In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGE^SNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGE^CNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGE^SNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition.

Nearly 50% of patients recur within two years after curatively intended resection of colorectal cancer liver metastasis (CRLM). The optimal surveillance strategy is unknown due to the lack of evidence. Here, we explored the potential for improving postoperative CRLM surveillance by performing serial circulating tumour DNA (ctDNA) assessments parallel to standard-of-care surveillance. 499 prospectively collected serial plasma samples from 96 patients undergoing CRLM resection were analysed using the tumour-agnostic methylation multiplex droplet-digital PCR test 'TriMeth'. Patients with ctDNA postoperatively or post adjuvant chemotherapy experienced a significant lower recurrence-free survival than patients without ctDNA (hazard ratio (HR) 4.5; P < 0.0001 and HR 8.4, P < 0.0001). ctDNA status was a stronger predictor of recurrence than standard clinical risk factors and carcinoembryonic antigen. Serial TriMeth analysis detected ctDNA before radiological recurrence in 55.6% of ctDNA-positive patients, with up to 10.6 months lead-time (median 3.1 months). During surveillance, 24% of patients had inconclusive CT scans, which was associated with a significant delay in recurrence diagnosis (median 3.5 months versus 1.0 month, P < 0.0001). Uniquely, ctDNA status at the time of inconclusive CT scans predicted recurrence with positive and negative predictive values of 100%, and 75% (P = 0.0003). Serial TriMeth analysis allowed ctDNA growth rate assessment and revealed that fast ctDNA growth was associated with poor overall survival (HR: 1.6, P = 0.0052). Serial postoperative ctDNA analysis has a strong prognostic value and is more sensitive for recurrence detection than standard-of-care CRLM surveillance tools. Altogether, TriMeth provides several opportunities for improving postoperative surveillance of CRLM patients.

In stage 2–3 colon cancer (CC), postsurgery circulating tumor DNA (ctDNA) assessment is crucial for guiding adjuvant chemotherapy (ACT) decisions. While existing assays detect ctDNA and help identify high-risk persons with CC for recurrence, their limited sensitivity after surgery poses challenges in deciding on ACT. Additionally, a substantial portion of persons with CC fail to clear ctDNA after ACT, leading to recurrence. In this study, we performed whole-exome sequencing (WES) of ctDNA at different time points in participants with relapsed CC in two independent cohorts, alongside transcriptomic and proteomic analyses of metastases, to enhance comprehension of progression mechanisms. A plasma WES-based tumor-agnostic assay demonstrated higher sensitivity in detecting minimal residual disease (MRD) compared to current assays. Immune evasion appears to be the primary driver of progression in the localized CC setting, indicating the potential efficacy of immunotherapy for microsatellite stability in persons with CC. Organoid modeling further supports the promising potential of targeted therapy in eradicating MRD, surpassing conventional treatments.

Background: Microsatellite instability (MSI), resulting from a defective mismatch repair system, occurs in approximately 15% of sporadic colorectal cancers (CRC). Since MSI is associated with a poor response to 5-fluorouracile based chemotherapy and is a positive predictive marker of immunotherapy, it is routine practice to evaluate the MSI status of resected tumors in CRC patients. MSIsensor is a novel computational tool for determining MSI status using Next Generation Sequencing. However, it is not widely used in the clinic and has not been independently validated in exome data from CRC. To facilitate clinical implementation of computational determination of MSI status, we compared MSIsensor to current gold standard methods for MSI testing. Methods: MSI status was determined for 130 CRC patients (UICC stage I-IV) using immunohistochemistry, PCR based microsatellite stability testing and by applying MSIsensor to exome sequenced tumors and paired germline DNA. Furthermore, we investigated correlation between MSI status, mutational load and mutational signatures. Results: Eighteen out of 130 (13.8%) patients were microsatellite instable. We found a 100% agreement between MSIsensor and gold standard methods for MSI testing. All MSI tumors were hypermutated. In addition, two microsatellite stable (MSS) tumors were hypermutated, which was explained by a dominant POLE signature and pathogenic POLE mutations (p.Pro286Arg and p.Ser459Phe). Conclusion: MSIsensor is a robust tool, which can be used to determine MSI status of tumor samples from exome sequenced CRC patients.

Circulating tumor DNA (ctDNA) is a promising biomarker, reflecting the presence of tumor cells. Sequencing-based detection of ctDNA at low tumor fractions is challenging due to the crude error rate of sequencing. To mitigate this challenge, we developed ultra-deep mutation-integrated sequencing (UMIseq), a fixed-panel deep targeted sequencing approach, which is universally applicable to all colorectal cancer (CRC) patients. UMIseq features UMI-mediated error correction, the exclusion of mutations related to clonal hematopoiesis, a panel of normal samples for error modeling, and signal integration from single-nucleotide variations, insertions, deletions, and phased mutations. UMIseq was trained and independently validated on pre-operative (pre-OP) plasma from CRC patients (n = 364) and healthy individuals (n = 61). UMIseq displayed an area under the curve surpassing 0.95 for allele frequencies (AFs) down to 0.05%. In the training cohort, the pre-OP detection rate reached 80% at 95% specificity, while it was 70% in the validation cohort. UMIseq enabled the detection of AFs down to 0.004%. To assess the potential for detection of residual disease, 26 post-operative plasma samples from stage III CRC patients were analyzed. From this we found that the detection of ctDNA was associated with recurrence. In conclusion, UMIseq demonstrated robust performance with high sensitivity and specificity, enabling the detection of ctDNA at low allele frequencies.

Objective: Circulating tumor DNA (ctDNA) is a candidate biomarker of cancer with practice-changing potential in the detection of both early and residual disease. Disease stage and tumor size affect the probability of ctDNA detection, whereas little is known about the influence of other tumor characteristics on ctDNA detection. This study investigates the impact of tumor cell whole-genome doubling (WGD) on the detection of ctDNA in plasma collected preoperatively from newly diagnosed colorectal cancer (CRC) patients. Methods: WGD was estimated from copy numbers derived from whole-exome sequencing (WES) data of matched tumor and normal DNA from 833 Danish CRC patients. To explore if tumor WGD status impacts ctDNA detection, we applied tumor-informed ctDNA analysis to preoperative plasma samples from all patients. Results: Patients with WGD+ tumors had 53% increased odds of being ctDNA positive (OR = 1.53, 95%CI: 1.12–2.09). After stratification for UICC stage, the association persisted for Stage I (OR = 2.44, 95%CI: 1.22–5.03) and Stage II (OR = 1.76, 95%CI: 1.11–2.81) but not for Stage III (OR = 0.83, 95%CI: 0.44–1.53) patients. Conclusion: The presence of WGD significantly increases the probability of detecting ctDNA, particularly for early-stage disease. In patients with more advanced disease, the benefit of WGD on ctDNA detection is less pronounced, consistent with increased DNA shedding from these tumors, making ctDNA detection less dependent on the amount of ctDNA released per tumor cell.