IL17a and IL21 combined with surgical status predict the outcome of ovarian cancer patients

Yu Li Chen, Cheng Yang Chou, Ming Cheng Chang, Han Wei Lin, Ching Ting Huang, Shu Feng Hsieh, Chi An Chen, Wen Fang Cheng

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Aside from tumor cells, ovarian cancer-related ascites contains the immune components. The aim of this study was to evaluate whether a combination of clinical and immunological parameters can predict survival in patients with ovarian cancer. Ascites specimens and medical records from 144 ovarian cancer patients at our hospital were used as the derivation group to select target clinical and immunological factors to generate a risk-scoring system to predict patient survival. Eighty-two cases from another hospital were used as the validation group to evaluate this system. The surgical status and expression levels of interleukin 17a (IL17a) and IL21 in ascites were selected for the risk-scoring system in the derivation group. The areas under the receiver operating characteristic (AUROC) curves of the overall score for disease-free survival (DFS) of the ovarian cancer patients were 0.84 in the derivation group, 0.85 in the validation group, and 0.84 for all the patients. The AUROC curves of the overall score for overall survival (OS) of cases were 0.78 in the derivation group, 0.76 in the validation group, and 0.76 for all the studied patients. Good correlations between overall risk score and survival of the ovarian cancer patients were demonstrated by sub-grouping all participants into four groups (P for trend <0.001 for DFS and OS). Therefore, acombination of clinical and immunological parameters can provide a practical scoring system to predict the survival of patients with ovarian carcinoma. IL17a and IL21 can potentially be used as prognostic and therapeutic biomarkers.

Original languageEnglish
Pages (from-to)703-711
Number of pages9
JournalEndocrine-Related Cancer
Volume22
Issue number5
DOIs
Publication statusPublished - 2015 Oct 1

All Science Journal Classification (ASJC) codes

  • Endocrinology, Diabetes and Metabolism
  • Oncology
  • Endocrinology
  • Cancer Research

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