ArticleDatabase : the journal of biological databases and curation2015
HCSD: the human cancer secretome database.
Article in Database : the journal of biological databases and curation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Pan-cancer secreted proteome and skeletal muscle regulation: insight from a proteogenomic data-driven knowledge base.Functional & integrative genomics · 2025Review
- Identification of stromal cell-derived factor 4 as a liquid biopsy-based diagnostic marker in solid cancers.Scientific reports · 2023Article
- SheddomeDB 2023: A Revision of an Ectodomain Shedding Database Based on a Comprehensive Literature Review and Online Resources.Journal of proteome research · 2023Review
- NGAL as a Potential Target in Tumor Microenvironment.International journal of molecular sciences · 2021Review
- Cellular Fitness Phenotypes of Cancer Target Genes from Oncobiology to Cancer Therapeutics.Cells · 2021Article
- Secret3D Workflow for Secretome Analysis.STAR protocols · 2020Article
- Blockade of Stat3 oncogene addiction induces cellular senescence and reveals a cell-nonautonomous activity suitable for cancer immunotherapy.Oncoimmunology · 2020Article
- Article
- Liquid Biopsy for the Detection of Resistance Mechanisms in NSCLC: Comparison of Different Blood Biomarkers.Journal of clinical medicine · 2019Review
- Locally advanced rectal cancer transcriptomic-based secretome analysis reveals novel biomarkers useful to identify patients according to neoadjuvant chemoradiotherapy response.Scientific reports · 2019Article
- A Systematic Investigation of the Malignant Functions and Diagnostic Potential of the Cancer Secretome.Cell reports · 2019Article
- Cellular Interactions in the Tumor Microenvironment: The Role of Secretome.Journal of Cancer · 2019Review
- Cx43-Associated Secretome and Interactome Reveal Synergistic Mechanisms for Glioma Migration and MMP3 Activation.Frontiers in neuroscience · 2019Article
- Cancer Self-Defense: An Immune Stealth.Cancer research · 2017Review
- SheddomeDB: the ectodomain shedding database for membrane-bound shed markers.BMC bioinformatics · 2017Review
- VerSeDa: vertebrate secretome database.Database : the journal of biological databases and curation · 2017Article
- Cancer Metabolism: A Modeling Perspective.Frontiers in physiology · 2015Review
- A Proteomic Analysis of the Malignant Mesothelioma Secretome Using iTRAQ.Cancer genomics & proteomicsArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The human cancer secretome database (HCSD) is a comprehensive database for human cancer secretome data. The cancer secretome describes proteins secreted by cancer cells and structuring information about the cancer secretome will enable further analysis of how this is related with tumor biology. The secreted proteins from cancer cells are believed to play a deterministic role in cancer progression and therefore may be the key to find novel therapeutic targets and biomarkers for many cancers. Consequently, huge data on cancer secretome have been generated in recent years and the lack of a coherent database is limiting the ability to query the increasing community knowledge. We therefore developed the Human Cancer Secretome Database (HCSD) to fulfil this gap. HCSD contains >80 000 measurements for about 7000 nonredundant human proteins collected from up to 35 high-throughput studies on 17 cancer types. It has a simple and user friendly query system for basic and advanced search based on gene name, cancer type and data type as the three main query options. The results are visualized in an explicit and interactive manner. An example of a result page includes annotations, cross references, cancer secretome data and secretory features for each identified protein.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.