ArticleEBioMedicine2019
Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer.
Article in EBioMedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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22 citing papers in PubMed, 41 citations in OpenAlex.
- OT-knn: A neighborhood-aware optimal transport framework for aligning spatial transcriptomics data.PLoS computational biology · 2026Article
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- Computational decoding of cell-cycle phase effects on cancer hallmarks across breast cancer subtypes.Breast cancer research : BCR · 2025Article
- Spatial TCR clonality and clonal expansion in the in situ microenvironment of non-small cell lung cancer.Journal for immunotherapy of cancer · 2025Article
- Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review).Oncology letters · 2024Review
- Mapping cancer biology in space: applications and perspectives on spatial omics for oncology.Molecular cancer · 2024Review
- Spatial transcriptomics in breast cancer: providing insight into tumor heterogeneity and promoting individualized therapy.Frontiers in immunology · 2024Review
- A unified pipeline for FISH spatial transcriptomics.Cell genomics · 2023Article
- Spatial tumour gene signature discriminates neoplastic from non-neoplastic compartments in colon cancer: unravelling predictive biomarkers for relapse.Journal of translational medicine · 2023Article
- Spatially resolved transcriptomics: advances and applications.Blood science (Baltimore, Md.) · 2023Review
- Novel insights from spatial transcriptome analysis in solid tumors.International journal of biological sciences · 2023Review
- The emerging landscape of spatial profiling technologies.Nature reviews. Genetics · 2022Review
- Article
- Spatial Resolution ofFrontiers in immunology · 2022Article
- Spatial transcriptomics technology in cancer research.Frontiers in oncology · 2022Review
- Spatial Transcriptomics for Tumor Heterogeneity Analysis.Frontiers in genetics · 2022Review
- Applicability of spatial transcriptional profiling to cancer research.Molecular cell · 2021Review
- Spatially resolved transcriptomics and its applications in cancer.Current opinion in genetics & development · 2021Review
- Expansion sequencing: Spatially precise in situ transcriptomics in intact biological systems.Science (New York, N.Y.) · 2021Article
- Non-genetic mechanisms of therapeutic resistance in cancer.Nature reviews. Cancer · 2020Review
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Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene expression analysis of breast cancer largely relies on homogenized tissue samples. Due to the high degree of cellular and molecular heterogeneity of tumor tissues, bulk tissue-based analytical approaches can only provide very limited system-level information about different signaling mechanisms and cellular interactions within the complex tissue context.
methodsWe describe an analytical approach using in situ sequencing (ISS), enabling highly multiplexed, spatially and morphologically resolved gene expression profiling. Ninety-one genes including prognostic and predictive marker profiles, as well as genes involved in specific cellular pathways were mapped within whole breast cancer tissue sections, covering luminal A/B-like, HER2-positive and triple negative tumors. Finally, all these features were combined and assembled into a molecular-morphological OncoMap for each tumor tissue.
findingsOur in situ approach spatially revealed intratumoral heterogeneity with regard to tumor subtype as well as to the OncotypeDX recurrence score and even uncovered areas of minor cellular subpopulations. Since ISS-resolved molecular profiles are linked to their histological context, a deeper analysis of the core and periphery of tumor foci enabled identification of specific gene expression patterns associated with these morphologically relevant regions.
interpretationISS generated OncoMaps represent useful tools to extend our general understanding of the biological processes behind tumor progression and can further support the identification of novel therapeutical targets as well as refine tumor diagnostics. FUND: Swedish Cancerfonden, UCAN, Vetenskapsrådet, Cancer Genomics Netherlands, Iris, Stig och Gerry Castenbäcks Stiftelse, BRECT, PCM Program, King Gustaf V Jubilee Fund, BRO, KI and Stockholm County Council, Alice Wallenberg Foundation.
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