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Journal of Cancer
Article . 2017 . Peer-reviewed
Data sources: Crossref
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Journal of Cancer
Article
License: CC BY NC
Data sources: UnpayWall
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PubMed Central
Conference object . 2017
Data sources: PubMed Central
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Immune Cell Population in Ovarian Tumor Microenvironment

Authors: Cai, Dong Li; Jin, Li-Ping;

Immune Cell Population in Ovarian Tumor Microenvironment

Abstract

Ovarian cancer, the third most common with highest mortality rates gynecological malignancy among women in China, is characterized by a unique tumor immune microenvironment. Immune-cell population infiltrated into the tumor tissue among patients with ovarian cancer are associated positively or negatively with antitumor activity. The imbalance between immune activation and immune suppression can result in oncogenesis and cancer progression. Therefore, intense investigation of the immunologic mechanism of ovarian cancer is urgently needed, and a comprehensive understanding of the network in which immune cells interact with the microenvironment, tumor cells and each other will greatly promote the development of more effective immunotherapies for ovarian cancer. In this review, we will focus on the main immune-cell population in ovarian tumor microenvironment, discuss their role in tumor progression and try to give the readers a new perspective in finding more promising therapeutic targets for cancers.

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  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    66
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
66
Top 1%
Top 10%
Top 10%
Green
gold