Abstract PR013: Distinct Oral Bacterial Signatures in Rectal Cancer Tumors Associated with Age of Onset and Treatment Response
Notice bibliographique
Résumé
Abstract Young-onset rectal cancer (YORC, <50 years) incidence is rising, representing 20% of colorectal cancers, yet underlying mechanisms driving this epidemic remain unclear. The tumoral microbiome has emerged as a critical modulator of colorectal cancer pathogenesis, affecting tumor growth, inflammation, metastasis, and chemoresistance through complex host-microbe interactions. Emerging evidence demonstrates that specific bacterial species, including Fusobacterium nucleatum, promote tumorigenesis and therapeutic resistance in colorectal cancer models. We previously reported distinct microbial signatures between YORC and later-onset rectal cancer (LORC, ≥50 years), with tumor-associated oral bacteria correlating with treatment failure. Building on these findings, we expanded our analysis to quantify oral bacterial burden across multiple sample types and determine its clinical impact on therapeutic response. We conducted metagenomic analysis on oral (61), fecal (82), tumor (110), and 111 tumor-adjacent normal (TAN) samples from 227 treatment-naïve patients with locally advanced rectal cancer receiving standardized neoadjuvant chemoradiotherapy. Oral bacterial burden was quantified using reference bacterial taxonomies from the Human Oral Microbiome Database. Major pathological response (MPR) was defined as ≤10% residual viable tumor cells following neoadjuvant therapy. Metagenomes are being evaluated to detect and quantify known microbial genomic markers associated with colorectal cancer, including Bacteroides fragilis toxin and polyketide synthase genes found in colibactin producing E. coli. In this expanded cohort, both YORC and LORC tumors demonstrated significantly higher burden of oral bacteria compared to paired TAN tissues (p<0.001), confirming tumor-specific bacterial enrichment. Predominant oral species colonizing tumors included Parvimonas micra, Gemella morbillorum, Streptococcus sanguinis, Streptococcus salivarius, Prevotella intermedia, and multiple Fusobacterium species. Remarkably, tumoral oral bacterial burden negatively correlated with achieving MPR (p=0.014), with the strongest association observed in LORC patients. TAN tissues showed no correlation with pathological response (p>0.05), while fecal samples demonstrated significantly lower oral bacterial burden than tumors (p<0.05) with no correlation to treatment response, emphasizing the unique and clinically relevant tumoral microenvironment. Tumoral oral bacterial burden represents a potential biomarker for predicting neoadjuvant therapy response in rectal cancer patients. This discovery suggests that precision medicine approaches through targeted antimicrobial interventions to deplete tumor-associated oral bacteria may improve therapeutic outcomes. Our findings support the scientific rationale for ongoing clinical trials testing anaerobe-targeting antibiotics as adjuvant therapy (NCT06569368). Further validation in expanded cohorts and additional clinical evidence is needed to establish the clinical utility of microbiome-guided treatment approaches in colorectal cancer care. Citation Format: Nadim J. Ajami, Ashish V. Damania, Abderrahman Day, Matthew C. Wong, Pranoti V. Sahasrabhojane, Yasmine M. Hoballah, Vivian R. Orellana, Jillian S. Losh, Brenda D. Melendez, Mona M. Ahmed, Lon W. Fong, Bharat B. Singh, Melissa W. Taggart, Khalida Wani, Davis R. Ingram, Diana D. Shamsutdinova, Alexander Lazar, Jumanah Y. Alshenafi, Zuzana Lutter-Berka, Ryan B. Morgan, Taylor M. Neilson, Laurence Diggs, Ramy S. Behman, Paula M. Smith, George J. Chang, David Menter, Christopher D. Johnston, Susan Bullman, Yi-Qian Nancy. You, Scott Kopetz, Michael G. White, Jennifer A. Wargo. Distinct Oral Bacterial Signatures in Rectal Cancer Tumors Associated with Age of Onset and Treatment Response [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr PR013.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».