The role of gut microbiome in modulating response to immune checkpoint inhibitor therapy in cancer
Why this work is in the frame
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Bibliographic record
Abstract
Abstract: Immunotherapy has led to a paradigm shift in the treatment of several cancers. There have been significant efforts to identify biomarkers that can predict response and toxicities related to immune checkpoint inhibitor (ICPI) therapy. Despite these advances, it has been challenging to tease out why a subset of patients benefit more than others or why certain patients experience immune-related adverse events (irAEs). Although the immune-modulating properties of the human gut bacterial ecosystem are yet to be fully elucidated, there has been growing interest in evaluating the role of the gut microbiome in shaping the therapeutic response to cancer immunotherapy. Considerable research efforts are currently directed to utilizing metagenomic and metabolic profiling of stool microbiota in patients on ICPI-based therapies. Dysbiosis or loss of microbial diversity has been associated with a poor treatment response to ICPIs and worse survival outcomes in cancer patients. Emerging data have shown that certain bacterial strains, such as Faecalibacterium that confer sensitivity to ICPI, also have a higher propensity to increase the risk of irAEs. Additionally, the microbiome can modulate the local immune response at the intestinal interface and influence the trafficking of bacterial peptide primed T-cells distally, influencing the toxicity patterns to ICPI. Antibiotic or diet induced alterations in composition of the microbiome can also indirectly alter the production of certain bacterial metabolites such as deoxycholate and short chain fatty acids that can influence the anti-tumor tolerogenesis. Gaining sufficient understanding of the exact mechanisms underpinning the interplay between ICPI induced anti-tumor immunity and the immune modulatory role gut microbiome can be vital in identifying potential avenues of improving outcomes to cancer immunotherapy. In the current review, we have summarized and highlighted the key emerging data supporting the role of gut microbiome in regulating response to ICPIs in cancer.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it