HistoAtlas: A Pan-Cancer Morphology Atlas Linking Histomics to Molecular Programs and Clinical Outcomes
Abstract
HistoAtlas creates a comprehensive computational map linking histomic features from H&E slides to clinical outcomes and molecular profiles across multiple cancer types.
We present HistoAtlas, a pan-cancer computational atlas that extracts 38 interpretable histomic features from 6,745 diagnostic H&E slides across 21 TCGA cancer types and systematically links every feature to survival, gene expression, somatic mutations, and immune subtypes. All associations are covariate-adjusted, multiple-testing corrected, and classified into evidence-strength tiers. The atlas recovers known biology, from immune infiltration and prognosis to proliferation and kinase signaling, while uncovering compartment-specific immune signals and morphological subtypes with divergent outcomes. Every result is spatially traceable to tissue compartments and individual cells, statistically calibrated, and openly queryable. HistoAtlas enables systematic, large-scale biomarker discovery from routine H&E without specialized staining or sequencing. Data and an interactive web atlas are freely available at https://histoatlas.com .
Community
Hi!
HistoAtlas is a pan-cancer computational histopathology atlas that extracts 38 interpretable morphology features from 6,745 H&E diagnostic slides across 21 TCGA cancer types, then systematically links every feature to survival, gene expression, somatic mutations, pathways, and immune subtypes.
Key results
- 4.4 billion cells detected and classified into 9 morphological types using Owkin's HistoPLUS model
- 88,920 significant molecular correlations (FDR < 0.05) between morphology and transcriptomics/genomics
- Intratumoral lymphocyte density is protective pan-cancer (HR = 0.84, p < 0.0001, n = 5,957), while stromal lymphocyte density has a weaker effect. Where immune cells sit matters more than how many there are.
- 10 unsupervised morphological clusters recover canonical biology (Wnt in CRC, estrogen response in BRCA/PRAD, immune rejection in THYM) without any molecular input
- Two "immune-cold" clusters have opposite survival outcomes, suggesting binary hot/cold classification misses biologically distinct subtypes
What you can explore
The full interactive atlas is live at https://histoatlas.com: UMAP embeddings, Kaplan-Meier curves, molecular correlations, cluster characterization, and individual slide deep-dives. No login, no backend, everything loads instantly from pre-computed static JSON.
All associations are covariate-adjusted, BH-corrected, and classified into evidence tiers. We explicitly report what the atlas cannot detect (minimum detectable effect sizes) and which cancer types are out-of-distribution for the segmentation model.
Links
- Interactive atlas: https://histoatlas.com
- RRID: SCR_028056
Feedback welcome!
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