Oncotarget

Research Papers:

DNA aneuploidy and breast cancer: a meta-analysis of 141,163 cases

Jing Xu, Lei Huang and Jun Li _

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Oncotarget. 2016; 7:60218-60229. https://doi.org/10.18632/oncotarget.11130

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Abstract

Jing Xu1,*, Lei Huang2,4,*, Jun Li1,3

1Department of Medical Oncology, the First Affiliated Hospital of Anhui Medical University, Hefei, China

2Department of Gastrointestinal Surgery, the First Affiliated Hospital of Anhui Medical University, Hefei, China

3Department of Tumor Cytology, the First Affiliated Hospital of Anhui Medical University, Hefei, China

4German Cancer Research Center (DKFZ), Heidelberg, Germany

*Jing Xu and Lei Huang contributed equally to this work

Correspondence to:

Jun Li, email: [email protected]

Lei Huang, email: [email protected]

Keywords: breast cancer, diploidy, aneuploidy, estrogen receptor, survival

Received: April 19, 2016    Accepted: July 19, 2016    Published: August 09, 2016

ABSTRACT

Background & Aims: DNA ploidy, a DNA flow cytometry parameter, reflects tumor cell cycle. In breast cancer (BC), ploidy status characterizes genotypic stability and potential metastatic capacity. It is suggested that aneuploidy is an independent prognosticator for BC patients and could aid for individualized medicine. There are extensive studies concerning the prognostic significance of DNA aneuploidy, however, its clinical utility remains controversial. Herein we conducted a meta-analysis to determine the correlation between DNA ploidy status and BC characteristics and survival.

Methods: The electronic databases PubMed, EMBASE, and Web of Science were searched for relevant studies. The major investigated parameters were the BC aneuploidy rates in relation to tumor stage, size, lymph node metastasis, grading, estrogen receptor (ER) status, disease-free survival (DFS), and overall survival (OS). Hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) for DFS and OS were extracted from each study before meta-analyzed. Risk ratios (RRs) were computed using the fixed-effect or random-effects model according to data heterogeneity, and the Mantel-Haenszel or the inverse-variance method was adopted where appropriate to obtain pooled estimates using RevMan 5.3. The Egger’s test was conducted with Stata 11.

Results: Pooled analyses of data from 29 studies involving a total of 141,163 cases showed that BC patients with more advanced tumors (stage I vs. stages II-IV, RR=0.84; 95% CI, 0.74 to 0.96; P=0.01), larger tumors (≤2 cm vs. >2 cm: RR=0.82; 95% CI, 0.77 to 0.87; P<0.00001), lymph node metastasis (pN0 vs. pN1-3: RR=0.85; 95% CI, 0.83 to 0.87, P<0.00001), poorer tumor proliferation (G2 vs. G1: RR=1.58; 95% CI, 1.40 to 1.79; P<0.00001; G3 vs. G1: RR=2.17; 95% CI, 1.77 to 2.67; P<0.00001; G3 vs. G2: RR=1.41; 95% CI, 1.25 to 1.60; P<0.00001), and ER status (ER vs. ER+: RR=1.32; 95% CI, 1.22 to 1.43; P<0.00001) were significantly more frequently aneuploid. BC patients with diploid tumors had better clinical outcomes than those with aneuploid cancers. The pooled HR estimates were0.73 (P<0.0001) for DFS and 0.72 (P=0.0001) for OS, respectively.

Conclusion: This meta-analysis implies that DNA aneuploidy is a significant predictor for BC progression and survival, and should be focused on in the therapeutic planning.


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