PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 21, 2007Proceedings of the National Academy of Sciences1,381 citationsOpen Access

Programmed cell death 1 ligand 1 and tumor-infiltrating CD8 + T lymphocytes are prognostic factors of human ovarian cancer

View Full Paper
JHJunzo HamanishiMMMasaki MandaiMIMasashi Iwasaki

Key Points

Key points are not available for this paper at this time.

Abstract

The ligands for programmed cell death 1 (PD-1), an immunoinhibitory receptor belonging to CD28/cytotoxic T lymphocyte antigen 4 family, are PD-1 ligand 1 and 2 (PD-Ls). Recent reports suggest that the aberrant expression of PD-Ls on tumor cells impairs antitumor immunity, resulting in the immune evasion of the tumor cells. Although an inverse correlation between the expression level of PD-Ls and patients' prognosis has been reported for several malignant tumors, the follow-up period was limited because of the lack of the antibody (Ab) applicable to paraffin-embedded specimens. Here we generated a new Ab against PD-1 ligand 1 (PD-L1) and analyzed the expression level of PD-Ls in human ovarian cancer using paraffin-embedded specimens. Patients with higher expression of PD-L1 had a significantly poorer prognosis than patients with lower expression. Although patients with higher expression of PD-1 ligand 2 also had a poorer prognosis, the difference was not statistically significant. A significant inverse correlation was observed between PD-L1 expression and the intraepithelial CD8(+) T lymphocyte count, suggesting that PD-L1 on tumor cells directly suppresses antitumor CD8(+) T cells. Multivariate analysis showed the expression of PD-L1 on tumor cells and intraepithelial CD8(+) T lymphocyte count are independent prognostic factors. The PD-1/PD-L pathway can be a good target for restoring antitumor immunity in ovarian cancer.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Hamanishi et al. (2007) studied this question.

synapsesocial.com/papers/6a0982be00217ed3fb33f8b5https://doi.org/10.1073/pnas.0611533104
Ask AI
Helpful
Bookmark
Share
View Full Paper