Circulating Tumor Cells Atlas – an open-access repository capturing tumor cells heterogeneity and their ecosystem

Circulating Tumor Cells Atlas – an open-access repository capturing tumor cells heterogeneity and their ecosystem | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Circulating Tumor Cells Atlas – an open-access repository capturing tumor cells heterogeneity and their ecosystem Anna Muchlińska, Julia Richert, Robert Wenta, Aleksandra Parteka, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9052403/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Liquid biopsy is increasingly used in precision medicine, highlighting the need for standardized, image-based reference resources for reproducible identification and characterization of circulating tumor cells (CTCs). We present CTC Atlas (www.CTCAtlas.org), an open-access, community-oriented platform providing a curated compendium of CTCs with diverse morphological and molecular features, alongside other circulating tumor-associated cell types, including cancer-associated fibroblasts, macrophages, endothelial cells, and imaging artifacts. The platform integrates high-quality microscopy images with matched omics data, enabling systematic annotation, reproducible analysis, and comparative studies of tumor-related cells across laboratories. CTC Atlas addresses the lack of standardized reference frameworks in liquid biopsy, supporting reproducible workflows and facilitating cross-study comparisons. By providing structured, accessible datasets, the platform advances the understanding of tumor cell heterogeneity and dissemination dynamics in circulation and lays the groundwork for improved clinical applications of CTC-based liquid biopsy. liquid biopsy circulating tumor cells imaging flow cytometry cell atlas tumor progression phenotype cell morphology standardization tumor microenvironment Figures Figure 1 Figure 2 Figure 3 Figure 4 Main Text Liquid biopsy Liquid biopsy ( Fig. 1 ) has been recognized as groundbreaking tool in the early detection and monitoring of various solid tumors, challenging the current limitations of large-scale, molecular-driven cancer treatment personalization. Unlike conventional tissue biopsies, which require invasive, usually single-use procedures, liquid biopsy allows for the minimally or even non-invasive, sequential collection of biological fluids, mainly peripheral blood (1). This approach allows for detection of tumour-related biomarkers such as circulating tumour cells (CTCs), circulating tumour / free DNA (ct/cfDNA), extracellular vesicles (EVs), peptides, metabolites, and RNA ( Fig. 1) in a potentially reproducible manner and at ultrasensitive levels, enabling identification of even trace amounts of clinically relevant analytes (2,3). Fig. 1 Basics of liquid biopsy Liquid biopsy in one shot: various body fluids and different examined analytes used in liquid biopsy assays. Created with BioRender.com. Over the past two decades, advances in technologies for studying tumor dissemination have highlighted the value of liquid biopsy as a tool for capturing tumor heterogeneity and enabling precision oncology (4–6). By providing mechanistic insights into tumor progression, liquid biopsy supports early and ultrasensitive diagnostics, real-time monitoring of disease dynamics and treatment response, and assessment of minimal residual disease (MRD). Despite its clinical potential, the broad implementation of liquid biopsy assays remains limited. A major barrier is the lack of standardised, universally applicable protocols and guidelines transferable for all liquid biopsy technologies. This might negatively impact reproducibility and accuracy of liquid biopsy tests, thereby postponing universal implementation of those tests into daily clinical practice (7). In this article, we address this unmet need by introducing an open-access, atlas-based resource, the CTC Atlas (www.CTCatlas.org), as a repository of CTC-related data designed to support standardized, image-based identification and molecular characterization of circulating tumor and tumor-associated cells, which should facilitate more reliable integration of liquid biopsy technologies into research and clinical workflows, as well as better understanding of metastatic process. Liquid biopsy and need of its standardization Despite major technological advances, liquid biopsy assays remain highly sensitive to pre-analytical variability, including differences in sample collection, transportation, storage, and processing (8). Such factors might critically affect the stability and integrity of analytes such as circulating tumor cells (CTCs), ct/cfDNA, and extracellular vesicles, thereby influencing assay sensitivity, reproducibility, and inter-study comparability. In addition, methodological heterogeneity between laboratories, spanning analyte isolation, detection platforms, and bioinformatic pipelines, can introduce discrepancies, artifacts and even biases in biomarker quantification and interpretation, ultimately impacting clinical decision-making (9). To address these challenges, meticulous reporting of experimental conditions following BRISQ guidelines (10), implementation of standardized protocols, and rigorous quality control across all analytical steps are essential for reliable clinical translation of liquid biopsy technologies. Standardization challenges are particularly pronounced in CTC detection due to their extreme rarity, phenotypic heterogeneity and plasticity, and the lack of strictly tumor-specific markers covering all types of CTC populations. The FDA-approved CellSearch® system, based on EpCAM and keratin expression, remains the most widely used and validated platform (11,12). However, epithelial–mesenchymal transition (EMT) leads to down-regulation of epithelial markers, rendering mesenchymal CTC subpopulations poorly detectable and potentially excluding cells critical for metastasis (13–15). The lack of CTC-specific mesenchymal markers, morphological diversity of CTC phenotypes (16), and difficulties in defining universal internal and external controls further complicate normalization and threshold definition across studies and centres. Beyond biological variability, molecular imaging technologies commonly used for CTC detection face substantial technical standardization issues. Differences in imaging platforms, acquisition parameters, reagents and even their batches, and image analysis pipelines result in variability in resolution, sensitivity, and signal interpretation. Inconsistent reporting of technical parameters, limited availability of reference standards, subjective image scoring, and lack of harmonized quantification metrics hinder reproducibility, regulatory compliance, and cross-institutional validation (17,18). Addressing these limitations requires standardized imaging guidelines, automated analysis pipelines, reference materials, and publicly available benchmark datasets (19,20). Several international initiatives, including the European Liquid Biopsies Academy, CANCER-ID, BloodPAC, and the International Liquid Biopsy Standardization Alliance, have initiated efforts toward harmonization (20–23). However, universally accepted guidelines and open-access reference standards are still needed to enable robust, global implementation of liquid biopsy in precision oncology. Atlases as tool to standardize and boost precision oncology Meanwhile, the development of comprehensive atlases and online platforms has transformed molecular biology and medicine by organizing vast amounts of rapidly growing biomedical data, in particular, those from ‘omic’ technologies. Already existing and continuously expanding resources, ranging from large-scale omics atlases such as The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), and Human Cell Atlas (HCA), through integrative biological knowledge bases including STRING and MalaCards, to clinically oriented reference platforms such as Pathology Outlines, play a crucial role in systematizing and sharing large datasets, while also serving as reference points for biomarkers, technologies and diverse biomedical research and clinical applications. (24–28). These tools provide structured, standardized, and integrated data that catalyze discoveries in molecular biology and translational medicine. This is exemplified by the decade-long existence of the TCGA platform and its profound impact on precision oncology. With multiomic data derived from over 20,000 tumors, TCGA has been cited as a reference in almost 40,161 scientific publications, including 12,198 publications putatively translating into oncological treatments (PubMed search: "TCGA" and "TCGA + therapy," respectively, as of 4.03.2026). Expanding the role of atlases in precision medicine, many modern platforms are leveraging artificial intelligence (AI) for data analysis, biomarker discovery, and pattern recognition. Referring specifically to molecular imaging field, several repositories and platforms already provide access to images derived from immunohistochemical and immunofluorescence stainings, visualized by different microscopy modalities (listing e.g., CytoData, Cell Image Library, BioImageArchive, Image Data Resource). Among these, the Human Protein Atlas (HPA) represents a well-established example of an integrative initially imaging-based resource, combining standardized staining protocols with high-resolution microscopy to enable spatially resolved visualization of protein expression across normal and cancer tissues. Such atlas-driven approaches demonstrate how standardized imaging data can support reproducibility, cross-validation, and biomarker discovery. In contrast, within the field of liquid biopsy, comprehensive atlas-based resources integrating standardized imaging data are still largely lacking. Open-access datasets remain limited, being primarily represented by ct/cfDNA datasets dispersed across various multi(gen)omic platforms, such as COSMIC (29). Unlike primary tumor research, where standardized repositories and frameworks guide molecular profiling, liquid biopsy analysis suffers from limited data sharing amplified by a variety in methodologies and biomarker definitions. While some consortia and initiatives, such as CANCER-ID, EV-TRACK or BloodPac already aim to standardize the analysis of liquid biopsy assays and centralize datasets of specific analytes (30,31) publicly available databases dedicated to systematic, image-based characterization of CTCs are, to the best of our knowledge, still absent. Therefore, our platform, the CTC Atlas (www.CTCatlas.org), is designed to fill this gap by providing an open-access repository dedicated to CTC images and associated metadata ( Fig. 2 ). This initiative aims to represent a pivotal step towards integrating liquid biopsy data into precision medicine, ultimately improving the standardization of CTC identification, despite their high heterogeneity and plasticity, and potentially enabling AI-powered automated diagnostic solutions in the future. Fig. 2 Concept and purpose of the CTC Atlas. The CTC Atlas is an open-access, image-based reference platform designed to standardize the identification and characterization of circulating tumor cells by integrating curated imaging data with clinical and molecular context, thereby supporting reproducible analyses, AI-ready benchmarking, and clinical translation of liquid biopsy approaches. CTC Atlas and its future directions Here, we introduce an open-access platform aiming to present high-quality images of cancer-related circulating cells, with main focus on CTCs of different phenotypes and features, visualized using various technologies and panels of markers, together with large collections of molecular data related to tumor dissemination. As a starting point we supplied this platform with high-resolution images of cells acquired using imaging flow cytometry (imFC), a technology that we implemented and optimized for CTC analysis (32). The initial image collection originates from our firstly validated protocols, applied to large patients cohorts and variety of tumor types, using well-known and commonly used markers for CTC detection, and published as original peer-reviewed studies in scientific journals (15,16,33,34) with raw files reposited in open-access, general-purpose research data repositories such as Zenodo (Supplementary Data 1). Nevertheless, the platform is designed as a growing resource and will be progressively extended with additional images from different laboratories, using various isolation and detection methods, as well as diverse biological and clinical set-ups, all described in details in associated methodological descriptions and ID cards. In parallel, the image repository is initially complemented with multigene expression data on matched primary tumors and will be further extended by additional molecular data such as single-cell transcriptomics, molecular profiling of further matched primary tumors or plasma cytokines measurements, enabling integrative, multi-modal characterization of tumor dissemination process. In brief, over the relatively short period since we implemented imFC technology in liquid biopsy (32), our team has acquired over 40 mln high-resolution images of single and clustered cells derived from peripheral blood mononuclear cells (PBMC) fractions of almost 1000 oncological patients (i.e., breast, prostate, lung, ovarian, renal, colorectal, pancreatic cancer patients) and healthy individuals. So far, all those individuals were recruited at the University Clinical Center (Gdansk, Poland) based on the written informed consents and protocols approved by the local Ethics Committee. The blood was collected to EDTA-tubes, processed using density gradient centrifugation (34), stored in 4% paraformaldehyde, and, to date, examined using two different immunofluorescent protocols analyzed by high throughput and high resolution technology, imFC (i.e., pan-keratin / vimentin / DAPI / CD45 / CD31 / alpha Smooth Muscle Actin (α-SMA) / CD29 protocol (34) and pan-keratin / androgen receptor / epidermal growth factor receptor (EGFR) / DAPI / CD45 / CD31) (not published yet). Applying this workflow, we have generated >10TB of raw imaging data and a library of over 600 putative CTCs, characterized by different features, some of which were defined in CTCs for the first time (e.g., protrusions, micronuclei, mitotic figures) (15,16). Based on this library and archived images of other cells in PBMC fractions, we created the CTC Atlas to present curated images of CTCs, including, in the future, also ambiguous and questionable CTCs, as well as a plethora of putative progression-related cellular objects detected in the blood of oncological patients, such as circulating fibroblasts, macrophages, endothelila cells and even artefacts. The strength of this platform lies in the detailed annotation of both clinical and technical parameters associated with each identified object, according to EQUATOR recommendations. In parallel, we incorporated the first matched omics dataset, generated by NanoString multigene expression profiling of matched primary tumors (35) integrated with CTC status in prostate cancer patients. This so-called “molecular calculator” will be progressively expanded to include additional molecular profiles of CTC-positive and CTC-negative patients, covering different molecules (mRNA, cytokines, metabolites, etc.) assessed in corresponding primary tumors, blood cells or plasma, and, in the future, also in metastatic tumors. With the first version of CTC Atlas released in February 2025, we presented initially >150 cellular objects including CTCs of different phenotypes and characteristics (reflecting high heterogeneity and plasticity of those cells, and also their clusterization and interaction status), circulating fibroblasts and leukocytes, which will be soon complemented by addition of images of circulating endothelial cells, neutrophil extracellular traps and selected artefacts ( Fig. 3A ). For CTCs identification we followed commonly applied criteria implemented from CellSearch® and other imaging technologies, i.e.: intact morphology, presence of DAPI+ nucleus of not obvious leukocyte shape (such as neutrophil segmented nucleus), cell size of at least 5 µm and the absence of exclusion markers such as CD45 and/or CD31 ( Fig. 3B ). However, analyzing morphological details of CTCs (16) and attempting first deep learning-aided models for automated detection of those cells (data not shown), which led to discovery of some features neglected in CTC identification by scientists’ eye (e.g., H entropy, a measure of intracellular complexity derived from the heterogeneity of fluorescence intensity), we conclude that those criteria have to be revised and improved in order to nail genuine CTCs. Thus, one of the goals of CTC Atlas is to characterize and present a potentially broad panel of so far not investigated measurable features of putative CTCs, including their size, shape, phenotype, and other morphological details such as protrusions, micronuclei, nucleus-to-cytoplasm ratio, etc ( Fig. 3C ). Fig. 3 CTC identification in brief Types of tumor-progression related cellular objects observed in blood of oncological patients ( A ), criteria of CTCs identification ( B ) and features of CTCs evaluable on 2D images ( C ). Created with BioRender.com. In the future, it might also encompass various radiomic parameters, such as intensity, texture, and the spatial distribution of these analyzed features, acquired in both bright-field (emphasizing morphology) and fluorescence (highlighting marker presence) channels ( Fig. 3C ). It should initiate detailed reporting such characteristics comprehensively among all studies, which, in consequence, should also boost investigation on the biology of disseminating tumor cells. In the future, continuous research and debate on CTC identification should lead to an upgrade of CTC identification criteria and ease the implementation of CTC tests into diagnostics, thus improving precision oncology. In the current version of CTC Atlas, we use metrics describing general, clinical, and technical information, as well as sample preparation and cell characteristics, including presence of specific markers, micronucleus or protrusions, their size and shape, as well as clusterization status and interactions with other cells ( Fig. 3C , Fig. 4 ). Fig. 4 CTC Atlas’ objects identification card Example of CTC description applied in the 1 st version of CTC Atlas (launched February 2025). Currently CTC Atlas comprises CTCs derived from two types of blood: peripheral blood and tumor draining vein blood. In the future, CTC Atlas will expand to include a larger number of cellular objects of different kinds and origins, encompassing tumor progression-related cells from further tumor entities, collected at different clinical timepoints and under different regimens, as well as from additional body fluids such as cerebrospinal or urine. First, we aim to extend the molecular calculator and add cells stained for further markers using different multimarker protocols, present a broader spectrum of CTC characteristics, as well as extend the range of studied cancer types, to elevate the publicly available library of rare cell types circulating in blood and associated with tumor progression. Our repository also aims to be extended to include images of CTCs detected using different isolation methods and further imaging technologies, leveraging both our resources and collaborations with other scientific centers, thereby supporting the development of a reference library and enabling AI-assisted detection of clinically relevant cells. Ultimately, we intend to optimize and implement fluorescent in situ hybridization (FISH) protocols to allow the identification of CTCs based on genetic aberrations, which would provide a more definitive classification of malignant cells than protein-based phenotyping. In parallel, we will perform comparisons of results across all protocols and cancer types, continuously updating the statistical analysis of all examined parameters as new data are generated. In the future, we will integrate images of identified CTCs with multiomic datasets from single cells and matched primary tumors, together with peripheral blood cytokine profiles representing the systemic immune context of the CTC-associated ecosystem, to provide a comprehensive multidimensional picture of disseminating tumor cells. Finally, the webpage is and will be further updated with both scientific and popular-science content summarizing the basics and recent advances in liquid biopsy to improve public understanding and provide reference materials for both professional and lay audiences. Summary In the era of open-access large data platforms, data sharing in science gains a new dimension, leveraging technologies, experimental and diagnostic workflows, and fastening the implementation of molecular biology achievements into clinical practice. It enables standardization, and opens broad discussion about the guidelines that are crucial for each technological approach, including those applied in liquid biopsy. Here, we introduce, to the best of our knowledge, the first open-access repository of images of CTCs representing various phenotypes and accompanied by detailed annotations reflecting their heterogeneity. CTC Atlas aims to provide the research community with a tool enabling future advances in CTC identification, and improving the understanding of the metastatic process, thus paving the way for implementation of CTC-based assays into precision oncology. CTC Atlas will adhere to internationally recognized standards of scientific excellence and welcome verified images of cancer-related cells from different technologies and institutions, with the long-term goal of advancing CTC identification and analysis. Abbreviations CTCs circulating tumor cells cfDNA circulating free DNA ctDNA circulating tumor DNA EMT epithelial–mesenchymal transition imFC imaging flow cytometry MRD minimal residual disease EVs extracellular vesicles TCGA The Cancer Genome Atlas HPA Human Protein Atlas HCA Human Cell Atlas STRING Search Tool for the Retrieval of Interacting Genes EpCAM epithelial cell adhesion molecule BRISQ Biospecimen Reporting for Improved Study Quality Declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki and approved by the Independent Bioethics Committee for Scientific Research at the Medical University of Gdansk (study protocols: #NKBBN/286/2018, #NKBBN/748/2019–2020, and #NKBBN/ 434/2017). The patients provided written informed consent to participate in the study. Consent for publication Not applicable Competing interests The authors declare that they have no competing interests. Funding This research was funded by a grant from the Ministry of Science and Higher Education, Poland (#NdS-II/SP/0398/2023/01 for NBK). Author Contribution Study conceptualization, design and supervision: NBK; experiments and analysis: AM, JR, RW, AP, MP, BPU; data curation: AM, JR, RW, AP, MP; resources: AZ, NBK; funding and administrative management: NBK; draft writing: AM, RW, AP, NBK. All authors read and approved the final manuscript. Acknowledgement We thank all patients and healthy donors who agreed to donate blood. We thank all clinicians cooperating in different projects for their involvement in the recruitment of the patients and collection of clinical data. Figures preparation was supported by BioRender under the license for the Medical University of Gdańsk. 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Improved Characterization of Circulating Tumor Cells and Cancer-Associated Fibroblasts in One-Tube Assay in Breast Cancer Patients Using Imaging Flow Cytometry. Cancers (Basel). 2023;15(16):4169. doi: 10.3390/CANCERS15164169/S1 Nastały P, Smentoch J, Popęda M, Martini E, Maiuri P, Żaczek AJ, et al. Low Tumor-to-Stroma Ratio Reflects Protective Role of Stroma against Prostate Cancer Progression. Journal of Personalized Medicine 2021, Vol 11,. 2021;11(11). doi: 10.3390/JPM11111088 Additional Declarations No competing interests reported. Supplementary Files SupplementaryData1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9052403","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":604460056,"identity":"1f8c9689-457f-4a0b-9a8f-dec7e7baece1","order_by":0,"name":"Anna Muchlińska","email":"","orcid":"","institution":"Medical University of Gdańsk","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Muchlińska","suffix":""},{"id":604460057,"identity":"b3209e74-d3f8-4df8-be21-67161db402ce","order_by":1,"name":"Julia Richert","email":"","orcid":"","institution":"Medical University of Gdańsk","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"","lastName":"Richert","suffix":""},{"id":604460058,"identity":"3f4050d9-95bc-4e41-9b40-5f551b828c9d","order_by":2,"name":"Robert Wenta","email":"","orcid":"","institution":"Medical University of Gdańsk","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"","lastName":"Wenta","suffix":""},{"id":604460059,"identity":"2a118dd4-c116-4a99-8432-6b27eef7a7c9","order_by":3,"name":"Aleksandra Parteka","email":"","orcid":"","institution":"Medical University of Gdańsk","correspondingAuthor":false,"prefix":"","firstName":"Aleksandra","middleName":"","lastName":"Parteka","suffix":""},{"id":604460060,"identity":"6158f4bf-d828-4e29-a8a6-9e13c2172174","order_by":4,"name":"Marta Popęda","email":"","orcid":"","institution":"Medical University of Gdańsk","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"","lastName":"Popęda","suffix":""},{"id":604460061,"identity":"2a71638d-8ddc-48ed-abbc-5c3594626b83","order_by":5,"name":"Beata Pieczyńska-Uziębło","email":"","orcid":"","institution":"Medical University of Gdańsk","correspondingAuthor":false,"prefix":"","firstName":"Beata","middleName":"","lastName":"Pieczyńska-Uziębło","suffix":""},{"id":604460062,"identity":"deb649c9-c048-44d0-93fc-bb2f5611769e","order_by":6,"name":"Anna Żaczek","email":"","orcid":"","institution":"Medical University of Gdańsk","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Żaczek","suffix":""},{"id":604460063,"identity":"a9d58e7e-40e7-42f5-b3cf-0e68ea665c38","order_by":7,"name":"Natalia Bednarz-Knoll","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYDACCTbGB2DGASAbSMkQo4XZAFkLDzFa2CRI02Iu3ZZW+bVtmxzfAeaDt3kY7hDWYjnn2LHbsm23jSUPsCVb8zA8I6zF4EZ6223JttuJGw7wmEnzMBwmTksxUEv9hgP834jVknaM8WPb7QSDAzxsRGq5cyxZmuHcbcOZh9mMLecYEOOX222GH3+U3ZbnO9788MabijtyBLWAADPYZGawCQeI0sHA+APBJlLLKBgFo2AUjCgAAASoPhHvkjLXAAAAAElFTkSuQmCC","orcid":"","institution":"Medical University of Gdańsk","correspondingAuthor":true,"prefix":"","firstName":"Natalia","middleName":"","lastName":"Bednarz-Knoll","suffix":""}],"badges":[],"createdAt":"2026-03-06 16:08:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9052403/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9052403/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104582659,"identity":"c395cce8-69cf-4746-8ee7-042dc60eea0e","added_by":"auto","created_at":"2026-03-13 15:13:39","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1834966,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBasics of liquid biopsy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLiquid biopsy in one shot: various body fluids and different examined analytes used in liquid biopsy assays. Created with BioRender.com.\u003c/p\u003e","description":"","filename":"MuchlinskaetalFigure1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9052403/v1/9b09e4812a91d11f380b298d.jpeg"},{"id":104582661,"identity":"4e6a7f11-5b1f-4ff3-9553-2f6745c07a29","added_by":"auto","created_at":"2026-03-13 15:13:39","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":237483,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConcept and purpose of the CTC Atlas.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe CTC Atlas is an open-access, image-based reference platform designed to standardize the identification and characterization of circulating tumor cells by integrating curated imaging data with clinical and molecular context, thereby supporting reproducible analyses, AI-ready benchmarking, and clinical translation of liquid biopsy approaches.\u003c/p\u003e","description":"","filename":"MuchlinskaetalFigure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9052403/v1/037cf308e8ab58134e71e371.jpg"},{"id":104582658,"identity":"886b47a8-f997-425f-8789-f98930a21e40","added_by":"auto","created_at":"2026-03-13 15:13:39","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3481014,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCTC identification in brief\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTypes of tumor-progression related cellular objects observed in blood of oncological patients (\u003cstrong\u003eA\u003c/strong\u003e), criteria of CTCs identification (\u003cstrong\u003eB\u003c/strong\u003e) and features of CTCs evaluable on 2D images (\u003cstrong\u003eC\u003c/strong\u003e). Created with BioRender.com.\u003c/p\u003e","description":"","filename":"MuchlinskaetalFigure3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9052403/v1/36cc6865e1889465c8975934.jpeg"},{"id":104582663,"identity":"cc9054dd-d37a-4300-a1df-4f80fca7fa76","added_by":"auto","created_at":"2026-03-13 15:13:40","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":332824,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCTC Atlas’ objects identification card\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExample of CTC description applied in the 1\u003csup\u003est\u003c/sup\u003e version of CTC Atlas (launched February 2025).\u003c/p\u003e","description":"","filename":"MuchlinskaetalFigure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9052403/v1/13a8b48e47d367fe1280341c.jpg"},{"id":104782163,"identity":"6bc0db28-e586-4541-a9f0-09b5f9e206f7","added_by":"auto","created_at":"2026-03-17 07:56:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6533874,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9052403/v1/d10ccf67-a4c1-4d70-ad03-e1cd5b1a4315.pdf"},{"id":104582662,"identity":"7563a015-6482-4f21-b247-bfb32f966b75","added_by":"auto","created_at":"2026-03-13 15:13:39","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":20484,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9052403/v1/08cc904ce82ecdb9d3ae832c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Circulating Tumor Cells Atlas – an open-access repository capturing tumor cells heterogeneity and their ecosystem","fulltext":[{"header":"Main Text","content":"\u003cp\u003e\u003cstrong\u003eLiquid biopsy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLiquid biopsy (\u003cstrong\u003eFig. 1\u003c/strong\u003e) has been recognized as groundbreaking tool in the early detection and monitoring of various solid tumors, challenging the current limitations of large-scale, molecular-driven cancer treatment personalization. Unlike conventional tissue biopsies, which require invasive, usually single-use procedures, liquid biopsy allows for the minimally or even non-invasive, sequential collection of biological fluids, mainly peripheral blood (1). This approach allows for detection of tumour-related biomarkers such as circulating tumour cells (CTCs), circulating tumour / free DNA (ct/cfDNA), extracellular vesicles (EVs), peptides, metabolites, and RNA (\u003cstrong\u003eFig. 1)\u003c/strong\u003e in a potentially reproducible manner and at ultrasensitive levels, enabling identification of even trace amounts of clinically relevant analytes (2,3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. 1 Basics of liquid biopsy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLiquid biopsy in one shot: various body fluids and different examined analytes used in liquid biopsy assays. Created with BioRender.com.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Over the past two decades, advances in technologies for studying tumor dissemination have highlighted the value of liquid biopsy as a tool for capturing tumor heterogeneity and enabling precision oncology (4\u0026ndash;6). By providing mechanistic insights into tumor progression, liquid biopsy supports early and ultrasensitive diagnostics, real-time monitoring of disease dynamics and treatment response, and assessment of minimal residual disease (MRD). Despite its clinical potential, the broad implementation of liquid biopsy assays remains limited. A major barrier is the lack of standardised, universally applicable protocols and guidelines transferable for all liquid biopsy technologies. This might negatively impact reproducibility and accuracy of liquid biopsy tests, thereby postponing universal implementation of those tests into daily clinical practice (7). In this article, we address this unmet need by introducing an open-access, atlas-based resource, the CTC Atlas (www.CTCatlas.org), as a repository of CTC-related data designed to support standardized, image-based identification and molecular characterization of circulating tumor and tumor-associated cells, which should facilitate more reliable integration of liquid biopsy technologies into research and clinical workflows, as well as better understanding of metastatic process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLiquid biopsy and need of its standardization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite major technological advances, liquid biopsy assays remain highly sensitive to pre-analytical variability, including differences in sample collection, transportation, storage, and processing (8). Such factors might critically affect the stability and integrity of analytes such as circulating tumor cells (CTCs), ct/cfDNA, and extracellular vesicles, thereby influencing assay sensitivity, reproducibility, and inter-study comparability. In addition, methodological heterogeneity between laboratories, spanning analyte isolation, detection platforms, and bioinformatic pipelines, can introduce discrepancies, artifacts and even biases in biomarker quantification and interpretation, ultimately impacting clinical decision-making (9). To address these challenges, meticulous reporting of experimental conditions following BRISQ guidelines (10), implementation of standardized protocols, and rigorous quality control across all analytical steps are essential for reliable clinical translation of liquid biopsy technologies.\u003c/p\u003e\n\u003cp\u003eStandardization challenges are particularly pronounced in CTC detection due to their extreme rarity, phenotypic heterogeneity and plasticity, and the lack of strictly tumor-specific markers covering all types of CTC populations. The FDA-approved CellSearch\u0026reg; system, based on EpCAM and keratin expression, remains the most widely used and validated platform (11,12). However, epithelial\u0026ndash;mesenchymal transition (EMT) leads to down-regulation of epithelial markers, rendering mesenchymal CTC subpopulations poorly detectable and potentially excluding cells critical for metastasis (13\u0026ndash;15). The lack of CTC-specific mesenchymal markers, morphological diversity of CTC phenotypes (16), and difficulties in defining universal internal and external controls further complicate normalization and threshold definition across studies and centres.\u003c/p\u003e\n\u003cp\u003eBeyond biological variability, molecular imaging technologies commonly used for CTC detection face substantial technical standardization issues. Differences in imaging platforms, acquisition parameters, reagents and even their batches, and image analysis pipelines result in variability in resolution, sensitivity, and signal interpretation. Inconsistent reporting of technical parameters, limited availability of reference standards, subjective image scoring, and lack of harmonized quantification metrics hinder reproducibility, regulatory compliance, and cross-institutional validation (17,18). Addressing these limitations requires standardized imaging guidelines, automated analysis pipelines, reference materials, and publicly available benchmark datasets (19,20).\u003c/p\u003e\n\u003cp\u003eSeveral international initiatives, including the European Liquid Biopsies Academy, CANCER-ID, BloodPAC, and the International Liquid Biopsy Standardization Alliance, have initiated efforts toward harmonization (20\u0026ndash;23). However, universally accepted guidelines and open-access reference standards are still needed to enable robust, global implementation of liquid biopsy in precision oncology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAtlases as tool to standardize and boost precision oncology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMeanwhile, the development of comprehensive atlases and online platforms has transformed molecular biology and medicine by organizing vast amounts of rapidly growing biomedical data, in particular, those from \u0026lsquo;omic\u0026rsquo; technologies. Already existing and continuously expanding resources, ranging from large-scale omics atlases such as The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), and Human Cell Atlas (HCA), through integrative biological knowledge bases including STRING and MalaCards, to clinically oriented reference platforms such as Pathology Outlines, play a crucial role in systematizing and sharing large datasets, while also serving as reference points for biomarkers, technologies and diverse biomedical research and clinical applications. (24\u0026ndash;28). These tools provide structured, standardized, and integrated data that catalyze discoveries in molecular biology and translational medicine. This is exemplified by the decade-long existence of the TCGA platform and its profound impact on precision oncology. With multiomic data derived from over 20,000 tumors, TCGA has been cited as a reference in almost 40,161 scientific publications, including 12,198 publications putatively translating into oncological treatments (PubMed search: \u0026quot;TCGA\u0026quot; and \u0026quot;TCGA + therapy,\u0026quot; respectively, as of 4.03.2026). Expanding the role of atlases in precision medicine, many modern platforms are leveraging artificial intelligence (AI) for data analysis, biomarker discovery, and pattern recognition.\u003c/p\u003e\n\u003cp\u003eReferring specifically to molecular imaging field, several repositories and platforms already provide access to images derived from immunohistochemical and immunofluorescence stainings, visualized by different microscopy modalities (listing e.g., CytoData, Cell Image Library, BioImageArchive, Image Data Resource). Among these, the Human Protein Atlas (HPA) represents a well-established example of an integrative initially imaging-based resource, combining standardized staining protocols with high-resolution microscopy to enable spatially resolved visualization of protein expression across normal and cancer tissues. Such atlas-driven approaches demonstrate how standardized imaging data can support reproducibility, cross-validation, and biomarker discovery. In contrast, within the field of liquid biopsy, comprehensive atlas-based resources integrating standardized imaging data are still largely lacking. Open-access datasets remain limited, being primarily represented by ct/cfDNA datasets dispersed across various multi(gen)omic platforms, such as COSMIC (29). Unlike primary tumor research, where standardized repositories and frameworks guide molecular profiling, liquid biopsy analysis suffers from limited data sharing amplified by a variety in methodologies and biomarker definitions. While some consortia and initiatives, such as CANCER-ID, EV-TRACK or BloodPac already aim to standardize the analysis of liquid biopsy assays and centralize datasets of specific analytes (30,31) publicly available databases dedicated to systematic, image-based characterization of CTCs are, to the best of our knowledge, still absent. Therefore, our platform, the CTC Atlas (www.CTCatlas.org), is designed to fill this gap by providing an open-access repository dedicated to CTC images and associated metadata (\u003cstrong\u003eFig. 2\u003c/strong\u003e). This initiative aims to represent a pivotal step towards integrating liquid biopsy data into precision medicine, ultimately improving the standardization of CTC identification, despite their high heterogeneity and plasticity, and potentially enabling AI-powered automated diagnostic solutions in the future.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. 2\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eConcept and purpose of the CTC Atlas.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe CTC Atlas is an open-access, image-based reference platform designed to standardize the identification and characterization of circulating tumor cells by integrating curated imaging data with clinical and molecular context, thereby supporting reproducible analyses, AI-ready benchmarking, and clinical translation of liquid biopsy approaches.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCTC Atlas and its future directions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHere, we introduce an open-access platform aiming to present high-quality images of cancer-related circulating cells, with main focus on CTCs of different phenotypes and features, visualized using various technologies and panels of markers, together with large collections of molecular data related to tumor dissemination. As a starting point we supplied this platform with high-resolution images of cells acquired using imaging flow cytometry (imFC), a technology that we implemented and optimized for CTC analysis (32). The initial image collection originates from our firstly validated protocols, applied to large patients cohorts and variety of tumor types, using well-known and commonly used markers for CTC detection, and published as original peer-reviewed studies in scientific journals (15,16,33,34) with raw files reposited in open-access, general-purpose research data repositories such as Zenodo (Supplementary Data 1). Nevertheless, the platform is designed as a growing resource and will be progressively extended with additional images from different laboratories, using various isolation and detection methods, as well as diverse biological and clinical set-ups, all described in details in associated methodological descriptions and ID cards. In parallel, the image repository is initially complemented with multigene expression data on matched primary tumors and will be further extended by additional molecular data such as single-cell transcriptomics, molecular profiling of further matched primary tumors or plasma cytokines measurements, enabling integrative, multi-modal characterization of tumor dissemination process.\u003c/p\u003e\n\u003cp\u003eIn brief, over the relatively short period since we implemented imFC technology in liquid biopsy (32), our team has acquired over 40 mln high-resolution images of single and clustered cells derived from peripheral blood mononuclear cells (PBMC) fractions of almost 1000 oncological patients (i.e., breast, prostate, lung, ovarian, renal, colorectal, pancreatic cancer patients) and healthy individuals. So far, all those individuals were recruited at the University Clinical Center (Gdansk, Poland) based on the written informed consents and protocols approved by the local Ethics Committee. The blood was collected to EDTA-tubes, processed using density gradient centrifugation (34), stored in 4% paraformaldehyde, and, to date, examined using two different immunofluorescent protocols analyzed by high throughput and high resolution technology, imFC (i.e., pan-keratin / vimentin / DAPI / CD45 / CD31 / alpha Smooth Muscle Actin (\u0026alpha;-SMA) / CD29 protocol (34) and pan-keratin / androgen receptor / epidermal growth factor receptor (EGFR) / DAPI / CD45 / CD31) (not published yet). Applying this workflow, we have generated \u0026gt;10TB of raw imaging data and a library of over 600 putative CTCs, characterized by different features, some of which were defined in CTCs for the first time (e.g., protrusions, micronuclei, mitotic figures) (15,16). Based on this library and archived images of other cells in PBMC fractions, we created the CTC Atlas to present curated images of CTCs, including, in the future, also ambiguous and questionable CTCs, as well as a plethora of putative progression-related cellular objects detected in the blood of oncological patients, such as circulating fibroblasts, macrophages, endothelila cells and even artefacts. The strength of this platform lies in the detailed annotation of both clinical and technical parameters associated with each identified object, according to EQUATOR recommendations. In parallel, we incorporated the first matched omics dataset, generated by NanoString multigene expression profiling of matched primary tumors (35) integrated with CTC status in prostate cancer patients. This so-called \u0026ldquo;molecular calculator\u0026rdquo; will be progressively expanded to include additional molecular profiles of CTC-positive and CTC-negative patients, covering different molecules (mRNA, cytokines, metabolites, etc.) assessed in corresponding primary tumors, blood cells or plasma, and, in the future, also in metastatic tumors.\u003c/p\u003e\n\u003cp\u003eWith the first version of CTC Atlas released in February 2025, we presented initially \u0026gt;150 cellular objects including CTCs of different phenotypes and characteristics (reflecting high heterogeneity and plasticity of those cells, and also their clusterization and interaction status), circulating fibroblasts and leukocytes, which will be soon complemented by addition of images of circulating endothelial cells, neutrophil extracellular traps and selected artefacts (\u003cstrong\u003eFig. 3A\u003c/strong\u003e). For CTCs identification we followed commonly applied criteria implemented from CellSearch\u0026reg; and other imaging technologies, i.e.: intact morphology, presence of DAPI+ nucleus of not obvious leukocyte shape (such as neutrophil segmented nucleus), cell size of at least 5 \u0026micro;m and the absence of exclusion markers such as CD45 and/or CD31 (\u003cstrong\u003eFig. 3B\u003c/strong\u003e). However, analyzing morphological details of CTCs (16) and attempting first deep learning-aided models for automated detection of those cells (data not shown), which led to discovery of some features neglected in CTC identification by scientists\u0026rsquo; eye (e.g., H entropy, a measure of intracellular complexity derived from the heterogeneity of fluorescence intensity), we conclude that those criteria have to be revised and improved in order to nail genuine CTCs. Thus, one of the goals of CTC Atlas is to characterize and present a potentially broad panel of so far not investigated measurable features of putative CTCs, including their size, shape, phenotype, and other morphological details such as protrusions, micronuclei, nucleus-to-cytoplasm ratio, etc (\u003cstrong\u003eFig. 3C\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFig. 3 CTC identification in brief\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTypes of tumor-progression related cellular objects observed in blood of oncological patients (\u003cstrong\u003eA\u003c/strong\u003e), criteria of CTCs identification (\u003cstrong\u003eB\u003c/strong\u003e) and features of CTCs evaluable on 2D images (\u003cstrong\u003eC\u003c/strong\u003e). Created with BioRender.com.\u003c/p\u003e\n\u003cp\u003eIn the future, it might also encompass various radiomic parameters, such as intensity, texture, and the spatial distribution of these analyzed features, acquired in both bright-field (emphasizing morphology) and fluorescence (highlighting marker presence) channels (\u003cstrong\u003eFig. 3C\u003c/strong\u003e). It should initiate detailed reporting such characteristics comprehensively among all studies, which, in consequence, should also boost investigation on the biology of disseminating tumor cells. In the future, continuous research and debate on CTC identification should lead to an upgrade of CTC identification criteria and ease the implementation of CTC tests into diagnostics, thus improving precision oncology. In the current version of CTC Atlas, we use metrics describing general, clinical, and technical information, as well as sample preparation and cell characteristics, including presence of specific markers, micronucleus or protrusions, their size and shape, as well as clusterization status and interactions with other cells (\u003cstrong\u003eFig. 3C\u003c/strong\u003e, \u003cstrong\u003eFig. 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. 4 CTC Atlas\u0026rsquo; objects identification card\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExample of CTC description applied in the 1\u003csup\u003est\u003c/sup\u003e version of CTC Atlas (launched February 2025).\u003c/p\u003e\n\u003cp\u003eCurrently CTC Atlas comprises CTCs derived from two types of blood: peripheral blood and tumor draining vein blood. In the future, CTC Atlas will expand to include a larger number of cellular objects of different kinds and origins, encompassing tumor progression-related cells from further tumor entities, collected at different clinical timepoints and under different regimens, as well as from additional body fluids such as cerebrospinal or urine. First, we aim to extend the molecular calculator and add cells stained for further markers using different multimarker protocols, present a broader spectrum of CTC characteristics, as well as extend the range of studied cancer types, to elevate the publicly available library of rare cell types circulating in blood and associated with tumor progression. Our repository also aims to be extended to include images of CTCs detected using different isolation methods and further imaging technologies, leveraging both our resources and collaborations with other scientific centers, thereby supporting the development of a reference library and enabling AI-assisted detection of clinically relevant cells. Ultimately, we intend to optimize and implement fluorescent in situ hybridization (FISH) protocols to allow the identification of CTCs based on genetic aberrations, which would provide a more definitive classification of malignant cells than protein-based phenotyping. In parallel, we will perform comparisons of results across all protocols and cancer types, continuously updating the statistical analysis of all examined parameters as new data are generated. In the future, we will integrate images of identified CTCs with multiomic datasets from single cells and matched primary tumors, together with peripheral blood cytokine profiles representing the systemic immune context of the CTC-associated ecosystem, to provide a comprehensive multidimensional picture of disseminating tumor cells. Finally, the webpage is and will be further updated with both scientific and popular-science content summarizing the basics and recent advances in liquid biopsy to improve public understanding and provide reference materials for both professional and lay audiences.\u003c/p\u003e"},{"header":"Summary","content":"\u003cp\u003eIn the era of open-access large data platforms, data sharing in science gains a new dimension, leveraging technologies, experimental and diagnostic workflows, and fastening the implementation of molecular biology achievements into clinical practice. It enables standardization, and opens broad discussion about the guidelines that are crucial for each technological approach, including those applied in liquid biopsy. Here, we introduce, to the best of our knowledge, the first open-access repository of images of CTCs representing various phenotypes and accompanied by detailed annotations reflecting their heterogeneity. CTC Atlas aims to provide the research community with a tool enabling future advances in CTC identification, and improving the understanding of the metastatic process, thus paving the way for implementation of CTC-based assays into precision oncology. CTC Atlas will adhere to internationally recognized standards of scientific excellence and welcome verified images of cancer-related cells from different technologies and institutions, with the long-term goal of advancing CTC identification and analysis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCTCs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecirculating tumor cells\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ecfDNA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecirculating free DNA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ectDNA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecirculating tumor DNA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEMT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eepithelial\u0026ndash;mesenchymal transition\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eimFC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eimaging flow cytometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eminimal residual disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEVs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eextracellular vesicles\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTCGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe Cancer Genome Atlas\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHPA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuman Protein Atlas\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuman Cell Atlas\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSTRING\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSearch Tool for the Retrieval of Interacting Genes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEpCAM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eepithelial cell adhesion molecule\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBRISQ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBiospecimen Reporting for Improved Study Quality\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki and approved by the Independent Bioethics Committee for Scientific Research at the Medical University of Gdansk (study protocols: #NKBBN/286/2018, #NKBBN/748/2019\u0026ndash;2020, and #NKBBN/ 434/2017). The patients provided written informed consent to participate in the study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was funded by a grant from the Ministry of Science and Higher Education, Poland (#NdS-II/SP/0398/2023/01 for NBK).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eStudy conceptualization, design and supervision: NBK; experiments and analysis: AM, JR, RW, AP, MP, BPU; data curation: AM, JR, RW, AP, MP; resources: AZ, NBK; funding and administrative management: NBK; draft writing: AM, RW, AP, NBK. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank all patients and healthy donors who agreed to donate blood. We thank all clinicians cooperating in different projects for their involvement in the recruitment of the patients and collection of clinical data. Figures preparation was supported by BioRender under the license for the Medical University of Gdańsk.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll presented data are available on the webpage: http:/www.CTCatlas.org .The raw datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLone SN, Nisar S, Masoodi T, Singh M, Rizwan A, Hashem S, et al. Liquid biopsy: a step closer to transform diagnosis, prognosis and future of cancer treatments. 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Journal of Personalized Medicine 2021, Vol 11,. 2021;11(11). doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/JPM11111088\u003c/span\u003e\u003cspan address=\"10.3390/JPM11111088\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"liquid biopsy, circulating tumor cells, imaging flow cytometry, cell atlas, tumor progression, phenotype, cell morphology, standardization, tumor microenvironment","lastPublishedDoi":"10.21203/rs.3.rs-9052403/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9052403/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLiquid biopsy is increasingly used in precision medicine, highlighting the need for standardized, image-based reference resources for reproducible identification and characterization of circulating tumor cells (CTCs). We present CTC Atlas (www.CTCAtlas.org), an open-access, community-oriented platform providing a curated compendium of CTCs with diverse morphological and molecular features, alongside other circulating tumor-associated cell types, including cancer-associated fibroblasts, macrophages, endothelial cells, and imaging artifacts. The platform integrates high-quality microscopy images with matched omics data, enabling systematic annotation, reproducible analysis, and comparative studies of tumor-related cells across laboratories. CTC Atlas addresses the lack of standardized reference frameworks in liquid biopsy, supporting reproducible workflows and facilitating cross-study comparisons. By providing structured, accessible datasets, the platform advances the understanding of tumor cell heterogeneity and dissemination dynamics in circulation and lays the groundwork for improved clinical applications of CTC-based liquid biopsy.\u003c/p\u003e","manuscriptTitle":"Circulating Tumor Cells Atlas – an open-access repository capturing tumor cells heterogeneity and their ecosystem","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-13 15:13:35","doi":"10.21203/rs.3.rs-9052403/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bf139566-33ec-4ef2-8ba1-c8bfec19b40a","owner":[],"postedDate":"March 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-13T15:13:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-13 15:13:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9052403","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9052403","identity":"rs-9052403","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}