Abstract 6689: Whole genome cell-free tumor DNA mutational signatures from blood for early detection of recurrence of low stage lung adenocarcinoma

Introduction: Lung cancer remains the leading cause of cancer-related deaths. Surgery is the best option for early lung cancer, and the role of adjuvant therapy remains controversial. Liquid biopsy offers a noninvasive approach to monitor cancer burden. Targeted sequencing of circulating cell free tumor DNA (ctDNA) in blood has shown success for diagnosis; however, low tumor burden and dynamic evolution of low stage disease is challenging for targeted panels. Thus, we hypothesized that a whole genome sequencing (WGS)-derived patient specific mutational signature from a matched tumor-normal WGS can provide sensitive and specific approach to detect mutations and copy numbers in ctDNA for monitoring of lung adenocarcinoma patients.

Methods: We successfully profiled 50 Stage 1 or 2 lung adenocarcinomas. ctDNA was extracted from 1-2 mL of plasma, tumor DNA was extracted from pathology tissue and normal germline DNA from the white blood cells. WGS using was performed on matched tumor and normal DNA, and ctDNA extracted from plasma. WGS coverage was 40x for matched tumor-normal and 20x for ctDNA. We derived a personalized mutational pattern for each tumor and used an AI-based error suppression model for quantification and ultra-sensitive detection of ctDNA in plasma samples. A patient-specific personalized genome-wide compendium of somatic mutations and copy numbers was established and ctDNA tested at 3 to 18 available time points during the therapy or follow up. A personalized mutational signature for detection ctDNA from WGS was quantified and the ctDNA Tumor Fraction (TF) was compared to the clinical status and time to recurrence.

Results: Tumor specific signatures were derived from matched tumor-normal samples with >5% tumor purity and <30% duplications rate. Out of all patients, 33 patients showed no recurrence and 12 recurred. Tumor-specific signatures detected the presence of the tumor signature in plasma with TF as low as 10−5. Based on positive minimal residual disease in plasma, the recurrence prediction sensitivity was 0.75 and specificity 0.82, with positive predictive value of 0.6 and negative predictive value 0.9. WGS ctDNA predicted recurrence with a median lead time of 508 days before clinical/imaging recurrence. In one case we were able to identify the second primary by deconvoluting known and novel ctDNA mutations. ctDNA mutational profiles enabled identification of smoking mutational signature matching clinical history, and APOBEC and ageing signatures as well as tumor mutational burden.

Conclusions: Patient-specific WGS tumor signature from plasma derived ctDNA enables specific and ultrasensitive tracking of minimal residual disease in low stage lung adenocarcinoma patients. Molecularly positive status can be used to predict recurrence and identify patients with clinical low stage disease that may benefit from adjuvant therapy.

Citation Format: Ivy Tran, Alejandro Vargas, Reid Wilkins, Isabella Pizzillo, Kenneth Tokoro, Danielle Afterman, Tomer Lauterman, Maja Kuzman, Santiago Gonzalez, Dunja Glavas, James Smadbeck, Dillon Maloney, Jurica Levatic, Samuel Phillips, Sunil Deochand, Michael Yahalom, Ryan Ptashkin, Iman Tavassoly, Zohar Donenhirsh, Eric White, Ravi Kandasamy, Ury Alon, Paz Polak, Boris Oklander, Asaf Zviran, Matija Snuderl, Harvey I. Pass. Whole genome cell-free tumor DNA mutational signatures from blood for early detection of recurrence of low stage lung adenocarcinoma. [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 6689.

Abstract 3401: Whole genome cell-free tumor DNA mutational signatures for noninvasive monitoring of pediatric brain cancers

Introduction: Liquid biopsy offers a noninvasive approach to monitor cancer burden during therapy and surveillance period. However, in pediatric brain cancers, liquid biopsy methods from the blood have been unsuccessful due to a low tumor burden and low number of mutations in coding regions. We hypothesized that a whole genome sequencing (WGS)-derived patient specific mutational signature from a matched tumor-normal WGS can provide a sensitive and specific approach to detect mutations in circulating cell free tumor DNA (ctDNA) and provide blood-based monitoring in pediatric patients with brain tumor.

Methods: All tumors were analyzed and molecularly subclassified using whole genome DNA methylation profiling and machine learning classifier. Tumor DNA was extracted from pathology tissue and normal germline DNA from the white blood cells, while ctDNA was extracted from 1-2 mL of post-surgery or follow-up plasma samples, WGS was applied to sequence DNA from matched tumor-normal and plasma samples. WGS coverage was 40x for matched tumor-normal DNA and 20x for ctDNA. Using the C2i assay, we derived a personalized mutational pattern for each tumor and used an AI-based error suppression model for quantification and ultra-sensitive detection of ctDNA in plasma samples. A patient-specific personalized genome-wide compendium of somatic mutations was established and ctDNA tested at 1 to 3 available time points during the therapy or surveillance period. 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 contained in it. The ctDNA Tumor Fraction (TF) was compared to the clinical status and MR-based imaging.

Results: We profiled 7 pediatric brain tumors, including 2 medulloblastomas (one Group 3, one Group 4), 3 pediatric glioblastomas IDH wild-type, 1 ependymoma PFA subtype and one low grade ganglioglioma. Tumor specific signatures were identified and detected in the plasma of 5 patients with clinical disease with a TF range 0.02-0.0005 but not in 2 patients with no tumor at the time of blood collection. In two children with a medulloblastoma and glioblastoma, the decrease of tumor fraction in ctDNA over 2 (TF: 0.002 to 0.0009) and 3 time points (TF: 0.0005 to undetectable), respectively, correlated with response to therapy based on imaging.

Conclusions: Patient-specific WGS tumor signature in ctDNA from blood can be used for sensitive monitoring of children with brain tumors.

Citation Format: Ivy Tran, Kristyn Galbraith, Guisheng Zhao, Robyn Borsuk, Joyce Varkey, Sharon Gardner, Jeffrey Allen, David Harter, Jeffrey Wisoff, Eveline T. Hidalgo, 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, G. Praveen Raju, Theodore Nicolaides, Asaf Zviran, Matija Snuderl. Whole genome cell-free tumor DNA mutational signatures for noninvasive monitoring of pediatric brain cancers [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 3401.

Abstract 1959: Sensitive detection of circulating tumor DNA by whole genome sequencing: Validation of MRDetect using serial blood samples from stage III colorectal cancer patients

Background: While detection of circulating tumor DNA (ctDNA) is associated with poor cancer prognosis, the clinical utility for guiding treatment decisions is unresolved. Patients with minimal residual disease (MRD) often have less than one genome equivalent of ctDNA per 10 mL blood. Consequently, it is stochastic whether a 10 mL sample contains ctDNA from a particular genomic locus. Consequently, the sensitivity of ctDNA detection methods targeting a limited number of tumor loci is heavily affected by sampling bias. To overcome this challenge, we developed MRDetect; a whole genome sequencing (WGS) approach, which detects ctDNA using the patient-specific cumulative signal from tens of thousands of mutations throughout the genome. Recently, we showed how MRDetect found ctDNA fractions down to 10-4. Here, we performed a validation study to confirm the prognostic impact of MRDetect.

Aim: Validation of MRDetect for sensitive ctDNA detection to monitor residual disease in stage III colorectal cancer (CRC) patients treated with curative intent.

Methods: From a large, uniform cohort of stage III CRC patients n = 146), we had plasma samples collected every third month (n = 938, median = 9 per patient) and a median follow-up of 34 months. For each patient, a genome-wide mutational signature was established by WGS of tumor and matched normal DNA. Enhanced by an AI-based error suppression model, this signature was used to detect ctDNA in 1-2 mL plasma samples using WGS (20x coverage). We used de-novo point mutation and copy number variation analysis to investigate cancer evolution after treatment. To evaluate the reproducibility of MRDetect, aliquot samples (n = 2x190 samples) from 5 recurrence and 10 non-recurrence patients were processed and sequenced at two independent laboratories. Outcome measures: ctDNA status, tumor fraction, false positive rate, Time To ctDNA Recurrence (TTcR), and Time To radiological Recurrence (TTrR).

Results: Analysis of paired samples showed great reproducibility with high agreement between both ctDNA status calls (Cohens Kappa = 0.81) and the estimated tumor fractions (r2 = 0.99). MRDetect revealed post-operative ctDNA in all recurrence patients (5/5) with detected tumor fractions down to 2 x 10-4. Median TTcR was 0.9 month (range 0.5 - 7.3 months) while median TTrR was 12.8 months (range 11.3 - 31.1 months). The false positive rate was 1% (1/100), assessed in longitudinal samples from the 10 non-relapsing patients. Tumor evolution dynamics in plasma samples revealed novel amplification and deletions, which were absent in the primary tissue but confirmed in metachronous metastases. We will present results from the full cohort at AACR 2022.

Conclusion: MRDetect detects ctDNA with high sensitivity and specificity and enables effective postoperative assessment of MRD, cancer evolution dynamics and early relapse detection.

Citation Format: Amanda Frydendahl, Thomas Reinert, Jesper Nors, Sunil Deochand, Dillon Maloney, Noah Friedman, Tomer Lauterman, Danielle Afterman, Imane Bourzgui, Nidhi Ramaraj, Zohar Donenhirsh, Ronel Veksler, Ravi Kandasamy, Iman Tavassoly, Jonathan Rosenfeld, Anders Husted Andersen, Uffe S. Løve, Per V. Andersen, Ole Thorlacius-Ussing, Lene Hjerrild Iversen, Kåre Andersson Gotschalck, Boris Oklander, Asaf Zviran, Claus Lindbjerg Andersen. Sensitive detection of circulating tumor DNA by whole genome sequencing: Validation of MRDetect using serial blood samples from stage III colorectal cancer patients [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 1959.

Abstract 540: Genome-wide circulating tumor DNA for monitoring treatment response and metastatic relapse in bladder cancer

Background: Neoadjuvant chemotherapy (NAC) followed by radical cystectomy (CX), is gold standard treatment in localized muscle-invasive bladder cancer (MIBC). About 45% of patients with MIBC develop metastatic relapse within 2 years after CX. The response rate to chemotherapy and immune checkpoint inhibitors (ICI) is relatively low, and biomarker tests for monitoring response are needed. Furthermore, biomarkers for early detection of minimal residual disease (MRD) after CX is needed to enable earlier treatment initiation. Tumor-informed detection of mutations in cell-free DNA (cfDNA) from peripheral blood has shown promising results in its ability to monitor MRD. However, the low tumor fraction after surgery and limited input material obtained from a typical plasma sample limits the probability of detecting low metastatic burden scenarios. Here we implemented and applied locally a whole-genome sequencing (WGS) approach to circulating tumor DNA (ctDNA) monitoring for improving ctDNA detection.

Methods: A total of 140 MIBC patients undergoing NAC and CX were enrolled, including a test cohort (n=19) and a validation cohort (n=120). cfDNA was extracted from ~1mL plasma (n=1100) and procured from longitudinal plasma sampling during NAC (response measure), pre-cystectomy (response measure), post-surgery (relapse monitoring) and during immunotherapy (ICI treatment). WGS was applied to tumor/germline pairs (coverage >30x/20x) and plasma cfDNA (>20x) facilitating detection of genome wide genomic alterations and quantification of ctDNA using the MRDetect method.

Results: We developed a personalized tumor-informed WGS model by integrating genome-wide mutation and copy number variation data coupled with advanced signal processing and AI-based error suppression. Patient-specific somatic variant patterns were then used for detecting and measuring the ctDNA levels in low-input blood samples by WGS. The assay sensitivity allowed for detection of tumor fractions down to 8*10-5. Furthermore, in our test cohort of 19 patients, we detected ctDNA after CX in 7 of 8 patients with clinical relapse (88% sensitivity) and detected no ctDNA in 11 of 11 patients with no clinical relapse (100% specificity). We observed a positive lead-time for MRD-based recurrence detection compared to CT-based reccurence detection (9 months on average). The full dataset is currently being processed and will be presented at the AACR 2022 meeting.

Conclusions: For precision oncology, we need to develop quantitative and non-invasive methodologies to help tailor the treatments to individual patients and monitor them for further clinical decision-making. The results indicate the clinical potential of personalized genome-wide mutation integration as an ultra-sensitive, non-invasive method for MRD detection and treatment response monitoring which could aid in clinical management of patients with bladder cancer.

Citation Format: Iver Nordentoft, Karin Birkenkamp-Demtröder, Emil Christensen, Sunil Deochand, Dillon Maloney, Danielle Afterman, Tomer Lauterman, Noah Friedman, Imane Bourzgui, Nidhi Ramaraj, Zohar Donenhirsh, Ronel Veksler, Sia Viborg, Mads Agerbæk, Jørgen Bjerggaard Jensen, Jonathan Rosenfeld, Ravi Kandasamy, Iman Tavassoly, Boris Oklander, Asaf Zviran, Lars Dyrskjøt. Genome-wide circulating tumor DNA for monitoring treatment response and metastatic relapse in bladder cancer [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 540.

Abstract 5114: 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)

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.