Abstract PR013: Distinct Oral Bacterial Signatures in Rectal Cancer Tumors Associated with Age of Onset and Treatment Response
Bibliographic record
Abstract
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.
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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) | 0.001 | 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".