The Immune Landscape and Its Potential for Immunotherapy in Advanced Biliary Tract Cancer
Bibliographic record
Abstract
Biliary tract cancers (BTC) are a highly heterogeneous group of cancers at the genomic, epigenetic and molecular levels. The vast majority of patients initially present at an advanced (unresectable) disease stage due to a lack of symptoms and an aggressive tumour biology. Chemotherapy has been the mainstay of treatment in patients with advanced BTC but the survival outcomes and prognosis remain poor. The addition of immune checkpoint inhibitors (ICI) to chemotherapy have shown only a marginal benefit over chemotherapy alone due to the complex tumour immune microenvironment of these cancers. This review appraises our current understanding of the immune landscape of advanced BTC, including emerging transcriptome-based classifications, highlighting the mechanisms of immune evasion and resistance to ICI and their therapeutic implications. It describes the shifting treatment paradigm from traditional chemotherapy to immunotherapy combinations as well as the potential biomarkers for predicting response to ICI.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".