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Molecular Genetics of Endometrial Carcinoma

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Attention for Chapter 9: PI3K/PTEN/AKT Genetic Mouse Models of Endometrial Carcinoma
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Chapter title
PI3K/PTEN/AKT Genetic Mouse Models of Endometrial Carcinoma
Chapter number 9
Book title
Molecular Genetics of Endometrial Carcinoma
Published in
Advances in experimental medicine and biology, January 2017
DOI 10.1007/978-3-319-43139-0_9
Pubmed ID
Book ISBNs
978-3-31-943137-6, 978-3-31-943139-0
Authors

Ayesha Joshi, Lora Hedrick Ellenson, Joshi, Ayesha, Ellenson, Lora Hedrick

Abstract

The PI3K/PTEN/AKT pathway is the most frequently mutated pathway in endometrial carcinoma. Mouse models are invaluable tools to understand, at the molecular level, the contributions of components of this pathway towards initiation and progression of endometrial carcinoma. This chapter summarizes results of germline and tissue specific knockout mouse models generated to understand how mutations in components of this pathway lead to development of carcinoma and its interactions with other frequently altered pathways like mismatch repair and estrogen signaling. The mouse models show that loss of both alleles of Pten is necessary and sufficient for complex atypical hyperplasia (CAH) to develop but insufficient for progression to carcinoma. Additional events like mutations in Pik3ca or mismatch repair deficiency are required for progression to carcinoma. The models show that the interaction between Pten and estrogen signaling is complex. In the absence of estrogen, Pten loss is sufficient for development of CAH. Additionally, lack of ERα on a background of Pten loss leads to the development of carcinoma.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 22%
Lecturer 1 11%
Student > Bachelor 1 11%
Other 1 11%
Student > Master 1 11%
Other 0 0%
Unknown 3 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 33%
Medicine and Dentistry 2 22%
Business, Management and Accounting 1 11%
Unspecified 1 11%
Unknown 2 22%