Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment.

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-EDGESNV 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-EDGECNV 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-EDGESNV 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.

Error-Corrected Deep Targeted Sequencing of Circulating Cell-Free DNA from Colorectal Cancer Patients for Sensitive Detection of Circulating Tumor DNA.

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.

Detection and characterization of lung cancer using cell-free DNA fragmentomes.

Non-invasive approaches for cell-free DNA (cfDNA) assessment provide an opportunity for cancer detection and intervention. Here, we use a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation in a prospective study of 365 individuals at risk for lung cancer. We validate the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 lung cancer patients. Combining fragmentation features, clinical risk factors, and CEA levels, followed by CT imaging, detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites distinguished individuals with small cell lung cancer from those with non-small cell lung cancer with high accuracy (AUC = 0.98). A higher fragmentation score represented an independent prognostic indicator of survival. This approach provides a facile avenue for non-invasive detection of lung cancer.

Age-stratified reference intervals unlock the clinical potential of circulating cell-free DNA as a biomarker of poor outcome for healthy individuals and patients with colorectal cancer.

Circulating cell-free DNA (cfDNA) has spurred much interest as a biomarker in oncology. However, inter- and intra-individual cfDNA levels vary greatly. Consequently, in order to base clinical decisions on cfDNA measurements, normal reference intervals are essential to avoid that ordinary variation is confused with clinically relevant change. The lack of reference intervals may potentially explain the ambiguous results reported in the field. Our study aimed to establish reference intervals and to evaluate the association between cfDNA and demographic and clinical variables, including colorectal cancer (CRC). Plasma samples and clinical data from 2817 subjects were collected including 1930 noncancer individuals and 887 CRC patients. cfDNA was measured using droplet digital polymerase chain reaction (PCR). The large cohort combined with robust cfDNA quantification enabled establishment of reference intervals (<67 years: 775-4860 copies/mL; ≥67 years: 807-6561 copies/mL). A cfDNA level above the age-stratified 90% percentile was prognostic of reduced survival in both noncancer individuals and CRC patients, with HR values of 2.56 and 2.01, respectively. Moreover, cfDNA levels increased significantly with age, elevated BMI and chronic diseases. In CRC, the cfDNA level was increased for Stage IV, but not Stage I to Stage III cancer. In summary, the use of reference intervals revealed that high cfDNA levels were predictive of shorter survival in both noncancer individuals and CRC patients, and that CRC development did not affect the cfDNA level until metastatic dissemination. Furthermore, cfDNA levels were impacted by age and chronic diseases. Conclusively, our study presents reference intervals that will help pave the way for clinical utilization of cfDNA.

Epigenetic Analysis of Circulating Tumor DNA in Localized and Metastatic Prostate Cancer: Evaluation of Clinical Biomarker Potential.

Novel and minimally-invasive prostate cancer (PCa)-specific biomarkers are needed to improve diagnosis and risk stratification. Here, we investigated the biomarker potential in localized and de novo metastatic PCa (mPCa) of methylated circulating tumor DNA (ctDNA) in plasma. Using the Marmal-aid database and in-house datasets, we identified three top candidates specifically hypermethylated in PCa tissue: DOCK2,HAPLN3, and FBXO30 (specificity/sensitivity: 80%-100%/75-94%). These candidates were further analyzed in plasma samples from 36 healthy controls, 61 benign prostatic hyperplasia (BPH), 102 localized PCa, and 65 de novo mPCa patients using methylation-specific droplet digital PCR. Methylated ctDNA for DOCK2/HAPLN3/FBXO30 was generally not detected in healthy controls, BPH patients, nor in patients with localized PCa despite a positive signal in 98%-100% of matched radical prostatectomy tissue samples. However, ctDNA methylation of DOCK2,HAPLN3, and/or FBXO30 was detected in 61.5% (40/65) of de novo mPCa patients and markedly increased in high- compared to low-volume mPCa (89.3% (25/28) vs. 32.1% (10/31), p < 0.001). Moreover, detection of methylated ctDNA was associated with significantly shorter time to progression to metastatic castration resistant PCa, independent of tumor-volume. These results indicate that methylated ctDNA (DOCK2/HAPLN3/FBXO30) may be potentially useful for identification of hormone-naïve mPCa patients who could benefit from intensified treatment.

Novel DNA methylation biomarkers show high sensitivity and specificity for blood-based detection of colorectal cancer-a clinical biomarker discovery and validation study.

BACKGROUND: Early detection plays an essential role to reduce colorectal cancer (CRC) mortality. While current screening methods suffer from poor compliance, liquid biopsy-based strategies for cancer detection is rapidly gaining promise. Here, we describe the development of TriMeth, a minimal-invasive blood-based test for detection of early-stage colorectal cancer. The test is based on assessment of three tumour-specific DNA methylation markers in circulating cell-free DNA. RESULTS: A thorough multi-step biomarker discovery study based on DNA methylation profiles of more than 5000 tumours and blood cell populations identified CRC-specific DNA methylation markers. The DNA methylation patterns of biomarker candidates were validated by bisulfite sequencing and methylation-specific droplet digital PCR in CRC tumour tissue and peripheral blood leucocytes. The three best performing markers were first applied to plasma from 113 primarily early-stage CRC patients and 87 age- and gender-matched colonoscopy-verified controls. Based on this, the test scoring algorithm was locked, and then TriMeth was validated in an independent cohort comprising 143 CRC patients and 91 controls. Three DNA methylation markers, C9orf50, KCNQ5, and CLIP4, were identified, each capable of discriminating plasma from colorectal cancer patients and healthy individuals (areas under the curve 0.86, 0.91, and 0.88). When combined in the TriMeth test, an average sensitivity of 85% (218/256) was observed (stage I: 80% (33/41), stage II: 85% (121/143), stage III: 89% (49/55), and stage IV: 88% (15/17)) at 99% (176/178) specificity in two independent plasma cohorts. CONCLUSION: TriMeth enables detection of early-stage colorectal cancer with high sensitivity and specificity. The reported results underline the potential utility of DNA methylation-based detection of circulating tumour DNA in the clinical management of colorectal cancer.

Genome-wide cell-free DNA fragmentation in patients with cancer.

Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer1. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.

Comparative analysis of 12 different kits for bisulfite conversion of circulating cell-free DNA.

Blood circulating cell-free DNA (cfDNA) is becoming popular in the search of promising predictive and prognostic biomarkers. Among these biomarkers, cfDNA methylation markers have especially gained considerable attention. A significant challenge in the utilization of cfDNA methylation markers is the limited amount of cfDNA available for analyses; reportedly, bisulfite conversion (BSC) reduce cfDNA amounts even further. Nevertheless, few efforts have focused on ensuring high cfDNA conversion efficiency and recovery after BSC. To compare cfDNA recovery of different BSC methods, we compared 12 different commercially available BSC kits. We tested whether DNA recovery was affected by the molecular weight and/or quantity of input DNA. We also tested BSC efficiency for each kit. We found that recovery varied for DNA fragments of different lengths: certain kits recovered short fragments better than others, and only 3 kits recovered DNA fragments of <100 bp well. In contrast, DNA input amount did not seem to affect DNA recovery: for quantities spanning between 820 and ∼25,000 genome equivalents per BSC, a linear relation was found between input and recovery amount. Overall, mean recovery ranged between 9 and 32%, with BSC efficiency of 97-99.9%. When plasma cfDNA was used as input for BSC, recovery varied from 22% for the poorest and 66% for the best performing kits, while conversion efficiency ranged from 96 to 100% among different kits. In conclusion, clear performance differences exist between commercially available BSC kits, both in terms of DNA recovery and conversion efficiency. The choice of BSC kit can substantially impact the amount of converted cfDNA available for downstream analysis, which is critical in a cfDNA methylation marker setting.

High folic acid diet enhances tumour growth in PyMT-induced breast cancer.

BACKGROUND: The B-vitamin folate is among the most studied bioactive food compound, and a dietary intake meeting the daily requirements has been found to reduce the risk of cancer and cardiovascular diseases as well as preventing neural tube defects during fetal development. Several countries have therefore introduced dietary fortification with folic acid. However, clinical and animal studies suggest that folic acid has a dual role in cancer development. METHODS: During the period of initial tumour progression, MMTV-PyMT (MMTV-polyoma virus middle T) transgenic mice were fed with normal diet and high folic acid diet. RESULTS: We found that PyMT-induced breast tumours highly express the cancer-specific folate receptor (FR), a feature they share with several human epithelial cancers in which expression of FRα correlates with tumour grade. Mice receiving a high folic acid diet displayed a significantly increased tumour volume compared with mice receiving normal diet. In the largest tumours, only found in mice on high folic acid diet, STAT3 was activated. In primary cells from PyMT tumours, STAT3 was activated upon treatment with folic acid in culture. CONCLUSIONS: Our results offer a novel molecular explanation for folic acid-induced growth of existing tumours.