the expansion of the endogenous anellovirus family (De Vlaminck Cell 2013). Accordingly, anellovirus was detected significantly more often in PTLD patients (91% of samples) compared to DLBCL NOS (2.8%) and controls (1.4%) (Fig 1E, p < 0.0001). As the standard-of-care R-CHOP regimen for DLBCL has activity against both B- and T- lymphocytes, we hypothesized that an immunosuppressive effect might be observed. In non-transplant DLBCL patients receiving R-CHOP (n=31), we detected anellovirus in 6% of samples at the time of first chemotherapy infusion, 16% immediately before cycle 2, but in no samples from post-treatment patients in complete response (Fig 1F). Viral integration into the host genome is associated with malignant transformation. We profiled a cohort of EBER+ cHL (n=8) and found circulating EBV/human chimeric reads suggesting integration in all cases. Viral fragment size distribution also distinguishes integrated DNA from shorter free episomes and may increase cancer screening performance (Lam PNAS 2018). We profiled EBV fragment sizes in cHL and PTLD patients grouped by EBER positivity. Plasma from EBER+ cHL and PTLD patients was significantly enriched in longer fragments (Fig 1G), suggesting nucleosomal protection of EBV integrated within tumor genomes but not their benign episomal counterparts. Conclusions: Viral infection in lymphoma has diagnostic and prognostic significance: elevated circulating EBV levels are associated with active PTLD (Kanakry Blood 2016) and poor outcomes in advanced HL (Kanakry Blood 2013) and DLBCL (Tisi Leuk & Lymph 2015). Our work demonstrates the utility of cfDNA sequencing for simultaneous characterization of malignancy, infection, and immunosuppression. The integration of viral dynamics into cfDNA analysis may assist in risk stratification and treatment monitoring in lymphoma patients. Disclosures Dührsen: Amgen: Research Funding; Celgene: Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Roche: Honoraria, Research Funding; Gilead: Consultancy, Honoraria; Janssen: Honoraria. Hüttmann:Celgene: Other: Travel expenses; Roche: Other: Travel expenses. Meignan:F. Hoffman-La Roche Ltd: Honoraria. Casasnovas:Janssen: Consultancy; Takeda: Honoraria; Janssen: Honoraria; MSD: Honoraria; Merck: Honoraria; Gilead Sciences: Honoraria; Celgene: Honoraria; Roche: Consultancy; Roche: Research Funding; takeda: Consultancy; Gilead Sciences: Consultancy; Roche: Honoraria; Gilead Sciences: Research Funding; merck: Consultancy; MSD: Consultancy. Westin:Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Apotex: Membership on an entity's Board of Directors or advisory committees; Novartis Pharmaceuticals Corporation: Membership on an entity's Board of Directors or advisory committees; Celgen: Membership on an entity's Board of Directors or advisory committees. Gaidano:Amgen: Consultancy, Honoraria; Morphosys: Honoraria; Janssen: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Roche: Consultancy, Honoraria. Advani:Bayer: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Agensys: Research Funding; Infinity: Research Funding; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Merck: Research Funding; Janssen: Research Funding; Cell Medica: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Kyowa: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Millenium: Research Funding; Celgene: Research Funding; Kura: Research Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Regeneron: Research Funding; Autolus: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Gilead/Kite: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Forty Seven Inc.: Research Funding; Celgene: Research Funding.

Introduction. Minimal residual disease (MRD) is the most powerful prognostic factor in acute lymphoblastic leukemia (ALL). Currently, real-time quantitative PCR (RQ-PCR) is the most widely used molecular method for MRD assessment, rigorously standardized within the EuroMRD consortium. According to the EuroMRD guidelines (Van der Velden et al. Leukemia 2007), a non-negligible fraction of patients with very low MRD levels are classified as positive not-quantifiable (PNQ), a definition that may result problematic in the clinical practice. Digital-droplet-PCR (ddPCR) allows an absolute quantification without the need of a standard curve and has the potential to overcome some limitations of RQ-PCR. High degrees of efficiency, sensitivity and accuracy have been reported for ddPCR compared to RQ-PCR, but no established guidelines for ddPCR MRD analysis and interpretation have so far been defined and its ability to correctly evaluate very low MRD levels is still under investigation. In the present study, we assessed MRD by ddPCR in pediatric ALL cases classified as PNQ and/or negative by RQ-PCR at days +33 and/or +78 of the AIEOP-BFM ALL 2000 trial, to evaluate the potential of ddPCR for low MRD quantification and patients' risk stratification. Patients and Methods. A total of 211 pediatric ALL patients enrolled in the AIEOP-BFM ALL 2000 trial were included in the study. We analyzed 124 B-lineage ALL patients defined as intermediate risk (IR) who had high positive MRD at day +33 and at day +78 were either PNQ (n=45, Slow Early Responders (SER)) or negative (n=79). A case-control design was applied to 36 B- and T-lineage relapsed ALL patients (cases) who at day +33 had PNQ MRD (n=12, IR) or were negative (n=24, standard risk (SR)) and to matched controls (21 and 30 patients who did not present a relapse). ddPCR analysis was performed as previously published (Della Starza et al, BJH 174, 541-9, 2016), by using 1.5 μg and 3.0 μg DNA of the follow-up samples. In the absence of an international consensus, data have been analyzed using two alternative guidelines; results are reported according to Della Starza et al (BJH 2016). Results. Among 45 SER patients, ddPCR performed on 1.5 μg DNA of PNQ samples at day +78 revealed that 13 were quantifiable (Q), 16 PNQ and 16 negative (NEG) . When 3.0 μg of DNA were used (41/45 samples due to material availability), 12 were Q, 19 PNQ and 10 NEG. Event-free survival (EFS) curves are shown in Fig. 1a. Among the 79 patients with high positive MRD at day +33 but who were negative at day +78, ddPCR on 1.5 μg DNA of day +78 identified 5 as Q, 17 PNQ and 57 NEG. When 3.0 μg DNA was used (77/79 samples), 9 patients were Q, 27 PNQ and 41 NEG. EFS curves are reported in Fig. 1b. When ddPCR was applied to 33 PNQ samples at day +33, 2 were Q, 9 PNQ and 22 NEG; when using 3.0 μg of DNA, 1 was Q, 15 were PNQ and 17 NEG. EFS curves are shown in Fig. 1c. Lastly, ddPCR on 1.5 μg of day +33 DNA of 54 SR patients showed 5 PNQ and 49 NEG, whilst by using 3.0 μg on 53 sample, 7 were PNQ and 46 NEG. Conclusions. Our data demonstrate that ddPCR is a very promising tool for the evaluation of MRD in ALL cases with very low or negative RQ-PCR MRD results. In particular, among SER patients most relapses occurred in cases with quantifiable ddPCR MRD at day +78, while patients with negative or PNQ MRD by ddPCR at day +78 had a better outcome. Based on these results, high-risk treatment could be offered only to ddPCR quantifiable cases. Among patients with highly positive MRD at day +33 and negative at day +78, the small number of cases with quantifiable disease by ddPCR at present does not allow to establish the impact of quantification; consistently with SER patients, the outcome was similar for patients with negative or PNQ MRD by ddPCR at day +78. Similarly, among patients with PNQ MRD by RQ-PCR at day +33, a similar outcome was observed for cases negative or PNQ by ddPCR. Lastly, in most SR patients ddPCR confirmed the negative results of RQ-PCR at day +33, associated with an extremely good kinetics of disease reduction, independently of the MRD PCR method. Overall, our data indicate that ddPCR is as sensitive as RQ-PCR and can provide a potentially more accurate prognostic stratification for cases defined as PNQ MRD by RQ-PCR, in view of its ability to quantify without a standard curve. The application of ddPCR in a prospective clinical protocol with international guidelines is needed to define whether it can result in an overall improvement of pediatric ALL patients' stratification and outcome. Disclosures Foà: AMGEN: Other: ADVISORY BOARD; JANSSEN: Other: ADVISORY BOARD, Speakers Bureau; CELTRION: Other: ADVISORY BOARD; INCYTE: Other: ADVISORY BOARD; ABBVIE: Other: ADVISORY BOARD, Speakers Bureau; ROCHE: Other: ADVISORY BOARD, Speakers Bureau; NOVARTIS: Speakers Bureau; CELGENE: Other: ADVISORY BOARD, Speakers Bureau; GILEAD: Speakers Bureau.

7572Background: Diffuse large B cell (DLBCL)-like post-transplant lymphoproliferative disorder (PTLD) affects 2-5% of transplant recipients. Although 50% of PTLDs can be related to Epstein-Barr vir...

e18051Background: Transplant recipients experience a 2 to 10-fold increased risk of head and neck cancers (HNC) compared to the general population, with about 10-15% of transplant recipients develo...

Background The diversity of clinical tumor profiling approaches (small panels to whole exomes with matched or unmatched germline analysis) may engender uncertainty about their benefits and liabilities, particularly in light of reported germline false positives in tumor-only profiling and use of global mutational and/or neoantigen data. The goal of this study was to determine the impact of genomic analysis strategies on error rates and data interpretation across contexts and ancestries. Methods We modeled common tumor profiling modalities—large (n = 300 genes), medium (n = 48 genes), and small (n = 15 genes) panels—using clinical whole exomes (WES) from 157 patients with lung or colon adenocarcinoma. We created a tumor-only analysis algorithm to assess germline false positive rates, the impact of patient ancestry on tumor-only results, and neoantigen detection. Results After optimizing a germline filtering strategy, the germline false positive rate with tumor-only large panel sequencing was 14 % (144/1012 variants). For patients whose tumor-only results underwent molecular pathologist review (n = 91), 50/54 (93 %) false positives were correctly interpreted as uncertain variants. Increased germline false positives were observed in tumor-only sequencing of non-European compared with European ancestry patients (p

Inherited mutations in DNA-repair genes such as BRCA2 are associated with increased risks of lethal prostate cancer. Although the prevalence of germline mutations in DNA-repair genes among men with localized prostate cancer who are unselected for family predisposition is insufficient to warrant routine testing, the frequency of such mutations in patients with metastatic prostate cancer has not been established.We recruited 692 men with documented metastatic prostate cancer who were unselected for family history of cancer or age at diagnosis. We isolated germline DNA and used multiplex sequencing assays to assess mutations in 20 DNA-repair genes associated with autosomal dominant cancer-predisposition syndromes.A total of 84 germline DNA-repair gene mutations that were presumed to be deleterious were identified in 82 men (11.8%); mutations were found in 16 genes, including BRCA2 (37 men [5.3%]), ATM (11 [1.6%]), CHEK2 (10 [1.9% of 534 men with data]), BRCA1 (6 [0.9%]), RAD51D (3 [0.4%]), and PALB2 (3 [0.4%]). Mutation frequencies did not differ according to whether a family history of prostate cancer was present or according to age at diagnosis. Overall, the frequency of germline mutations in DNA-repair genes among men with metastatic prostate cancer significantly exceeded the prevalence of 4.6% among 499 men with localized prostate cancer (P0.001), including men with high-risk disease, and the prevalence of 2.7% in the Exome Aggregation Consortium, which includes 53,105 persons without a known cancer diagnosis (P0.001).In our multicenter study, the incidence of germline mutations in genes mediating DNA-repair processes among men with metastatic prostate cancer was 11.8%, which was significantly higher than the incidence among men with localized prostate cancer. The frequencies of germline mutations in DNA-repair genes among men with metastatic disease did not differ significantly according to age at diagnosis or family history of prostate cancer. (Funded by Stand Up To Cancer and others.).

The apical damage kinase, ATR, is activated by replication stress (RS) both in response to DNA damage and during normal S-phase. Loss of function studies indicates that ATR acts to stabilize replication forks, block cell cycle progression and promote replication restart. Although checkpoint failure and replication fork collapse can result in cell death, no direct cytotoxic pathway downstream of ATR has previously been described. Here, we show that ATR directly reduces survival by inducing phosphorylation of the p50 (NF-κB1, p105) subunit of NF-кB and moreover, that this response is necessary for genome maintenance independent of checkpoint activity. Cell free and in vivo studies demonstrate that RS induces phosphorylation of p50 in an ATR-dependent but DNA damage-independent manner that acts to modulate NF-кB activity without affecting p50/p65 nuclear translocation. This response, evident in human and murine cells, occurs not only in response to exogenous RS but also during the unperturbed S-phase. Functionally, the p50 response results in inhibition of anti-apoptotic gene expression that acts to sensitize cells to DNA strand breaks independent of damage repair. Ultimately, loss of this pathway causes genomic instability due to the accumulation of chromosomal breaks. Together, the data indicate that during S-phase ATR acts via p50 to ensure that cells with elevated levels of replication-associated DNA damage are eliminated.

11565Background: Implementing cancer precision medicine requires interpretation of each potentially clinically relevant and biologically meaningful genomic alteration to aid clinical decision-makin...

5009Background: Inherited mutations in genes that regulate DNA repair processes such as BRCA1 and BRCA2 associate with increased risks of developing lethal prostate cancer (PC), and with response t...

1500Background: The expanding appeal of clinical tumor profiling has led to many sequencing strategies, ranging from small gene panels to exomes, with or without patient-matched germline data. This diversity of approaches may engender uncertainty about their benefits and liabilities, particularly in light of reported germline false positives in tumor-only profiling, and emerging immunotherapies that leverage genome-wide data. Methods: We modeled common tumor profiling modalities - large (n = 300 genes) and small (n= 15 or 48 genes) panels - onto clinical whole exomes (WES) from 157 patients with lung or colon adenocarcinoma. We created a tumor-only analysis algorithm to assess germline false positives (variants erroneously called as somatic), impact of patient ethnicity on results, and neoantigen detection. Results: The germline false positive rate with tumor-only large panel sequencing was 14% (144/1012 variants). For patients whose results underwent molecular pathologist review, 50/54 (93%) false positi...