Research Paper Volume 11, Issue 22 pp 10183—10202

Development and validation of a metastasis-associated prognostic signature based on single-cell RNA-seq in clear cell renal cell carcinoma

Chuanjie Zhang 1, *, , Hongchao He 1, *, , Xin Hu 2, *, , Ao Liu 1, , Da Huang 1, , Yang Xu 1, , Lu Chen 1, , Danfeng Xu 1, ,

  • 1 Department of Urology, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
  • 2 First Clinical Medical College of Nanjing Medical University, Nanjing, China
* Equal contribution

received: August 15, 2019 ; accepted: October 29, 2019 ; published: November 20, 2019 ;

https://doi.org/10.18632/aging.102434
How to Cite

Copyright © 2019 Zhang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Single-cell RNA sequencing (scRNA-seq) was recently adopted for deciphering intratumoral heterogeneity across cell sub-populations, including clear cell renal cell carcinoma (ccRCC). Here, we characterized the single-cell expression profiling of 121 cell samples and found 44 metastasis-associated marker genes. Accordingly, we trained and validated 17 pivotal metastasis-associated genes (MAGs) in 626 patients incorporating internal and external cohorts to evaluate the model for predicting overall survival (OS) and progression-free survival (PFS). Correlation analysis revealed that the MAGs correlated significantly with several risk clinical characteristics. Moreover, we conducted Cox regression analysis integrating these independent clinical variables into a MAGs nomogram with superior accuracy in predicting progression events. We further revealed the differential landscape of somatic tumor mutation burden (TMB) between two nomogram-score groups and observed that TMB was also a prognostic biomarker; patients with high MAGs-nomogram scores suffered from a higher TMB, potentially leading to worse prognosis. Last, higher MAGs-nomogram scores correlated with the upregulation of oxidative phosphorylation, the Wnt signaling pathway, and MAPK signaling crosstalk in ccRCC. Overall, we constructed the robust MAGs through scRNA-seq and validated the model in a large patient population, which was valuable for prognostic stratification and providing potential targets against metastatic ccRCC.

Abbreviations

ccRCC: clear cell renal cell carcinoma; scRNA-seq: single-cell RNA sequencing; MAGs: metastasis-associated signature genes; OS: overall survival; PFS: progression-free survival; TMB: tumor mutation burden; PDX-mRCC: patient-derived xenograft of metastatic renal cell carcinoma; PDX-pRCC: patient-derived xenograft of primary renal cell carcinoma; TCGA-KIRC: Kidney renal clear cell carcinoma from the Cancer Genome Atlas; ICGC: International Cancer Genome Consortium; LASSO: Least absolute shrinkage and selection operator; MAF: Mutation Annotation Format; FDR: false discovery rate; GSEA: gene set enrichment analysis; logFC: logarithm of fold change; adjPval: adjustment of P value.