Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 4 complete abstracts (789 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
A malignant neoplasm derived from glandular epithelium, in which cystic accumulations of retained secretions are formed. The neoplastic cells manifest varying degrees of anaplasia and invasiveness, and local extension and metastases occur. Cystadenocarcinomas develop frequently in the ovaries, where pseudomucinous and serous types are recognized. (Stedman, 25th ed)
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Cystadenocarcinomas.
Where it fits in the MeSH classification
- Broader topics
- Adenocarcinoma; Neoplasms, Cystic, Mucinous, and Serous
- Narrower topics
- Cystadenocarcinoma, Mucinous; Cystadenocarcinoma, Papillary; Cystadenocarcinoma, Serous
Research landscape
PubMed indexes 9,328 records tagged with the MeSH heading “Cystadenocarcinoma” (counts retrieved 2026-10-29). 1,654 of them (17.7%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 2,766 records.
Reviews account for 778 records (8.3%) and meta-analyses for 28. Randomized controlled trials number 74 (0.8%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.
Show the data
| Period | Records |
|---|---|
| through 1999 | 2,761 |
| 2000-2009 | 2,147 |
| 2010-2019 | 2,766 |
| 2020 onward | 1,654 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 778 | 8.3% |
| Meta-analyses | 28 | 0.3% |
| Randomized controlled trials | 74 | 0.8% |
Method: PubMed query "Cystadenocarcinoma"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.
Reading the evidence in cancer and oncology
Cancer research spans very different kinds of evidence. Laboratory studies in cell lines and animal models reveal mechanisms but often do not translate to patients. Early-phase trials mainly test safety and dosing, while phase 3 randomized trials and their meta-analyses are the usual basis for treatment conclusions. Outcomes also differ in meaning: tumour shrinkage, progression-free survival and overall survival are not interchangeable, and screening studies can be distorted by lead-time and overdiagnosis. When reading a result, check the cancer type and stage studied, the comparison treatment, and which outcome was measured.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Discovery and ranking of the most robust prognostic biomarkers in serous ovarian cancer | 2023 | Research article Design not recorded in structured metadata | 335 | cc by PMID 36856946 · DOI · PMC10400493 |
| Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer | 2023 | Research article Design not recorded in structured metadata | 43 | cc by PMID 37348499 · DOI · PMC10394173 |
| Overview of Tumor Heterogeneity in High-Grade Serous Ovarian Cancers | 2023 | Review article Design not recorded in structured metadata | 39 | cc by PMID 37894756 · DOI · PMC10606847 |
| Spatial proteomics of ovarian cancer precursors delineates early disease changes and drug targets | 2026 | Research article Design not recorded in structured metadata | 6 | cc by PMID 41233595 · DOI · PMC12759074 |
Discovery and ranking of the most robust prognostic biomarkers in serous ovarian cancer [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Progress in ovarian cancer treatment lags behind other tumor types.
- Closing excerpt
- Our results help to prioritize genes and to neglect those which are most likely to fail in studies aiming to establish new clinically useful biomarkers and therapeutic targets in serous ovarian cancer.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (252 words)
Progress in ovarian cancer treatment lags behind other tumor types. With diagnosis usually at an advanced stage, there is a high demand for reliable prognostic biomarkers capable of the selection of effective chemo- and targeted therapies. Our goal was to establish a large-scale transcriptomic database and use it to uncover and rank survival-associated genes. Ovarian cancer cohorts with transcriptome-level gene expression data and clinical follow-up were identified from public repositories. All samples were normalized and entered into an integrated database. Cox univariate survival analysis was performed for all genes and was followed by multivariate analysis for selected genes involving clinical and pathological variables. False discovery rate was computed for multiple hypothesis testing and a 1% cutoff was used to determine statistical significance. The complete integrated database comprises 1816 samples from 17 datasets. Altogether, 2468 genes were correlated to progression-free survival (PFS), and 704 genes were correlated with overall survival (OS). The most significant genes were WBP1L, ASAP3, CNNM2, and NCAPH2 for progression-free survival and CSE1L, NUAK1, ALPK2, and SHKBP1 for overall survival. Genes significant for PFS were also preferentially significant for predicting OS as well. All data including HR and p values as well as the used cutoff values for all genes for both PFS and OS are provided to enable the ranking of future biomarker candidates across all genes. Our results help to prioritize genes and to neglect those which are most likely to fail in studies aiming to establish new clinically useful biomarkers and therapeutic targets in serous ovarian cancer.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 36856946 · DOI · PMC10400493
Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer [2]
Abstract reading summary — source excerpts
- Opening excerpt
- Tertiary lymphoid structure (TLS) is associated with prognosis in copy-number-driven tumors, including high-grade serous ovarian cancer (HGSOC), although the function of TLS and its interaction with copy-number alterations in HGSOC are not fully understood.
- Closing excerpt
- Overall, we reveal that TLS coordinates intratumoral B cell and T cell response to HGSOC tumor, while the cancer genome evolves to counteract TLS formation and function.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (159 words)
Tertiary lymphoid structure (TLS) is associated with prognosis in copy-number-driven tumors, including high-grade serous ovarian cancer (HGSOC), although the function of TLS and its interaction with copy-number alterations in HGSOC are not fully understood. In the current study, we confirm that TLS-high HGSOC patients show significantly better progression-free survival (PFS). We show that the presence of TLS in HGSOC tumors is associated with B cell maturation and cytotoxic tumor-specific T cell activation and proliferation. In addition, the copy-number loss of IL15 and CXCL10 may limit TLS formation in HGSOC; a list of genes that may dysregulate TLS function is also proposed. Last, a radiomics-based signature is developed to predict the presence of TLS, which independently predicts PFS in both HGSOC patients and immune checkpoint inhibitor (ICI)-treated non-small cell lung cancer (NSCLC) patients. Overall, we reveal that TLS coordinates intratumoral B cell and T cell response to HGSOC tumor, while the cancer genome evolves to counteract TLS formation and function.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 37348499 · DOI · PMC10394173
Overview of Tumor Heterogeneity in High-Grade Serous Ovarian Cancers [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Ovarian cancers encompass a group of neoplasms originating from germinal tissues and exhibiting distinct clinical, pathological, and molecular features.
- Closing excerpt
- This review provides an overview of the complex nature of HGSOC, encompassing its various aspects of intratumor heterogeneity, histological patterns, and its dynamic evolution during progression and therapy resistance.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (214 words)
Ovarian cancers encompass a group of neoplasms originating from germinal tissues and exhibiting distinct clinical, pathological, and molecular features. Among these, epithelial ovarian cancers (EOCs) are the most prevalent, comprising five distinct tumor histotypes. Notably, high-grade serous ovarian cancers (HGSOCs) represent the majority, accounting for over 70% of EOC cases. Due to their silent and asymptomatic behavior, HGSOCs are generally diagnosed in advanced stages with an evolved and complex genomic state, characterized by high intratumor heterogeneity (ITH) due to chromosomal instability that distinguishes HGSOCs. Histologically, these cancers exhibit significant morphological diversity both within and between tumors. The histologic patterns associated with solid, endometrioid, and transitional (SET) and classic subtypes of HGSOCs offer prognostic insights and may indicate specific molecular profiles. The evolution of HGSOC from primary to metastasis is typically characterized by clonal ITH, involving shared or divergent mutations in neoplastic sub-clones within primary and metastatic sites. Disease progression and therapy resistance are also influenced by non-clonal ITH, related to interactions with the tumor microenvironment and further genomic changes. Notably, significant alterations occur in nonmalignant cells, including cancer-associated fibroblast and immune cells, during tumor progression. This review provides an overview of the complex nature of HGSOC, encompassing its various aspects of intratumor heterogeneity, histological patterns, and its dynamic evolution during progression and therapy resistance.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 37894756 · DOI · PMC10606847
Spatial proteomics of ovarian cancer precursors delineates early disease changes and drug targets [4]
Abstract reading summary — source excerpts
- Opening excerpt
- High-grade serous ovarian cancer (HGSOC) is often detected at an advanced stage, where curative treatment options are limited.
- Closing excerpt
- This study demonstrates the power of spatially resolved quantitative proteomics in understanding early carcinogenesis and provides a rich resource for biomarker and drug target research.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (164 words)
High-grade serous ovarian cancer (HGSOC) is often detected at an advanced stage, where curative treatment options are limited. Recent advances in ultrasensitive mass spectrometry-based spatial proteomics have provided a unique opportunity to uncover molecular drivers of early tumorigenesis and novel therapeutic targets. Here, we present a comprehensive proteomic analysis of serous tubal intraepithelial carcinoma (STIC), the HGSOC precursor lesion, and concurrent invasive carcinoma, covering more than 10,000 proteins from ultra-low input archival tissue. STIC and HGSOC showed highly similar proteomes, clustering into two subtypes with distinct tumor-immune microenvironments and common remodeling of the extracellular matrix. We discovered cell-of-origin signatures from secretory fallopian tube epithelial cells in STICs and identified early dysregulated pathways of therapeutic relevance. Targeting cholesterol biosynthesis by inhibiting the terminal steps via DHCR7 showed therapeutic effects in ovarian cancer cell lines and synergized with standard-of-care carboplatin treatment. This study demonstrates the power of spatially resolved quantitative proteomics in understanding early carcinogenesis and provides a rich resource for biomarker and drug target research.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41233595 · DOI · PMC12759074
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer [5]
- Research article High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints [6]
- Research article Classification of types of intraductal papillary-mucinous neoplasm of the pancreas: a consensus study [7]
- Research article Ovarian low-grade and high-grade serous carcinoma: pathogenesis, clinicopathologic and molecular biologic features, and diagnostic problems [8]
- Research article Cyst fluid analysis in the differential diagnosis of pancreatic cystic lesions: a pooled analysis [9]
- Research article Morphological subtypes of ovarian carcinoma: a review with emphasis on new developments and pathogenesis [10]
References
- Győrffy B. Discovery and ranking of the most robust prognostic biomarkers in serous ovarian cancer. . 2023. PMID 36856946 · DOI · PMC10400493
- Lu H, Lou H, Wengert G, Paudel R, Patel N, Desai S, et al.. Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer. . 2023. PMID 37348499 · DOI · PMC10394173
- Azzalini E, Stanta G, Canzonieri V, Bonin S. Overview of Tumor Heterogeneity in High-Grade Serous Ovarian Cancers. . 2023. PMID 37894756 · DOI · PMC10606847
- Makhmut A, Dragomir MP, Fritzsche S, Moebs M, Schmitt WD, Taube ET, et al.. Spatial proteomics of ovarian cancer precursors delineates early disease changes and drug targets. . 2026. PMID 41233595 · DOI · PMC12759074
- Bowtell DD, Böhm S, Ahmed AA, Aspuria PJ, Bast RC, Beral V, et al.. Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer. Nat Rev Cancer. 2015. PMID 26493647 · DOI · PMC4892184
- Lisio MA, Fu L, Goyeneche A, Gao ZH, Telleria C. High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints. Int J Mol Sci. 2019. PMID 30813239 · DOI · PMC6412907
- Furukawa T, Klöppel G, Volkan Adsay N, Albores-Saavedra J, Fukushima N, Horii A, et al.. Classification of types of intraductal papillary-mucinous neoplasm of the pancreas: a consensus study. Virchows Arch. 2005. PMID 16088402 · DOI
- Vang R, Shih IeM, Kurman RJ. Ovarian low-grade and high-grade serous carcinoma: pathogenesis, clinicopathologic and molecular biologic features, and diagnostic problems. Adv Anat Pathol. 2009. PMID 19700937 · DOI · PMC2745605
- van der Waaij LA, van Dullemen HM, Porte RJ. Cyst fluid analysis in the differential diagnosis of pancreatic cystic lesions: a pooled analysis. Gastrointest Endosc. 2005. PMID 16111956 · DOI
- McCluggage WG. Morphological subtypes of ovarian carcinoma: a review with emphasis on new developments and pathogenesis. Pathology. 2011. PMID 21716157 · DOI
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-10-29.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.