4.8 Article

Circulating exosomal mRNA signatures for the early diagnosis of clear cell renal cell carcinoma

期刊

BMC MEDICINE
卷 20, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s12916-022-02467-1

关键词

Clear cell renal cell carcinoma; Exosome; mRNA; Signature; Diagnosis

资金

  1. National Natural Science Foundation of China (NSFC) [81902616]
  2. Shuguang Program of Shanghai Education Development Foundation
  3. Shanghai Municipal Education Commission [16SG33]
  4. Science and technology support project in the field of biomedicine of Shanghai science and technology action plan [19441909200]

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This study identified novel potential biomarkers for clear cell renal cell carcinoma (ccRCC) based on exosomal mRNA profiling. Two emRNA-based signatures were developed for the early detection of ccRCC and differential diagnosis of uncertain renal masses. These signatures showed high accuracy in distinguishing ccRCCs from healthy controls and benign renal masses, indicating their potential as promising and noninvasive biomarkers for ccRCC detection.
Background There are no proven tumor biomarkers for the early diagnosis of clear cell renal cell carcinoma (ccRCC) thus far. This study aimed to identify novel biomarkers of ccRCC based on exosomal mRNA (emRNA) profiling and develop emRNA-based signatures for the early detection of ccRCC. Methods Four hundred eighty-eight participants, including 226 localized ccRCCs, 73 patients with benign renal masses, and 189 healthy controls, were recruited. Circulating emRNA sequencing was performed in 12 ccRCCs and 22 healthy controls in the discovery phase. The candidate emRNAs were evaluated with 108 ccRCCs and 70 healthy controls in the test and training phases. The emRNA-based signatures were developed by logistic regression analysis and validated with additional cohorts of 106 ccRCCs, 97 healthy controls, and 73 benign individuals. Results Five emRNAs, CUL9, KMT2D, PBRM1, PREX2, and SETD2, were identified as novel potential biomarkers of ccRCC. We further developed an early diagnostic signature that comprised KMT2D and PREX2 and a differential diagnostic signature that comprised CUL9, KMT2D, and PREX2 for RCC detection. The early diagnostic signature displayed high accuracy in distinguishing ccRCCs from healthy controls, with areas under the receiver operating characteristic curve (AUCs) of 0.836 and 0.830 in the training and validation cohorts, respectively. The differential diagnostic signature also showed great performance in distinguishing ccRCCs from benign renal masses (AUC = 0.816), including solid masses (AUC = 0.810) and cystic masses (AUC = 0.832). Conclusions We established and validated novel emRNA-based signatures for the early detection of ccRCC and differential diagnosis of uncertain renal masses. These signatures could be promising and noninvasive biomarkers for ccRCC detection and thus improve the prognosis of ccRCC patients.

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