Search

Introduction: Confounding signals originating from white blood cells (WBCs) have been reported as a potential source of false positives for blood-based early cancer detection and disease monitoring. Additionally, the level of aberrant signal originating from clonal expansion (CE) in precursor conditions, such as monoclonal B-cell lymphocytosis (MBL) and monoclonal gammopathy of undetermined significance (MGUS), is not well understood. To characterize CE in a potential screening population, we profiled samples from non-cancer (NC) participants and compared them to samples from participants with hematological precursor and neoplastic conditions (HPNCs). Methods: Using LymphoTrack IGH FR1 Assay (Invivoscribe, Inc), we sequenced DNA derived from WBCs from a subset of enrollees in the Circulating Cancer Genome Atlas study (NCT02889978) comprising NC participants, balanced for age and gender, and participants diagnosed with an HPNC (chronic lymphocytic leukemia [CLL], multiple myeloma [MM], MBL, or MGUS). Additional samples were titrated and processed to determine the limit of quantification (LoQ). Results: Using 12 titration samples, we determined the LoQ of detecting an unknown clone against a polyclonal background to be 0.1% of the total reads. The threshold used to determine evidence of CE was 2.5% of the total reads. We sequenced samples from 112 individuals, 67 of whom were NC participants (35 male of median [range] age 67 [33-85] years; 32 female of 60 [30-85] years). A large fraction of NC samples (10/67; 15%) showed evidence of CE: 9/10 (90%) were monoclonal with clonal percent total reads (PTR) ranging from 2.7% to 80.4% (median: 6.0%), and 7/9 had a mutation rate >2%, indicating somatic hypermutation (SHM). One sample exhibited oligoclonality with 2 clones (6.6% and 3.2%), and both had SHM. Most NC samples (57/67; 85%) lacked evidence of CE: median top clone PTR of 0.10% (mean: 0.18%; SD: 0.24%) and median Simpson clonality of 0.0021 (mean: 0.0030; SD: 0.0030). A positive correlation between the top clone PTR and age was also observed (⍴=0.41 all participants, ⍴=0.43 excluding 80.4% PTR). All CLL samples (9/11 monoclonal; 2/11 oligoclonal) and 3/4 MBL samples showed evidence of CE. Consistent with the observation that a limited number of plasma cells are expected to be in circulation, only 3/10 MM samples and 7/20 MGUS samples showed evidence of CE; 1 MM and 3 MGUS samples had a top clone PTR of >40%. Conclusion: A large fraction of NC samples (15%) had evidence of expanded lymphoid clones with SHM. The PTR of the top clone underscores the higher frequency of CE associated with increased age in asymptomatic participants. Clonal expansion of blood cell lineages can also carry genetic or epigenetic alterations that are similar to those associated with non-hematologic cancers. Thus, differentiating aberrant signals originating from various hematologic compartments is key for accurate early cancer detection. Citation Format: Jing Xiang, Qinwen Liu, Rita Shaknovich, Oliver Venn. Clonal B-cell expansion and the potential challenges to blood-based early cancer detection [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 779.

Introduction: Minimal or measurable residual disease (MRD) is an emerging independent predictor of progression-free and overall survival in several hematologic diseases. Despite many different methods used in clinical trials, few assays have clinical utility as a surrogate endpoint in a limited number of hematologic malignancies. MRD assays for lymphomas are mostly performed in research settings due to lack of harmonized methods, heterogeneity of diseases, and need for a primary tumor sample. We explored the feasibility of a pan hematologic malignancy classifier (“pan heme classifier”) based on GRAIL’s methylation platform as a potential tumor-agnostic plasma-based MRD assay for hematologic malignancies. Methods: First, 428 plasma samples from various hematologic malignancies including diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), mantle cell lymphoma (MCL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), and multiple myeloma (MM) were blindly tested retrospectively using the pan heme classifier. The majority of samples (375/428; 88%) were from relapsed/refractory (R/R) disease. Cancer signal detection and signal origin prediction were explored at various detection thresholds. Next, sensitivity of the pan heme classifier was evaluated using 74 (22 and 14 unique patients in CLL and MCL, respectively) post-treatment samples with orthogonal methods (flow cytometry in CLL and clonoSEQ in MCL). Finally, dilution experiments were carried out in 4 DLBCL and 4 CLL patient samples. Results: Of 428 samples, 408 (95%) passed quality control. At a prespecified detection threshold, we observed high (91%) cancer detection rate with high cancer signal origin accuracies: 100% in CLL, >98% in MM, >95% in non-Hodgkin lymphoma (DLBCL, FL, MCL), and 87% in AML samples. As expected, targeting lower detection thresholds resulted in increased cancer-positive calls. Cancer was reproducibly detected in 48 of 54 (89%) cases where paired samples were taken prior to treatment (screening and cycle 1, day 1), demonstrating high biologic reproducibility. Analysis of posttreatment CLL and MCL samples with cell-based orthogonal MRD assays suggests the current assay limit of detection (LOD) is ~10-3-10-4 MVAF (a methylation-based tumor fraction estimate). These data suggest that cancer signal score is strongly correlated to the observed MVAF. Furthermore, serially diluted DLBCL and CLL patient plasma samples were spiked into healthy volunteer plasma samples, suggesting an LOD of 10-4 MVAF. Conclusions: These data demonstrate that the pan heme classifier can identify cancer signal from R/R patients across multiple hematologic malignancies. We are currently working to further optimize the assay’s specificity and sensitivity. These results support the development of a blood-based tumor agnostic methylated ctDNA MRD assay with potential utility in several hematologic indications. Citation Format: Veerendra Munugalavadla, Gary de Jesus, Aleksandra Markovets, Qinwen Liu, Oliver Venn, Rafael White, Giulia Fabbri, Paul Labrousse, Dan Stetson, Brian Dougherty, Darren Hodgson, Jill Walker, Anas Younes, Daniel Auclair. Utility of ctDNA-based targeted methylation MRD assay for hematological malignancies [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 3369.

Introduction: Hematologic (heme) malignancies and their precursor conditions are highly prevalent. They are also diverse in biology, clinical presentation, and outcomes, underlining the importance of differentiating them. Previously, we demonstrated that a blood-based targeted methylation assay detected multiple cancer types across stages. Here, we examined test performance on various heme cancers, identifying specific methylation signatures. Methods: From the second substudy (training set) of the Circulating Cell-free Genome Atlas (CCGA) study (NCT02889978), we evaluated 325 participants from 17 different heme disease subtypes and 3,211 non-cancer controls enrolled without a cancer diagnosis. A cross-validated mutual information-based algorithm was used to identify features that discriminated heme subtypes. The resulting feature distribution was visualized using uniform manifold approximation and projection (UMAP) dimensionality reduction on held-out data. In cross validation with feature selection, we then trained a multinomial classifier to distinguish from among the major heme cancers and non-cancer and correlated the model's class probabilities to positions in feature space. Results: Dimensionality reduction and visualization of input features demonstrated that heme malignancies separated into five major clusters reflecting developmental lineages and disease ontogeny: myeloid, circulating lymphomas, hodgkin lymphomas, non-hodgkin lymphomas, and plasma cell neoplasm. The position of samples within each heme cluster correlated with the cancer signal strength. At 99.4% specificity [95% CI: 99.1, 99.7], heme cancer detection was 74.5% [69.4, 79.1] overall, 67.7% [41.1, 87.8] for myeloid, 77.9% [66.3, 86.9] for circulating lymphomas, 90.7% [73.2, 98.4] for hodgkin lymphomas, 68.6% [60.4, 76.1] for other non-hodgkin lymphomas, and 78.8% [67.0, 87.9] for plasma cell neoplasms. Of 18 non-cancer participants who were classified as having heme cancers, 4 were predicted as myeloid, 6 as circulating lymphoid, and 8 as other non-hodgkin lymphoid neoplasms ( Conclusion: Methylation features of cfDNA in patients with heme malignancies delineated five major clusters that reflected disease ontogeny and heme lineage. Lineage-specific signals followed a gradient suggestive of variation in disease-related methylation or tumor DNA shedding. These findings contribute to the understanding of biological signals that arise from various heme conditions. Since in general, most cfDNA arises from blood lineages, this knowledge will guide further efforts towards removing interfering biological signals from cfDNA-based cancer detection assays and achieving even more sensitive detection of multiple cancer types. Citation Format: Qinwen Liu, Rita Shaknovich, Xiaoji Chen, Zhao Dong, M. C. Maher, Samuel Gross, Alexander P. Fields, Jan Schellenberger, Kathryn N. Kurtzman, Eric T. Fung, Anne-Renee Hartman, Earl Hubbell, Arash Jamshidi, Alexander M. Aravanis, Oliver Venn. cfDNA methylation profiling distinguishes lineage-specific hematologic malignancies [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 139.

Accurate tissue of origin (TOO) prediction is crucial for effective clinical follow-up in early cancer detection from blood. In the second substudy of the Circulating Cell-free Genome Atlas (CCGA; NCT02889978), we trained logistic regression classifiers under cross-validation to detect and localize cancer. Input features were methylation states from a targeted cfDNA assay of 2023 participants. TOO classification accuracy was 89% across 20 pre-specified prediction classes. We subsequently sought to understand the causes of the remaining TOO errors. 45% of the errors fell into clusters reflecting similarities in developmental biology, histology, or oncological drivers. Here, we analyzed tissues that may be affected by HPV-driven cancers; these accounted for 21% of TOO errors. The original classifier, which used only human epigenetic states as input, demonstrated cross-scoring between likely HPV-driven cancers of the anus (N = 14) and cervix (N = 11), as well as confirmed HPV-positive head & neck (H&N) cancers (37/62). We also observed HPV-associated vulva (N = 9) and penis (N = 1) cancers, which were not directly trained as TOO classes, were assigned high H&N scores. To test the hypothesis of HPV-driven TOO confusion, we assessed HPV cfDNA and HPV-driven methylation in human peripheral blood cfDNA, and used a specialist classifier restricted to HPV-associated cancers to resolve errors. We corroborated putative HPV-positive participants using targeted sequencing of HPV16 and HPV18 cfDNA fragments, and showed that the number of unique HPV-derived fragments in a sample matched with expected cancer localizations, HPV subtypes, and HPV status. Consistent with the literature, we found little evidence of HPV viremia in non-cancer participants despite the high prevalence of transient HPV infections in the US population. At 99.8% specificity, a cross-validated cutoff on the number of HPV cfDNA fragments in a sample achieved sensitivities of 78.6% (11/14), 36.3% (4/11), 66.6% (6/9), 100% (1/1), and 81.0% (30/37), for anus, cervix, vulva, penis, and confirmed HPV-positive H&N cancers, respectively. These sensitivities were similar to those achieved by the epigenetic classifier. Finally, we trained a cross-validated specialist classifier using the same features as the TOO classifier, but restricted to HPV-driven cancers. This improved TOO accuracy for detected anal cancers from 11% (1/9) to 100% (9/9), with little effect on other classes. These data support that HPV presence may explain observed cross-scoring patterns between H&N, cervix, and anus TOO prediction classes, which were driven by recurrent epigenomic changes in participants with HPV-positive cancers as detected by this assay. This suggests that modelling axes of shared biology across cancer types can be useful for accurate cfDNA TOO classification, which is critical to direct diagnostic work-up of diverse cancer types in a multi-cancer early detection test. Citation Format: Robert Calef, Oliver Venn, M. Cyrus Maher, John F. Beausang, Earl Hubbell, Aman Patel, Alexander P. Fields, Joerg Bredno, Arash Jamshidi, Alexander M. Aravanis. HPV-driven cancers show distinct methylation signatures in cell-free DNA (cfDNA) [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 2114.

Background The Circulating Cell-free Genome Atlas (CCGA; NCT02889978) study is a prospective, multi-center, observational, case-control study with longitudinal follow-up to support the development of a plasma cfDNA-based multi-cancer early detection assay. We previously reported that the fraction of tumor-derived cfDNA fragments in plasma (estimated tumor fraction [TF]) is associated with detection of multiple cancer types using a prototype whole-genome bisulfite sequencing (WGBS) assay in a pre-specified substudy. In addition, detectability of breast cancer varied by hormone-receptor (HR) status: HR negative (HR-) breast cancer had a higher detection rate than the overall breast cancer cohort. Here, we performed a planned in-depth analysis of the breast cancer cohort to understand the main clinical and biological determinants of detectability using our WGBS assay. Methods Blood samples were prospectively collected from participants (pts) with newly-diagnosed, untreated breast cancer. In a pre-specified CCGA substudy, 511 (31.4%) of 1,628 pts had a clinicopathologic diagnosis of breast cancer (any stage, excluding stage 0) and a WGBS result. Pre-specified biological and clinical factors were assessed for correlation with TF: clinical stage, pathologic N stage, lesion size (by imaging), T stage, histologic grade, hormone receptor (HR) status, and proliferative rate (Ki-67 by IHC [MIB-1 clone]) via univariate and multivariate analyses. Ki-67 was obtained from pathology reports provided by enrollment sites and also assessed centrally (Mayo Clinic [Rochester, MN]). Stage-specific differences in detection rates between HR positive (HR+) and HR- breast cancers due to biological differences such as histologic grade and/or proliferative rate was also assessed. Results Of 511 pts, 94 (18.4%; 48.9% HR- and 12.3% in HR+) had WGBS-detected cancer. Higher TF was significantly associated with cancer detection (p Conclusions Using a prototype methylation-based plasma cfDNA cancer detection assay, TF was found to be associated with detection, and with clinical and biological features of breast cancer. Features routinely used to assess clinical aggressiveness (eg, HR- status and histologic grade) also demonstrated stage-specific associations with TF. Given the known relationship between TF and detection, these data suggest that clinical and biological cancer features may also provide insight into the variability of cancer detection using plasma-based cfDNA tests. Citation Format: Minetta C. Liu, Jodi M. Carter, Daniel W. Visscher, Karla Kopp, Rita Shaknovich, Xiaoji Chen, Kathryn N. Kurtzman, Shilpen Patel, Jacqueline D. Brooks, Carlo R. Cosenza, Jafi A. Lipson, Donald A. Richards, Fergus J. Couch, Zhao Dong, Hai Liu, Oliver Venn, Joerg Bredno, Eric T. Fung, Anne-Renee Hartman. Blood-based cancer detection in plasma cell-free DNA (cfDNA): Evaluating clinical and pathologic tumor characteristics in participants with breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-01-01.

Previous studies on transplanted tissue or single cancers indicated that cfDNA variant fragment lengths reflect their respective source. The Circulating Cell-free Genome Atlas (NCT02889978) study provides an opportunity to examine cfDNA variant fragment lengths across tumor types and describe the nature of cfDNA variants derived from different sources. Blood samples (N=1406) were evaluated from participants with (n=845) and without (n=561) cancer; cancer samples included 339 breast, 118 lung, 69 prostate, 45 colorectal, 27 uterine, 26 pancreas, 26 renal, 24 esophageal, 22 lymphoma, 19 head/neck, and 17 ovarian (113 remaining samples represented cancers with ≤15 samples each). cfDNA and genomic DNA from white blood cells (WBC) were subjected to a high-intensity targeted panel (507 genes, 60000X) with error-corrected sequencing; 533 samples also had matched tumor biopsy tissue subjected to whole-genome sequencing (30X). Somatic single-nucleotide variants (SNVs; that passed noise filters) were identified and classified using the sequencing results into one of four categories: tumor biopsy-matched (TBM; present in cfDNA and biopsy), WBC-matched (WM; present in cfDNA and WBC), non-matched (NM; low probability [P A total of 21604 SNVs were identified. The proportion of SNVs from each category were: 4% TBM, 68% WM, 19% NM, and 8% AMB. The number of samples (non-mutually exclusive) that had each SNV category were 152 TBM, 1338 WM, 499 NM, and 761 AMB. Across categories, the median (SD) length of fragments containing the reference allele was 167 (16.3). Median (SD) fragment lengths of TBM, WM, NM, and AMB were 156 (22.2), 169 (14.8), 158 (20.8), and 165 (17.8), respectively. AMB and WM median SNV fragment lengths were similar to that of the reference allele, suggesting that fragment length shifts are minimal in SNVs derived from clonal hematopoiesis (CH). Fragment lengths of TBM and NM SNVs were similar; further, most NM SNVs came from cfDNA samples in the cancer cohort, suggesting that NM SNVs may be tumor-derived. As expected in a population with a median (SD) age of 61 (12.2), most SNVs occurred in the WM category. The prediction model distinguished TBM from WM SNVs with an AUC of 0.87. However, at a specificity of 98% (to match filtering based on WBC sequencing), false-negative rates were 35% (TBM) and 52% (NM). Together, these data suggest that source prediction based on fragment length alone is less robust than source assignment using individual-matched WBC sequencing, highlighting the importance of accounting for CH-derived SNVs when using targeted cfDNA-based approaches for cancer detection. Citation Format: Earl Hubbell, Tara Maddala, Oliver Venn, Eric Scott, Susan Tang, Archana Shenoy, Alex Aravanis. Cell-free DNA (cfDNA) fragment length patterns of tumor- and blood-derived variants in participants with and without cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3372.

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 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.