中国仓鼠卵巢细胞
生物
细胞培养
细胞周期
细胞
卵巢
细胞生长
腺癌
分子生物学
癌症研究
细胞生物学
癌症
内分泌学
遗传学
作者
Yohannes Tesfaigzi,Paul S. Wright,Steven A. Belinsky
出处
期刊:American Journal of Physiology-lung Cellular and Molecular Physiology
[American Physical Society]
日期:2003-10-01
卷期号:285 (4): L889-L898
被引量:15
标识
DOI:10.1152/ajplung.00065.2003
摘要
Many studies have established the role of SPRR1B during squamous differentiation of skin and respiratory epithelial cells. However, its role in nonsquamous cells is largely unknown. We reported that expression of SPRR1B in Chinese hamster ovary (CHO) cells is increased as they enter the G 0 phase of the cell cycle. The purpose of this study was to further investigate the SPRR1B expression pattern in nonsquamous tumors and to study its role in these cells. Expression of SPRR1B was detected by Northern blotting in a higher percentage of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone-induced compared with beryllium metal-induced rat lung adenocarcinomas. In situ hybridizations confirmed that SPRR1B is expressed in individual or clusters of cells of nonsquamous cells from mouse, rat, and human adenocarcinomas. The same pattern of expression was observed in adenocarcinomas formed in nude mice from cell lines established from adenocarcinomas. SPRR1B expression was downregulated in the cell lines derived from adenocarcinoma when cells were enriched in G 0 at low confluence. Tetraploidy was induced in CHO, mouse, and human tumor cell lines by stably overexpressing SPRR1B, whereas control cells showed no change in ploidy. Inducible expression of this protein for shorter periods using the ecdyson system did not affect growth rate or the ploidy of CHO cells but accelerated entry into G 0 /G 1 compared with controls. These findings indicate that SPRR1B is likely coupled primarily to signals responsible for withdrawal from the proliferative state rather than the final stages of cellular quiescence and that its overexpression for prolonged periods may disrupt the normal progression of mitosis.
科研通智能强力驱动
Strongly Powered by AbleSci AI