Abstract LB102: Triaging oral premalignant lesions: Plasma ultrashort cell-free DNA-based liquid biopsy approach
Bibliographic record
Abstract
Abstract Background: Rapid advancements in cell-free DNA (cfDNA) based liquid biopsy (LB), has opened avenues of critical clinical importance. Recent discovery of a novel class of cell-free DNA 40-70 bps in length, ultrashort cfDNA (uscfDNA) is demonstrating immense potential as a cancer early detection biomarker. Globally, oral cavity squamous cell carcinomas (OCSCC) make up a significant proportion of head and neck squamous cell cancers. OCSCC commonly arises after the occurrence of oral premalignant lesions (OPLs), making it an ideal target for plasma-based LB screening initiatives. Methods: Current work focuses on preferential extraction of low molecular weight nucleic acids and single-stranded library preparation and sequencing, Broad Range cell-free DNA- Sequencing (BRcfDNA-Seq), to obtain uscf- & 167 bps mononucleosomal cfDNA (mncfDNA), for disease detection. Sequencing data was bioinformatically processed: paired-end reads merged (BBmerge), aligned with BWA-mem, deduplicated using SRSLY UMI, and blacklisted portions removed. This was followed by analysis for non-mutational features like fragmentomics, occurrence of G-Quad structures, 4-mer Motif sequences at the end of cfDNA sequences, functional genomic element peak formation by uscfDNA. These features have been recently described non-mutation metrics which have demonstrated evidence of clinical relevance. With non-mutational multi-modal analysis of uscfDNA, obtained using BRcfDNA-Seq, we were able to categorize oral premalignant disorders into two cohorts: one which progressed into OCSCC (PG-OPL) (n=19) & one which did not (nPG-OPL) (n=19). Results: Bioinformatic processing for fragmentomics, of the relative proportion of 40-53bps fragments to 54-70bps fragments in the uscfDNA population demonstrated a significant difference across 1700 chromosomal bins between PG & nPG-OPL (multiple t test, FDR 10%, p value = 0.044, AUROC = 0.7258). The occurrence of G-quadruplex structures in uscfDNA was also significantly different between the two groups (student t test, p= 0.02, AUROC= 0.6953). Examination of the end-motifs profiles of uscfDNA between PG-OPL & nPG-OPL samples showed the randomness of the motifs as revealed by the Shannon entropy score is significant between the two groups (p = 0.046, AUROC = 0.6482). We further evaluated individual motifs that could discriminate between the two groups and identified CCCC, CCCT, TGGG, etc. are highly discriminatory. uscfDNA contained a substantially higher proportion of functional genomic element sequences in the PG-OPL group than the nPG-OPL group like exon (p = 0.00067, AUROC = 0.7147) & 5’ UTR (p= 0.000006, AUROC= 0.7673) are different between the groups. Conclusion: Results demonstrated clinical relevance of BRcfDNA-Seq for plasma-derived cfDNA in assessment of malignancy progression of OPLs. These non-mutational multi-modal features of cfDNA maybe indicative of local and systemic factors associated with disease affecting cfDNA. Citation Format: Neeti Swarup, Jordan C. Cheng, Irene Choi, Mohammad Arshad Aziz, Kelly Y. Liu, Fang Wei, Feng Li, Yong Kim, Catherine Poh, David T. Wong. Triaging oral premalignant lesions: Plasma ultrashort cell-free DNA-based liquid biopsy approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB102.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".