Decoding c-Myc networks of cell cycle and apoptosis regulated genes in a transgenic mouse model of papillary lung adenocarcinomas

解读乳头状肺腺癌转基因小鼠模型中细胞周期和凋亡调控基因的 c-Myc 网络

阅读:3
作者:Yari Ciribilli, Prashant Singh, Reinhard Spanel, Alberto Inga, Jürgen Borlak

Abstract

The c-Myc gene codes for a basic-helix-loop-helix-leucine zipper transcription factor protein and is reported to be frequently over-expressed in human cancers. Given that c-Myc plays an essential role in neoplastic transformation we wished to define its activity in lung cancer and therefore studied its targeted expression to respiratory epithelium in a transgenic mouse disease model. Using histological well-defined tumors, transcriptome analysis identified novel c-Myc responsive cell cycle and apoptosis genes that were validated as direct c-Myc targets using EMSA, Western blotting, gene reporter and ChIP assays.Through computational analyses c-Myc cooperating transcription factors emerged for repressed and up-regulated genes in cancer samples, namely Klf7, Gata3, Sox18, p53 and Elf5 and Cebpα, respectively. Conversely, at promoters of genes regulated in transgenic but non-carcinomatous lung tissue enriched binding sites for c-Myc, Hbp1, Hif1 were observed. Bioinformatic analysis of tumor transcriptomic data revealed regulatory gene networks and highlighted mortalin and moesin as master regulators while gene reporter and ChIP assays in the H1299 lung cancer cell line as well as cross-examination of published ChIP-sequence data of 7 human and 2 mouse cell lines provided strong evidence for the identified genes to be c-Myc targets. The clinical significance of findings was established by evaluating expression of orthologous proteins in human lung cancer. Taken collectively, a molecular circuit for c-Myc-dependent cellular transformation was identified and the network analysis broadened the perspective for molecularly targeted therapies.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。