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Record W4294486668 · doi:10.1136/gutjnl-2022-iddf.81

IDDF2022-ABS-0260 Targeting GUT microbiota to prevent anastomotic tumors and distant metastasis in colorectal cancer surgery

2022· article· en· W4294486668 on OpenAlexaff
Roy Hajjar, Ayodeji S. Ajayi, Manon Oliero, Gabriela Fragoso, Ahmed Amine Alaoui, Thibault Cuisiniere, Claire Gerkins, Annie Calvé, Hervé Vennin Rendos, Carole Richard, Manuela M. Santos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsColorectal cancerMetastasisAnastomosisMedicineCancerGut floraSurgeryCancer researchInternal medicineImmunology

Abstract

fetched live from OpenAlex

Background Despite major advances in treatment and early detection, colorectal cancer (CRC) remains a leading cause of mortality worldwide. This is mainly due to cancer recurrence following surgical resection, which is the main CRC treatment. Colorectal resections involve an anastomosis to rejoin the remaining bowel ends to restore gastrointestinal continuity. It has been suggested that poor anastomotic healing and leakage (AL) allows cancer cells to implant at the anastomotic site thereby increasing the risk of local cancer recurrence and metastatic spread. In previous studies, we showed that inulin, a well-known prebiotic improves anastomotic healing by strengthening the gut barrier. Here we further investigated the relationship between the promotion of postoperative intestinal healing using prebiotics and anastomotic cancer local implantation and dissemination. Methods A 10 year’s retrospective review of AL and non-AL cases after CRC surgery was performed. To experimentally assess the effect of poor anastomotic healing on local tumor implantation, we subjected mice to colonic surgery and modulated wound repair by varying the number of sutures. The effect of dietary supplementation with inulin on the occurrence of local anastomotic tumors was assessed in a mouse model inoculated with tumor cells directly in the gut lumen after surgery. Finally, we investigated in mice whether inulin may prevent metastatic spread and growth of tumor cells in the liver by transplanting CRC cells surgically into the spleen. Results Patients experiencing AL (N = 135) displayed significantly lower overall survival and more cancer recurrence and progression compared to non-AL patients (N = 360) (IDDF2022-ABS-0260 Figure 1A Overall and oncological survival after colorectal cancer surgery, IDDF2022-ABS-0260 Figure 1B Overall and oncological survival after colorectal cancer surgery). Poor anastomotic healing in mice led to larger anastomotic tumors and peritoneal cancer dissemination. Inulin supplementation significantly inhibited local tumor implantation and metastatic spread, increased butyrate production, and decreased bacterial translocation. Conclusions AL was associated with worse oncological outcomes in patients and mice. Inulin was shown to reinforce the gut barrier function, decrease the implantation of cancer cells at the anastomosis site, and to prevent tumor dissemination and progression of liver metastasis. Our data suggest that improving anastomotic healing after CRC surgery through gut microbiota modulation not only prevents AL but may additionally inhibit anastomotic cancer recurrence and metastatic spread.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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.

Opus teacher head0.018
GPT teacher head0.282
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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