Abstract 5596: Cell free DNA levels and fragmentation patterns in different liquid biopsy analytes (blood, urine and vaginal fluid) in cervical cancer patients
Bibliographic record
Abstract
Abstract Background: Cervical cancer (CC) is the 4th most commonly diagnosed cancer among women, with approximately 528,000 new cases annually. Current screening approaches for this disease have certain limitations; Pap tests require dedicated cytopathology infrastructure, while human papillomavirus (HPV) DNA testing may lead to invasive procedures in patients with transient infection. Liquid biopsy has emerged as a minimally invasive approach to detect and monitor disease progression and treatment response. We and others have previously demonstrated the clinical utility of circulating tumor (ct)DNA to monitor HPV+ cancers. Moreover, cell free (cf)DNA fragmentation patterns have been found to be a biomarker of disease burden. This cfDNA is thought to originate largely as a result of cell death, where small fragments of ~167 bp are associated with apoptosis and larger fragments (>1000 bp) are associated with necrosis. Despite advances in liquid biopsy techniques, little is known about the composition of cfDNA from different analytes in CC patients. Methods: The aim of this study was to compare the presence and composition of cfDNA from different liquid biopsy analytes in patients with CC and high grade cervical intraepithelial neoplasia or dysplasia (CIN/CD). Blood, urine, and vaginal swabs were collected from 20 patients with CC and 9 patients with CIN/CD at the McGill University Health Centre. All samples were centrifuged twice to isolate supernatant. Samples were tested for HPV ctDNA by ddPCR. Analysis of fragment length was performed using the Agilent Bioanalyzer 2100. Dominant fragment was determined as the DNA fragment with the highest concentration, while overall fragment was calculated as the average fragment across all bioanalyzer peaks. Results: HPV16/18 ctDNA was detectable 14/20 CC patients and 2/6 CIN patients, and 0/3 CD patients in plasma, urine, and vaginal swab. Concordance for all sample types tested was seen in 90% of cases. On average, fragment analysis demonstrated 174, 195, and 183 bp dominant small fragments in plasma, urine and vaginal swab, respectively. Plasma samples showed only smaller fragments (range: 168-187 bp). Other analytes displayed a predominance of larger cfDNA, with an overall fragment size of 3996 and 5194 bp in urine and vaginal swab, respectively. Conclusions: HPV-DNA was detectable in all analytes sampled in patients with CC and CIN, with a trend of higher detection in CC samples. The fragmentation patterns of cfDNA varied between patients and within patients across analytes, with larger fragments - likely of necrotic origin - seen only in urine and vaginal swab cfDNA. Smaller fragments - likely related to apoptosis - were seen across all sample types studied. Overall, analysis of fragmentation may provide valuable insight into cfDNA origins in different sample types and provide a novel biomarker for diagnosis and surveillance. Citation Format: Sarah Tadhg Ferrier, Erica Mandato, Alexandra Bartolomucci, Thupten Tsering, Shuk On Annie Leung, Julia Valdemarin Burnier. Cell free DNA levels and fragmentation patterns in different liquid biopsy analytes (blood, urine and vaginal fluid) in cervical cancer patients. [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 5596.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".