J Cancer 2020; 11(5):997-1007. doi:10.7150/jca.38274 This issue

Research Paper

Development and validation of a robust multigene signature as an aid to predict early relapse in stage I-III clear cell and papillary renal cell cancer

Da-Long Cao1,2,# ✉, Wei-Xing Dai2,#, Yong-Qiang Huang1,2,#, Lei-Jun Yu1,2,#, Jun-Long Wu1,2, Guo-Hai Shi1,2, Hai-Liang Zhang1,2, Yao Zhu1,2, Bo Dai1,2, Ding-Wei Ye1,2✉

1. Department of Urology, Fudan University Shanghai Cancer Center, Shanghai 200032, China;
2. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China;
#The authors contributed equally.

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Citation:
Cao DL, Dai WX, Huang YQ, Yu LJ, Wu JL, Shi GH, Zhang HL, Zhu Y, Dai B, Ye DW. Development and validation of a robust multigene signature as an aid to predict early relapse in stage I-III clear cell and papillary renal cell cancer. J Cancer 2020; 11(5):997-1007. doi:10.7150/jca.38274. Available from https://www.jcancer.org/v11p0997.htm

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Abstract

Background and objectives: Multi-gene signature can be used as prognostic indicator in many types of cancer, but the association with early-relapse in patients with stage I-III clear cell and papillary renal cell cancer (RCC) is unknown. We aim to establish a mRNAs signature for improving prediction of early-relapse in patients with stage I-III clear cell and papillary RCC.

Methods: The data of 610 patients with stage I-III RCC from The Cancer Genome Atlas (TCGA) and 270 patients from Fudan University Shanghai Cancer Center (FUSCC) were extracted. Propensity score matching analysis, linear models for microarray data VOOM method, least absolute shrinkage and selection operation Cox regression modeling analysis was conducted in turn for selecting multi-mRNA signature. Survival differences were assessed by Kaplan-Meier estimate and compared using log-rank test. Multivariable Cox regression and time-dependent receiver operating characteristic curves were used to evaluate the association of mRNAs signature with relapse-free survival (RFS).

Results: Seventeen mRNAs were identified to constitute the early-relapse signature. Among patients with stage I-III RCC, those with high-risk score calculated from 17 mRNAs signature showed shorter RFS than those with low-risk score, both in TCGA discovery and internal validation sets, and in FUSCC discovery and internal validation sets (all p < 0.05). In multivariable Cox regression analysis, the 17 mRNAs signature remained an independent prognostic factor both in TCGA discovery (HR 2.43, 95%CI 1.98-2.96) and internal validation sets (HR 1.66, 95%CI 1.19-2.30), and FUSCC discovery (HR 1.28, 95%CI 1.13-1.43) and internal validation sets (HR 1.65, 95%CI 1.11-2.48). Additionally, the 17 mRNAs signature achieved a higher accuracy for RFS estimation beyond clinical indicator.

Conclusion: The 17 mRNAs signature could classify stage I-III RCC patients into low- or high-risk of early-relapse, and will help to guide interventions to optimize survival outcomes.

Keywords: Renal cell carcinoma, Early relapse, Prognosis, Biomarker, mRNA signature