A prognostic classifier consisting of 17 circulating cytokines is a novel predictor of overall survival for metastatic colorectal cancer patients.

Abstract:

:We aimed to determine the prognostic values of 39 circulating cytokines in Chinese patients with metastatic colorectal cancer (CRC) and to develop a novel cytokine-based prognostic classifier (CBPC) for prognostic prediction. A total of 176 patients were divided into two cohorts based on the date of first-line chemotherapy. The first 99 cases were assigned to the training cohort, and the remaining 77 cases were assigned to the validation cohort. Thirty-nine cytokines were simultaneously analyzed in the patient serum samples using multiplex bead-based Luminex technology. We used support vector machine-based methods and Cox proportional hazards models to develop a CBPC from the training cohort, which we then validated using the second patient cohort. Univariate analysis showed that FGF-2, TGFα, Flt-3L, GM-CSF, INFα2, GRO, IL-10, MCP-3, MDC, sIL-2Rα, IL-2, IL-7, IL-8, MCP-1, MIP-1β, TNFα and VEGF were significant risk factors affecting the overall survival (OS) of both the training cohort and the validation cohort. We developed a CBPC to predict the OS of metastatic CRC patients using these 17 cytokines (sensitivity, 0.835; specificity, 0.800). In the validation cohort, the CBPC was found to have significant power in predicting the OS of metastatic CRC patients. Our study showed that there were significant associations between cytokine expression and prognosis of the patients with metastatic CRC. The CBPC that we developed includes multiple circulating cytokines and may serve as a novel screening tool for identifying metastatic CRC patients with a high risk of short OS. These high-risk individuals may also be suitable for cytokine-targeted therapies.

journal_name

Int J Cancer

authors

Chen ZY,He WZ,Peng LX,Jia WH,Guo RP,Xia LP,Qian CN

doi

10.1002/ijc.29017

subject

Has Abstract

pub_date

2015-02-01 00:00:00

pages

584-92

issue

3

eissn

0020-7136

issn

1097-0215

journal_volume

136

pub_type

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