{
  "abstract": "Spatial transcriptomics often relies on reference-based deconvolution to infer cell types in a tissue context; however, public single-cell datasets can miss patient-specific biology. Here we introduce SIMPlex, a method that generates matched spatial and single-nucleus gene-expression profiles from the same 5 um FFPE section. We demonstrate context-matched profiles across mouse brain, breast cancer and prostate cancer tissues, resolving fine-grained cell-states with distinct spatial signatures. By extracting both spatial and nuclear layers, SIMPlex maximises the information recovered from a single tissue section, an advantage for scarce archival and clinical specimens.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 30,
  "authors": [
    {
      "name": "M. T. Machado"
    },
    {
      "name": "M. He"
    },
    {
      "name": "L. Alonso Galicia"
    },
    {
      "name": "Z. Andrusivova"
    },
    {
      "name": "E. Perisynaki"
    },
    {
      "name": "M. W. Myers"
    },
    {
      "name": "S. Giatrellis"
    },
    {
      "name": "S. O'Toole"
    },
    {
      "name": "B. Kiedik"
    },
    {
      "name": "R. Mauron"
    },
    {
      "name": "S. van der Leij"
    },
    {
      "name": "K. Harvey"
    },
    {
      "name": "J. Reeves"
    },
    {
      "name": "J. Escudero Morlanes"
    },
    {
      "name": "T. Hu"
    },
    {
      "name": "M. Long"
    },
    {
      "name": "M. Nilsson"
    },
    {
      "name": "T. Li"
    },
    {
      "name": "X. Chen"
    },
    {
      "name": "J. Hartman"
    },
    {
      "name": "M. Mihalffy"
    },
    {
      "name": "T. Wang"
    },
    {
      "name": "M. Vicari"
    },
    {
      "name": "L. Savolainen"
    },
    {
      "name": "A. Erickson"
    },
    {
      "name": "S. Figiel"
    },
    {
      "name": "A. Lamb"
    },
    {
      "name": "A. Swarbrick"
    },
    {
      "affs": [
        0
      ],
      "name": "J. Lundeberg"
    },
    {
      "name": "R. Mirzazadeh"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/55wwvg5xswh69.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.07.749790",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.07.749790v1.full",
  "id": "55wwvg5xswh69",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.07.749790v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "molecular biology"
    ],
    [
      "openalex",
      "1312|Single-cell and spatial transcriptomics"
    ]
  ],
  "openalex": "W7170086257",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.07.749790v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/55wwvg5xswh69.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:09Z",
      "native_id": "10.64898/2026.09.07.749790",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.07.749790v1"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "biorxiv:molecular biology",
      "subfield": "molecular-biology"
    }
  ],
  "title": "Highly resolved tumor architecture via matched spatial and nucleus transcriptomics from a single tissue section",
  "title_text": "Highly resolved tumor architecture via matched spatial and nucleus transcriptomics from a single tissue section",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:09Z",
  "url": "https://research.draconitic.com/paper/55wwvg5xswh69",
  "venue": "bioRxiv",
  "versions": []
}