Japanese
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Endocrine-Related Cancer 2019-May

Reciprocal interplay of miR-497 and MALAT1 promotes tumourigenesis of adrenocortical cancer.

登録ユーザーのみが記事を翻訳できます
ログインサインアップ
リンクがクリップボードに保存されます
Nunki Hassan
JingTing Zhao
Anthony Glover
Bruce Robinson
Stan Sidhu

キーワード

概要

Adrenocortical carcinoma (ACC) has high recurrence rates and poor prognosis with limited response to conventional cancer therapy. Recent contributions of high throughput transcriptomic profiling identified microRNA-497 (miR-497) as significantly underexpressed; whilst long noncoding RNA (lncRNA) MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) as overexpressed in ACC. miR-497 is located in the chromosomal region 17p13.1, in which there is a high frequency of loss of heterozygosity in ACC. We aim to investigate the interaction of miR-497 and MALAT1 in ACC and its functional roles in the process of tumourigenesis. In this study, we demonstrated miR-497 post-transcriptionally repressed MALAT1 whilst MALAT1 also competes for miR-497 binding to its molecular target, eIF4E (eukaryotic translation initiation factor 4E). We showed that overexpression of miR-497 and silencing of MALAT1 suppressed cellular proliferation and induced cell cycle arrest through downregulation of eIF4E expression. Furthermore, MALAT1 directly binds to SFPQ (Splicing Factor Proline and Glutamine Rich) protein, indicating its multifaceted roles in ACC pathophysiology. This is the first study to identify the feedback axis of miR-497-MALAT1/eIF4E in ACC tumourigenesis, providing novel insights into the molecular functions of noncoding RNAs in ACC.

Facebookページに参加する

科学に裏打ちされた最も完全な薬草データベース

  • 55の言語で動作します
  • 科学に裏打ちされたハーブ療法
  • 画像によるハーブの認識
  • インタラクティブGPSマップ-場所にハーブをタグ付け(近日公開)
  • 検索に関連する科学出版物を読む
  • それらの効果によって薬草を検索する
  • あなたの興味を整理し、ニュース研究、臨床試験、特許について最新情報を入手してください

症状や病気を入力し、役立つ可能性のあるハーブについて読み、ハーブを入力して、それが使用されている病気や症状を確認します。
*すべての情報は公開された科学的研究に基づいています

Google Play badgeApp Store badge