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Subcellular localization and protein levels of cyclin-dependent kinase inhibitor p27 independently predict for survival in epithelial ovarian cancer

  • Amanda Psyrri(corresponding author)
    ,
  • Aris Bamias
    ,
  • Ziwei Yu
    ,
  • Paul M. Weinberger
    ,
  • Mohamad Kassar
    ,
  • Sophia Markakis
*Corresponding author for this work
  • Yale Cancer Center
    ,
  • Yale University
    ,
  • National and Kapodistrian University of Athens
Scholary Output:
Contribution to journal
Article
Peer-review

Open access

Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well

Abstract

Purpose: p27 protein is regarded as a valuable prognostic biomarker in cancer with a potential use as a molecular target. However, different methods of immunohistochemical assessment have yielded conflicting results. Here, we sought to determine the prognostic value of p27 in ovarian cancer using a novel method of compartmentalized in situ protein analysis. Experimental Design: A tissue array composed of 150 advanced stage ovarian cancers uniformly treated, with surgical debulking followed by platinum-paclitaxel combination chemotherapy, was constructed. For evaluation of p27 protein expression, we used an immunofluorescence-based method of automated in situ quantitative measurement of protein analysis [automated quantitative analysis (AQUA)]. Results: The mean follow-up time of the patients was 34.3 months. Patients with low Fédération Internationale des Gynaecologistes et Obstetristes stage were more likely to have low nuclear p27 expression (P = 0.008). Low nuclear p27 expression was associated with improved 3-year overall survival (66% versus 20%, P = 0.0047) and disease-free survival (27% versus 12%, P = 0.022). In multivariable analysis, adjusting for well-characterized prognostic variables, low nuclear p27 expression level was the most significant prognostic factor for both disease-free and overall survival. Conclusions: Our results indicate that quantitative assessment of nuclear p27 expression level by automated in situ quantitative analysis is a strong predictor for outcome in ovarian cancer.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 8384-8390 (7 pages)

Journal (Volume, Issue Number)

Clinical Cancer Research (Volume 11, Issue 23)

Publication milestones

  • Published - 12/01/2005

Publication status

Published - 12/01/2005

ISSN

1078-0432

Publication IDs

  • Scopus: 28544433273
  • PubMed: 16322299

Publication metrics

Metrics

SciVal
FWCI
0.63
SciVal
Author count
11
SciVal
citations
31
SciVal
Paper percentile
80
Fractional count
1
Fractional count
0.09
Fractional count
10
Fractional count
0.91
Fractional count
1
Fractional count
1
Scopus
citations

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Citation count
34
Captures
18