Literature DB >> 16751981

Histopathological characteristics of a novel knock-in mouse prostate cancer model.

G Wu1, D Wang, H Wang, J Yuan, J W Xuan.   

Abstract

Prostate cancer is relatively unique to man. There is no naturally occurring prostate cancer in the mouse. Pre-clinical studies involve the establishment of a genetically engineered mouse prostate cancer model with features close to those of the human situation. A new knock-in mouse adenocarcinoma prostate (KIMAP) model was established, which showed close-to-human kinetics of tumor development. In order to determine if the similar kinetics is associated with heterogeneous tumor architecture similar to the human situation, we utilized a new mouse histological grading system (Gleason analogous grading system) similar to the Gleason human grading system and flow cytometry DNA analysis to measure and compare the adenocarcinoma of the KIMAP model with human prostate cancer. Sixty KIMAP prostate cancer samples from 60 mice were measured and compared with human prostate cancer. Flow cytometry DNA analysis was performed on malignant prostate tissues obtained from KIMAP models. Mice with prostate cancer from KIMAP models showed a 53.3% compound histological score rate, which was close to the human clinical average (50%) and showed a significant correlation with age (P = 0.001). Flow cytometry analyses demonstrated that most KIMAP tumor tissues were diploid, analogous to the human situation. The similarities of the KIMAP mouse model with tumors of the human prostate suggest the use of this experimental model to complement studies of human prostate cancer.

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Year:  2006        PMID: 16751981     DOI: 10.1590/s0100-879x2006000600008

Source DB:  PubMed          Journal:  Braz J Med Biol Res        ISSN: 0100-879X            Impact factor:   2.590


  1 in total

1.  Oral administration of E-type prostanoid (EP) 1 receptor antagonist suppresses carcinogenesis and development of prostate cancer via upregulation of apoptosis in an animal model.

Authors:  Masahito Masato; Yasuyoshi Miyata; Hiroki Kurata; Hidenori Ito; Kensuke Mitsunari; Akihiro Asai; Yuichiro Nakamura; Kyohei Araki; Yuta Mukae; Tsuyoshi Matsuda; Junki Harada; Tomohiro Matsuo; Kojiro Ohba; Hideki Sakai
Journal:  Sci Rep       Date:  2021-10-13       Impact factor: 4.379

  1 in total

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