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 (784 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
Benign unilocular lytic areas in the proximal end of a long bone with well defined and narrow endosteal margins. The cysts contain fluid and the cyst walls may contain some giant cells. Bone cysts usually occur in males between the ages 3-15 years.
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: Bone Cyst; Cyst, Bone; Cysts, Bone; Solitary Cysts; Cyst, Solitary; Cysts, Solitary; Solitary Cyst; Intraosseous Ganglion.
Where it fits in the MeSH classification
- Broader topics
- Cysts; Bone Diseases
- Narrower topics
- Bone Cysts, Aneurysmal; Jaw Cysts
Research landscape
PubMed indexes 14,538 records tagged with the MeSH heading “Bone Cysts” (counts retrieved 2026-10-29). 1,392 of them (9.6%) were published from 2020 onward, and the busiest period so far is through 1999 with 7,857 records.
Reviews account for 1,476 records (10.2%) and meta-analyses for 38. Randomized controlled trials number 45 (0.3%) 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 | 7,857 |
| 2000-2009 | 2,467 |
| 2010-2019 | 2,822 |
| 2020 onward | 1,392 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 1,476 | 10.2% |
| Meta-analyses | 38 | 0.3% |
| Randomized controlled trials | 45 | 0.3% |
Method: PubMed query "Bone Cysts"[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 |
|---|---|---|---|---|
| The World Health Organization Classification of Odontogenic Lesions: A Summary of the Changes of the 2022 (5th) Edition | 2022 | Review article Design not recorded in structured metadata | 174 | cc by PMID 35578902 · DOI · PMC9999699 |
| Update on aneurysmal bone cyst: pathophysiology, histology, imaging and treatment | 2022 | Review article Design not recorded in structured metadata | 101 | cc by PMID 35941207 · DOI · PMC9360065 |
| Digital pathology-based artificial intelligence models for differential diagnosis and prognosis of sporadic odontogenic keratocysts | 2024 | Research article Design not recorded in structured metadata | 33 | cc by PMID 38403665 · DOI · PMC10894880 |
| Multiomics Reveals IL-17 Drives Epithelial Keratinization and Proliferation via EHF in Odontogenic Keratocysts | 2026 | Research article Design not recorded in structured metadata | 0 | cc by PMID 42123694 · DOI · PMC13163638 |
The World Health Organization Classification of Odontogenic Lesions: A Summary of the Changes of the 2022 (5th) Edition [1]
Abstract reading summary — source excerpts
- Opening excerpt
- The 5th edition of the World Health Organization (WHO) Classification of Head and Neck Tumors opened to online access in March 2022.
- Closing excerpt
- In this article, we review the odontogenic tumors and cysts of the jaw sections of the Odontogenic and Maxillofacial Bone Tumors Chapter, outlining changes from the 2017 WHO classification and summarizing the essential diagnostic criteria and new developments.
- 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 (141 words)
The 5th edition of the World Health Organization (WHO) Classification of Head and Neck Tumors opened to online access in March 2022. This edition is conceptually similar to the previous classification of odontogenic lesions. The only newly defined entity in odontogenic lesions is adenoid ameloblastoma, which is classified under benign epithelial odontogenic tumors. While not odontogenic, the surgical ciliated cyst is a new entry to the cyst classification of the jaws. In other respects, a very important change was made in the new blue books that added 'essential and desirable diagnostic criteria' for each entity to highlight the features considered indispensable for diagnosis. In this article, we review the odontogenic tumors and cysts of the jaw sections of the Odontogenic and Maxillofacial Bone Tumors Chapter, outlining changes from the 2017 WHO classification and summarizing the essential diagnostic criteria and new developments.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 35578902 · DOI · PMC9999699
Update on aneurysmal bone cyst: pathophysiology, histology, imaging and treatment [2]
Abstract reading summary — source excerpts
- Opening excerpt
- Aneurysmal bone cyst (ABC) is a benign but locally aggressive lesion that predominantly affects children and young adults.
- Closing excerpt
- , Denosumab).
- 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)
Aneurysmal bone cyst (ABC) is a benign but locally aggressive lesion that predominantly affects children and young adults. ABC, which accounts for approximately 70% of the cases, is now recognized to be a true neoplasm, whereas ABC-like changes associated to other bone neoplasms (also referred in the literature as secondary ABC) accounts for the remaining 30%. The solid variant of ABC is also considered a true neoplasm but is rare. ABC can involve any bone in the body, and although it has a metaphyseal preference, it can involve any part of a bone and soft tissues. As with any bone tumor, the initial evaluation of ABCs should be done with radiographs followed by magnetic resonance imaging or less frequently computed tomography for further characterization. The imaging appearance of ABC is variable; however, a lytic and expansile lesion with fluid-fluid levels is the most common presentation. The main differential diagnosis of an ABC in the pediatric population is unicameral bone cyst (UBC) and telangiectatic osteosarcoma, therefore a biopsy is recommended before treatment. The therapeutic options of ABC range from curettage with or without adjuncts such as phenol, liquid nitrogen, argon laser and bone grafting or bone substitutes to more recently employed alternatives such as image-guided sclerotherapy with various sclerosing agents and monoclonal antibodies (e.g., Denosumab).
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 35941207 · DOI · PMC9360065
Digital pathology-based artificial intelligence models for differential diagnosis and prognosis of sporadic odontogenic keratocysts [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Odontogenic keratocyst (OKC) is a common jaw cyst with a high recurrence rate.
- Closing excerpt
- The AI model that is based on digital pathology shows promise potential for applications in odontogenic diseases of the jaw.
- 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 (230 words)
Odontogenic keratocyst (OKC) is a common jaw cyst with a high recurrence rate. OKC combined with basal cell carcinoma as well as skeletal and other developmental abnormalities is thought to be associated with Gorlin syndrome. Moreover, OKC needs to be differentiated from orthokeratinized odontogenic cyst and other jaw cysts. Because of the different prognosis, differential diagnosis of several cysts can contribute to clinical management. We collected 519 cases, comprising a total of 2 157 hematoxylin and eosin-stained images, to develop digital pathology-based artificial intelligence (AI) models for the diagnosis and prognosis of OKC. The Inception_v3 neural network was utilized to train and test models developed from patch-level images. Finally, whole slide image-level AI models were developed by integrating deep learning-generated pathology features with several machine learning algorithms. The AI models showed great performance in the diagnosis (AUC = 0.935, 95% CI: 0.898-0.973) and prognosis (AUC = 0.840, 95%CI: 0.751-0.930) of OKC. The advantages of multiple slides model for integrating of histopathological information are demonstrated through a comparison with the single slide model. Furthermore, the study investigates the correlation between AI features generated by deep learning and pathological findings, highlighting the interpretative potential of AI models in the pathology. Here, we have developed the robust diagnostic and prognostic models for OKC. The AI model that is based on digital pathology shows promise potential for applications in odontogenic diseases of the jaw.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 38403665 · DOI · PMC10894880
Multiomics Reveals IL-17 Drives Epithelial Keratinization and Proliferation via EHF in Odontogenic Keratocysts [4]
Abstract reading summary — source excerpts
- Opening excerpt
- This study aims to investigate epithelial cell (EpC) heterogeneity in odontogenic keratocysts (OKCs) and the molecular mechanisms driving their characteristic keratinization and rapid proliferation.
- Closing excerpt
- Targeting this axis presents a promising therapeutic strategy to manage OKC growth and prevent recurrence.
- 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 (199 words)
This study aims to investigate epithelial cell (EpC) heterogeneity in odontogenic keratocysts (OKCs) and the molecular mechanisms driving their characteristic keratinization and rapid proliferation. We integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to profile OKC EpCs, validating findings via immunostaining and comparative analysis with normal oral mucosa. The regulatory roles of interleukin-17 (IL-17) and the transcription factor EHF were functionally assessed in vitro using human oral keratinocytes. Multi-omics mapping identified a distinct epithelial subpopulation (EpC2) characterized by robust keratinization, elevated keratin 13 (KRT13), and upregulated IL-17 signaling. Clinical OKC tissues exhibited significant upregulation and spatial co-localization of IL-17 and KRT13. In vitro, IL-17 robustly promoted cellular proliferation and KRT13 expression. Regulon analysis pinpointed EHF as the core transcription factor driving EpC2. EHF knockdown suppressed proliferation and downregulated KRT13, while overexpression amplified these processes. Crucially, IL-17 stimulation failed to rescue KRT13 expression in EHF-depleted cells, suggesting EHF as a critical downstream mediator. We present a comprehensive single-cell and spatial transcriptomic atlas of the OKC epithelium. The IL-17/EHF signaling axis appears to be a fundamental driver of OKC pathogenesis, promoting pathological hyperkeratinization and cellular proliferation. Targeting this axis presents a promising therapeutic strategy to manage OKC growth and prevent recurrence.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42123694 · DOI · PMC13163638
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 Update from the 5th Edition of the World Health Organization Classification of Head and Neck Tumors: Odontogenic and Maxillofacial Bone Tumours [5]
- Research article Bone cysts: unicameral and aneurysmal bone cyst [6]
- Research article Frequency of odontogenic cysts and tumors: a systematic review [7]
- Research article Cancer Surveillance in Gorlin Syndrome and Rhabdoid Tumor Predisposition Syndrome [8]
- Research article Aneurysmal bone cyst [9]
- Research article Odontogenic Cysts and Neoplasms [10]
References
- Soluk-Tekkesin M, Wright JM. The World Health Organization Classification of Odontogenic Lesions: A Summary of the Changes of the 2022 (5th) Edition. . 2022. PMID 35578902 · DOI · PMC9999699
- Restrepo R, Zahrah D, Pelaez L, Temple HT, Murakami JW. Update on aneurysmal bone cyst: pathophysiology, histology, imaging and treatment. . 2022. PMID 35941207 · DOI · PMC9360065
- Cai X, Zhang H, Wang Y, Zhang J, Li T. Digital pathology-based artificial intelligence models for differential diagnosis and prognosis of sporadic odontogenic keratocysts. . 2024. PMID 38403665 · DOI · PMC10894880
- Yi JR, Zhong NN, Liu XH, Zhu ZR, Zhang YJ, Wang J, et al.. Multiomics Reveals IL-17 Drives Epithelial Keratinization and Proliferation via EHF in Odontogenic Keratocysts. . 2026. PMID 42123694 · DOI · PMC13163638
- Vered M, Wright JM. Update from the 5th Edition of the World Health Organization Classification of Head and Neck Tumors: Odontogenic and Maxillofacial Bone Tumours. Head Neck Pathol. 2022. PMID 35312978 · DOI · PMC9019005
- Mascard E, Gomez-Brouchet A, Lambot K. Bone cysts: unicameral and aneurysmal bone cyst. Orthop Traumatol Surg Res. 2015. PMID 25579825 · DOI
- Johnson NR, Gannon OM, Savage NW, Batstone MD. Frequency of odontogenic cysts and tumors: a systematic review. J Investig Clin Dent. 2014. PMID 23766099 · DOI
- Foulkes WD, Kamihara J, Evans DGR, Brugières L, Bourdeaut F, Molenaar JJ, et al.. Cancer Surveillance in Gorlin Syndrome and Rhabdoid Tumor Predisposition Syndrome. Clin Cancer Res. 2017. PMID 28620006 · DOI · PMC7309678
- Rapp TB, Ward JP, Alaia MJ. Aneurysmal bone cyst. J Am Acad Orthop Surg. 2012. PMID 22474093 · DOI
- Bilodeau EA, Collins BM. Odontogenic Cysts and Neoplasms. Surg Pathol Clin. 2017. PMID 28153133 · 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.