{
  "id": 12225540,
  "title": "Slide-level batch structure limits histology-guided supervision of transcriptomic foundation models",
  "url": "https://urgent.news/2026/10/05/slide-level-batch-structure-limits-histology-guided-supervision-of",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-05T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.30.755585v1?rss=1"
  },
  "original_language": "en",
  "account": "Spatial transcriptomics merges spatial gene expression data with tissue morphology within a single tissue section. Transcriptomic foundation models utilize these expression profiles to generate versatile representations, although they may maintain slide- and cohort-specific variations that mask biological signals. The researchers investigated if matched H&E histology could enhance these representations as a training-time supervisory signal that is discarded during inference. Across three transcriptomic foundation models, histology-guided supervision yielded no consistent aggregate improvement in cross-donor annotation transfer, even though it facilitated stronger transfer from histology alone. The researchers discovered that gene-expression embeddings from spot-based spatial transcriptomics are low-dimensional and heavily structured by slide identity, which limits the shared gene-morphology signal available for cross-modal transfer. Guidance proved beneficial for some morphologically distinctive classes but diminished held-out gene predictivity broadly across the transcriptome. These findings imply that cross-modal supervision can reorganize information already encoded in a fixed representation but cannot retrieve information the representation does not retain. This underscores the significance of identifying slide-specific structure before implementing such supervision. The code for this study is accessible at https://github.com/ratschlab/vision-guided-transcriptomics-fm-2026.",
  "summary": "Spatial transcriptomics pairs spatially resolved gene expression with tissue morphology in the same tissue section. Transcriptomic foundation models encode such expression profiles into general-purpose representations, but these representations can retain slide- and cohort-specific variation that obscures biological signal. Here, we test whether matched H&E histology can improve these…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}