Genomic characterization of cholangiocarcinoma with autoimmune etiologies.
Bibliographic record
Abstract
531 Background: Chronic inflammation from autoimmune conditions is a well-recognized risk factor for cholangiocarcinoma in the Western world. Cholangiocarcinomas in the setting of autoimmune disease have earlier age-of-onset and worse prognosis. Currently, their biology is inadequately understood, and the risks and benefits of immunotherapy approaches in this population are unknown. We describe the clinical and genomic characteristics of a cohort of cholangiocarcinoma patients with autoimmune etiologies. Methods: In a prospective cohort of 43 patients with mismatch repair proficient cholangiocarcinoma, we performed whole-genome sequencing (WGS, n=43) and total RNA sequencing (RNA-seq, n=28). Among this cohort, 15 patients had cholangiocarcinoma with autoimmune etiologies, including primary sclerosing cholangitis (PSC, n=10), ulcerative colitis (UC, n=6), ankylosing spondylitis (AS, n=1), and Crohn’s disease (CD, n=3). Results: Patients with autoimmune conditions had a 6.46-fold higher Tumour Mutational Burden (TMB) ( P = 0.0010), characterized by higher load of indels ( P = 0.0006). TMB was greater than 10 mutations per megabase in 4 of 15 patients with autoimmune conditions and 0 of 28 patients in those without ( P = 0.0111). Autoimmune patients exhibited an enrichment in mutational signatures 5 ( P = 0.0154), 17 ( P = 0.0004), 28 ( P = 0.028) and 30 ( P = 0.0164). Despite a higher TMB, autoimmune tumours have similar patterns of driver mutations. Differential gene expression of bulk RNA-seq analysis revealed comparable transcriptional markers of immunogenicity, but autoimmune cancers are enriched in pathways involved with cell proliferation and cell-cycle checkpoints. One patient with PSC/UC was treated with gemcitabine, cisplatin, and durvalumab with a partial response, while another with Crohn’s disease had durvalumab added to gemcitabine and cisplatin at progression and experienced stable disease with a decreased CA19-9. Neither experienced immune-related adverse events. Conclusions: Cholangiocarcinoma with autoimmune etiologies have unique genomic features characterized by elevated TMB. Chemo-immunotherapy may be a novel therapeutic option in this subgroup of patients and warrants further study.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".