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Cited by 694

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Ovarian Cancer

Open access
Cho, Kathleen R., Shih, Ie-Ming·2009·Annual Review of Pathology: Mechanisms of Disease

Abstract

Ovarian carcinomas are a heterogeneous group of neoplasms and are traditionally subclassified based on type and degree of differentiation. Although current clinical management of ovarian carcinoma largely fails to take this heterogeneity into account, it is becoming evident that each major histological type has characteristic genetic defects that deregulate specific signaling pathways in the tumor cells. Moreover, within the most common histological types, the molecular pathogenesis of low-grade versus high-grade tumors appears to be largely distinct. Mouse models of ovarian carcinoma have been developed that recapitulate many of the morphological features, biological behavior, and gene-expression patterns of selected subtypes of ovarian cancer. Such models will likely prove useful for studying ovarian cancer biology and for preclinical testing of molecularly targeted therapeutics, which may ultimately lead to better clinical outcomes for women with ovarian cancer.

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Crossref · 10.1146/annurev.pathol.4.110807.092246

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Metadata

Authors
Cho, K. R., & Shih, I.-M.
Venue
Annual Review of Pathology: Mechanisms of Disease
Published
2009-02-01
Volume
4
Issue
1
Pages
287-313
ISSN
  • 1553-4006 (ISSN-L)
  • 1553-4014
OpenAlex
W4212835986
Cited by
694
References
6
FWCI
2.96
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Ovarian Cancer. https://app.cochat.ai/papers/10.1146/annurev.pathol.4.110807.092246
The paper
Cho, K. R., & Shih, I.-M. (2009). Ovarian Cancer. Annual Review of Pathology: Mechanisms of Disease. https://doi.org/10.1146/annurev.pathol.4.110807.092246

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.