Transcriptomic Models for Immunotherapy Response Prediction Show Limited Cross-cohort Generalisability
Immune checkpoint inhibitors (ICIs) have transformed cancer therapy; yet substantial proportion of patients exhibit intrinsic or acquired resistance, making accurate pre-treatment response prediction a critical unmet need. Transcriptomics-based biomarkers derived from bulk and single-cell RNA sequencing (scRNA-seq) offer a promising avenue for capturing tumour-immune interactions, yet the cross-cohort generalisability of existing prediction models remains unclear.We systematically benchmark nine state-of-the-art transcriptomic ICI response predictors, five bulk RNA-seq-based models (COMPASS, IRNet, NetBio, IKCScore, and TNBC-ICI) and four scRNA-seq-based models (PRECISE, DeepGeneX, Tres a...
| Authors | Yuheng Liang, Lucy Chhuo, Ahmadreza Argha et al. |
|---|---|
| Primary category | q-bio.GN |
| Published | 7 April 2026 |
| Last updated at source | 18 September 2026 |
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