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

Abstract

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.

GHITM regulates malignant phenotype and sensitivity to PD‐1 blockade of renal cancer cells via Notch signalling

“…For better prognosis prediction, a nomogram based on GHITM expression for KIRC was constructed to predict the 1‐, 3‐ and 5‐year survival rates of patients, and there was a good agreement between prediction and observation according to corresponding calibration curves (Figure 2C,D). A 5‐year survival rate of early RCC is over 90%, but no efficient biomarker was found for early diagnosis of KIRC over the past several decades 32 . GHITM diagnostic value in KIRC was evaluated using GEO and TCGA datasets.…”

Role of exosomes in non-small cell lung cancer and EGFR-mutated lung cancer

“…In this context, the identification of subclasses of extracellular vesicles derived from cancer cells and microenvironmental components associated with well-defined pathological processes would allow them to serve as complementary biomarkers of circulating cfDNA and circulating tumor cells. In recent years, several studies have demonstrated the value of exosomes as cancer biomarkers, allowing longitudinal monitoring of tumor heterogeneity and early identification of cancer subtypes ( 154 , 155 ), as well as monitoring microenvironmental subversion ( 156 ), tumor progression and prognostic decisions ( 157 ), and response to therapy to tailor therapeutic interventions ( 158 , 159 ). Further developments in this field will bring us closer to the most important goal of providing personalized cancer care.…”

Exosomal cargos-mediated metabolic reprogramming in tumor microenvironment

“…Regarding functional exosomal mRNAs, an early study reported that exosomal mRNAs can complete translation in receptor cells [150]. Recently, exosomal mRNAs CUL9, KMT2D, PBRM1, PREX2 and SETD2 were found to be possible novel potential biomarkers for clear cell renal cell carcinoma (ccRCC) [151]. Studies on exosomal ncRNAs have focused on miRNAs, lncRNAs & circR-NAs.…”