Tomer Lauterman

BACKGROUND AND OBJECTIVE: Circulating tumor DNA (ctDNA) can be used for sensitive detection of minimal residual disease (MRD). However, the probability of detecting ctDNA in settings of low tumor burden is limited by the number of mutations analyzed and the plasma volume available. We used a whole-genome sequencing (WGS) approach for ctDNA detection in patients with urothelial carcinoma. METHODS: We used a tumor-informed WGS approach for ctDNA-based detection of MRD and evaluation of treatment responses. We analyzed 916 longitudinally collected plasma samples from 112 patients with localized muscle-invasive bladder cancer who received neoadjuvant chemotherapy (NAC) before radical cystectomy. Recurrence-free survival (primary endpoint), overall survival, and ctDNA dynamics during NAC were assessed. KEY FINDINGS AND LIMITATIONS: We found that WGS-based ctDNA detection is prognostic for patient outcomes with a median lead time of 131 d over radiographic imaging. WGS-based ctDNA assessment after radical cystectomy identified recurrence with sensitivity of 91% and specificity of 92%. In addition, genomic characterization of post-treatment plasma samples with a high ctDNA level revealed acquisition of platinum therapy-associated mutational signatures and copy number variations not present in the primary tumors. The sequencing depth is a limitation for studying tumor evolution. CONCLUSIONS AND CLINICAL IMPLICATIONS: Our results support the use of WGS for ultrasensitive ctDNA detection and highlight the possibility of plasma-based tracking of tumor evolution. WGS-based ctDNA detection represents a promising option for clinical use owing to the low volume of plasma needed and the ease of performing WGS, eliminating the need for personalized assay design.

INTRODUCTION: Circulating tumor (ctDNA) can be used to detect residual disease after cancer treatment. Detecting low-level ctDNA is challenging, due to the limited number of recoverable ctDNA fragments at any target loci. In response, we applied tumor-informed whole-genome sequencing (WGS), leveraging thousands of mutations for ctDNA detection. METHODS: Performance was evaluated in serial plasma samples (n = 1283) from 144 stage III colorectal cancer patients. Tumor/normal WGS was used to establish a patient-specific mutational fingerprint, which was searched for in 20x WGS plasma profiles. For reproducibility, paired aliquots of 172 plasma samples were analyzed in two independent laboratories. De novo variant calling was performed for serial plasma samples with a ctDNA level > 10 % (n = 17) to explore genomic evolution. RESULTS: WGS-based ctDNA detection was prognostic of recurrence: post-operation (Hazard ratio [HR] 6.75, 95 %CI 3.18-14.3, p < 0.001), post-adjuvant chemotherapy (HR 28.9, 95 %CI 10.1-82.8; p < 0.001), and during surveillance (HR 22.8, 95 %CI 13.7-37.9, p < 0.0001). The 3-year cumulative incidence of ctDNA detection in recurrence patients was 95 %. ctDNA was detected a median of 8.7 months before radiological recurrence. The independently analyzed plasma aliquots showed excellent agreement (Cohens Kappa=0.9, r = 0.99). Genomic characterization of serial plasma revealed significant evolution in mutations and copy number alterations, and the timing of mutational processes, such as 5-fluorouracil-induced mutations. CONCLUSION: Our study supports the use of WGS for sensitive ctDNA detection and demonstrates that post-treatment ctDNA detection is highly prognostic of recurrence. Furthermore, plasma WGS can identify genomic differences distinguishing the primary tumor and relapsing metastasis, and monitor treatment-induced genomic changes.

Abstract Background: Early detection of recurrence and monitoring of MRD post-surgery is critical for clinical decision-making to tailor adjuvant therapy. In early-stage NSCLC, circulating tumor DNA (ctDNA) detection is especially challenging, requiring highly sensitive and specific assays. Therefore, we used a WGS approach (MRDetect) for ultra-sensitive ctDNA detection in NSCLC patients (pts) undergoing curative surgery. Methods: We conducted a pilot study to evaluate the MRDetect approach in serial plasma samples (including pre-surgery, post-surgery and follow-up [f/u] timepoints) from resected stage IB-IIIA NSCLC pts. Pts underwent routine surveillance by computed tomography scans. ctDNA was extracted from ~1mL plasma. MRDetect uses WGS by a tumor-informed approach (sequencing coverage 40x for tumor, 20x for plasma DNA) combined with AI-based error suppression models (trained and calibrated with a non-cancer cohort, n=17) to increase the signal to noise ratio for precise ctDNA detection, and improve the accuracy of readouts especially for low tumor burden scenarios. The assay reports the detection and quantification of ctDNA burden in blood with a prognostic value for risk of recurrence. The ability of the assay to predict recurrence from a single sample, taken at the clinical landmark point (median 1.6 mths post-surgery, range 0.1-6.5) was evaluated. Results: Overall, 52 NSCLC pts were enrolled (n=88 plasma samples) with median clinical f/u of 32.6 mths (range 3.1-98.6). There were 43 pts with post-surgery landmark samples, with median age 62 years, 70% were male, 79% were adenocarcinoma and 49% were EGFR mutated. 26% were stage IB and 37% each were stage II and III. There were 15/18 (sensitivity 83%) pts with confirmed radiological recurrence in which MRDetect was positive, including 6/7 (86%) EGFR mutated pts. The median RFS in MRDetect positive pts was 15.2 mths (range 3.7-33.4). Among 25 pts with no recurrence (median f/u 25.6 mths), MRDetect reported 4 pts to be MRD positive (specificity 84%). These results were consistent between EGFR mutated (sensitivity 86%, specificity 86%) and wildtype pts (sensitivity 82%, specificity 82%). For longitudinal samples (n=17 pts), negative ctDNA was associated with absence of recurrence in 14/15 pts (specificity 93%). At the AACR meeting, results from a planned larger validation study will be presented. Conclusion: Using a robust WGS implemented AI-based computational platform (MRDetect), we demonstrate high sensitivity and specificity detection of MRD in both EGFR mutated and wildtype NSCLC. With an increasing number of therapeutic options in the adjuvant setting for NSCLC, an ultra-sensitive MRD assay has the potential to facilitate personalized clinical decision-making for tailoring both the need and choice of adjuvant therapies. Citation Format: Aaron C. Tan, Stephanie P. Saw, Gillianne G. Lai, Kevin L. Chua, Angela Takano, Boon-Hean Ong, Tina P. Koh, Amit Jain, Wan Ling Tan, Quan Sing Ng, Ravindran Kanesvaran, Tanujaa Rajasekaran, Sunil Deochand, Dillon Maloney, Danielle Afterman, Tomer Lauterman, Noah Friedman, Imane Bourzgui, Nidhi Ramaraj, Zohar Donenhirsh, Ronel Veksler, Jonathan Rosenfeld, Ravi Kandasamy, Iman Tavassoly, Boris Oklander, Asaf Zviran, Wan-Teck Lim, Eng-Huat Tan, Anders J. Skanderup, Mei-Kim Ang, Daniel S. Tan. Ultra-sensitive detection of minimal residual disease (MRD) through whole genome sequencing (WGS) using an AI-based error suppression model in resected early-stage non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5114.

Abstract Circulating tumor DNA (ctDNA) can be used for sensitive detection of minimal residual disease (MRD). However, the probability of detecting ctDNA at low tumor burden is limited by the number of mutations analyzed and available plasma volume. Here we applied a tumor-informed whole genome sequencing (WGS) approach for ctDNA-based MRD detection (91% sensitivity, 92% specificity) and treatment response evaluation in 916 longitudinally collected plasma samples from 112 patients with localized muscle-invasive bladder cancer. We show that WGS-based ctDNA detection is prognostic of patient outcomes with a median lead time of 131 days over radiographic imaging. We performed genomic characterization of post-treatment plasma samples with a high ctDNA level and observed acquisition of the platinum therapy-associated mutational signatures and copy number variations not present in the primary tumors. Our results support the use of WGS for ultra-sensitive ctDNA detection and highlight the additional possibility for plasma-based tracking of tumor evolution. Statement of significance Our study supports the clinical potential of using a WGS-based strategy for sensitive ctDNA detection in patients with MIBC. Thus, WGS-based ctDNA detection constitutes a promising option for clinical use due to low requirements for plasma input and the ease of performing WGS, eliminating the need for personalized assay design.

2064 Background: Patients with the central nervous system (CNS) tumors are largely followed up by imaging. Current plasma-based liquid biopsy techniques have limited utility in neuro-oncology due to a low circulating cell-free tumor DNA (ctDNA) burden, blood-brain barrier, and low number of mutations in coding regions. Whole genome sequencing (WGS)-derived patient specific mutational signature from a matched tumor-normal WGS can provide a personalized, highly sensitive and specific approach to detect mutations in ctDNA and provide blood-based monitoring in brain tumor patients. Furthermore, it can be performed on lower amount of peripheral blood since WGS requires less sequencing depth compared to targeted ctDNA panels. Methods: We have profiled a cohort of 28 extra- and intra-axial adult and pediatric brain tumors including adult and pediatric low- and high-grade glioma (9), meningiomas (11), medulloblastomas (5), ependymomas (2), neurocytoma (1). Tumor DNA was extracted from archival pathology tissue, normal DNA from unsorted white blood cells, and ctDNA from 1-2 mL of post-surgery plasma. WGS was performed with 40x coverage for Tumor-Normal DNA and 20x for ctDNA. Using WGS of matched Tumor-Normal and plasma samples, we derived a personalized mutational pattern using SNVs, indels, and copy numbers for quantification and ultra-sensitive detection of ctDNA in plasma samples. An AI-based error suppression model was implemented to filter out the noise in the cell-free DNA (cfDNA) while the personalized mutational signature was used to detect the ctDNA in the cfDNA and to amplify the somatic signal to determine the Tumor Fraction at the time of diagnosis, during the therapy or surveillance period. The ctDNA Tumor Fraction (TF) was compared to the clinical status and MRI-based imaging. Results: All subtypes of brain tumors contained enough mutations to derive personalized mutational signatures. Most mutations were distributed in the noncoding DNA. TF correlated with clinical status and with the disease course on imaging at given time points reaching a 10 -4 minimal residual disease detection sensitivity. We were able to detect ctDNA across all WHO grades ranging from WHO 1 meningioma to WHO 4 glioblastoma and medulloblastoma. Furthermore, we were able to detect tumor-specific copy number aberrations such as MYCN amplification in plasma samples and mutational signatures. Conclusions: Here we demonstrate that patient-specific WGS tumor signature in ctDNA from plasma can be used for sensitive monitoring of adults and children with primary low- and high-grade CNS tumors.