{
  "abstract": "Introduction: Cancer genotypes influence transcriptional programs, spatial organization, histopathology, and treatment-response states, yet these molecular and tissue-level features are often analyzed separately in public-data studies. VISTA was developed as a variant-informed, multimodal framework for modeling genotype-linked tissue states and prioritizing validation-ready biological hypotheses.\n\nMethods: VISTA integrates somatic variants, protein-region and AlphaMissense-informed priors, RNA-state scoring, whole-slide image embeddings, immunotherapy cohorts, spatial and single-cell references, cell-line dependency maps, and pharmacogenomic screens. We evaluated the framework in KEAP1/NFE2L2-altered lung cancer and melanoma, using the NRF2 stress axis as a biologically defined test case. Analyses incorporated project-adjusted modeling, bootstrap confidence intervals, permutation testing, leave-project sensitivity analyses, independent tumor-level validation cohorts, fixed-effect external meta-analysis, model-system analyses using DepMap/CCLE, tissue-context analyses, immunotherapy cohorts, and exploratory whole-slide image analyses.\n\nResults: In TCGA LUAD, LUSC, and SKCM pilot cohorts, KEAP1 and NFE2L2 alterations were consistently associated with NRF2 stress activation across project-adjusted models and sensitivity analyses. Independent analyses of CPTAC LUAD, CPTAC LSCC, and non-TCGA LUAD cohorts reproduced higher NRF2-state scores in KEAP1/NFE2L2-altered tumors. Fixed-effect external meta-analysis supported associations with both KEAP1 mutation and combined KEAP1-or-NFE2L2 alteration status. DepMap/CCLE analyses provided complementary model-system evidence: KEAP1/NFE2L2-mutant models had higher NRF2 scores, while NRF2-high or KEAP1/NFE2L2-mutant contexts showed stronger NFE2L2 dependency. Tissue-context analyses positioned NRF2 stress near hypoxic, stromal, myeloid, and immune programs. Immunotherapy cohorts supported the relevance of NRF2-associated states to treatment-response biology, while also indicating limited utility for static pan-cancer prediction. Exploratory whole-slide image analyses using pathology foundation-model embeddings identified morphology associations with myeloid, hypoxic, and CAF/TGF-beta barrier programs.\n\nDiscussion: VISTA provides an evidence-layered approach to variant-informed tissue-state modeling. By integrating genomic, transcriptomic, imaging, spatial, cellular, dependency, and pharmacogenomic evidence, it can help prioritize genotype-linked cancer states and validation-ready hypotheses. VISTA is not intended to function as a stand-alone clinical predictor; its claims are bounded by the evidence available in each data layer and by the biological and clinical context of the analyzed cohorts.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Cardiology, The Affiliated Hospital of Southwest Medical University",
    "Key Laboratory of Medical Electrophysiology, Ministry of Education, Institute of Cardiovascular Research",
    "The Key Laboratory of Optimal Utilization of Natural Medicine Resources (The Union Key Laboratory of Guiyang City-Guizhou Medical University), School of Pharmaceutical Sciences, Guizhou Medical University",
    "School of Medical Information and Engineering, Southwest Medical University",
    "Basic Medicine Research Innovation Center for Cardiometabolic Diseases, Ministry of Education, Southwest Medical University",
    "Nucleic Acid Medicine of Luzhou Key Laboratory"
  ],
  "article_type": "research support, non u.s. gov't",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Mowei Kong"
    },
    {
      "affs": [
        1
      ],
      "name": "Qiuing Li"
    },
    {
      "affs": [
        1
      ],
      "name": "Xingwei Zhao"
    },
    {
      "affs": [
        2
      ],
      "name": "Yu Wang"
    },
    {
      "affs": [
        3
      ],
      "name": "Yamei Luo"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Yang Yu"
    },
    {
      "affs": [
        0,
        1,
        4,
        5
      ],
      "name": "Chunxiang Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cnz7nakmtpwxa.bib",
  "cited_by": 0,
  "doi": "10.3389/fimmu.2026.1957511",
  "fulltext_url": "https://europepmc.org/articles/PMC13680486",
  "id": "cnz7nakmtpwxa",
  "issns": [
    "1664-3224"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1957511/full",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Genomics, phytochemicals, and oxidative stress"
    ]
  ],
  "openalex": "W7220718737",
  "pdf_url": "https://europepmc.org/articles/PMC13680486?pdf=render",
  "pmcid": "PMC13680486",
  "pmid": "42903351",
  "published": "2026-10-06",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/cnz7nakmtpwxa.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:15Z",
      "native_id": "10.3389/fimmu.2026.1957511",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1957511/full"
    },
    {
      "first_seen": "2026-10-30T12:19:57Z",
      "native_id": "MED:42903351",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42903351"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Genomics, phytochemicals, and oxidative stress",
      "subfield": "molecular-biology"
    }
  ],
  "title": "Variant-informed multimodal tissue-state modeling reveals an NRF2 stress niche and dependency axis in KEAP1/NFE2L2-altered cancer",
  "title_text": "Variant-informed multimodal tissue-state modeling reveals an NRF2 stress niche and dependency axis in KEAP1/NFE2L2-altered cancer",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:57Z",
  "url": "https://research.draconitic.com/paper/cnz7nakmtpwxa",
  "venue": "Frontiers in Immunology",
  "versions": []
}