Surrogate markers of intestinal dysfunction associated with survival in advanced cancers
Bibliographic record
Abstract
Deviations in the diversity and composition of the gut microbiota are called “gut dysbiosis”. They have been linked to various chronic diseases including cancers and resistance to immunotherapy. Stool shotgun based-metagenomics informs on the ecological composition of the gut microbiota and the prevalence of homeostatic bacteria such as Akkermansia muciniphila (Akk), while determination of the serum addressin MAdCAM-1 instructs on endothelial gut barrier dysfunction. Here we examined patient survival during chemo-immuno-therapy in 955 cancer patients across four independent cohorts of non-small cell lung (NSCLC), genitourinary (GU) and colorectal (CRC) cancers, according to hallmarks of gut dysbiosis. We show that Akk prevalence represents a stable and favorable phenotype in NSCLC and CRC cancer patients. Over-dominance of Akk above the healthy threshold was observed in dismal prognosis in NSCLC and GU and mirrored an immunosuppressive gut ecosystem and excessive intestinal epithelial exfoliation in NSCLC. In CRC, the combination of a lack of Akk and low sMAdCAM-1 levels identified a subset comprising 28% of patients with reduced survival, independent of the immunoscore. We conclude that gut dysbiosis hallmarks deserve integration within the diagnosis toolbox in oncological practice.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".