MétaCan
Menu
Back to cohort

Abstract PR009: Bugs in Space: Spatial Analysis of the Immune-Microbial Axis in Rectal Cancer Reveals a Unique Interface in Young Onset Rectal Cancers

2025· article· en· W4417203945 on OpenAlexaboutno aff
Ryan B. Morgan, Reed I. Ayabe, Brenda Melendez, Taylor Neilson, Laurence P. Diggs, Norman Galbraith, Ashish Damania, Bharat Singh, Matthew C. Wong, Pranoti Sahasrabhojane, Yasmine Hoballah, Melissa W. Taggart, Alexander J. Lazar, Khalida Wani, Davis R. Ingram, Diana Shamsutdinova, Jumanah Alshenaifi, Zuzana Lutter-Berka, David G. Menter, Ramy Behman, Paula Marincola Smith, George J. Chang, Nadim J. Ajami, Susan Bullman, Christopher D. Johnston, Scott Kopetz, J. Joshua Smith, Jennifer A. Wargo, Y. Nancy You, Michael G. White

Bibliographic record

VenueClinical Cancer Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsColorectal cancerImmune systemTranscriptomeMicrobiomeDigital polymerase chain reactionTumor microenvironmentCancerGene expression profiling

Abstract

fetched live from OpenAlex

Abstract Several hypotheses have been postulated to define the mechanism behind the rising incidence of young onset rectal cancer (YORC). These hypotheses often relate to differences in a population’s exposome and back to a patient’s gut or tumor microbiome. We previously demonstrated a unique tumoral microbiome in YORC (<50 years old) versus late-onset (≥50 years old, LORC) rectal cancers through metagenomic quantification of intra-tumoral bacteria. Here we further compare tumoral immune signatures in response to the presence of tumoral bacteria between YORC and LORC. We build on previous bulk sequencing analyses to correlate tumoral microbial presence with rectal cancer outcomes and tumor immune infiltrates with the hypothesis that tumoral bacteria lead to derangements in local host immune response as a mechanism to affect response rates to neoadjuvant therapy. Pretreatment biopsies from rectal adenocarcinomas were studied using NanoString GeoMx digital spatial profiling using the Whole Human Transcriptome Atlas and 16S rRNA probes. We initially studied the impact of bacterial presence in these tumors and noted distinct immune profiles when comparing sterile (Baclow) with bacterially enriched (Bachigh) regions of the tumor. In Bachigh regions, a higher proportion of memory B-cells (p=0.042) and M1 macrophages (p=0.023) and lower abundance of naïve B cells (p=0.046) were noted – suggesting a decrease in adaptive immunity in Bachigh regions of the tumor. Importantly lower bacterial density and increased B cell activity each correlated with higher rates of pathologic response. Differential expression of genes previously associated with deleterious microbes and tumor progression such as CXCL8 (p<0.001), VIM (p=0.010), TGFBI (p=0.004), and SPP1 (p=0.018) were noted in Bachigh tumor regions. While CXCL8 (p=0.046), MYC (p=0.024), VEGFA (p=0.008), and ICAM1 (p=0.005) were upregulated in Bachigh stromal regions. This underscores the important role tumoral bacteria play in rectal cancer derangement of the host immune response and the associated evasion of tumor response to cytotoxic neoadjuvant therapy resulting in poorly controlled progression of these tumors. When comparing the effect of bacteria on these immune infiltrates in YORC and LORC, we see B cell maturation suppressed in the Bachigh regions of YORC with a decrease in memory B cell populations (p=0.005) and a concomitant increase in naïve B cells (p=0.004). While LORC Bachigh regions were associated with an immune landscape skewed toward innate inactivation and an increase in neutrophils (p=0.091), dendritic cells (p=0.011), and inactivated NK cells (p=0.026) and an increase in extracellular matrix (ECM) organization, proteoglycans, and degradation. Ongoing studies will confirm whether this differential response between YORC and LORC patients is secondary to age, specific bacterial populations, or a combination of factors. Ultimately, however, these bacteria provide intriguing targets for clearance as being studied (NCT06569368) during neoadjuvant therapy for locally advanced rectal cancers. Citation Format: Ryan Morgan, Reed Ayabe, Brenda Melendez, Taylor Neilson, Laurence Diggs, Norman Galbraith, Ashish Damania, Bharat Singh, Matthew Wong, Pranoti Sahasrabhojane, Yasmine Hoballah, Melissa Taggart, Alexander Lazar, Khalida Wani, Davis Ingram, Diana Shamsutdinova, Jumanah Alshenaifi, Zuzana Lutter-Berka, David Menter, Ramy Behman, Paula M. Smith, George J. Chang, Nadim Ajami, Susan Bullman, Christopher Johnston, Scott Kopetz, J. Joshua. Smith, Jennifer A. Wargo, Y. Nancy. You, Michael G. White. Bugs in Space: Spatial Analysis of the Immune-Microbial Axis in Rectal Cancer Reveals a Unique Interface in Young Onset Rectal Cancers [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 PR009.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.050
GPT teacher head0.481
Teacher spread0.430 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueClinical Cancer ResearchSame topicCancer Research and TreatmentsFrench-language works237,207