Assessing the changes to the gut microbiome following radiation therapy in a bladder cancer context
Bibliographic record
Abstract
According to the Canadian Cancer Society, bladder cancer (BC) is projected to be the 5th most common cancer in Canada in 2023, with a projected 13,400 total cases amongst Canadians.Of those cases, 30% are muscle-invasive (MIBC), where the standard of care, radical cystectomy, involves the complete removal of the bladder.This results in reduction in quality of life, characterized by urinary and sexual impairment.Additionally, as bladder cancer is more prevalent among older individuals, many MIBC patients will not be able to undergo surgery.Because of this, there is a need for effective bladder sparing alternatives.Radiation therapy (RT) has emerged as a viable approach in appropriately selected patients, but about 25-30% of patients do not respond and will need a salvage cystectomy.Additionally, RT is likely to induce its own adverse events, thus also reducing quality of life.Various factors are thus being studied on how to improve response to radiation while minimizing adverse events.One such factor being studied is the gut microbiome, which is implicated in radiation-induced toxicity as well as response to various combination therapies commonly used with RT.Although the effects of RT on the microbiome have been heavily studied, this relationship is still unknown in a bladder cancer context.To study this relationship, we performed several in vivo experiments in which RT was administered to the mouse.These experiments included a non-tumor model where 6x6Gy radiation was administered to the bladder, and a UPPL1540 (UPPL) cold bladder tumor model where 2x5Gy radiation was administered to the tumor on the right flank.After RT was administered, stool samples were collected from all mice, and were sequenced using 16S rRNA gene sequencing.Using this sequence data, bioinformatic analysis was performed to acquire information on the composition, diversity, and functional pathways of the microbiota.From these experiments, we found several bacteria whose relative abundance was significantly adjusted post-RT in both mouse models.Additionally, RT-induced changes to the gut microbiota were found to be both sex-dependent, and time-dependent, where different time points showed different microbial signatures.Whether these changes induce a more beneficial or harmful microbiota is still unknown, as increases and decreases were observed in both beneficial and harmful bacteria; the role of many affected features in bladder cancer is still unknown.Microbial diversity was mostly unchanged by radiation.RT was also found to also adjust the abundance of various functional pathways in the gut microbiome, most notably the Proteasome pathway, which was upregulated in both experiments.A better understanding of the effects of bladder cancer RT on the gut microbiota would allow for microbiota-centric interventions to reduce radiation-induced toxicity and improve the effectiveness of combination therapies.However, although these results allow for a better understanding of these effects, the clinical implications are still unknown, and thus further research needs to be conducted to assess the clinical relevance of these changes before any interventions can be implemented.Résumé Selon la Société canadienne du cancer, le cancer de la vessie (CV) devrait être le cinquième cancer le plus fréquent au Canada en 2023, avec un total de 13 400 cas projetés parmi les Canadiens.Parmi ces cas, 30 % sont des cancers à invasion musculaire (CIMV), pour lesquels la norme de soins, la cystectomie radicale, implique la résection complète de la vessie.Il en résulte une réduction de la qualité de vie, caractérisée par des troubles urinaires et sexuels.En outre, le CV étant plus fréquent chez les personnes âgées, de nombreux patients atteints de MIBC ne pourront pas subir d'intervention chirurgicale.C'est pourquoi il est nécessaire de trouver des solutions efficaces pour préserver la vessie.La radiothérapie (RT) s'est imposée comme une approche viable chez les patients convenablement sélectionnés, mais environ 25 à 30 % des patients ne réagissent pas et doivent subir une cystectomie de sauvetage.En outre, la radiothérapie est susceptible d'induire ses propres effets indésirables, réduisant ainsi la qualité de vie.Différents facteurs sont donc étudiés pour améliorer la réponse à la radiothérapie tout en minimisant les effets indésirables.L'un de ces facteurs est le microbiome intestinal, qui est impliqué dans la toxicité induite par les radiations ainsi que dans la réponse à diverses thérapies combinées couramment utilisées avec la RT.Bien que les effets de la radiothérapie sur le microbiome aient été largement étudiés, cette relation est encore inconnue dans le contexte du CV.Pour étudier cette relation, nous avons réalisé plusieurs expérimentations in vivo au cours desquelles la RT a été administrée à la souris.Ces expérimentations comprenaient un modèle non
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".