biostudies-literatureUnknown15(1)Huang KBNational Key Research and Development Program of ChinaIntegrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-clNature communications6215https://www.ebi.ac.uk/biostudies/studies/S-EPMC11266571biostudies-literatureA multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma.PMC11266571Li XSZhao HWCao JZLiu RYCao MZhang JLi CXLiao BOuyang KXu YZZhou FJZhong WDDong BJXiong SWXie DXue WHan GPWu JTTang QChen WCai MYHuang KBGui CPHuang YRPan YHHsieh JTJiang FNQu GMYu YFJiang ZYLuo JHGuo JPZhang XKLiu ZPLi PXWei JHCao YHan HChen YHChen WFFeng ZHfalseA multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma.Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-cl2024-01-01T00:00:00Z2024 Jul2026-06-01T10:01:02.476Z2025-04-19T13:11:24.304ZS-EPMC112665713904366410.1038/s41467-024-50369-y