Abstract LB102: Triaging oral premalignant lesions: Plasma ultrashort cell-free DNA-based liquid biopsy approach
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».