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Cancer Epidemiol Biomarkers Prev. 2019 Sep 18. pii: cebp.0359.2019. doi: 10.1158/1055-9965.EPI-19-0359. [Epub ahead of print]

A novel scoring system for pivotal autophagy-related genes predicts outcomes after chemotherapy in advanced ovarian cancer patients.

Author information

1
Department of Toxicology, Zhejiang University School of Public Health.
2
Pathology, Zhejiang University School of Medicine.
3
Department of Gynecological Oncology, Zhejiang Cancer Hospital.
4
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, The First Affiliated Hospital, Zhejiang University School of Medicine.
5
Department of Pathology, School of Medicine, Zhejiang University.
6
Department of Physiology, National University of Singapore.
7
Department of Toxicology of School of Public Health, and Department of Gynecologic Oncology of Women's Hospital, Zhejiang University School of Medicine.
8
Department of Toxicology of School of Public Health, Zhejiang University School of Public Health georgewuer@126.com.

Abstract

BACKGROUND:

In the clinical practice of ovarian cancer, the application of autophagy, an important regulator of carcinogenesis and chemoresistance, is still limited. This study aimed to establish a scoring system based on expression profiles of pivotal autophagy-related (ATG) genes in stage III/IV ovarian cancer patients who received chemotherapy.

METHODS:

Data of ovarian serous cystadenocarcinoma in The Cancer Genome Atlas (TCGA-OV) were used as training dataset. Two validation datasets comprised patients in a Chinese local database and a dataset from the Gene Expression Omnibus (GEO). ATG genes significantly (P < 0.1) associated with overall survival (OS) were selected and aggregated into an ATG scoring scale, of which the abilities to predict OS and recurrence-free survival (RFS) were examined.

RESULTS:

43 autophagy-related genes were selected to develop the ATG score. In TCGA-OV, patients with lower ATG scores had better OS [hazard ratio, 0.41; 95% confidence interval (CI), 0.26-0.65; P < 0.001) and RFS (hazard ratio, 0.47; 95% CI, 0.27-0.82; P = 0.007). After complete or partial remission to primary therapy, the rate of recurrence was 47.2% in the low-score group and 68.3% in the high-score group (odds ratio, 0.42; 95% CI, 0.18-0.92; P = 0.03). Such findings were verified in the two validation datasets.

CONCLUSION:

We established a novel scoring system based on pivotal ATG genes, which accurately predicts the outcomes of advanced ovarian cancer patients after chemotherapy.

IMPACT:

The present ATG scoring system may provide a novel perspective and a promising tool for the development of personalized therapy in the future.

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