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Proteomic analysis of gynecologic cancer tissue

ABSTRACT: Using iTRAQ technology, we performed shotgun proteomics of gynecological cancer tissues, which tumor cells were captured by laser microdissection to identify biomarker candidate proteins, for gynecological cancer.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Ovary, Uterine Endometrium

DISEASE(S): Malignant Neoplasm Of Ovary

SUBMITTER: Satoshi Serada

LAB HEAD: Tetsuji Naka

PROVIDER: PXD001849 | Pride | 2016-04-27

REPOSITORIES: Pride

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			Action	DRS
	20130617HiramatsuDr-LMD-iTRAQ02.RAW	Raw
	20130617HiramatsuDr-LMD-iTRAQ03.RAW	Raw
	20130617HiramatsuDr-LMD-iTRAQ04.RAW	Raw
	20130617HiramatsuDr-LMD-iTRAQ05.RAW	Raw
	20130617HiramatsuDr-LMD-iTRAQ06.RAW	Raw

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Publications

Similar protein expression profiles of ovarian and endometrial high-grade serous carcinomas.

Hiramatsu Kosuke K Yoshino Kiyoshi K Serada Satoshi S Yoshihara Kosuke K Hori Yumiko Y Fujimoto Minoru M Matsuzaki Shinya S Egawa-Takata Tomomi T Kobayashi Eiji E Ueda Yutaka Y Morii Eiichi E Enomoto Takayuki T Naka Tetsuji T Kimura Tadashi T

British journal of cancer 20160218 5

<h4>Background</h4>Ovarian and endometrial high-grade serous carcinomas (HGSCs) have similar clinical and pathological characteristics; however, exhaustive protein expression profiling of these cancers has yet to be reported.<h4>Methods</h4>We performed protein expression profiling on 14 cases of HGSCs (7 ovarian and 7 endometrial) and 18 endometrioid carcinomas (9 ovarian and 9 endometrial) using iTRAQ-based exhaustive and quantitative protein analysis.<h4>Results</h4>We identified 828 tumour-e ...[more]

PMID: 26889980

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Classification of High-Grade Serous Ovarian Cancer Using Tumor Morphologic Characteristics

Project description:Despite the similar histologic appearances of high-grade serous ovarian cancers (HGSOCs), clinical observations point to marked differences in their gross appearances. Some patients have numerous small nodules, whereas others have bulkier disease; some patients have widespread disease, whereas others have more localized disease. However, a systematic framework for classifying such gross morphologic differences does not exist. The implementation of a laparoscopic triage algorithm for patients with advanced HGSOC enabled us to prospectively obtain detailed video images of HGSOC that could be analyzed to identify morphologic subtypes. In this study, we aimed to develop and characterize a gross morphologic classification system for HGSOC. Specifically, we assessed whether HGSOC can be reliably divided into distinct gross morphologic subtypes and whether such subtypes have different clinical outcomes and molecular features.

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Analyses of Human Brain Metastases of Breast Cancer Reveal the Association between HK2 Up-Regulation and Poor Prognosis

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