Non‐invasive diagnosis and surveillance of bladder cancer with driver and passenger DNA methylation in a prospective cohort study
Authors: Xiao Yu , Ju Lingao , Qian Kaiyu , Jin Wan , Wang Gang , Zhao Yan , Jiang Wei , Liu Nan , Wu Kai , Peng Minsheng , Cao Rui , Li Sheng , Shi Hongjie , Gong Yan , Zheng Hang , Liu Tongzu , Luo Yongwen , Ma Haoli , Chang Luyuan , Li Gang , Cao Xinyue , Tian Ye , Xu Zilin , Yang Zhonghua , Shan Liuying , Guo Zhongqiang , Yao Dongai , Zhou Xianlong , Chen Xintong , Guo Zicheng , Liu Dongmei , Xu Song , Ji Chundong , Yu Fang , Hong Xin , Luo Jun , Cao Hong , Zhang Yi , Wang Xinghuan 
Published: August 2022

Background

State‐of‐art non‐invasive diagnosis processes for bladder cancer (BLCA) harbour shortcomings such as low sensitivity and specificity, unable to distinguish between high‐ (HG) and low‐grade (LG) tumours, as well as inability to differentiate muscle‐invasive bladder cancer (MIBC) and non‐muscle‐invasive bladder cancer (NMIBC). This study investigates a comprehensive characterization of the entire DNA methylation (DNAm) landscape of BLCA to determine the relevant biomarkers for the non‐invasive diagnosis of BLCA.

Methods

A total of 304 samples from 224 donors were enrolled in this multi‐centre, prospective cohort study. BLCA‐specific DNAm signature discovery was carried out with genome‐wide bisulfite sequencing in 32 tumour tissues and 12 normal urine samples. A targeted sequencing assay for BLCA‐specific DNAm signatures was developed to categorize tumour tissue against normal urine, or MIBC against NMIBC. Independent validation was performed with targeted sequencing of 259 urine samples in a double‐blinded manner to determine the clinical diagnosis and prognosis value of DNAm‐based classification models. Functions of genomic region harbouring BLCA‐specific DNAm signature were validated with biological assays. Concordances of pathology to urine tumour DNA (circulating tumour DNA [ctDNA]) methylation, genomic mutations or other state‐of‐the‐art diagnosis methods were measured.

Results

Genome‐wide DNAm profile could accurately classify LG tumour from HG tumour (LG NMIBC vs. HG NMIBC: p = .038; LG NMIBC vs. HG MIBC, p = .00032; HG NMIBC vs. HG MIBC: p = .82; Student's t‐test). Overall, the DNAm profile distinguishes MIBC from NMIBC and normal urine. Targeted‐sequencing‐based DNAm signature classifiers accurately classify LG NMIBC tissues from HG MIBC and could detect tumours in urine at a limit of detection of less than .5%. In tumour tissues, DNAm accurately classifies pathology, thus outperforming genomic mutation or RNA expression profiles. In the independent validation cohort, pre‐surgery urine ctDNA methylation outperforms fluorescence in situ hybridization (FISH) assay to detect HG BLCA (n = 54) with 100% sensitivity (95% CI: 82.5%–100%) and LG BLCA (n = 26) with 62% sensitivity (95% CI: 51.3%–72.7%), both at 100% specificity (non‐BLCA: n = 72; 95% CI: 84.1%–100%). Pre‐surgery urine ctDNA methylation signature correlates with pathology and predicts recurrence and metastasis. Post‐surgery urine ctDNA methylation (n = 61) accurately predicts recurrence‐free survival within 180 days, with 100% accuracy.

Conclusion

With the discovery of BLCA‐specific DNAm signatures, targeted sequencing of ctDNA methylation outperforms FISH and DNA mutation to detect tumours, predict recurrence and make prognoses.