Article

Integrated germline and somatic features reveal divergent immune pathways driving ICB response

2024-01-15

Abstract excerpt

Immune Checkpoint Blockade (ICB) has revolutionized cancer treatment, however mechanisms determining patient response remain poorly understood. Here we used machine learning to predict ICB response from germline and somatic biomarkers and interpreted the learned model to uncover putative mechanisms driving superior outcomes. Patients with higher T follicular helper infiltrates were robust to defects in the class-I...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 38f896f9-cf28-5849-b58b-39a8ee708d68
DOI: 10.1101/2024.01.12.575430

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Integrated germline and somatic features reveal divergent immune pathways driving ICB responseDOI 10.1101/2024.01.12.575430Read

Integrated Germline and Somatic Features Reveal Divergent Immune Pathways Driving Response to Immune Checkpoint BlockadeSemantic proximity Read

HINS: HLA-mediated immunogenic neoantigen score for robust prediction of immune checkpoint blockade responseSemantic proximity Read

HLA class II immunogenic mutation burden predicts response to immune checkpoint blockade.Semantic proximity Read

Improved prediction of immune checkpoint blockade efficacy across multiple cancer types.Semantic proximity Read

Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockadeSemantic proximity Read

Robust prediction of patient outcomes with immune checkpoint blockade therapy for cancer using common clinical, pathologic, and genomic featuresSemantic proximity Read

Insights and Strategies of Melanoma Immunotherapy: Predictive Biomarkers of Response and Resistance and Strategies to Improve Response RatesSemantic proximity Read

Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition.Semantic proximity Read

Prediction of Immunotherapy Response in Melanoma through Combined Modeling of Neoantigen Burden and Immune-Related Resistance MechanismsSemantic proximity Read

Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade.Semantic proximity Read

A transcriptome-wide meta-analysis reveals lack of cancer-cell intrinsic determinants of response to immune checkpoint blockadeSemantic proximity Read

Robust prediction of patient outcomes with immune checkpoint blockade therapy for cancer using common clinical, pathologic, and genomic featuresSemantic proximity Read