Molecular analysis for ovarian cancer detection in patient-friendly samples.

BACKGROUND: High ovarian cancer mortality rates motivate the development of effective and patient-friendly diagnostics. Here, we explored the potential of molecular testing in patient-friendly samples for ovarian cancer detection. METHODS: Home-collected urine, cervicovaginal self-samples, and clinician-taken cervical scrapes were prospectively collected from 54 patients diagnosed with a highly suspicious ovarian mass (benign n = 25, malignant n = 29). All samples were tested for nine methylation markers, using quantitative methylation-specific PCRs that were verified on ovarian tissue samples, and compared to non-paired patient-friendly samples of 110 age-matched healthy controls. Copy number analysis was performed on a subset of urine samples of ovarian cancer patients by shallow whole-genome sequencing. RESULTS: Three methylation markers are significantly elevated in full void urine of ovarian cancer patients as compared to healthy controls (C2CD4D, P = 0.008; CDO1, P = 0.022; MAL, P = 0.008), of which two are also discriminatory in cervical scrapes (C2CD4D, P = 0.001; CDO1, P = 0.004). When comparing benign and malignant ovarian masses, GHSR shows significantly elevated methylation levels in the urine sediment of ovarian cancer patients (P = 0.024). Other methylation markers demonstrate comparably high methylation levels in benign and malignant ovarian masses. Cervicovaginal self-samples show no elevated methylation levels in patients with ovarian masses as compared to healthy controls. Copy number changes are identified in 4 out of 23 urine samples of ovarian cancer patients. CONCLUSIONS: Our study reveals increased methylation levels of ovarian cancer-associated genes and copy number aberrations in the urine of ovarian cancer patients. Our findings support continued research into urine biomarkers for ovarian cancer detection and highlight the importance of including benign ovarian masses in future studies to develop a clinically useful test.

Ovarian cancer is often found late with limited treatment options. Currently, it is difficult to diagnose ovarian cancer correctly and no recommended early detection or screening methods exist. Our aim was to explore the use of DNA-based tests in patient-friendly samples for ovarian cancer detection. Patient-friendly samples are patient materials that can be collected from home without pain or discomfort, such as self-collected vaginal swabs and urine. Using DNA-based tests, we found that urine of women with ovarian cancer contains ovarian cancer-associated signals. Our findings encourage further development of a potential urine test for ovarian cancer detection. This approach could aid early detection and guide women with ovarian masses to appropriate specialist care.

Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis.

The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n = 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n = 220). cfDNA detection correlates with a shorter overall (p = 0.0086) and recurrence-free (p = 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n = 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.

Real-time analysis of the cancer genome and fragmentome from plasma and urine cell-free DNA using nanopore sequencing.

Cell-free DNA (cfDNA) can be isolated and sequenced from blood and/or urine of cancer patients. Conventional short-read sequencing lacks deployability and speed and can be biased for short cfDNA fragments. Here, we demonstrate that with Oxford Nanopore Technologies (ONT) sequencing we can achieve delivery of genomic and fragmentomic data from liquid biopsies. Copy number aberrations and cfDNA fragmentation patterns can be determined in less than 24 h from sample collection. The tumor-derived cfDNA fraction calculated from plasma of lung cancer patients and urine of bladder cancer patients was highly correlated (R = 0.98) with the tumor fraction calculated from short-read sequencing of the same samples. cfDNA size profile, fragmentation patterns, fragment-end composition, and nucleosome profiling near transcription start sites in plasma and urine exhibited the typical cfDNA features. Additionally, a high proportion of long tumor-derived cfDNA fragments (> 300 bp) are recovered in plasma and urine using ONT sequencing. ONT sequencing is a cost-effective, fast, and deployable approach for obtaining genomic and fragmentomic results from liquid biopsies, allowing the analysis of previously understudied cfDNA populations.

The landscape of cell-free mitochondrial DNA in liquid biopsy for cancer detection.

BACKGROUND: Existing methods to detect tumor signal in liquid biopsy have focused on the analysis of nuclear cell-free DNA (cfDNA). However, non-nuclear cfDNA and in particular mitochondrial DNA (mtDNA) has been understudied. We hypothesize that an increase in mtDNA in plasma could reflect the presence of cancer, and that leveraging cell-free mtDNA could enhance cancer detection. RESULTS: We survey 203 healthy and 664 cancer plasma samples from three collection centers covering 12 cancer types with whole genome sequencing to catalogue the plasma mtDNA fraction. The mtDNA fraction is increased in individuals with cholangiocarcinoma, colorectal, liver, pancreatic, or prostate cancer, in comparison to that in healthy individuals. We detect almost no increase of mtDNA fraction in individuals with other cancer types. The mtDNA fraction in plasma correlates with the cfDNA tumor fraction as determined by somatic mutations and/or copy number aberrations. However, the mtDNA fraction is also elevated in a fraction of patients without an apparent increase in tumor-derived cfDNA. A predictive model integrating mtDNA and copy number analysis increases the area under the curve (AUC) from 0.73 when using copy number alterations alone to an AUC of 0.81. CONCLUSIONS: The mtDNA signal retrieved by whole genome sequencing has the potential to boost the detection of cancer when combined with other tumor-derived signals in liquid biopsies.

Genome-wide and panel-based cell-free DNA characterization of patients with resectable esophageal adenocarcinoma.

Circulating tumor DNA (ctDNA) holds promise in resectable esophageal adenocarcinoma (EAC) to predict patient outcome but is not yet sensitive enough to be clinically applicable. Our aim was to combine ctDNA mutation data with shallow whole-genome sequencing (sWGS)-derived copy number tumor fraction estimates (ichorCNA) to improve pathological response and survival prediction in EAC. In total, 111 stage II/III EAC patients with baseline (n = 111), post-neoadjuvant chemoradiotherapy (nCRT) (n = 68), and pre-surgery (n = 92) plasma samples were used for ctDNA characterization. sWGS (<5× coverage) was performed on all time-point samples, and copy number aberrations were estimated using ichorCNA. Baseline and pre-surgery samples were sequenced using a custom amplicon panel for mutation detection. Detection of baseline ctDNA was successful in 44.3% of patients by amplicon sequencing and 10.5% by ichorCNA. Combining both, ctDNA could be detected in 50.5% of patients. Baseline ctDNA positivity was related to higher T stage (cT3, 4) (p = 0.017). There was no relationship between pathological response and baseline ctDNA positivity. However, baseline ctDNA metrics (variant allele frequency > 1% or ichorCNA > 3%) were associated with a high risk of disease progression [HR = 2.23 (95% CI 1.22-4.07), p = 0.007]. The non-clearance of a baseline variant or ichorCNA > 3% in pre-surgery samples was related to early progression [HR = 4.58 (95% CI 2.22-9.46), p < 0.001]. Multi-signal analysis improves detection of ctDNA and can be used for prognostication of resectable EAC patients. Future studies should explore the potential of multi-modality sequencing for risk stratification and treatment adaptation based on ctDNA results. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The Effect of Preanalytical and Physiological Variables on Cell-Free DNA Fragmentation.

BACKGROUND: Assays that account for the biological properties and fragmentation of cell-free DNA (cfDNA) can improve the performance of liquid biopsy. However, preanalytic and physiological differences between individuals on fragmentomic analysis are poorly defined. METHODS: We analyzed the impact of collection tube, plasma processing time, and physiology on the size distribution of cfDNA, their genome-wide representation, and sequence diversity at the cfDNA fragment ends using shallow whole-genome sequencing. RESULTS: Neither different stabilizing collection tubes nor processing times affected the cfDNA fragment sizes, but could impact the genome-wide fragmentation patterns and fragment-end sequences of cfDNA. In addition, beyond differences depending on the gender, the physiological conditions tested between 63 individuals (age, body mass index, use of medication, and chronic conditions) minimally influenced the outcome of fragmentomic methods. CONCLUSIONS: Fragmentomic approaches have potential for implementation in the clinic, pending clear traceability of analytical and physiological factors.

Fragmentation patterns and personalized sequencing of cell-free DNA in urine and plasma of glioma patients.

Glioma-derived cell-free DNA (cfDNA) is challenging to detect using liquid biopsy because quantities in body fluids are low. We determined the glioma-derived DNA fraction in cerebrospinal fluid (CSF), plasma, and urine samples from patients using sequencing of personalized capture panels guided by analysis of matched tumor biopsies. By sequencing cfDNA across thousands of mutations, identified individually in each patient's tumor, we detected tumor-derived DNA in the majority of CSF (7/8), plasma (10/12), and urine samples (10/16), with a median tumor fraction of 6.4 × 10-3 , 3.1 × 10-5 , and 4.7 × 10-5 , respectively. We identified a shift in the size distribution of tumor-derived cfDNA fragments in these body fluids. We further analyzed cfDNA fragment sizes using whole-genome sequencing, in urine samples from 35 glioma patients, 27 individuals with non-malignant brain disorders, and 26 healthy individuals. cfDNA in urine of glioma patients was significantly more fragmented compared to urine from patients with non-malignant brain disorders (P = 1.7 × 10-2 ) and healthy individuals (P = 5.2 × 10-9 ). Machine learning models integrating fragment length could differentiate urine samples from glioma patients (AUC = 0.80-0.91) suggesting possibilities for truly non-invasive cancer detection.

Toward the Early Detection of Cancer by Decoding the Epigenetic and Environmental Fingerprints of Cell-Free DNA.

Widespread adaptation of liquid biopsy for the early detection of cancer has yet to reach clinical utility. Circulating tumor DNA is commonly detected though the presence of genetic alterations, but only a minor fraction of tumor-derived cell-free DNA (cfDNA) fragments exhibit mutations. The cellular processes occurring in cancer development mark the chromatin. These epigenetic marks are reflected by modifications in the cfDNA methylation, fragment size, and structure. In this review, we describe how going beyond DNA sequence information alone, by analyzing cfDNA epigenetic and immune signatures, boosts the potential of liquid biopsy for the early detection of cancer.