Oxnard, Geoffrey R.

TPS9077 Background: ALCHEMIST (Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trial) is a clinical trial platform of the National Cancer Institute that offers biomarker analysis for high-risk resected non-small cell lung cancer (NSCLC) to support randomized trials of novel adjuvant therapies within the National Clinical Trials Network (NCTN). EA5142, a trial of adjuvant nivolumab for patients (pts) without EGFR / ALK alterations, has completed enrollment. Given the survival benefit seen with 1st-line chemo-immunotherapy (chemo-IO) for advanced NSCLC without EGFR / ALK alterations, there was compelling rationale for the launch of a trial offering concurrent immunotherapy with adjuvant chemo. Here we report updated enrollment to ALCHEMIST as of Jan 14, 2020. Methods: ALCHEMIST includes a screening trial (A151216, 5362 registered) that enrolls pts with completely resected clinical stage IB (≥4 cm)–IIIA (per AJCC 7) NSCLC. Tissue and blood are collected, biomarker testing includes EGFR sequencing, ALK FISH and PD-L1 IHC. 733 active sites are enrolling across the NCTN. Pts with EGFR mutations may enroll to adjuvant erlotinib vs observation (A081105, 352 randomized); those with ALK fusions may enroll to adjuvant crizotinib vs observation (E4512, 99 randomized). A trial offering adjuvant nivolumab vs observation regardless of PD-L1 status (EA5142, 935 randomized) recently completed enrollment. To support ongoing investigation of adjuvant immunotherapy, ALCHEMIST is adding A081801 (opens spring 2020). Pts will be randomized to one of 3 arms: chemo-IO with pembrolizumab during and after chemo vs sequential chemo followed by pembrolizumab vs chemo alone. Pts with pathological N2 nodes are eligible and can undergo postoperative radiotherapy after completing chemo. Pts are eligible if enrolled to A151216, negative for EGFR and ALK alterations, and with PD-L1 testing completed (required for stratification). Local testing for EGFR, ALK and PD-L1 will be accepted for enrollment; central testing will not delay randomization. Pts may not have received any therapy except surgery for the lung cancer and must be age >18, Eastern Cooperative Oncology Group performance status 0-1, have no active autoimmune disease requiring systemic treatment within 2 years, must not be pregnant or nursing, have no active second malignancy within 3 years and meet standard organ function values. By building off the ongoing ALCHEMIST platform, we hope to facilitate rapid enrollment to A081801 across participating NCTN sites. Clinical trial information: NCT02194738.

44 Background: A noninvasive cfDNA blood test detecting multiple cancers at earlier stages could decrease cancer mortality. In earlier discovery work, whole-genome bisulfite sequencing outperformed whole-genome and targeted sequencing approaches for multi-cancer detection across stages at high specificity. Here, multi-cancer detection and TOO localization using bisulfite sequencing of plasma cfDNA to identify methylomic signatures was evaluated in preparation for clinical validation, utility, and implementation studies. Methods: 2301 analyzable participants (1422 cancer [ > 20 tumor types, all stages], 879 non-cancer) were included in this prespecified substudy from the Circulating Cell-free Genome Atlas (CCGA) (NCT02889978) study - a prospective, multi-center, observational, case-control study with longitudinal follow-up. Plasma cfDNA was subjected to a targeted methylation sequencing assay using high-efficiency methylation chemistry to enrich for methylation targets, and a machine learning classifier determined cancer status and tissue of origin (TOO). Observed methylation fragments characteristic of cancer and TOO were combined across targeted regions and assigned a relative probability of cancer and of a specific TOO. Results: Performance is reported at 99% specificity (ie, a combined false positive rate across all cancer types of 1%), a level required for population-level screening. Across cancer types, sensitivity ranged from 59 to 86%. Combined cancer detection (sensitivity [95% CI]) was 34% (27-43%) in stage I (n = 151), 77% (70-83%) in stage II (n = 171), 84% (79-89%) in stage III (n = 204), and 92% (88-95%) in stage IV (n = 281). TOO was provided for 94% of all cancers detected; of these, TOO was correct in > 90% of cases. Conclusions: Detection of multiple deadly cancers across stages using methylation signatures in plasma cfDNA was achieved with a single, fixed, low false positive rate, and simultaneously provided accurate TOO localization. This targeted methylation assay is undergoing validation in preparation for prospective clinical investigation as a cancer detection diagnostic. Clinical trial information: NCT02889978.

5574 Background: A noninvasive cell-free DNA (cfDNA)-based cancer detection assay offers the hope of a blood test that might reduce morbidity and mortality of cancers, particularly those without recommended screening tests (eg, some gynecologic cancers). CCGA (NCT02889978) is a prospective, multi-center, longitudinal, case-control study evaluating models for discriminating cancer versus non-cancer. Here, we report F/U of control participants (pts) who demonstrated a cancer-signal in CCGA. Methods: Clinically evaluable samples (N = 2508) from pts enrolled without a cancer diagnosis (dx; NC) and treatment-naive pts with newly diagnosed cancer (C) were divided into training (n = 1564; 580 NC, 984 C) and test (n = 944; 368 NC, 576 C) sets. Classification performance (cancer/non-cancer) was assessed via 3 prototype assays: whole-genome bisulfite (WGBS), whole-genome (WGS), and targeted (507 gene) sequencing. Notable outlier NC pts were identified with cancer-like scores in either ≥2 assay classification results or by the presence of known cancer drivers with ≥1 assay classification result suggesting cancer. All pts are currently in F/U in accordance with study protocol (to date: 80% with > 10 mo and 15% with > 22 mo F/U). Results: Among training and test sets, 8 ( < 1%) NC pts were identified with a cancer-like signal. To-date, 2 have been diagnosed with a gynecologic malignancy: 1 stage IIIc clear cell endometrial carcinoma and 1 stage IIIc ovarian cancer, 3 and 2 months (mo) post-enrollment [PE], respectively. Among C pts in the study, sensitivity (at 98% specificity; WGBS) in these cancer types was: uterine/endometrial: 11% (n = 27 train) and 22% (n = 9 test); ovarian: 82% (n = 17) and 71% (n = 7). In addition, a third NC pt was diagnosed with a stage IV lung cancer 15 mo PE. Conclusions: This cfDNA-based assay detected a cancer-like signal that anticipated a clinical presentation of cancer in undiagnosed pts as early as 15 months prior to the actual dx. High specificity ( > 99%) requires accounting for undiagnosed cancers in study design and analysis. Together, these data suggest that this prototype assay may have high performance detecting a variety of gynecological and other cancers. Clinical trial information: NCT02889978.

3049 Background: For multi-cancer detection using cfDNA, TOO determination is critical to enable safe and efficient diagnostic follow-up. Previous array-based studies captured < 2% of genomic CpGs. Here, we report genome-wide fragment-level methylation patterns across 811 cancer cell methylomes representing 21 tumor types (97% of SEER cancer incidence), and define effects of this methylation database on TOO prediction within a machine learning framework. Methods: Genomic DNA from 655 formalin-fixed paraffin-embedded (FFPE) tumor tissues and 156 isolated cells from tumors was subjected to a prototype 30x whole-genome bisulfite sequencing (WGBS) assay, as previously reported in the Circulating Cell-free Genome Atlas (CCGA) study (NCT02889978). Two independent TOO models, one with and one without the methylation database, were fitted on training samples; each was used to predict on the test set. A WGBS classifier was used to detect cancer at 98% specificity; reported TOO results reflect percent agreement between predicted and true TOO among those detected cancers (166 cases: 81 stage I-III, 69 stage IV, 16 non-informative). Results: Genome-wide methylation data generated from this database allowed fragment-level analysis and coverage of ~30 million CpGs across the genome (~60-fold greater than array-based approaches). Incorrect TOO assignments decreased by 35% (20% to 13%) after incorporating methylation database information into TOO classification. Improvement was observed across all cancer types and was consistent in early-stage cancers (stage I-III). Respective performances in breast cancer (n = 23) were 87% vs 96%; in lung cancer (n = 32) were 85% vs 88%; in hepatobiliary (n = 10) were 70% vs 90%; and in pancreatic cancer (n = 17) were 94% vs 100%. Results using an optimized approach informed by these results in a large cohort of CCGA participants will be reported. Conclusions: Incorporating data from a large methylation database improved TOO performance in multiple cancer types. This supports feasibility of this methylation-based approach as an early cancer detection test across cancer types. Clinical trial information: NCT02889978.

1545 Background: Screening tests for early cancer detection are often criticized due to risk of overdiagnosis—detection of good prognosis cancers which may not require immediate treatment. We recently reported development of cfDNA sequencing approaches for cancer detection; longitudinal follow-up (F/U) data were utilized here to evaluate prognostic significance of cancer detection using cfDNA. Methods: Plasma cfDNA samples were subjected to whole-genome bisulfite sequencing (WGBS, 30X) as part of a previously-reported Circulating Cell-free Genome Atlas (CCGA; NCT02889978) substudy. This exploratory analysis evaluated the overall survival (OS) of training and test set participants (pts) with cancer (20 cancer types, any stage I-IV). Combining train and test set pts, univariate and multivariate analyses (Cox proportional hazards) assessed OS association with WGBS result (cancer detected vs not detected, set at 98% specificity), clinical stage (IV vs I-III), diagnostic method (symptom- vs screen-detected), sex, age, and histologic grade. Results: Of 827 pts from the training set with F/U (median 12.2 mo), 334 (40.4%) had WGBS-detected cancer. Among 127 (15.4%) pts with cancer that died during F/U, cancer was detected in 104 (81.9%). Results were similar in the test set. In univariate analyses all variables were associated with prognosis, including WGBS result (HR 7.7 p<0.001). In multivariate analyses accounting for other covariates, the three variables that most significantly remained prognostic were WGBS (HR 3.0, p<0.001), clinical stage (HR 3.3, p<0.001), and diagnostic method (HR 3.0, p<0.001). Validation of these findings is ongoing in an independent cohort of ~5,000 cancer pts from CCGA using an optimized assay; updated performance results will be reported. Conclusions: Cancers detected using WGBS of cfDNA had a worse prognosis than cancers not detected. WGBS cancer detection carried comparable prognostic significance as clinical stage. By preferentially detecting higher risk cancers, cancer detection using plasma cfDNA may avoid some of the overdiagnosis that has been seen with some existing cancer screening methods. Clinical trial information: NCT02889978.

Abstract CCGA [NCT02889978] is the largest study of cfDNA-based early cancer detection; the first CCGA learnings from multiple cfDNA assays are reported here. This prospective, multi-center, observational study has enrolled 10,012 of 15,000 demographically-balanced participants at 141 sites. Blood was collected from participants with newly diagnosed therapy-naive cancer (C, case) and participants without a diagnosis of cancer (noncancer [NC], control) as defined at enrollment. This preplanned substudy included 878 cases, 580 controls, and 169 assay controls (n=1627) across 20 tumor types and all clinical stages. All samples were analyzed by: 1) Paired cfDNA and white blood cell (WBC)-targeted sequencing (60,000X, 507 gene panel); a joint caller removed WBC-derived somatic variants and residual technical noise; 2) Paired cfDNA and WBC whole-genome sequencing (WGS; 35X); a novel machine learning algorithm generated cancer-related signal scores; joint analysis identified shared events; and 3) cfDNA whole-genome bisulfite sequencing (WGBS; 34X); normalized scores were generated using abnormally methylated fragments. In the targeted assay, non-tumor WBC-matched cfDNA somatic variants (SNVs/indels) accounted for 76% of all variants in NC and 65% in C. Consistent with somatic mosaicism (i.e., clonal hematopoiesis), WBC-matched variants increased with age; several were non-canonical loss-of-function mutations not previously reported. After WBC variant removal, canonical driver somatic variants were highly specific to C (e.g., in EGFR and PIK3CA, 0 NC had variants vs 11 and 30, respectively, of C). Similarly, of 8 NC with somatic copy number alterations (SCNAs) detected with WGS, 4 were derived from WBCs. WGBS data revealed informative hyper- and hypo-fragment level CpGs (1:2 ratio); a subset was used to calculate methylation scores. A consistent “cancer-like” signal was observed in &lt;1% of NC participants across all assays (representing potential undiagnosed cancers). An increasing trend was observed in NC vs stages I-III vs stage IV (nonsyn. SNVs/indels per Mb [Mean±SD] NC: 1.01±0.86, stages I-III: 2.43±3.98; stage IV: 6.45±6.79; WGS score NC: 0.00±0.08, I-III: 0.27±0.98; IV: 1.95± 2.33; methylation score NC: 0±0.50; I-III: 1.02±1.77; IV: 3.94±1.70). These data demonstrate the feasibility of achieving &gt;99% specificity for invasive cancer, and support the promise of cfDNA assay for early cancer detection. Additional data will be presented on detected plasma:tissue variant concordance and on multi-assay modeling. Citation Format: Alexander A. Aravanis, Geoffrey R. Oxnard, Tara Maddala, Earl Hubbell, Oliver Venn, Arash Jamshidi, Ling Shen, Hamed Amini, John A. Beausang, Craig Betts, Daniel Civello, Konstantin Davydov, Saniya Fazullina, Darya Filippova, Sante Gnerre, Samuel Gross, Chenlu Hou, Roger Jiang, Byoungsok Jung, Kathryn Kurtzman, Collin Melton, Shivani Nautiyal, Jonathan Newman, Joshua Newman, Cosmos Nicolaou, Richard Rava, Onur Sakarya, Ravi Vijaya Satya, Seyedmehdi Shojaee, Kristan Steffen, Anton Valouev, Hui Xu, Jeanne Yue, Nan Zhang, Jose Baselga, Rosanna Lapham, Daron G. Davis, David Smith, Donald Richards, Michael V. Seiden, Charles Swanton, Timothy J. Yeatman, Robert Tibshirani, Christina Curtis, Sylvia K. Plevritis, Richard Williams, Eric Klein, Anne-Renee Hartman, Minetta C. Liu. Development of plasma cell-free DNA (cfDNA) assays for early cancer detection: first insights from the Circulating Cell-Free Genome Atlas Study (CCGA) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-343.

LBA8501 Background: Plasma cfDNA genomic analysis is used widely for the care of advanced lung cancer, but its suitability for early stage lung cancer detection is not well established. CCGA (NCT02889978) is a prospective, multi-center, observational study launched for the development of a noninvasive assay for cancer detection. Methods: Blood was prospectively collected (N = 1627) from 749 controls (no cancer diagnosis) and 878 participants (pts) with newly-diagnosed untreated cancer in this preplanned substudy, including 127 pts with lung cancer. Three prototype sequencing assays were performed: paired cfDNA and white blood cell (WBC) targeted sequencing (507 genes, 60,000X) for single nucleotide variants/indels; paired cfDNA and WBC whole genome sequencing (WGS) for copy number variation (30X); and cfDNA whole genome bisulfite sequencing (WGBS) for methylation (30X). For each assay, a classification model using 10-fold cross-validation was developed for all pts with cancer, then evaluated in the pts with lung cancer; sensitivity was estimated at 95% specificity. Results: We evaluated pts with lung cancer (127) and a subset of controls (580) with similar ages (mean±SD yrs: 67±9, 60±13), 85% and 43% were ever-smokers, and 46% and 22% were men, respectively. Of 3055 nonsynonymous mutations detected across 122 evaluable pts with lung cancer, > 50% were detected in WBC consistent with clonal hematopoiesis (CH). Accounting for CH, sensitivity in 63 stage I-IIIA pts evaluable across all 3 assays was 48% (35-61, targeted), 54% (41-67, WGS), and 56% (43-68, WGBS); in 54 stage IIIB-IV pts it was 85% (73-93, targeted), 91% (80-97, WGS), and 93% (82-98, WGBS) . Similar sensitivities were observed across histological subtypes (adenocarcinoma, squamous cell, small cell). Comparison to tumor WGS and multi-assay classification will be reported. Conclusions: Early stage lung cancers are detectable in cfDNA using a genome-wide sequencing approach. For lung cancer detection using targeted assays, CH must be accounted for to minimize false positives. Assay optimization is ongoing to allow further clinical development in the intended use population. Clinical trial information: NCT02889978.

Abstract The treatment of patients with metastatic non–small cell lung cancer (NSCLC) is slowly evolving from empirical cytotoxic chemotherapy to personalized treatment based on specific molecular alterations. Despite this 10-year evolution, targeted therapies have not been studied adequately in patients with resected NSCLC who have clearly defined actionable mutations. The advent of next-generation sequencing has now made it possible to characterize genomic alterations in unprecedented detail. The efforts begun by The Cancer Genome Atlas project to understand the complexities of the genomic landscape of lung cancer will be supplemented further by studying a large number of tumor specimens. The Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trial (ALCHEMIST) is an NCI-sponsored national clinical trials network (NCTN) initiative to address the needs to refine therapy for early-stage NSCLC. This program will screen several thousand patients with operable lung adenocarcinoma to determine whether their tumors contain specific molecular alterations [epidermal growth factor receptor mutation (EGFR) and anaplastic lymphoma kinase rearrangement (ALK)], making them eligible for treatment trials that target these alterations. Patients with EGFR mutation or ALK gene rearrangement in their tumor will be randomized to placebo versus erlotinib or crizotinib, respectively, after completion of their standard adjuvant therapy. ALCHEMIST will also contain a large discovery component that will provide an opportunity to incorporate genomic studies to fully understand the clonal architecture, clonal evolution, and mechanisms of resistance to therapy. In this review, we describe the concept, rationale, and outline of ALCHEMIST and the plan for genomic studies in patients with lung adenocarcinoma. Clin Cancer Res; 21(24); 5439–44. ©2015 AACR.