{
  "abstract": "The tumor microenvironment in colorectal cancer (CRC) is a heterogeneous ecosystem in which host cells and microbial communities interact dynamically, influencing disease progression. However, the clinical utility is limited by the lack of a scalable spatial host-microbiome technique and by insufficient integration of artificial intelligence for the interpretation of high-dimensional multi-omics data. To overcome the barriers, we present AlphaFISH, a platform technology integrating both technical and computational innovations for multi-omics spatial analysis of clinical biopsies at subcellular resolution. The system uses a sequencing-free, high-throughput, spatial profiling technique to construct, to date, the largest clinical spatial transcriptomics and spatial microbiome datasets acquired from 149 colorectal biopsies from 68 human subjects, supported by a comprehensive scRNA-seq atlas covering 4.27 million cells across 650 patients for robust cell annotation. Deep learning of the cohort-scale dual-omics data, consisting of more than 10 million subcellular sampling vectors, enables the development of a transformer model with joint embeddings of gene expression, spatial architecture, and the microbial microenvironment in colon tissues, achieving nearly 90% accuracy in predicting CRC-associated pathological features using unseen spatial omics inputs. The AI interrogation further predicts tumour recurrence at 81% accuracy in 28 patients followed within 1 year post tumor resection period. AlphaFISH reveals that spatial interactions between Fusobacterium and cellular niche consisting of tumor and T cells serve as key markers of CRC malignancy, progression, and recurrence, indicating the critical role of spatial bacterial-immune crosstalks.",
  "abstract_shown": true,
  "affiliations": [
    "City University of Hong Kong; Hong Kong Centre for Cerebro-Cardiovascular Health Engineering; COSDAF, City University of Hong Kong; Shenzhen Research Institute,"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "name": "F. Guo"
    },
    {
      "name": "H. Sun"
    },
    {
      "name": "C. Hu"
    },
    {
      "name": "M. Hao"
    },
    {
      "name": "Y. Wan"
    },
    {
      "name": "C. Xiong"
    },
    {
      "name": "F. Gao"
    },
    {
      "name": "L.-Y. Mak"
    },
    {
      "name": "X. Deng"
    },
    {
      "name": "A. Goel"
    },
    {
      "name": "J. Ke"
    },
    {
      "name": "J. Ma"
    },
    {
      "affs": [
        0
      ],
      "name": "P. Shi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/a4sptnhs3qfnw.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.29.26363734",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.09.29.26363734v1.full",
  "id": "a4sptnhs3qfnw",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.09.29.26363734v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "health informatics"
    ],
    [
      "openalex",
      "1312|Single-cell and spatial transcriptomics"
    ]
  ],
  "openalex": "W7220385907",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.09.29.26363734v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-29",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/a4sptnhs3qfnw.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:07Z",
      "native_id": "10.64898/2026.09.29.26363734",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.09.29.26363734v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:health informatics",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Cohort-scale Spatial Host-Microbiome Predicts Post-Resection Recurrence in Colorectal Cancer",
  "title_text": "Cohort-scale Spatial Host-Microbiome Predicts Post-Resection Recurrence in Colorectal Cancer",
  "type": "preprint",
  "updated_at": "2026-10-30T12:20:07Z",
  "url": "https://research.draconitic.com/paper/a4sptnhs3qfnw",
  "venue": "medRxiv",
  "versions": []
}