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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

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Supplemental methods

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Supplemental Tables S1-S12

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Supplementary Figures related to Figures 1, 2, 3, and 4.

Table S2: Surveillance plasma sample ctDNA metrics. Table S3: Baseline plasma sample ctDNA metrics. Table S4: Surveillance plasma sample variants in ctDNA detected samples. Table S5: Baseline plasma variants in available samples. Table S6: Tumor variants detected by whole exome and targeted sequencing. Table S7: Canonical genes implicated in clonal hematopoiesis.

Table S1 shows summary patient demographics, pathologic features, and treatment details

Purpose:Treatment with PD-(L)1 blockade can produce remarkably durable responses in patients with non–small cell lung cancer (NSCLC). However, a significant fraction of long-term responders ultimately progress and predictors of late progression are unknown. We hypothesized that circulating tumor DNA (ctDNA) analysis of long-term responders to PD-(L)1 blockade may differentiate those who will achieve ongoing benefit from those at risk of eventual progression.Experimental Design:In patients with advanced NSCLC achieving long-term benefit from PD-(L)1 blockade (progression-free survival ≥ 12 months), plasma was collected at a surveillance timepoint late during/after treatment to interrogate ctDNA by Cancer Personalized Profiling by Deep Sequencing. Tumor tissue was available for 24 patients and was profiled by whole-exome sequencing (n = 18) or by targeted sequencing (n = 6).Results:Thirty-one patients with NSCLC with long-term benefit to PD-(L)1 blockade were identified, and ctDNA was analyzed in surveillance blood samples collected at a median of 26.7 months after initiation of therapy. Nine patients also had baseline plasma samples available, and all had detectable ctDNA prior to therapy initiation. At the surveillance timepoint, 27 patients had undetectable ctDNA and 25 (93%) have remained progression-free; in contrast, all 4 patients with detectable ctDNA eventually progressed [Fisher P < 0.0001; positive predictive value = 1, 95% confidence interval (CI), 0.51–1; negative predictive value = 0.93 (95% CI, 0.80–0.99)].Conclusions:ctDNA analysis can noninvasively identify minimal residual disease in patients with long-term responses to PD-(L)1 blockade and predict the risk of eventual progression. If validated, ctDNA surveillance may facilitate personalization of the duration of immune checkpoint blockade and enable early intervention in patients at high risk for progression.

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PURPOSE Clinical outcomes of patients with CNS lymphomas (CNSLs) are remarkably heterogeneous, yet identification of patients at high risk for treatment failure is challenging. Furthermore, CNSL diagnosis often remains unconfirmed because of contraindications for invasive stereotactic biopsies. Therefore, improved biomarkers are needed to better stratify patients into risk groups, predict treatment response, and noninvasively identify CNSL. PATIENTS AND METHODS We explored the value of circulating tumor DNA (ctDNA) for early outcome prediction, measurable residual disease monitoring, and surgery-free CNSL identification by applying ultrasensitive targeted next-generation sequencing to a total of 306 tumor, plasma, and CSF specimens from 136 patients with brain cancers, including 92 patients with CNSL. RESULTS Before therapy, ctDNA was detectable in 78% of plasma and 100% of CSF samples. Patients with positive ctDNA in pretreatment plasma had significantly shorter progression-free survival (PFS, P < .0001, log-rank test) and overall survival (OS, P = .0001, log-rank test). In multivariate analyses including established clinical and radiographic risk factors, pretreatment plasma ctDNA concentrations were independently prognostic of clinical outcomes (PFS HR, 1.4; 95% CI, 1.0 to 1.9; P = .03; OS HR, 1.6; 95% CI, 1.1 to 2.2; P = .006). Moreover, measurable residual disease detection by plasma ctDNA monitoring during treatment identified patients with particularly poor prognosis following curative-intent immunochemotherapy (PFS, P = .0002; OS, P = .004, log-rank test). Finally, we developed a proof-of-principle machine learning approach for biopsy-free CNSL identification from ctDNA, showing sensitivities of 59% (CSF) and 25% (plasma) with high positive predictive value. CONCLUSION We demonstrate robust and ultrasensitive detection of ctDNA at various disease milestones in CNSL. Our findings highlight the role of ctDNA as a noninvasive biomarker and its potential value for personalized risk stratification and treatment guidance in patients with CNSL. [Media: see text]

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.

Background: Comparison of a blood or tissue sample with a matched germline control is a key step for accurate detection of somatic mutations. This is particularly important for tracking minimal residual disease (MRD), since alterations erroneously considered to be tumor derived may lead to false detection. Use of blood leukocytes as a germline control is critical not only for appropriate censoring of constitutional allelic variants, but also for addressing those associated with clonal hematopoiesis (CH). However, such matched germline is not always available, or may be suboptimal when contaminated with tumor cells. We hypothesized that accurate tumor genotyping might be feasible without a matched germline, using a dedicated algorithmic framework relying on clonal relationships of alleles of interest (i.e., phylons). Methods: Here, we introduce RePhyNER (Recursive Phylon Nomination, Enumeration, and Recovery), an algorithm for addressing this challenge in serial liquid biopsies. RePhyNER relies on the assumption that when comparing two specimens from the same individual (e.g., before and after therapy), the genomic variants of interests (e.g., tumor somatic mutations) behave differently in their allelic levels when compared to variants needing to be censored (e.g., germline constitutional alleles or CH). Using the change in mean allelic level of all variants in ≥2 samples, RePhyNER relies on a recursive approach to test each candidate somatic variant’s corresponding change gradient against this distribution using count-based statistics. Results: We used simulations to assess the importance of multiple parameters including fraction of contaminating variants or alleles and mean allelic fold-change. These simulations showed substantially superior performance of a recursive approach and revealed that for ≥2-fold changes in the mean VAF in a pair of samples, RePhyNER accurately removed >99% of contaminating alleles while preserving ~100% of true variants. We then applied RePhyNER to 108 plasma cell-free DNA (cfDNA) samples from 47 patients with classic Hodgkin Lymphoma (cHL) profiled by PhasED-Seq and compared MRD-detection performance with or without matched germline. RePhyNER substantially improved specificity by ~30% (68% vs 99%), and Precision by ~50% (46% vs 96%), while only modestly reducing sensitivity (100% vs 91%). We next applied PhasED-Seq to a cohort of cHL patients (n=65) without matched germline information. MRD positivity within the first 2 cycles of therapy was associated with inferior outcome when using RePhyNER (P Conclusions: RePhyNER enables germline-free and accurate genotyping for MRD detection. Notably, RePhyNER obviates the need for additional germline profiling overcoming key limitations described above and avoids the additional associated costs of sequencing. Citation Format: Mohammad Shahrokh Esfahani, Stefan Alig, Emily Hamilton, Joseph Schroers-Martin, Brian Sworder, Jan Boegeholz, Mari Olsen, Chih Long Liu, David Kurtz, Maximilian Diehn, Ash Alizadeh. RePhyNER: Overcoming limitations of access to matched germline for serial liquid biopsy applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1045.

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.

Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.

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.

Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II molecules would be valuable for vaccine development and cancer immunotherapies. Current computational methods trained on in vitro binding data are limited by insufficient training data and algorithmic constraints. Here we describe MARIA (major histocompatibility complex analysis with recurrent integrated architecture; https://maria.stanford.edu/ ), a multimodal recurrent neural network for predicting the likelihood of antigen presentation from a gene of interest in the context of specific HLA class II alleles. In addition to in vitro binding measurements, MARIA is trained on peptide HLA ligand sequences identified by mass spectrometry, expression levels of antigen genes and protease cleavage signatures. Because it leverages these diverse training data and our improved machine learning framework, MARIA (area under the curve = 0.89–0.92) outperformed existing methods in validation datasets. Across independent cancer neoantigen studies, peptides with high MARIA scores are more likely to elicit strong CD4+ T cell responses. MARIA allows identification of immunogenic epitopes in diverse cancers and autoimmune disease. A neural network trained on diverse datasets improves prediction of HLA class II epitope presentation.

Single-cell RNA-sequencing has emerged as a powerful technique for characterizing cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. We previously developed an approach for digital cytometry, called CIBERSORT, that enables estimation of cell type abundances from bulk tissue transcriptomes. We now introduce CIBERSORTx, a machine learning method that extends this framework to infer cell-type-specific gene expression profiles without physical cell isolation. By minimizing platform-specific variation, CIBERSORTx also allows the use of single-cell RNA-sequencing data for large-scale tissue dissection. We evaluated the utility of CIBERSORTx in multiple tumor types, including melanoma, where single-cell reference profiles were used to dissect bulk clinical specimens, revealing cell-type-specific phenotypic states linked to distinct driver mutations and response to immune checkpoint blockade. We anticipate that digital cytometry will augment single-cell profiling efforts, enabling cost-effective, high-throughput tissue characterization without the need for antibodies, disaggregation or viable cells. CIBERSORTx, a suite of computational tools, enables inference of cell type abundance and cell-type-specific gene expression profiles from bulk RNA profiles.

Current regimens for the detection and surveillance of bladder cancer are invasive and have suboptimal sensitivity. Here, we present a novel high-throughput sequencing (HTS) method for detection of urine tumor DNA (utDNA) called utDNA CAPP-Seq (uCAPP-Seq) and apply it to 67 healthy adults and 118 patients with early-stage bladder cancer who had urine collected either prior to treatment or during surveillance. Using this targeted sequencing approach, we detected a median of 6 mutations per patient with bladder cancer and observed surprisingly frequent mutations of the PLEKHS1 promoter (46%), suggesting these mutations represent a useful biomarker for detection of bladder cancer. We detected utDNA pretreatment in 93% of cases using a tumor mutation–informed approach and in 84% when blinded to tumor mutation status, with 96% to 100% specificity. In the surveillance setting, we detected utDNA in 91% of patients who ultimately recurred, with utDNA detection preceding clinical progression in 92% of cases. uCAPP-Seq outperformed a commonly used ancillary test (UroVysion, P = 0.02) and cytology and cystoscopy combined (P ≤ 0.006), detecting 100% of bladder cancer cases detected by cytology and 82% that cytology missed. Our results indicate that uCAPP-Seq is a promising approach for early detection and surveillance of bladder cancer. Significance: This study shows that utDNA can be detected using HTS with high sensitivity and specificity in patients with early-stage bladder cancer and during post-treatment surveillance, significantly outperforming standard diagnostic modalities and facilitating noninvasive detection, genotyping, and monitoring. This article is highlighted in the In This Issue feature, p. 453

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.

Purpose: Treatment with PD-(L)1 blockade can produce remarkably durable responses in patients with non–small cell lung cancer (NSCLC). However, a significant fraction of long-term responders ultimately progress and predictors of late progression are unknown. We hypothesized that circulating tumor DNA (ctDNA) analysis of long-term responders to PD-(L)1 blockade may differentiate those who will achieve ongoing benefit from those at risk of eventual progression. Experimental Design: In patients with advanced NSCLC achieving long-term benefit from PD-(L)1 blockade (progression-free survival ≥ 12 months), plasma was collected at a surveillance timepoint late during/after treatment to interrogate ctDNA by Cancer Personalized Profiling by Deep Sequencing. Tumor tissue was available for 24 patients and was profiled by whole-exome sequencing (n = 18) or by targeted sequencing (n = 6). Results: Thirty-one patients with NSCLC with long-term benefit to PD-(L)1 blockade were identified, and ctDNA was analyzed in surveillance blood samples collected at a median of 26.7 months after initiation of therapy. Nine patients also had baseline plasma samples available, and all had detectable ctDNA prior to therapy initiation. At the surveillance timepoint, 27 patients had undetectable ctDNA and 25 (93%) have remained progression-free; in contrast, all 4 patients with detectable ctDNA eventually progressed [Fisher P < 0.0001; positive predictive value = 1, 95% confidence interval (CI), 0.51–1; negative predictive value = 0.93 (95% CI, 0.80–0.99)]. Conclusions: ctDNA analysis can noninvasively identify minimal residual disease in patients with long-term responses to PD-(L)1 blockade and predict the risk of eventual progression. If validated, ctDNA surveillance may facilitate personalization of the duration of immune checkpoint blockade and enable early intervention in patients at high risk for progression.

Korrespondenz zu 10.1200/JCO.2018.78.5246

Introduction: Clinical outcomes for patients with central nervous system lymphoma (CNSL) are remarkably heterogeneous, yet identification of patients at high risk for treatment failure remains challenging with existing methods. In addition, diagnosis of CNSL requires invasive neurosurgical biopsies that carry procedural risks and often cannot be performed in frail or elderly patients. Circulating tumor DNA (ctDNA) has shown great potential as a noninvasive biomarker in systemic lymphomas. Yet, previous studies revealed low ctDNA detection rates in blood plasma of CNSL patients. In this study, we utilized ultrasensitive targeted high-throughput sequencing technologies to explore the role of ctDNA for disease classification, MRD detection, and early prediction of clinical outcomes in patients with CNSL. Methods: We applied Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) and Phased Variant Enrichment and Detection Sequencing (PhasED-Seq, Kurtz et al, Nat Biotech 2021) to 85 tumor biopsies, 131 plasma samples, and 62 CSF specimens from 92 CNSL patients and 44 patients with other brain cancers or inflammatory cerebral diseases, targeting 794 distinct genetic regions. Concentrations of ctDNA were correlated with radiological measures of tumor burden and tested for associations with clinical outcomes at distinct clinical time points. We further developed a novel classifier to noninvasively distinguish CNS lymphomas from other CNS tumors based on their mutational landscapes in plasma and CSF, using supervised training of a machine learning approach from tumor whole genome sequencing data and own genotyping analyses, followed by its independent validation. Results: We identified genetic aberrations in 100% of CNSL tumor biopsies (n=63), with a median of 262 mutations per patient. Pretreatment plasma ctDNA was detectable in 78% of plasma samples and in 100% of CSF specimens (Fig. 1a), with ctDNA concentrations ranging from 0.0004 - 5.94% allele frequency (AF, median: 0.01%) in plasma and 0.0049 - 50.47% AF (median: 0.62%) in CSF (Fig. 1b). Compared to ctDNA concentrations in patients with systemic diffuse large B-cell lymphoma (DLBCL, data from Kurtz et al., J Clin Oncol, 2018), plasma ctDNA levels in CNSL were in median more than 200-fold lower (Fig. 1b). We observed a significant correlation of ctDNA concentrations with total radiographic tumor volumes (TRTV) measured by MRI (Fig. 1c,d), but no association with clinical risk scores (i.e., MSKCC score) or concurrent steroid treatment. Assessment of ctDNA at pretreatment time points predicted progression-free survival (PFS) and overall survival (OS), both as continuous and binary variable (Fig. 1e,f). Notably, patients could be stratified into risk groups with particularly favorable or poor prognoses by combining ctDNA and TRTV as pretreatment biomarkers (Fig. 1g). Furthermore, ctDNA positivity during curative-intent induction therapy was significantly associated with clinical outcomes, both PFS and OS (Fig. 1h). Finally, we applied our novel machine learning classifier to 207 specimens from an independent validation cohort of CNSL and Non-CNSL patients. We observed high specificity (100%) and positive predictive value (100%) for noninvasive diagnosis of CNSL, with a sensitivity of 57% for CSF and 21% for plasma, suggesting that a significant subset of CNSL patients might be able to forego invasive surgical biopsies. Conclusions: We demonstrate robust and ultrasensitive detection of ctDNA at various disease milestones in CNSL. Our findings suggest that ctDNA accurately mirrors tumor burden and serves as a valuable clinical biomarker for risk stratification, outcome prediction, and surgery-free lymphoma classification in CNSL. We foresee an important potential future role of ctDNA as a decision-making tool to guide treatment in patients with CNSL. Figure 1 Figure 1. Disclosures Esfahani: Foresight Diagnostics: Current holder of stock options in a privately-held company. Kurtz: Genentech: Consultancy; Roche: Consultancy; Foresight Diagnostics: Consultancy, Current holder of stock options in a privately-held company. Schorb: Riemser Pharma GmbH: Honoraria, Research Funding; Roche: Research Funding; AbbVie: Research Funding. Diehn: BioNTech: Consultancy; RefleXion: Consultancy; Roche: Consultancy; AstraZeneca: Consultancy; Foresight Diagnostics: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; CiberMed: Current holder of stock options in a privately-held company, Patents & Royalties; Illumina: Research Funding; Varian Medical Systems: Research Funding. Alizadeh: Foresight Diagnostics: Consultancy, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Gilead: Consultancy; Roche: Consultancy, Honoraria; Celgene: Consultancy, Research Funding; Janssen Oncology: Honoraria; CAPP Medical: 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; Cibermed: Consultancy, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Bristol Myers Squibb: Research Funding.

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.

Biological heterogeneity in diffuse large B cell lymphoma (DLBCL) is partly driven by cell-of-origin subtypes and associated genomic lesions, but also by diverse cell types and cell states in the tumor microenvironment (TME). However, dissecting these cell states and their clinical relevance at scale remains challenging. Here, we implemented EcoTyper, a machine learning framework integrating transcriptome deconvolution and single-cell RNA sequencing, to characterize clinically relevant DLBCL cell states and ecosystems. Using this approach, we identified five cell states of malignant B cells that vary in prognostic associations and differentiation status. We also identified striking variation in cell states for 12 other lineages comprising the TME and forming cell-state interactions in stereotyped ecosystems. While cell-of-origin subtypes have distinct TME composition, DLBCL ecosystems capture clinical heterogeneity within existing subtypes and extend beyond cell-of-origin and genotypic classes. These results resolve the DLBCL microenvironment at systems-level resolution and identify opportunities for therapeutic targeting (https://ecotyper.stanford.edu/lymphoma).

Cancer somatic mutations can generate neoantigens that distinguish malignant from normal cells. However, the personalized identification and validation of neoantigens remains a major challenge. Here we discover neoantigens in human mantle-cell lymphomas by using an integrated genomic and proteomic strategy that interrogates tumour antigen peptides presented by major histocompatibility complex (MHC) class I and class II molecules. We applied this approach to systematically characterize MHC ligands from 17 patients. Remarkably, all discovered neoantigenic peptides were exclusively derived from the lymphoma immunoglobulin heavy- or light-chain variable regions. Although we identified MHC presentation of private polymorphic germline alleles, no mutated peptides were recovered from non-immunoglobulin somatically mutated genes. Somatic mutations within the immunoglobulin variable region were almost exclusively presented by MHC class II. We isolated circulating CD4+ T cells specific for immunoglobulin-derived neoantigens and found these cells could mediate killing of autologous lymphoma cells. These results demonstrate that an integrative approach combining MHC isolation, peptide identification, and exome sequencing is an effective platform to uncover tumour neoantigens. Application of this strategy to human lymphoma implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.

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.

The activated B cell (ABC-like) subtype of diffuse large B cell lymphoma (DLBCL) is characterized by chronic activation of signaling initiated by immunoglobulin μ (IgM). By analyzing the DNA copy number profiles of 1000 DLBCL tumors, we identified gains of 18q21.2 as the most frequent genetic alteration in ABC-like DLBCL. Using integrative analysis of matched gene expression profiling data, we found that the TCF4 (E2-2) transcription factor gene was the target of these alterations. Overexpression of TCF4 in ABC-like DLBCL cell lines led to its occupancy on immunoglobulin (IGHM) and MYC gene enhancers and increased expression of these genes at the transcript and protein levels. Inhibition of TCF4 activity with dominant-negative constructs was synthetically lethal to ABC-like DLBCL cell lines harboring TCF4 DNA copy gains, highlighting these gains as an attractive potential therapeutic target. Furthermore, the TCF4 gene was one of the top BRD4-regulated genes in DLBCL cell lines. BET proteolysis-targeting chimera (PROTAC) ARV771 extinguished TCF4, MYC, and IgM expression and killed ABC-like DLBCL cells in vitro. In DLBCL xenograft models, ARV771 treatment reduced tumor growth and prolonged survival. This work highlights a genetic mechanism for promoting immunoglobulin signaling in ABC-like DLBCL and provides a functional rationale for the use of BET inhibitors in this disease.

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.

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.

SummaryObesity-related inflammation of metabolic tissues, including visceral adipose tissue (VAT) and liver, are key factors in the development of insulin resistance (IR), though many of the contributing mechanisms remain unclear. We show that nucleic-acid-targeting pathways downstream of extracellular trap (ET) formation, unmethylated CpG DNA, or ribonucleic acids drive inflammation in IR. High-fat diet (HFD)-fed mice show increased release of ETs in VAT, decreased systemic clearance of ETs, and increased autoantibodies against conserved nuclear antigens. In HFD-fed mice, this excess of nucleic acids and related protein antigens worsens metabolic parameters through a number of mechanisms, including activation of VAT macrophages and expansion of plasmacytoid dendritic cells (pDCs) in the liver. Consistently, HFD-fed mice lacking critical responders of nucleic acid pathways, Toll-like receptors (TLR)7 and TLR9, show reduced metabolic inflammation and improved glucose homeostasis. Treatment of HFD-fed mice with inhibitors of ET formation or a TLR7/9 antagonist improves metabolic disease. These findings reveal a pathogenic role for nucleic acid targeting as a driver of metabolic inflammation in IR.

High-throughput sequencing of circulating tumor DNA (ctDNA) promises to facilitate personalized cancer therapy. However, low quantities of cell-free DNA (cfDNA) in the blood and sequencing artifacts currently limit analytical sensitivity. To overcome these limitations, we introduce an approach for integrated digital error suppression (iDES). Our method combines in silico elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules. Individually, these two methods each improve the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq) by about threefold, and synergize when combined to yield ∼15-fold improvements. As a result, iDES-enhanced CAPP-Seq facilitates noninvasive variant detection across hundreds of kilobases. Applied to non-small cell lung cancer (NSCLC) patients, our method enabled biopsy-free profiling of EGFR kinase domain mutations with 92% sensitivity and >99.99% specificity at the variant level, and with 90% sensitivity and 96% specificity at the patient level. In addition, our approach allowed monitoring of NSCLC ctDNA down to 4 in 10(5) cfDNA molecules. We anticipate that iDES will aid the noninvasive genotyping and detection of ctDNA in research and clinical settings.

Summary Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we demonstrate that pre-treatment circulating tumor DNA (ctDNA) and peripheral CD8 T cell levels are independently associated with DCB. We further show that ctDNA dynamics after a single infusion can aid in identification of patients who will achieve DCB. Integrating these determinants, we developed and validated an entirely noninvasive multiparameter assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA-On-treatment) that robustly predicts which patients will achieve DCB with higher accuracy than any individual feature. Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICIs.

The tumor microenvironment (TME) plays critical roles in cancer development, tumor progression, and susceptibility to therapy. However, the phenotypic states and interaction patterns of its underlying cell types remain poorly understood. To address this challenge, we developed a new computational framework, EcoTyper, for large-scale dissection of cell states and cellular communities (i.e., ecosystems) from tumor genomic profiles. EcoTyper integrates single-cell RNA sequencing (scRNA-seq) with CIBERSORTx, an algorithm for bulk RNA-seq deconvolution (Newman et al., Nat Biotechnol, 2019), to identify and validate cellular states and ecosystems that reflect fundamental distinctions in TME biology. Here we applied EcoTyper to diffuse large B cell lymphoma (DLBCL), an aggressive B cell malignancy with clinically distinct molecular subtypes and several immunologically-active therapies. We sought to determine whether EcoTyper could reveal novel biological variation in the DLBCL TME linked to tumor subtypes and genotypes, therapeutic responses, and clinical outcomes. We applied our approach to define transcriptional states from 13 cell types, including malignant, immune, and stromal cells, in over 1,500 DLBCL tumors. Remarkably, nearly all cell states identified by EcoTyper were validated in independent scRNA-seq and bulk RNA-seq datasets. Moreover, many cells states reflected novel phenotypic groupings, and the majority showed strong associations with overall survival, specific mutational profiles, and tumor molecular subtypes. Additionally, by identifying DLBCL tumors with similar communities of cellular states, we defined novel cellular ecosystems, or “ecotypes”, with distinct biological characteristics and clinical outcomes. Several ecotypes showed significant enrichments in canonical or novel tumor genotypes, suggesting an evolutionary interplay between the tumor and host TME. In summary, we developed a novel computational framework to dissect the TME at scale and present the most comprehensive atlas to date of cell states and cellular communities in DLBCL. Our approach is extensible to nearly any cancer type and may lead to the development of novel diagnostics and individualized immunotherapies. Citation Format: Chloe B. Steen, Bogdan Luca, Mohammad S. Esfahani, Barzin Y. Nabet, Brian Sworder, Farshad Farshidfar, David Kurtz, Chih Long Liu, Ranjana H. Advani, Yasodha Natkunam, June H. Myklebust, Maximilian Diehn, Andrew Gentles, Ash Alizadeh, Aaron M. Newman. Landscape of tumor cell states and cellular ecosystems in diffuse large B cell lymphoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1557.

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICI) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we analyze 211 samples from 99 patients and demonstrate that pre-treatment circulating tumor DNA (ctDNA) and circulating immune profiles are independently associated with DCB. We further show that ctDNA dynamics after a single ICI infusion can identify the majority of patients who will achieve DCB. Integrating these determinants, we describe an entirely noninvasive multi-analyte assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA- On-treatment) that robustly predicted DCB, and that was validated in two independent cohorts (AUC = 0.89-0.93, PPV = 92-100%, HR = 0.04-0.11). Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICI. Citation Format: Barzin Y. Nabet, Mohammad S. Esfahani, Emily G. Hamilton, Jacob J. Chabon, Everett J. Moding, Hira Rizvi, Chloe B. Steen, Aadel A. Chaudhuri, Chih Long Liu, Angela B. Hui, Henning Stehr, Linda Goljenola, Michael C. Jin, Young-Jun Jeon, Diane Tseng, Taha Merghoub, Joel W. Neal, Heather A. Wakelee, Sukhmani K. Padda, Kavitha J. Ramchandran, Millie Das, Rene F. Bonilla, Christopher Yoo, Emily L. Chen, Ryan B. Ko, Aaron M. Newman, Matthew D. Hellmann, Ash A. Alizadeh, Maximilian Diehn. A noninvasive approach for early prediction of therapeutic benefit from immune checkpoint inhibition for lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5666.