{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T15:11:57Z","timestamp":1788880317614,"version":"build-2803163510"},"reference-count":50,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100004359","name":"Vetenskapsr\u00e5det","doi-asserted-by":"publisher","award":["2023\u201004842"],"award-info":[{"award-number":["2023\u201004842"]}],"id":[{"id":"10.13039\/501100004359","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Intl Journal of Cancer"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Spot\u2010based spatial transcriptomics (ST) allows for unbiased gene expression analysis within tissue architecture, overcoming the limitations of single\u2010cell RNA sequencing (scRNA\u2010seq) by preserving spatial context. However, the high spatial resolution in ST leads to cellular heterogeneity within spots, requiring computational deconvolution to infer cellular compositions. While scRNA\u2010seq serves as a key reference for deconvolution, the impact of reference composition on its accuracy is still unclear. In this study, we systematically evaluate the impact of reference selection for cellular deconvolution and provide helpful guidelines for researchers. Pseudospots mimicking 55\u2009\u03bcm Visium spots were generated from spatial transcriptomics data to evaluate global and cell type\u2010specific deconvolution in primary (Xenium) and metastatic (MERFISH) breast cancer samples. Focusing on state\u2010of\u2010the\u2010art deconvolution tools Cell2location and RCTD, we assess the influence of varying reference sizes, cell type distributions, and reference\u2010ST pairings, as well as the usage of large breast cancer and cross\u2010cancer atlases. Our findings demonstrate that even small references can yield accurate deconvolution, with RCTD and Cell2location exhibiting similar results. Spatial domains of prominent cell types like cancer and stromal cells were detected, although their contributions were systematically under\u2010 or over\u2010estimated. Additionally, Reference\u2010ST sample matching enhances accuracy compared to the usage of cross\u2010patient references, while large diverse breast cancer atlases also provided reliable results. This study concluded that reference selection had modest effects on RCTD and Cell2location, but matching samples and large atlases stabilize outcomes. Nonetheless, performance varies between cell types and annotation levels, and deconvolution results should always be interpreted with caution.<\/jats:p>","DOI":"10.1002\/ijc.70733","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T14:46:36Z","timestamp":1788878796000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Impact of Single\u2010Cell\n                    <scp>RNA<\/scp>\n                    Reference Selection for the Deconvolution of Breast Cancer Spatial Transcriptomics Datasets"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-1401-1189","authenticated-orcid":false,"given":"Stefan","family":"Altendorfer","sequence":"first","affiliation":[{"name":"Department of Medicine Huddinge Karolinska Institutet  Stockholm Sweden"},{"name":"Cancer Epigenomics, German Cancer Research Center (DKFZ)  Heidelberg Baden\u2010W\u00fcrttemberg Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7401-6174","authenticated-orcid":false,"given":"Scott J.","family":"Walker","sequence":"additional","affiliation":[{"name":"Department of Computational Biology and Medical Sciences University of Tokyo  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3295-8729","authenticated-orcid":false,"given":"Carsten O.","family":"Daub","sequence":"additional","affiliation":[{"name":"Department of Medicine Huddinge Karolinska Institutet  Stockholm Sweden"},{"name":"Science for Life Laboratory  Stockholm Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,8]]},"reference":[{"key":"e_1_2_12_2_1","first-page":"229","article-title":"Global Cancer Statistics 2022: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries","volume":"74","author":"Bray F.","year":"2024","journal-title":"CA: A Cancer Journal for Clinicians"},{"key":"e_1_2_12_3_1","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1002\/cac2.12358","article-title":"Breast Cancer: An Up\u2010To\u2010Date Review and Future Perspectives","volume":"42","author":"Hong R.","year":"2022","journal-title":"Cancer Communications"},{"key":"e_1_2_12_4_1","doi-asserted-by":"crossref","DOI":"10.3390\/ijms23126806","article-title":"Breast Cancer Metastasis: Mechanisms and Therapeutic Implications","volume":"23","author":"Park M.","year":"2022","journal-title":"International Journal of Molecular Sciences"},{"key":"e_1_2_12_5_1","volume-title":"Subtypes of Breast Cancer Breast Cancer","author":"Orrantia\u2010Borunda E.","year":"2022"},{"key":"e_1_2_12_6_1","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.gendis.2018.05.001","article-title":"Breast Cancer Development and Progression: Risk Factors, Cancer Stem Cells, Signaling Pathways, Genomics, and Molecular Pathogenesis","volume":"5","author":"Feng Y.","year":"2018","journal-title":"Genes & Diseases"},{"key":"e_1_2_12_7_1","doi-asserted-by":"crossref","DOI":"10.1002\/ctm2.694","article-title":"Single\u2010Cell RNA Sequencing Technologies and Applications: A Brief Overview","volume":"12","author":"Jovic D.","year":"2022","journal-title":"Clinical and Translational Medicine"},{"key":"e_1_2_12_8_1","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1038\/s41389-021-00355-6","article-title":"Single\u2010Cell RNA Sequencing Reveals Cell Heterogeneity and Transcriptome Profile of Breast Cancer Lymph Node Metastasis","volume":"10","author":"Xu K.","year":"2021","journal-title":"Oncogene"},{"key":"e_1_2_12_9_1","doi-asserted-by":"crossref","DOI":"10.3389\/fimmu.2022.868813","article-title":"Mapping Breast Cancer Microenvironment Through Single\u2010Cell Omics","volume":"13","author":"Tan Z.","year":"2022","journal-title":"Frontiers in Immunology"},{"key":"e_1_2_12_10_1","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1126\/science.aaf2403","article-title":"Visualization and Analysis of Gene Expression in Tissue Sections by Spatial Transcriptomics","volume":"353","author":"St\u00e5hl P. 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