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3072 Background: The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) previously demonstrated that a blood-based multi-cancer early detection (MCED) test utilizing cell-free DNA (cfDNA) sequencing in combination with machine learning could detect cancer signals across multiple cancer types and predict cancer signal origin. Cancer classes were defined within the CCGA study for sensitivity reporting. Separately, cancer types defined by the American Joint Committee on Cancer (AJCC) criteria, which outline unique staging requirements and reflect a distinct combination of anatomic site, histology and other biologic features, were assigned to each cancer participant using the same source data for primary site of origin and histologic type. Here, we report CCGA ‘cancer class’ designation and AJCC ‘cancer type’ assignment within the third and final CCGA3 validation substudy to better characterize the diversity of tumors across which a cancer signal could be detected with the MCED test that is nearing clinical availability. Methods: CCGA is a prospective, multicenter, case-control, observational study with longitudinal follow-up (overall population N = 15,254). Plasma cfDNA from evaluable samples was analyzed using a targeted methylation bisulfite sequencing assay and a machine learning approach, and test performance, including sensitivity, was assessed. For sensitivity reporting, CCGA cancer classes were assigned to cancer participants using a combination of the type of primary cancer reported by the site and tumor characteristics abstracted from the site pathology reports by GRAIL pathologists. Each cancer participant also was separately assigned an AJCC cancer type based on the same source data using AJCC staging manual (8th edition) classifications. Results: A total of 4077 participants comprised the independent validation set with confirmed status (cancer: n = 2823; non-cancer: n = 1254 with non-cancer status confirmed at year-one follow-up). Sensitivity was reported for 24 cancer classes (sample sizes ranged from 10 to 524 participants), as well as an “other” cancer class (59 participants). According to AJCC classification, the MCED test was found to detect cancer signals across 50+ AJCC cancer types, including some types not present in the training set; some cancer types had limited representation. Conclusions: This MCED test that is nearing clinical availability and was evaluated in the third CCGA substudy detected cancer signals across 50+ AJCC cancer types. Reporting CCGA cancer classes and AJCC cancer types demonstrates the ability of the MCED test to detect cancer signals across a set of diverse cancer types representing a wide range of biologic characteristics, including cancer types that the classifier has not been trained on, and supports its use on a population-wide scale. Clinical trial information: NCT02889978.

3052 Background: Cell-free DNA (cfDNA) tumor fraction (TF), the proportion of tumor molecules in a cfDNA sample, is a direct measurement of signal for cfDNA cancer applications. The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) is a prospective, multi-center, observational, case-control study designed to support development of a methylation-based, multi-cancer detection test in which a classifier is trained to distinguish cancer from non-cancer. Here we leveraged CCGA data to examine the relationship between cfDNA containing tumor DNA methylation patterns, TF, and cancer classification performance. Methods: The CCGA classifier was trained on whole-genome bisulfite sequencing (WGBS) and targeted methylation (TM) sequencing data to detect cancer versus non-cancer. 822 samples had biopsy WGBS performed; of those, 231 also had cfDNA targeted methylation (TM) and cfDNA whole-genome sequencing (WGS). Biopsy WGBS identified somatic single nucleotide variants (SNV) and methylation variants (MV; defined as methylation patterns in sequenced DNA fragments observed commonly in biopsy but rarely [ < 1/10,000] in the cfDNA of non-cancer controls [n = 898]). Observed tumor fragment counts (SNV in WGS; MV in TM), were modeled as a Poisson process with rate dependent on TF. TF and classifier limits of detection (LOD) were each assessed using Bayesian logistic regression. Results: Across biopsy samples, a median of 2,635 MV was distributed across the genome, with a median of 86.8% shared with ≥1 participant, and a median of 69.3% targeted by the TM assay. TF LOD from MV was 0.00050 (95% credible interval [CI]: 0.00041 - 0.00061); MV and SNV estimates were concordant (Spearman’s Rho: 0.820). MV TF estimates explained classifier performance (Spearman’s Rho: 0.856) and allowed determination of the classifier LOD (0.00082 [95% CI: 0.00057 - 0.00115]). Conclusions: These data demonstrate the existence of methylation patterns in tumor-derived cfDNA fragments that are rarely found in individuals without cancer; their abundance directly measured TF, and was a major factor influencing classification performance. Finally, the low classifier LOD (~0.1%) motivates further clinical development of a methylation-based assay for cancer detection. Clinical trial information: NCT02889978 .

243 Background: Circulating Cell-free Genome Atlas (CCGA; NCT02889978) is a multi-center, case-control, observational study with longitudinal follow-up to develop a cfDNA assay in which classifiers were trained on whole-genome bisulfite sequencing (WGBS) and targeted methylation (TM) sequencing data for detection of multiple cancer types. Previously, we showed that the fraction of ctDNA fragments (TF) was a stronger predictor of cancer detection than clinical stage and an equivalent predictor for survival. Given that CRC tumors can be described via surface area (TSA) and microscopic tumor extent (microinvasion), CRC was used as a model to examine the biophysical determinants of TF. Methods: Detection of multiple cancers with WGBS at 98% and TM at > 99% specificity, and methods for determining TF, were previously reported. A model to predict the presence of detectable cfDNA fragments for CRC adenocarcinomas of stages I, II, and III included TSA and microinvasion beyond the subserosa. Predictors were combined assuming a linear increase of cfDNA shedding with tumor size, with scaling factors depending on microinvasion. Model parameters were determined for 27 participants (7, 11, 9 for stages I, II, III, resp.) with WGBS and applied to 40 participants (12, 15, 13 for I, II, III, resp.) with TM assay and information on tumor size and microinvasion. Results: CRC detection at stages I/II/III was 33/46, 61/73, 57/74% for WGBS/TM. TF predicted detection with AUC = 97.6. The model predicted TF as TSA multiplied by 3.81*10−6 / mm2 for tumors that invaded beyond the subserosa (p < 0.001). This was 4.4x higher than estimates for tumors below the subserosa. The model trained on the WGBS assay predicted CRC detection in the TM assay with an AUC of 0.844. Conclusions: This model used TSA (number of tumor cells) and microinvasion (bloodstream access) to predict the fraction of CRC ctDNA fragments in blood without needing to account for stage. Tumors not penetrating the subserosa had low ctDNA shedding that likely limited detection. These findings may generalize to other cancer types, providing principles to predict ctDNA shedding and thus cancer detectability based on microinvasion and surface area. 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.

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.

12003Background: CHIP is defined by the presence of age-dependent acquired mutations in hematopoietic progenitor cells and has been reported to occur in up to 30% of individuals 60-70 years of age....

536Background: New breast cancer screening approaches are needed to detect clinically aggressive subtypes that may not be detected by mammography or are detected late in unscreened populations. CCG...

11526 Background: A large fraction of cfDNA fragments are derived from hematopoietic sources. Somatic alterations in cfDNA can be tumor-derived but also could represent somatic changes associated with clonal hematopoiesis. We performed deep sequencing of both plasma cfDNA and matched white blood cell (WBC) genomic DNA (gDNA) to determine the contribution of clonal hematopoiesis to the variants observed in cfDNA. Four cohorts were investigated: metastatic breast (BC), non-small cell lung (NSCLC), castration-resistant prostate cancer (CRPC), and non-cancer participants (pts). Methods: Metastatic cancer pts with de novo or progressive disease were prospectively enrolled. Non-cancer pts were blood bank donors. Plasma cfDNA and matched WBC gDNA were sequenced using a targeted 508-gene panel (2 Mb) to > 60,000X raw depth. Variant calling used a novel pipeline that employed molecular barcoding for error suppression followed by de novo assembly and graph-based variant calling. Results: Of 151 metastatic cancer pts (48 BC, 49 NSCLC, 54 CRPC), median age was 64 (30-87) with 53% female and 33% treatment naive. Of 47 non-cancer pts, median age was 61 (20-78) with 51% female. Analysis of cfDNA identified 1072 variants (AF > 0.1%, > 2 mutant reads, passing bioinformatic quality filters) which were also detected in WBC gDNA as non-germline ( < 35% allele frequency [AF]) non-synonymous variants. For these cfDNA variants, AF ranged from 0.1-14.4% and correlated with AF in WBC gDNA (r2 = 0.47, p < 0.001). Mutated genes were consistent with clonal hematopoiesis, with the most frequently mutated genes being DNMT3A, TET2, PPM1D, and TP53 (215, 77, 45, and 36 variants, respectively). For both cancer and non-cancer pts (age > 45), median number of overlapping variants was 5 per pt (range 0-22). The number of WBC gDNA and cfDNA variants per individual was positively associated with age (p < 0.001) in both cancer and non-cancer pts (interaction p = 0.08). Conclusions: Somatic cfDNA variants are frequently derived from clonal hematopoiesis and increase with age. Accurate assessment of somatic alterations in cfDNA should account for this phenomenon to distinguish between tumor-derived and WBC-derived variants.