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Record W2997215171 · doi:10.1002/hep.31092

Identification of Four Immune Subtypes Characterized by Distinct Composition and Functions of Tumor Microenvironment in Intrahepatic Cholangiocarcinoma

2019· article· en· W2997215171 on OpenAlex
Sylvie Job, Delphine Rapoud, Alexandre Dos Santos, Patrick Gonzalez, Christophe Desterke, Gérard Pascal, Nabila Elarouci, Mira Ayadi, René Adam, Daniel Azoulay, Denis Castaing, Éric Vibert, Daniel Cherqui, Didier Samuel, António Sá Cunha, Agnès Marchio, Pascal Pineau, Catherine Guettier, Aurélien de Reyniès, J Faivre

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHepatology · 2019
Typearticle
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsnot available
FundersFP7 HealthInstitute of GeneticsLigue Contre le CancerEuropean Commission
KeywordsIntrahepatic CholangiocarcinomaIdentification (biology)Immune systemTumor microenvironmentBiologyPathologyCancer researchMedicineImmunologyEcology

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Intrahepatic cholangiocarcinoma (ICC) is a severe malignant tumor in which the standard therapies are mostly ineffective. The biological significance of the desmoplastic tumor microenvironment (TME) of ICC has been stressed but was insufficiently taken into account in the search for classifications of ICC adapted to clinical trial design. We investigated the heterogeneous tumor stroma composition and built a TME-based classification of ICC tumors that detects potentially targetable ICC subtypes. APPROACH AND RESULTS: We established the bulk gene expression profiles of 78 ICCs. Epithelial and stromal compartments of 23 ICCs were laser microdissected. We quantified 14 gene expression signatures of the TME and those of 3 functional indicators (liver activity, inflammation, immune resistance). The cell population abundances were quantified using the microenvironment cell population-counter package and compared with immunohistochemistry. We performed an unsupervised TME-based classification of 198 ICCs (training set) and 368 ICCs (validation set). We determined immune response and signaling features of the different immune subtypes by functional annotations. We showed that a set of 198 ICCs could be classified into 4 TME-based subtypes related to distinct immune escape mechanisms and patient outcomes. The validity of these immune subtypes was confirmed over an independent set of 368 ICCs and by immunohistochemical analysis of 64 ICC tissue samples. About 45% of ICCs displayed an immune desert phenotype. The other subtypes differed in nature (lymphoid, myeloid, mesenchymal) and abundance of tumor-infiltrating cells. The inflamed subtype (11%) presented a massive T lymphocyte infiltration, an activation of inflammatory and immune checkpoint pathways, and was associated with the longest patient survival. CONCLUSION: We showed the existence of an inflamed ICC subtype, which is potentially treatable with checkpoint blockade immunotherapy.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.221
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it