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Follicular lymphomas (FL) are characterized by BCL2 translocations, often detectable in blood years before FL diagnosis, but also observed in aging healthy individuals, suggesting additional lesions are required for lymphomagenesis. We directly characterized early cooperating mutations by ultradeep sequencing of prediagnostic blood and tissue specimens from 48 subjects who ultimately developed FL. Strikingly, CREBBP lysine acetyltransferase (KAT) domain mutations were the most commonly observed precursor lesions, and largely distinguished patients developing FL (14/48, 29%) from healthy adults with or without detected BCL2 rearrangements (0/13, P = 0.03 and 0/20, P = 0.007, respectively). CREBBP variants were detectable a median of 5.8 years before FL diagnosis, were clonally selected in FL tumors, and appeared restricted to the committed B-cell lineage. These results suggest that mutations affecting the CREBBP KAT domain are common lesions in FL cancer precursor cells (CPC), with the potential for discriminating subjects at risk of developing FL or monitoring residual disease.Significance:Our study provides direct evidence for recurrent genetic aberrations preceding FL diagnosis, revealing the combination of BCL2 translocation with CREBBP KAT domain mutations as characteristic committed lesions of FL CPCs. Such prediagnostic mutations are detectable years before clinical diagnosis and may help discriminate individuals at risk for lymphoma development.

Supplementary Methods and Figures S1-S5

Background: This study investigated whether receiving the results of predictive genetic testing for Lynch syndrome, indicating the presence or absence of an inherited predisposition to various cancers, including colorectal cancer, was associated with change in individual colonoscopy and smoking behaviors, which could prevent colorectal cancer.Methods: The study population included individuals with no previous diagnosis of colorectal cancer, whose families had already identified deleterious mutations in the mismatch repair or EPCAM genes. Hypotheses were generated from a simple health economics model and tested against individual-level panel data from the Australasian Colorectal Cancer Family Registry.Results: The empirical analysis revealed evidence consistent with some of the hypotheses, with a higher likelihood of undergoing colonoscopy in those who discovered their genetic predisposition to colorectal cancer and a lower likelihood of quitting smoking in those who discovered their lack thereof.Conclusions: Predictive genetic information about Lynch syndrome was associated with change in individual colonoscopy and smoking behaviors but not necessarily in ways to improve population health.Impact: The study findings suggest that the impact of personalized medicine on disease prevention is intricate, warranting further analyses to determine the net benefits and costs. Cancer Epidemiol Biomarkers Prev; 25(11); 1524–33. ©2016 AACR.

Table S1. Study participants' smoking status. Table S2. Estimation results of the logit regression models only on the study participants who underwent colonoscopy before baseline. Table S3. Estimation results of the logit regression model only on the study participants who smoked before baseline. Table S4. Estimation results: subgroup analyses only on the study participants with no previous cancer diagnosis at follow-up

Circulating tumor DNA (ctDNA) is an emerging biomarker for many cancers, but the limited sensitivity of current detection methods reduces its utility for diagnosing minimal residual disease. Here we describe phased variant enrichment and detection sequencing (PhasED-Seq), a method that uses multiple somatic mutations in individual DNA fragments to improve the sensitivity of ctDNA detection. Leveraging whole-genome sequences from 2,538 tumors, we identify phased variants and their associations with mutational signatures. We show that even without molecular barcodes, the limits of detection of PhasED-Seq outperform prior methods, including duplex barcoding, allowing ctDNA detection in the parts-per-million range in patient samples. We profiled 678 specimens from 213 patients with B-cell lymphomas, including serial cell-free DNA samples before and during therapy for diffuse large B-cell lymphoma. In patients with undetectable ctDNA by CAPP-Seq after two cycles of therapy, an additional 25% have ctDNA detectable by PhasED-Seq and have worse outcomes. Finally, we demonstrate the application of PhasED-Seq to solid tumors., Editorial summary The sensitivity of circulating tumor DNA detection is improved by identifying sequences with two or more mutations.

Profiling of circulating tumor DNA (ctDNA) in the bloodstream shows promise for noninvasive cancer detection. Chromatin fragmentation features have previously been explored to infer gene expression profiles from cell-free DNA (cfDNA), but current fragmentomic methods require high concentrations of tumor-derived DNA and provide limited resolution. Here we describe promoter fragmentation entropy as an epigenomic cfDNA feature that predicts RNA expression levels at individual genes. We developed 'epigenetic expression inference from cell-free DNA-sequencing' (EPIC-seq), a method that uses targeted sequencing of promoters of genes of interest. Profiling 329 blood samples from 201 patients with cancer and 87 healthy adults, we demonstrate classification of subtypes of lung carcinoma and diffuse large B cell lymphoma. Applying EPIC-seq to serial blood samples from patients treated with PD-(L)1 immune-checkpoint inhibitors, we show that gene expression profiles inferred by EPIC-seq are correlated with clinical response. Our results indicate that EPIC-seq could enable noninvasive, high-throughput tissue-of-origin characterization with diagnostic, prognostic and therapeutic potential.

BACKGROUND: New ultrasensitive methods for detecting residual disease after surgery are needed in human papillomavirus–associated oropharyngeal squamous cell carcinoma (HPV+OPSCC). METHODS: To determine whether the clearance kinetics of circulating tumor human papillomavirus DNA (ctHPVDNA) is associated with postoperative disease status, a prospective observational study was conducted in 33 patients with HPV+OPSCC undergoing surgery. Blood was collected before surgery, postoperative days 1 (POD 1), 7, and 30 and with follow-up. A subcohort of 12 patients underwent frequent blood collections in the first 24 hours after surgery to define early clearance kinetics. Plasma was run on custom droplet digital polymerase chain reaction (ddPCR) assays for HPV genotypes 16, 18, 33, 35, and 45. RESULTS: In patients without pathologic risk factors for recurrence who were observed after surgery, ctHPVDNA rapidly decreased to 350 copies/mL) and remained elevated until adjuvant treatment (n = 3/3). Patients with intermediate POD 1 ctHPVDNA levels (1.2–58.4 copies/mL) all possessed pathologic risk factors for microscopic residual disease (n = 9/9). POD 1 ctHPVDNA levels were higher in patients with known adverse pathologic risk factors such as extranodal extension >1 mm (P = .0481) and with increasing lymph nodes involved (P = .0453) and were further associated with adjuvant treatment received (P = .0076). One of 33 patients had a recurrence that was detected by ctHPVDNA 2 months earlier than clinical detection. CONCLUSIONS: POD 1 ctHPVDNA levels are associated with the risk of residual disease in patients with HPV+OPSCC undergoing curative intent surgery and thus could be used as a personalized biomarker for selecting adjuvant treatment in the future.

PURPOSE Patients with Diffuse Large B-cell Lymphoma (DLBCL) in need of immediate therapy are largely under-represented in clinical trials. The diagnosis-to-treatment interval (DTI) has recently been described as a metric to quantify such patient selection bias, with short DTI being associated with adverse risk factors and inferior outcomes. Here, we characterized the relationships between DTI, circulating tumor DNA (ctDNA), conventional risk factors, and clinical outcomes, with the goal of defining objective disease metrics contributing to selection bias. PATIENTS AND METHODS We evaluated pretreatment ctDNA levels in 267 patients with DLBCL treated across multiple centers in Europe and the United States using Cancer Personalized Profiling by Deep Sequencing. Pretreatment ctDNA levels were correlated with DTI, total metabolic tumor volumes (TMTVs), the International Prognostic Index (IPI), and outcome. RESULTS Short DTI was associated with advanced-stage disease ( P < .001) and higher IPI ( P < .001). We also found an inverse correlation between DTI and TMTV ( RS = −0.37; P < .001). Similarly, pretreatment ctDNA levels were significantly associated with stage, IPI, and TMTV (all P < .001), demonstrating that both DTI and ctDNA reflect disease burden. Notably, patients with shorter DTI had higher pretreatment ctDNA levels ( P < .001). Pretreatment ctDNA levels predicted short DTI independent of the IPI ( P < .001). Although each risk factor was significantly associated with event-free survival in univariable analysis, ctDNA level was prognostic of event-free survival independent of DTI and IPI in multivariable Cox regression (ctDNA: hazard ratio, 1.5; 95% CI [1.2 to 2.0]; IPI: 1.1 [0.9 to 1.3]; −DTI: 1.1 [1.0 to 1.2]). CONCLUSION Short DTI largely reflects baseline tumor burden, which can be objectively measured using pretreatment ctDNA levels. Pretreatment ctDNA levels therefore have utility for quantifying and guarding against selection biases in prospective DLBCL clinical trials.

7565 Background: Detection of circulating tumor DNA (ctDNA) has prognostic value in diverse tumors, including DLBCL. Despite uses for assessing molecular response to therapy, current methods using immunoglobulin or hybrid-capture sequencing have suboptimal sensitivity, particularly when disease-burden is low. This contributes to a high false negative rate at key milestones such as at the end of therapy (EOT; Kumar A, ASH 2020). We explored the utility of detecting multiple mutations (phased variants, PVs) on individual cell-free DNA (cfDNA) strands to improve MRD in DLBCL. Methods: We applied Phased Variant Enrichment and Detection Sequencing to track PVs from 485 specimens from 117 DLBCL patients undergoing first-line therapy. We sequenced cfDNA prior to, during, and after therapy to assess the prognostic value of MRD. We compared the performance of PhasED-Seq to current techniques, including SNV-based CAPP-Seq and duplex sequencing. Results: To establish its detection limit for ctDNA, we compared the background error-profile of of PVs and SNVs in cfDNA sequencing from healthy subjects. PV-detection by PhasED-Seq demonstrated a lower background profile than SNVs, even when considering duplex molecules (n = 12; 8.0e-7 vs 3.3e-5 and 1.2e-5; P < 0.0001). We also assessed analytical sensitivity within a ctDNA limiting dilution series from 3 patients, simulating tumor fractions from 0.1% to 0.00005% (1:2,000,000). PhasED-Seq outperformed SNV-based methods and duplex sequencing for recovery of expected tumor content below 0.01% (P < 0.0001 and P = 0.005 respectively by paired t-test). We then explored disease detection in clinical samples. We identified SNVs and PVs from pretreatment tumor or plasma and followed these variants in serial cfDNA. Using SNV-based methods, 40% and 59% of patients had undetectable ctDNA after 1 or 2 cycles (n = 82 and 88). However, 24% and 25% of these cases had detectable ctDNA by PhasED-Seq. Importantly, MRD detection by PhasED-Seq was prognostic for event-free survival even in patients with undetectable ctDNA by SNVs. We next explored the utility of PhasED-Seq at the EOT in 19 subjects, 5 of whom experienced eventual disease progression. While only 2/5 cases with progression had detectable disease at EOT using SNVs, PhasED-Seq detected all 5/5 cases. PhasED-Seq also correctly identified all patients (14/14) without clinical relapse as having no residual disease, including one patient who discontinued therapy after 1 cycle due to toxicity, but remains in remission > 5 years after this single treatment. This resulted in superior classification of patients for EFS using PVs compared with SNVs (C-statistic: 0.98 vs 0.60, P = 0.02). Conclusions: Tracking PVs results in significantly lower background rates than SNV-based approaches, enabling detection to parts per million range. PhasED-Seq improves on disease detection in DLBCL at the EOT, allowing possible MRD-driven consolidative approaches.

Korrespondenz zu 10.1200/JCO.2018.78.5246

Background: Mutations in chromatin modifying genes (CMGs) including KMT2D, CREBBP, EZH2, and EP300 have been inferred as early events in follicular lymphoma (FL) by truncal status in mature tumors and persistence between diagnosis and relapse. We previously reported frequent detection of CREBBP lysine acetyltransferase (KAT) domain mutations in pre-diagnostic blood and tissue specimens from individuals later developing FL (Schroers-Martin et al, ASH Annual Meeting 2017). However, the limited availability of paired tumor biopsies has precluded confirmation of concordance between precursor lesions and subsequent clinical malignancy. Methods: The American Cancer Society (ACS) Cancer Prevention Study-II (CPS-II) LifeLink cohort collected screening blood or saliva samples from over 100,000 cancer-free American participants between 1998 and 2002. To evaluate detection of tumor-confirmed variants in pre-diagnostic specimens, we identified 29 FL patients with available FFPE tumor biopsy and screening sample (Fig A). The median age at screening was 71 years (range 56-83) with a median time to FL diagnosis of 56 months (TTD, range 6-139). Tumor biopsies were sequenced utilizing hybrid capture sequencing for commonly mutated lymphoma genes. DNA extracted from pre-diagnostic blood or saliva cell pellet specimens was sequenced utilizing error-corrected CAPP-Seq (Newman et al Nat Biotech 2016) to a median depth of 5204x. We sequenced to similar depths peripheral blood DNA from control cohorts of individuals with detectable t(14;18) but no subsequent lymphoma diagnosis (n=14) and healthy individuals without detectable t(14;18) by PCR (n=20). Results: Coding mutations were identified from all tumors with a mutational distribution similar to prior FL sequencing studies. Tumor-derived variants were detected in 7 of 29 paired pre-diagnostic specimens (24%) at a median TTD of 44 months (range 11-112 months, Fig B). The statistical significance of detection was assessed using a previously described approach based on Monte Carlo sampling (Newman et al Nat Biotech 2016) and the error distribution of affected loci in control cohorts. While an outlier case contained concordant TNFRSF14, FOXO1, and STAT6 mutations 90 months pre-diagnosis at an elevated allelic fraction (AF) of 1.8%, the mean AF of other detected precursor variants was 0.091%. Individuals with detected variants were not older (Fig C) nor significantly closer to clinical diagnosis (Fig D). The most frequently detected lesions were CREBBP (6/15 cases, 40%) and BCL2 (3/13, 23%) with one case demonstrating a fuller mutational profile including FOXO1 and ARID1A at 44 months before diagnosis. All detected precursor CREBBP variants localized to the KAT domain, reflecting prior observations in pre-diagnostic samples without confirmatory biopsy (Fig E). Of note, saliva cell pellets may contain 30% or more hematopoietic DNA (Kaur et al Chimerism 2012) and we detected tumor-confirmed variants in both saliva and blood screening specimens (Fig F) with no significant difference in AF (Fig G). In an illustrative independent case with available imaging, a patient undergoing radical prostatectomy was found to have involvement of a pelvic lymph node with in situ follicular neoplasia (ISFN). Staging PET/CT showed no evidence of FL (Fig H) and he was followed expectantly for 4 years without emergent disease. Eight years after surgery he presented with inguinal swelling and bilateral FDG-avid adenopathy on PET/CT. Excisional biopsy confirmed low grade FL and sequencing for M7-FLIPI revealed a CREBBP KAT domain variant. Retrospective sequencing of serial peripheral blood specimens from his initial surveillance showed detectable CREBBP R1446C at the earliest collected time point (AF range 0.019-0.046%) rising to AF 0.082% after clinical diagnosis. Conclusions: Precursor FL mutations are detectable in peripheral blood and saliva years prior to clinical diagnosis with a spectrum of variants enriched in CREBBP and BCL2 and concordant with subsequent FL tumors. Such lesions may assist in stratifying individuals at elevated risk of clinical malignancy, including after identification of pathologic precursors such as ISFN. Figure 1 Figure 1. Disclosures Kurtz: Foresight Diagnostics: Consultancy, Current holder of stock options in a privately-held company; Roche: Consultancy; Genentech: Consultancy. Khodadoust: Alexion, AstraZeneca Rare Disease: Other: Study investigator; CRISPR Therapeutics, Nutcracker Therapeutics: Research Funding; Myeloid Therapeutics: Membership on an entity's Board of Directors or advisory committees. Diehn: Roche: Consultancy; AstraZeneca: Consultancy; RefleXion: Consultancy; BioNTech: Consultancy; Varian Medical Systems: Research Funding; Illumina: Research Funding; CiberMed: Current holder of stock options in a privately-held company, Patents & Royalties; Foresight Diagnostics: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company. Roulland: BMS: Research Funding. Alizadeh: Bristol Myers Squibb: Research Funding; Gilead: Consultancy; CAPP Medical: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Celgene: Consultancy, Research Funding; Roche: Consultancy, Honoraria; Janssen Oncology: Honoraria; Foresight Diagnostics: Consultancy, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Cibermed: Consultancy, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Forty Seven: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company.

Background: Follicular lymphoma (FL) is genetically characterized by translocations involving the BCL2 locus on chromosome 18q21. However, up to 70% of healthy individuals also carry detectable t(14;18)-positive cells, suggesting BCL2 translocation is critical but not sufficient for FL development. Chromatin modifying genes (CMGs) including KMT2D, CREBBP, EZH2, and EP300 are almost ubiquitously mutated in FL. We previously reported the direct characterization by ultra-deep sequencing of pre-diagnostic blood and tissue specimens from 19 subjects who ultimately developed FL. CREBBP lysine acetyltransferase (KAT) domain mutations were the most commonly observed precursor lesions, detected in blood a median of 7.5 years before diagnosis in patients developing FL (8/19, 42%) but not in healthy adults with or without detected BCL2 translocations (0/13, p=0.01 and 0/20, p While the BCL2 translocation is thought to occur in pre-B-cell precursors in the bone marrow, the high prevalence of CMG mutations raises the possibility that, analogous to myeloid age-related clonal hematopoiesis, such early lesions could occur in hematopoietic stem cells (HSCs) rather than in the committed B-cell lineage. Methods: To address this question of mutational hierarchy, we studied blood, bone marrow aspirate, and lymph node samples from 6 patients with CREBBP or KMT2D mutations in their FL tumor. We analyzed flow-sorted purified hematopoietic cell populations by deep sequencing, including isotype-specific mature B-cell, mature T-cell, and precursor populations encompassing HSCs and common lymphoid progenitors (CLPs). Patients additionally underwent routine clinical sequencing of tumor biopsy and marrow specimens. Results: Bulk sequencing of a diagnostic bone marrow aspirate from patient FL002 revealed a CREBBP mutation concordant with FL tumor biopsy. To ascertain the population bearing this mutation, we sorted to high purity viable marrow aspirate cells (Fig. A). The CREBBP mutation was confirmed in the mature B-cell compartment at an AF of 40.3% but was not detected in other cell populations. To validate this finding, a similar sorting strategy was employed on viable bone marrow aspirate or peripheral blood samples from another 4 FL patients bearing CREBBP mutations (Fig B). In each case, CREBBP was absent from the CD34+ precursor population. In patient CIML004 a characteristic KMT2D stop mutation was likewise absent in precursors. An atypical case sheds additional light on the localization of early FL mutations. Patient LYM267 was diagnosed with Grade 1-2 FL bearing CREBBP and NRAS mutations. Eight years into a prolonged remission after chemoimmunotherapy, he developed cutaneous and gingival myeloid sarcoma without radiographic or histopathological evidence of FL recurrence. While the CREBBP mutation was not detected in myeloid sarcoma or bone marrow biopsies, concordant NRAS mutations and clonal VDJ rearrangements were seen in all 3 compartments (Fig. C). This unusual clonal lineage favors the occurrence of the CREBBP mutation later than the branch point between morphologically distinct lymphoid and myeloid tumors, likely in the committed B-cell lineage after pre-BCR rearrangements (Fig D). Conclusions: HSCs are believed to be the cell of origin in several lymphoid leukemias, and mouse models have demonstrated lymphoma development with induced CREBBP lesions in HSCs (Horton et al Nat Cell Bio 2017). However, in sorted hematopoietic cell populations from marrow and peripheral blood, we observed CREBBP mutations in B-cell lineages but never in CD34+/CD20- precursor populations or paired lymphoid/myeloid disease. Our data therefore are not in support of HSCs as a precursor reservoir in FL. Given that cells harboring the t(14;18) translocation in healthy individuals appear derived from the germinal center, recurrent mutations in CREBBP are likely to occur after the pre-B-cell stage. Figure Disclosures Kurtz: Genentech: Consultancy; Foresight Diagnostics: Other: Ownership; Roche: Consultancy. Khodadoust:Kyowa Kirin: Consultancy; Seattle Genetics: Consultancy. Nadel:Innate Pharma: Research Funding; Institut Roche: Research Funding. Diehn:RefleXion: Consultancy; Varian Medical Systems: Research Funding; Illumina: Research Funding; Roche: Consultancy; BioNTech: Consultancy; AstraZeneca: Consultancy. Roulland:Celgene/BMS: Research Funding; Roche: Honoraria. Alizadeh:Pharmacyclics: Consultancy; Genentech: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Chugai: Consultancy; Gilead: Consultancy; Pfizer: Research Funding; Roche: Consultancy.

BACKGROUND Selection biases can impair the generalizability of clinical trials. Studies investigating aggressive diseases such as Diffuse Large B-cell Lymphoma (DLBCL) can be particularly affected by such biases since clinical urgency and need for therapy may not allow the requisite extensive screening and consent processes for trials. Diagnosis-to-Treatment Interval (DTI) has recently been proposed as a novel metric to capture this phenomenon (Maurer et al, JCO, 2018), and short DTI is associated with both adverse clinical factors and adverse clinical outcomes. Intriguingly, DTI was independent of clinical risk factors like the International Prognostic Index (IPI) suggesting that widely applied prognostic scores do not adequately reflect risk factors considered for clinical decision making. In this study, we aim to assess whether pretreatment levels of circulating tumor DNA (ctDNA) are associated with shorter DTI and may constitute an objective measure of clinical urgency. METHODS We quantified pretreatment ctDNA levels in plasma samples from 178 patients treated in 5 US and European centers for large cell lymphoma (DLBCL, Follicular lymphoma grade 3b, or High-grade-B-cell-lymphoma) using Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) as previously described (Kurtz, JCO 2018; Scherer, STM 2016). Pretreatment ctDNA levels were correlated with DTI, clinical factors and treatment outcome. RESULTS Pretreatment ctDNA was detectable in 175/178 cases. Median number of single nucleotide variants (SNV) detected per patient was 129 (range 0-628). Pretreatment ctDNA levels ranged from 0 - 1.4 x105 haploid genome equivalents per milliliter of plasma (hGE/ml, median 239). Median DTI was 19 days (range 0-141, Figure 1A) and was similar in distribution to 2 previously described cohorts from the US and Europe (Maurer et al, JCO 2018). Shorter DTI was associated with higher ctDNA levels (RS=-0.39, P= 1.4 x10-7, Figure 1B). Patients with longer DTI had improved Event-Free Survival (EFS, Hazard Ratio (HR) for DTI: 0.9/week, P= 0.03). However, this association was lost when adjusting for pretreatment ctDNA levels (HR for DTI: 0.95/week, P= 0.39; HR for log10(ctDNA): 1.7, P= 5.8 x10-5). In a multivariate analysis including DTI, ctDNA and IPI, only ctDNA levels were significantly associated with EFS (HR for log10(ctDNA): 1.6, P= 0.002, n=178, Figure 1C). Pretreatment ctDNA levels remained the only prognostic factor for EFS in a second multivariate analysis also considering pretreatment metabolic tumor volume (MTV, HR for log10(ctDNA): 1.8, P= 0.01, n=93, Figure 1D). DISCUSSION Shorter DTI is associated with higher pretreatment ctDNA levels in patients with aggressive B-cell lymphomas. When comparing to established factors (DTI, IPI, MTV), pretreatment ctDNA levels appear to best predict clinical outcomes. This suggests that quantification of ctDNA better reflects disease burden and treatment urgency than existing clinical biomarkers. Pretreatment ctDNA level may therefore be a valuable metric for disease aggressiveness of patients included in clinical trials, and may help identify studies suffering from selection bias. This may be particularly useful for noncontrolled Phase I/II single arm trials, but also for stratification in randomized trials. Disclosures Kurtz: Roche: Consultancy. Dührsen:Alexion: Honoraria; Novartis: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Janssen: Honoraria; Takeda: Consultancy, Honoraria; Celgene: Research Funding; CPT: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Teva: Honoraria; Roche: Honoraria, Research Funding. Hüttmann:Takeda: Honoraria; Gilead: Honoraria; University Hospital Essen: Employment. Westin:Juno: Other: Advisory Board; Novartis: Other: Advisory Board, Research Funding; Janssen: Other: Advisory Board, Research Funding; Kite: Other: Advisory Board, Research Funding; Curis: Other: Advisory Board, Research Funding; Celgene: Other: Advisory Board, Research Funding; 47 Inc: Research Funding; Unum: Research Funding; MorphoSys: Other: Advisory Board; Genentech: Other: Advisory Board, Research Funding. Gaidano:AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Astra-Zeneca: Consultancy, Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sunesys: Consultancy, Honoraria. Rossi:Abbvie: Honoraria, Other: Scientific advisory board; Janseen: Honoraria, Other: Scientific advisory board; Roche: Honoraria, Other: Scientific advisory board; Astra Zeneca: Honoraria, Other: Scientific advisory board; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Diehn:Novartis: Consultancy; BioNTech: Consultancy; AstraZeneca: Consultancy; Quanticell: Consultancy; Roche: Consultancy. Alizadeh:Pfizer: Research Funding; Chugai: Consultancy; Celgene: Consultancy; Gilead: Consultancy; Pharmacyclics: Consultancy; Janssen: Consultancy; Genentech: Consultancy; Roche: Consultancy.

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.

Background: This study investigated whether receiving the results of predictive genetic testing for Lynch syndrome, indicating the presence or absence of an inherited predisposition to various cancers, including colorectal cancer, was associated with change in individual colonoscopy and smoking behaviors, which could prevent colorectal cancer. Methods: The study population included individuals with no previous diagnosis of colorectal cancer, whose families had already identified deleterious mutations in the mismatch repair or EPCAM genes. Hypotheses were generated from a simple health economics model and tested against individual-level panel data from the Australasian Colorectal Cancer Family Registry. Results: The empirical analysis revealed evidence consistent with some of the hypotheses, with a higher likelihood of undergoing colonoscopy in those who discovered their genetic predisposition to colorectal cancer and a lower likelihood of quitting smoking in those who discovered their lack thereof. Conclusions: Predictive genetic information about Lynch syndrome was associated with change in individual colonoscopy and smoking behaviors but not necessarily in ways to improve population health. Impact: The study findings suggest that the impact of personalized medicine on disease prevention is intricate, warranting further analyses to determine the net benefits and costs. Cancer Epidemiol Biomarkers Prev; 25(11); 1524–33. ©2016 AACR.

Primary perineal closure following abdominal perineal resection (APR) is reported to have a wound complication rate as high as 66%, whereas flap reconstruction reduces wound complications to 15% to 35%. A modified de-epithelialized V-Y fasciocutaneous flap aims to further improve results in this patient population.To study the breaking force of a simple interrupted suture in either skin or subcutaneous fat, various quantitative assessments were performed in a porcine flap model using uniaxial static tensile testing with an Instron tensiometer, with a single or triple row of 3 Vicryl sutures in both skin and fat.An outcomes analysis was performed in 24 patients who underwent modified V-Y flap reconstruction after APR. Primary outcome was wound complications including infection, dehiscence, seroma, hematoma, and pelvic fluid collections.Tensile strength of sutures anchored in skin was found to be up to 8 times stronger than sutures anchored in subcutaneous fat in a single row and 3 times as strong in 3 rows (breaking force, 500.2 N vs 263.7 N). In our patient cohort of 24 irradiated cancer patients, 10 (42%) had wound healing complications. Wound dehiscence of various degrees accounted for 80% of these complications. Five patients with wound complications (50%) had associated pelvic fluid collections (infection, 1; wound dehiscence, 4). Minor dehiscence was more likely to occur after suture removal and less likely to be associated with pelvic collections compared to patients with major dehiscence. Our study yields total complication rates lower than what is reported in the literature for anterolateral thigh or gracilis flap including much lower infection rates, and almost similar results to the commonly used vertical rectus myocutaneous muscle.Tension-free de-epithelialized V-Y flap use after APR effectively reconstructs the defect while eliminating an additional donor site. Benchtop studies suggest enhanced flap integrity yielded by layered closure. Wound complications can be managed with local care in their majority (90%). Staggering or delaying suture removal can decrease minor dehiscence. Based on analysis of our results, review of the literature and consideration of donor site morbidity, we believe that modified V-Y flap is the best approach for APR reconstruction in irradiated patients.

Summary Accurate prediction of long-term outcomes remains a challenge in the care of cancer patients. Due to the difficulty of serial tumor sampling, previous prediction tools have focused on pretreatment factors. However, emerging non-invasive diagnostics have increased opportunities for serial tumor assessments. We describe the Continuous Individualized Risk Index (CIRI), a method to dynamically determine outcome probabilities for individual patients utilizing risk predictors acquired over time. Similar to “win probability” models in other fields, CIRI provides a real-time probability by integrating risk assessments throughout a patient’s course. Applying CIRI to patients with diffuse large B cell lymphoma, we demonstrate improved outcome prediction compared to conventional risk models. We demonstrate CIRI’s broader utility in analogous models of chronic lymphocytic leukemia and breast adenocarcinoma and perform a proof-of-concept analysis demonstrating how CIRI could be used to develop predictive biomarkers for therapy selection. We envision that dynamic risk assessment will facilitate personalized medicine and enable innovative therapeutic paradigms.

Introduction: Cell-free DNA (cfDNA) and circulating tumor DNA (ctDNA) have an emerging diagnostic role in multiple malignancies including in lymphomas (Kurtz et al ASH 2017). In classical Hodgkin Lymphoma (cHL), malignant Reed Sternberg (RS) cells are rare, requiring laser capture microdissection from archival tissues or flow sorting from viable tumor cell suspensions for genotyping. We profiled ctDNA in cHL to assess the utility of ctDNA in the noninvasive evaluation of somatic single nucleotide variants (SNVs), somatic copy number alterations (SCNAs), and tumor EBV status. Methods: A total of 53 subjects with HL (29 with early stage and 24 with advanced disease) were studied encompassing a total of 95 blood and tissue samples (72 from Stanford, 23 from UZ Leuven). Plasma samples were sequenced with CAPP-Seq (Newman et al Nat Biotech 2016), using a panel informed by the genotyping of primary tumor biopsies. The genotypes of cHL patients were compared to that of 189 patients with other B-cell malignancies. Given the thoracic distribution of most cHL, we also compared ctDNA levels to that of 55 lung carcinomas. ctDNA levels were calculated as the product of the cfDNA concentration and the mean allelic fraction of somatic mutations. Results: The median pretreatment ctDNA level in cHL was 125 hGE/mL (15 - 5277 hGE/mL), corresponding to a median variant allelic fraction (VAF) of 3.2% (0.3 - 13.9%) (Fig 1A). Pretreatment ctDNA burden was greater in cHL cases than in follicular lymphoma (FL) cases (p = 0.002), but was not significantly different from that of diffuse large B-cell lymphoma (DLBCL) (p = 0.26). Plasma genotyping in cHL and DLBCL also identified similar numbers of SNVs, recovering a median of 108 mutations in cHL and 117 mutations in DLBCL (p = 0.53). In samples with available diagnostic PET/CT, pre-treatment ctDNA levels in cHL were significantly correlated with total metabolic tumor volume (MTV) (Spearman ρ = 0.615, p = 0.006) (Fig 1B), but not with diagnostic PET/CT SUVmax, stage, bulky status (>10 cm), B-symptoms, or presence of extranodal disease. Surprisingly, despite the lower tumor purity of RS cells in cHL tumor masses than that of malignant B-cells in DLBCL, the relationship between ctDNA and PET/CT estimates of disease burden in cHL was highly similar to that of DLBCL. Specifically, cHL and DLBCL were statistically indistinguishable for the ratio between ctDNA levels and MTV (mean ctDNA/MTV of 2.1 vs 1.5 hGE/mL per cm3 tumor, p = 0.38), and both were significantly higher than that of non small cell lung carcinoma (NSCLC) (p < 0.0001) (Fig 1C). In patients with available mid-treatment cfDNA (n = 10), we monitored ctDNA concentrations and observed that circulating tumor burden falls rapidly, with a third of our patients reaching undetectable levels within the first month after start of therapy. PD-L1 copy number gains, previously shown to be prognostic for survival in cHL treated with checkpoint inhibitors, were observed in 42% of cHL patients with ctDNA VAFs above our SCNA limit of detection (1%) and were genotyped significantly more frequently than in other non-PMBCL B-cell malignancies (42% vs 18%, p = 0.005) (Fig 1D). Coding SNVs in the most commonly mutated genes involved STAT6 (24%), SOCS1 (20%), GNA13 (20%), TNFAIP3 (18%), and B2M (16%) while noncoding SNVs in IGK and IGH were more abundant in cHL and DLBCL respectively (Fig 1E). EBV tumor cell presence has previously been shown to be prognostic in cHL (Keegan et al JCO 2005). Prior to therapy, EBV cfDNA constituted a significantly larger fraction of total cfDNA in patients confirmed by EBER ISH to have EBV+ cHL than in either EBER-negative cHL patients or healthy controls (p < 0.0001) (Fig 1F). Conclusions: Levels of ctDNA in cHL are higher than might be expected based on tumor purity, with pre-treatment levels similar to DLBCL and higher than FL. ctDNA allows for reliable noninvasive genotyping of cHL at diagnosis, encompassing coding and non-coding SNVs and additional clinically significant factors such as tumor EBV status and SCNAs. Additional cases are currently being profiled and expanded analyses of genotyping and monitoring will also be presented at the meeting. Disclosures Dührsen: Celgene: Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Roche: Honoraria, Research Funding; Janssen: Honoraria; Amgen: Research Funding; Gilead: Consultancy, Honoraria. Hüttmann:Roche: Other: Travel expenses; Celgene: Other: Travel expenses. Gaidano:Gilead: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Morphosys: Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Westin:Apotex: Membership on an entity's Board of Directors or advisory committees; Celgen: Membership on an entity's Board of Directors or advisory committees; Kite Pharma: 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. Advani:Regeneron: Research Funding; Kyowa: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Infinity: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Millenium: Research Funding; Cell Medica: 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; Agensys: Research Funding; Forty Seven Inc.: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Kura: Research Funding; Astra Zeneca: Consultancy, 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; Autolus: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Celgene: Research Funding; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Bayer: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Merck: Research Funding.

Purpose Outcomes for patients with diffuse large B-cell lymphoma remain heterogeneous, with existing methods failing to consistently predict treatment failure. We examined the additional prognostic value of circulating tumor DNA (ctDNA) before and during therapy for predicting patient outcomes. Patients and Methods We studied the dynamics of ctDNA from 217 patients treated at six centers, using a training and validation framework. We densely characterized early ctDNA dynamics during therapy using cancer personalized profiling by deep sequencing to define response-associated thresholds within a discovery set. These thresholds were assessed in two independent validation sets. Finally, we assessed the prognostic value of ctDNA in the context of established risk factors, including the International Prognostic Index and interim positron emission tomography/computed tomography scans. Results Before therapy, ctDNA was detectable in 98% of patients; pretreatment levels were prognostic in both front-line and salvage settings. In the discovery set, ctDNA levels changed rapidly, with a 2-log decrease after one cycle (early molecular response [EMR]) and a 2.5-log decrease after two cycles (major molecular response [MMR]) stratifying outcomes. In the first validation set, patients receiving front-line therapy achieving EMR or MMR had superior outcomes at 24 months (EMR: EFS, 83% v 50%; P = .0015; MMR: EFS, 82% v 46%; P < .001). EMR also predicted superior 24-month outcomes in patients receiving salvage therapy in the first validation set (EFS, 100% v 13%; P = .011). The prognostic value of EMR and MMR was further confirmed in the second validation set. In multivariable analyses including International Prognostic Index and interim positron emission tomography/computed tomography scans across both cohorts, molecular response was independently prognostic of outcomes, including event-free and overall survival. Conclusion Pretreatment ctDNA levels and molecular responses are independently prognostic of outcomes in aggressive lymphomas. These risk factors could potentially guide future personalized risk-directed approaches.

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.

Decision-making processes involving environmental issues often require assessing several conflicting factors. Apart from the ecological and conservation considerations, there is the need to adhere to international and regional policies and treaties, technical and logistical aspects, whilst also taking into account the views and opinions of local communities that may be affected. The ways in which these differing aspects are classified and ranked – and in this sense, valued – will impact on how environmental decisions are made. Since the 1960s there have been concerted efforts to assign value to environmental assets and the use of economic valuation for environmental assessment is increasingly being used as a means to make the value of nature and biodiversity visible in political realms. One environmental assessment framework that has gained importance on a global scale is the ecosystem services approach. This is an economic valuation approach in which ecosystems are divided into categories and valued in terms of ecosystem services – defined as benefits people obtain from the environment. However, valuing the environment through these economic and anthropocentric perspectives has raised debates regarding how to apply economic logic to environmental valuation as well as the implications regarding how the environment and issues pertaining to it are conceptualized and addressed. Given that valuation and the methods that measure and assign value are entirely socially constructed, understanding the methods (and the practices within them) for environmental valuation can shed light on the performativities involved as well as highlighting how nature is being enacted as a result. This thesis will investigate the methods and practices involved for valuing ecosystem services in the context of the empirical case study of the Recharge.green project, whose main goal was to facilitate decision-making processes regarding renewable energy expansion in the Alps.

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: While the majority of diffuse large B-cell lymphoma (DLBCL) patients are cured with R-CHOP immunochemotherapy, a significant proportion of patients still experience disease relapse. Studies using interim PET (iPET) to select patients for therapy intensification have failed to improve survival, at least partially, due to imperfect risk stratification. Circulating tumor DNA (ctDNA) is an emerging biomarker in lymphoma and ctDNA dynamics early in therapy have been shown to predict treatment outcomes in DLBCL (Kurtz, JCO 2018). Here, we assess the utility of interim ctDNA after 3 cycles of front-line therapy, in the context of standardized interim PET/CT imaging and PET-driven adaptive therapy. Methods: We quantified ctDNA levels using Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) in plasma samples collected before treatment and prior to cycle 4 in 39 patients with de novo DLBCL. 28 patients were from the NHL21 trial of the Australasian Leukaemia Lymphoma Group, in which patients initially received R-CHOP14 as frontline therapy (Hertzberg, Haem 2017). Patients with positive iPET after cycle 4 were escalated to R-ICE (rituximab, ifosfamide, carboplatin, etoposide) followed by 90Y-ibritumomab tiuxetan-BEAM (BCNU, etoposide, cytarabine, melphalan) and autologous stem cell transplant (ASCT). iPET negative patients continued R-CHOP14 for a total of 6 cycles. iPET was evaluated centrally by 2 nuclear imaging specialists according to the International Harmonization Project (IHP) criteria. An additional group of 11 patients received 6 cycles of R-CHOP as standard therapy at Stanford University. All survival analyses are calculated from date of diagnosis. Matched germline DNA was sequenced in 28/39 cases and all samples were uniformly processed at Stanford. Results: Median follow-up for progression-free survival (PFS) for the patients from the NHL21 cohort was 2.6 years [95%CI 2.23; 2.97]. Within the 28 NHL21 patients evaluated, mean baseline metabolic tumor volume was 898.76 cm3(+/- 112.01). Of the 28 patients with interim PET data, 10 were iPET-positive. Agnostic to ctDNA detection, the 2 year mean progression free survival (PFS) for these 10 patients was 60.0% [95% CI 36.2; 99.5%] as compared to 66.7% [95% CI 48.1%; 92.4%] within the iPET-negative group (Hazard Ratio (HR) 1.649 [95% CI 0.50; 5.4], p=0.4, Fig 1A). Within the 39 patients monitored across both cohorts, 17 patients possessed detectable disease by ctDNA at C4D1 with a mean disease burden of 3.59 haploid genome equivalents per milliliter of plasma (hGE/mL, +/- 1.23). Plasma genotyping within the 28 patients from the NHL21 cohort discovered an average of 112.9 single nucleotide variants (SNVs) which were then used to monitor plasma samples at the C4D1 timepoint, comparable to a broader cohort of NHL cases previously described (Kurtz, JCO2018). 2-year PFS of the 22 patients with undetectable disease as assessed by ctDNA at C4D1 was 81.82 [95% CI 67.2; 99.6] compared to 47.1% within the 17 patients with detectable ctDNA [95% CI 28.4; 77.9] (HR 4.42 [95% CI 1.32; 13.76],p=0.006, Fig. 1B). Detection of ctDNA at C4D1 also has a prognostic value for overall survival (p=0.02, Fig. 1C). iPET concordance with with C4D1 ctDNA-positivity was 50% and within the 18 patients who were iPET-negative as part of the NHL21 study and did not receive therapy escalation, 9 patients with undetectable disease by ctDNA demonstrated 88.9% 2-year PFS [95% CI 70.6; 1.00] compared to 44.4% [95% CI 21.4; 92.3] for the 9 patients with detectable ctDNA (p=0.03, Fig. 1D). Conclusions: Late in the course of DLBCL therapy, ctDNA carries promising value as a biomarker for stratifying predicted patient response to therapy as evidenced by additional detection of additional 50% detection of relapsing cases not categorized as iPET-positive. Data from additional patients and relationships between ctDNA response as measured by EMR (C2D1), MMR (C3D1), and C4D1 will be presented at the meeting. Disclosures Kurtz: Roche: Consultancy. Opat:Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Mundipharma: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Beigene: Research Funding; Pharmacyclics LLC, an AbbVie Company: Research Funding; Amgen: Research Funding; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Epizyme: Research Funding; CSL: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Hertzberg:BMS: Honoraria; MSD: Consultancy; Roche: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy. Gandhi:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria; Roche: Honoraria, Other: Travel Support; Merck: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Honoraria, Research Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding. Diehn:BioNTech: Consultancy; Novartis: Consultancy; AstraZeneca: Consultancy; Quanticell: Consultancy; Roche: Consultancy. Alizadeh:Pfizer: Research Funding; Chugai: Consultancy; Celgene: Consultancy; Gilead: Consultancy; Pharmacyclics: Consultancy; Janssen: Consultancy; Genentech: Consultancy; Roche: Consultancy.

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.

Background: Circulating tumor DNA (ctDNA) is an emerging biomarker in non-Hodgkin lymphomas (NHLs). Current methods for ctDNA minimal residual disease (MRD) are limited by two factors - low input DNA amounts and high background error rates. VDJ sequencing (i.e., IgHTS) has low background but is limited by low cell-free DNA (cfDNA). Tracking multiple mutations via CAPP-Seq improves sensitivity, but detection is limited by background errors. Clustered mutations have been described in multiple cancers including NHLs and potentially have lower error rates. We explored clustered mutations from whole-genome sequencing (WGS) to identify 'phased variants' (PVs), defined as multiple mutations on a single DNA molecule (Fig 1A). We designed a method to capture PVs for improved ctDNA detection and explored its utility for MRD in DLBCL. Methods: We reanalyzed WGS from 1455 tumors across 11 cancer types. We identified genomic regions recurrently containing PVs and designed an assay for deep cfDNA sequencing. We applied this assay to 171 patients with large B-cell lymphomas. We compared the performance of PVs for disease detection to current ctDNA techniques, including CAPP-Seq and duplex sequencing. Results: To utilize PVs, mutations must occur within a typical cfDNA strand (~170bp). We measured the frequency of putative PVs in WGS, focusing on pairs of mutations occurring within We designed an approach for enriching PVs from ~115kb (Phased variant Enrichment Sequencing, PhasE-Seq) and other regions recurrently mutated in B-NHLs. We compared PhasE-Seq and CAPP-Seq using tumor and plasma samples from 16 patients. Compared to CAPP-Seq, PhasE-Seq yielded more SNVs and PVs per case (median SNVs: 331 vs 114, P We then compared PhasE-Seq to alternative methods for MRD detection. We used limiting dilutions of patient ctDNA down to 1:1,000,000 to establish the detection limit (LOD, Fig 1D). PhasE-Seq outperformed CAPP-Seq and duplex sequencing for recovery of expected tumor content, with a high degree of linearity down to ~1:1,000,000. We applied standard CAPP-Seq and PhasE-Seq to patient cfDNA samples after two cycles of front-line therapy (n=92). We previously reported a 2.5-log reduction in ctDNA as prognostic at this time-point (Kurtz, JCO 2018). Using CAPP-Seq, 58% (53/92) of samples were undetectable. Using PhasE-Seq, 30% (16/53) of samples not detected by CAPP-Seq had evidence of MRD, with levels as low as 2:1,000,000. In patients with ctDNA undetected by CAPP-Seq, detection by PhasE-Seq significantly stratified outcomes (Fig 1E). Conclusions: PVs are frequent in NHLs, likely due to AID, and correlate with disease biology. PhasE-Seq allows for superior detection of ctDNA, including MRD detection in the majority of patients after 2 cycles. Targeted sequencing of ctDNA should consider PVs to maximize detection and guide precision approaches. Figure 1: A) Structure of phased variants B) Distribution of putative PVs from WGS data C) Genomic enrichment in PVs in lymphoma subtypes D) Dilution series comparing PhasE-Seq, CAPP-Seq, and duplex sequencing E) Waterfall plot showing ctDNA level vs outcome; undetectable ctDNA by CAPP-Seq is highlighted F) EFS of patients with undetectable ctDNA by CAPP-Seq after 2 cycles, stratified by PhasE-Seq Disclosures Kurtz: Roche: Consultancy. Diehn:Roche: Consultancy; AstraZeneca: Consultancy; Novartis: Consultancy; BioNTech: Consultancy; Quanticell: Consultancy. Alizadeh:Pharmacyclics: Consultancy; Janssen: Consultancy; Genentech: Consultancy; Roche: Consultancy; Gilead: Consultancy; Celgene: Consultancy; Chugai: Consultancy; Pfizer: Research Funding.

Background Diffuse large B-cell lymphomas (DLBCL) can be divided into subtypes that relate to their cell-of-origin: germinal center B-cell (GCB) and activated B-cell (ABC). These clinically distinct subtypes were originally discovered based on their unique transcriptional signatures, but they also harbor distinct genetic aberrations and epigenetic profiles. We previously showed the utility of genetic mutations in circulating tumor DNA (ctDNA) for DLBCL subtyping using cancer personalized profiling by deep sequencing (CAPP-Seq) [Scherer et al., Sci Transl Med 2016, Newman et al., Nat Med 2014]. Here, we assess epigenetic information encoded in cell-free DNA (cfDNA) for addressing this distinction. Methods We extended recent observations revealing nucleosome depletion at transcription start sites (TSS) of highly expressed genes within cfDNA [Snyder et al. 2016 Cell and Ulz et al. 2016 Nat Genetics]. Specifically, to overcome the inherent sensitivity limitations of cfDNA whole genome sequencing (WGS), we focused on 32 genes differentially expressed between DLBCL subtypes (as well as 70 control genes). We targeted 2 kb regions flanking each TSS for these genes by CAPP-Seq [Newman et al. 2014 Nature Med]. Plasma samples were collected from 41 individuals and cfDNA subjected to ultra-deep sequencing (~4000x) by CAPP-Seq. DLBCL cases were labeled as either ABC or GCB based on gene expression in tumor biopsies. Results We observed significant heterogeneity in the TSS profiles of individual genes. Despite this variation, many genes in our targeted panel exhibited discriminatory profiles. For example, CD20 (MS4A1), reliably distinguished DLBCL cases from control subjects in nucleosome depletion at the TSS as expected (p= 1.5e-05, Fig1a). Remarkably, when considering 32 genes differentially expressed between DLBCL subtypes, we observed significant differences in their TSS profiles in plasma from patients with GCB vs ABC DLBCL (p=0.0002, Fig 1b). For the majority of the subtype-specific genes, the pattern of nucleosome depletion at the TSS was consistent with expected expression (Fig 1b). Specifically, genes typically over-expressed in GCB DLBCL (e.g., CD10/MME, LMO2, SERPINA9), had significantly more TSS nucleosome depletion in cfDNA from GCB-like DLBCL patients. Conversely, we observed significantly more nucleosome depletion in cfDNA of ABC DLBCL patients at the TSS of genes known to be transcriptionally more active in ABC DLBCL (e.g., IRF4, PIM1, CCND2 and IL16). When aggregating the epigenetic profiles across these genes into a single cell-of-origin score, we observed significant stratification of patients with distinct DLBCL subtypes (Fig 1c, p=0.008). Across the cohort, this epigenetic cell-of-origin score from cfDNA showed significant correlation (Spearman rho=0.67, p=0.05) with a score derived from somatic mutations genotyped from ctDNA [Scherer et al. 2016 Sci Transl Med]. Conclusions Lymphoma subtypes exhibit distinct chromatin accessibility profiles that can be captured by targeted cell free DNA profiling, and that can serve as surrogates for expected gene expression differences. These epigenetic features can be used to noninvasively classify DLBCL molecular subtypes using blood plasma and should be readily extensible to other cancer classification problems. Extension of this approach to other epigenetic features could serve to further refine potential applications. Figure legend. Figure 1. (A) Sequencing coverage around the TSS of the B-cell antigen CD20 (MS4A1) is shown for three representative DLBCL patients (red) and three normal controls (gray). The boxplot shows summary of normalized depth across all samples (n=10 DLBCL, n=31 control). (B) The y-axis shows 32 genes with known ABC-favoring (blue) and GCB-favoring (orange) expression. The x-axis shows a delta score defined as log2( mean normalized depth across GCB samples - mean normalized depth across GCB samples). (C) Boxplot of the GCBness score obtained by subtracting the overall depth around the TSSs of a set of GCB-genes from the same metric for a set of ABC-genes. Disclosures No relevant conflicts of interest to declare.

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.

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: Outcomes for patients with diffuse large B-cell lymphoma (DLBCL) remain heterogeneous. Several clinical and molecular risk factors have been described, both at time of diagnosis (i.e., International Prognostic Index and cell of origin) and during therapy (i.e., interim PET scans). However, these risk factors fail to consistently identify individuals destined for treatment failure. We recently described circulating tumor DNA (ctDNA) as a novel biomarker in DLBCL, demonstrating pretreatment ctDNA levels are prognostic of outcomes (Scherer F, Sci Transl Med 2016). A major advantage of ctDNA assessment is the ability to collect serial assessments over time. However, the best approach for integrating multiple ctDNA measurements with established prognostic factors remains unknown. Using the dynamics of ctDNA, we developed a method to quantify personalized disease risk as it changes during therapy. Methods: We profiled 468 samples from 125 subjects collected during their first three cycles of immunochemotherapy using cancer personalized profiling by deep sequencing (CAPP-Seq). Early ctDNA dynamics were correlated with outcomes in a training cohort to define a response threshold that was tested in a validation cohort. Finally, we integrated ctDNA and clinical factors to dynamically assess disease risk over time in a continuous model. Results: Prior to therapy, ctDNA was detectable in 98% of subjects. Pretreatment levels of ctDNA were prognostic of event-free survival in patients receiving either frontline anthracycline-based (n=92) or salvage regimens (n=33) (EFS: HR 2.7, 95% CI 1.5-4.7, P=0.0005), confirming prior results. In the training cohort, ctDNA levels changed rapidly, with a 2-log or 100-fold decrease after one cycle (early molecular response, EMR) stratifying outcomes (Fig 1A). In the validation cohort, patients achieving EMR had superior outcomes at 24-months to those who did not (Fig 1B) (EFS: HR 24, 95% CI 6.6-89, P Next, we integrated serial ctDNA measurements with established risk-factors to develop a model to predict an individual's disease risk. This model - the Continuous Individualized Risk Index (CIRI) - provides a personalized estimate of disease risk over time. As more information becomes available during a patient's course of disease, CIRI updates the disease risk, integrating the new information (Fig 1C). In patients receiving frontline therapy, CIRI outperformed the IPI for identification of 24-month EFS and OS (Fig 1D-E) (EFS24: AUC 0.64 vs 0.79; net reclassification improvement 0.47, P=0.02; OS: AUC 0.56 vs 0.84; net reclassification improvement 0.74, P=0.004). Conclusions: Baseline and interim ctDNA measurements have prognostic significance in aggressive lymphomas. Integration of serial ctDNA measurements through a continuous, dynamic risk model can identify personalized outcome probabilities, yielding superior risk estimates. Dynamic risk assessment is potentially widely applicable and could guide future personalized therapeutic approaches. Figure 1: A) A spider-plot depicts the dynamics of ctDNA during the first two cycles of therapy in 14 subjects. B) A Kaplan-Meier estimate depicts EFS for patients achieving or not achieving EMR. C) A schema for CIRI is shown. When a patient is diagnosed with DLBCL, the IPI is calculated, giving an initial estimate of risk. Additional pretreatment risk factors (i.e., cell of origin and pretreatment ctDNA) can be added, thereby updating the estimate of risk. As a patient undergoes therapy, further predictors of risk are obtained, such as ctDNA at cycle 2 and cycle 3, and interim imaging. These predictors can be used to update the patient's estimated risk. Below is a CIRI risk model for two exemplar patients with the same initial pretreatment risk factors. Patient P214 (red) died of disease at day 210, while patient P224 (blue) is in a continued complete response. D) AUC for prediction of EFS and OS by IPI, EMR, interim PET scans, and CIRI. E) A Kaplan-Meier estimate demonstrates risk stratification of EFS by CIRI. Disclosures Advani: Sutro: Consultancy; Cell Medica: Research Funding; Janssen: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Celgene: Research Funding; Nanostring: Consultancy; Bayer Healthcare Pharmaceuticals: Research Funding; Juno Therapeutics: Consultancy; FortySeven: Research Funding; Gilead: Consultancy; Spectrum: Consultancy; Pharmacyclics: Research Funding; Agensys: Research Funding; Regeneron: Research Funding; Millennium: Research Funding; Infinity: Research Funding; Merck: Research Funding; Kura: Research Funding; Pharmacyclics: Consultancy; Seattle Genetics: Research Funding; Genentech: Research Funding. Newman: Roche: Consultancy. Westin: Celgene: Membership on an entity's Board of Directors or advisory committees; Apotex: Membership on an entity's Board of Directors or advisory committees; Kite Pharma: 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. Gaidano: Janssen: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Diehn: Varian Medical Systems: Research Funding; Roche: Consultancy; Novartis: Consultancy; Quanticel Pharmaceuticals: Consultancy. Alizadeh: Genentech: Consultancy; Celgene: Consultancy; CiberMed: Consultancy; Roche: Consultancy; Gilead: Consultancy.

7507 Background: Somatic copy number alterations (SCNAs) are common and clinically important genomic events in lymphomas. For example, MYC and BCL2 amplifications are associated with adverse outcomes (Quesada, ASH 2016), while PD-L1 ( CD274) amplifications are associated with improved response to checkpoint inhibitors (Ansell, NEJM 2015). However, noninvasive detection of these events from circulating tumor DNA (ctDNA) remains difficult. Using CAPP-Seq, a targeted high-throughput sequencing platform, we developed a method to profile both focal and broad SCNAs from plasma. Methods: We profiled plasmas from a cohort of 75 pretreatment diffuse large B-cell lymphoma patients and 48 healthy controls. Focal SCNAs were evaluated at ultra-high depths (~10,000x), allowing for detection of lesions at ~1% ctDNA fraction. Thresholds were tuned to allow a false positive rate of 1%, which was empirically validated in an independent healthy cohort (n = 15), yielding a panel-wide false discovery rate of ~2.3% (0% in our genes of interest). Sequencing reads outside the targeted regions were separately pooled and analyzed to evaluate arm and chromosome level SCNAs. Results: We detected SCNAs in clinically relevant genes at the frequencies reported in literature, including amplifications in MYC (8.0%), BCL2 (24.0%), and BCL6 (14.7%) and deletions in TP53 (13.3%) and CDKN2A (9.3%). Remarkably, 26.7% of the cohort demonstrated amplification of both PD-L1 and PD-L2 ( PDCD1LG2). Furthermore, we discovered amplifications in PD-L2, but not PD-L1, in 13.3% of our patients. Interestingly, PD-L1 amplifications were more common in patients with relapsed lymphoma than in those with treatment-naïve disease (43.5% vs 19.2%, p = 0.02). Most PD-L1 amplifications were focal (65%) while the remainder typically involved > 80% of Chr9p. Corresponding tissue profiling data is in progress and will also be presented. Conclusions: Noninvasive sampling of lymphoma ctDNA enables detection of both focal and broad SCNAs, including amplifications of MYC, BCL2, and PD-L1. The ability to noninvasively profile copy number altered regions allows for biopsy-free discovery of clinically significant structural alterations in lymphoma patients.

7538 Background: Patients with diffuse large B cell lymphoma (DLBCL) exhibit significant differences in clinical outcome based on cell-of-origin (COO). Patients are categorized as having germinal-center-like (GCB) or activated-B-cell-like (ABC) disease based on RNA microarray and histopathological analyses of tumor biopsies. We recently described an accurate sequencing-based method for determination of COO in DLBCL utilizing stereotyped differences in mutations (Scherer et al., 2016). Here, we further explore the mutational patterns in patients with differing molecular subtypes of DLBCL based on sequencing of circulating tumor DNA. Methods: We applied cancer personalized profiling by deep sequencing (CAPP-Seq) to pretreatment plasma samples and matched germline from a cohort of 115 patients with DLBCL. We then identified somatic alterations, which were used to determine COO molecular subtypes as previously described. Finally, we compared mutational patterns in patients with GCB and non-GCB DLBCL. Results: We detected a significantly greater number of total mutations (GCB: 1766 ± 160 mutations per Mb of targeted sequencing; non-GCB: 1364 ± 150 mutations per Mb of targeted sequencing; p < 0.05) and coding mutations (GCB: 145 ± 21 mutations per Mb of targeted sequencing; non-GCB: 28 ± 8.5 mutations per Mb of targeted sequencing; p < 0.001), particularly in immunoglobulin (Ig) regions (p < 0.05). In addition, GCB and non-GCB samples exhibited distinct mutational patterns within Ig regions. GCB samples were enriched for mutations in regions of switch mu (Sμ) (p < 0.01) and IGHV2-70 (p < 0.01), while non-GCB samples were enriched for mutations in regions of IGHG3 (p < 0.03), IGHV4-34 (p < 0.03), and IGLL5 (p < 0.05). GCB samples were also significantly enriched for coding mutations in SOCS1 (p < 0.01), a gene not included in our original COO classifier. Conclusions: Patients with GCB and non-GCB DLBCL exhibit distinct mutational patterns across both Ig and non-Ig loci of the genome. These differences in mutational patterns can be used to classify molecular subtypes noninvasively, potentially providing further utility to noninvasive genotyping and liquid biopsies.

Summary: Oral lichen planus (OLP) is an immune-mediated mucocutaneous disease associated with an increased risk in oral squamous cell carcinoma (OSCC). Nearly all cases of malignant transformation have been reported in patients >40 years old. We report the case of a 37-year-old woman with a 5-year history of erosive OLP who presented with malignant transformation to OSCC. Delineating the margins of the disease was impossible at presentation given her OLP, and she was initially treated with concurrent chemoradiation therapy. She then developed a recurrence of the mandibular alveolar ridge. The patient was successfully treated with a composite resection including a segmental mandibulectomy, buccal mucosa resection, partial glossectomy, and ipsilateral neck dissection. This was reconstructed with a free fibula osteo-septo-cutaneous flap. Mandibular OSCC is a rare complication of OLP with few reports on effective reconstructive interventions. The case represents the youngest reported patient with mandibular OSCC arising in the context of OLP and highlights the utility of the free vascularized fibula graft in the treatment of these patients.