메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
Kurmyshkina, Olga V (Institute of High-Tech Biomedicine, Petrozavodsk State University) Kovchur, Pavel I (Institute of High-Tech Biomedicine, Petrozavodsk State University) Volkova, Tatyana O (Institute of High-Tech Biomedicine, Petrozavodsk State University)
저널정보
아시아태평양암예방학회 Asian Pacific journal of cancer prevention : APJCP Asian Pacific journal of cancer prevention : APJCP 제16권 제11호
발행연도
2015.1
수록면
4,477 - 4,487 (11page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
In this review we summarize the results of studies employing high-throughput methods of profiling of HPV-associated cervical intraepithelial neoplasia (CIN) and squamous cell cervical cancers at key intracellular regulatory levels to demonstrate the unique identity of the landscape of molecular changes underlying this oncopathology, and to show how these changes are related to the 'natural history' of cervical cancer progression and the formation of clinically significant properties of tumors. A step-wise character of cervical cancer progression is a morphologically well-described fact and, as evidenced by genome-wide screenings, it is indeed the consistent change of the molecular profiles of HPV-infected epithelial cells through which they progressively acquire the phenotypic hallmarks of cancerous cells. In this sense, CIN/cervical cancer is a unique model for studying the driving forces and mechanisms of carcinogenesis. Recent research has allowed definition of the whole-genome spectrum of both random and regular molecular alterations, as well as changes either common to processes of carcinogenesis or specific for cervical cancer. Despite the existence of questions that are still to be investigated, these findings are of great value for the future development of approaches for the diagnostics and treatment of cervical neoplasms.

목차

등록된 정보가 없습니다.

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0