Expression signatures of exosomal long non-coding RNAs in urine serve as novel non-invasive biomarkers for diagnosis and recurrence prediction of bladder cancer

1Bladder cancer (BC) is the most common malignancy of the urinary tract worldwide. About 75% of patients are classified as non-muscle-invasive BC (NMIBC), which features a high recurrence rate. Moreover, roughly half of the muscle invasive BC (MIBC) patients will progress to metastasis and die within 3 years. The poor prognosis of BC is partially due to lack of an effective means for early diagnosis. At present, the diagnosis of BC mainly relies on cystoscopy. However, the invasiveness of such procedure limit its use in mass cancer screening. Urine cytology has been proved to be ineffective as a tool to detect low-grade malignancy. Therefore, discovery of effective biomarkers for detection and recurrence prediction of BC can play pivotal roles in improving the prognosis of BC patients.

2Exosomes are small vesicles with a diameter of approximately 30–150 nm. They are distributed in nearly all body fluids, including blood and urine. Exosomes can act as vehicles in cell-to-cell communication by transferring oncogenic molecules and play significant roles in tumorigenesis, progression and metastasis. These functional contents are not stochastically packed into exosomes, which may rely on signature motifs, leading to the variation of exosomal contents under different pathological conditions or in different original cell types. Studies have shown that BC cells can secrete exosomes into the urine and lncRNAs have been found to be stably present in exosomes. Therefore, analyzing the expression profiles of urinary exosome (UE)-derived lncRNAs would provide valuable clues for diagnosis of BC. In this study, we systematically analyzed the expression profiles of UE-derived lncRNAs in BC patients and established a three-lncRNA panel for BC detection. Finally, we the explored the prognostic value of the selected exosomal lncRNAs.

3Transmission electron microscopy (TEM) showed UEs have a diameter of 60–150 nm with a cup-shaped membrane (Fig. 1a). Western blotting of UEs demonstrated the presence of CD9 and TSG101, which are exosome markers (Fig. 1b). Nanoparticle tracking analysis (NTA) found that particles ranging from 20 nm to 200 nm in diameter accounted for 98.1% (Fig. 1c). The flow cytometry showed that the positive rate of CD63 and CD81 specific antibodies on the exosome surface was 90.9% and 93.6%, respectively (Fig. 1d). Collectively, these data indicated that exosomes existed in urine, which laid a foundation for further study of exosomal biomarkers. The methods are explained in Additional file 1.

4Eight lncRNAs (MALAT1, PCAT-1, SPRY4-IT1, UCA1, MEG3, H19, UBC1 and TUG1), which have been reported to play functional roles in tumorigenesis, were selected as candidate molecules. Then, in the training set, the expressions of eight lncRNAs in 104 BC patients and 104 healthy controls were assessed by qRT-PCR. MALAT1, PCAT-1 and SPRY4-IT1 were significantly up-regulated in BC patients compared with the healthy controls (p < 0.001) (Additional file 3: Table S2) (Additional file 4: Figure S1 a-c).

5To evaluate the performance of the identified lncRNAs for BC detection, we performed ROC curves in training set. The diagnostic accuracy of MALAT1, PCAT-1 and SPRY4-IT1, measured by AUC, was 0.844 (95% CI = 0.787 to 0.890, sensitivity = 72.1% and specificity = 84.6%), 0.832 (95% CI = 0.774 to 0.880, sensitivity = 72.1% and specificity = 81.7%) and 0.760 (95% CI = 0.696 to 0.817, sensitivity = 66.3% and specificity = 76.9%), respectively (Additional file 4: Figure S1 d-f). Subsequently, these lncRNAs were further verified in the validation set (80 BC patients and 80 healthy controls). The dysregulated expression trend was consistent between the two set (Additional file 3: Table S2). The corresponding AUCs of the three lncRNAs were 0.785 (95% CI =0.714 to 0.846, sensitivity =78.7% and specificity =67.5%), 0.810 (95% CI =0.741 to 0.868, sensitivity = 71.2% and specificity = 80.0%) and 0.799 (95% CI =0.728 to 0.858, sensitivity =87.5% and specificity =65%), respectively (Additional file 5: Figure S2).

6Next, two experiments were performed to verify the stability of UE-derived lncRNAs (MALAT1, PCAT-1 and SPRY4-IT1), considering that this is an essential prerequisite for biomarkers. Firstly, urine samples and exosome isolated nucleic acids were incubated with RNase A for 0, 30, 60 and 90 min. Strikingly, RNase A had no effect on the level of exosomal lncRNAs in the urine group (Additional file 6: Figure S3 a-c). However, the exosome isolated nucleic acids group was completely degraded by the treatment of RNase A within 30 min (Additional file 6: Figure S3 d-f). Secondly, urine samples were stored at − 80 °C for 1, 2 and 3 months. Results indicated that this treatment had no effect on the expression levels of MALAT1, PCAT-1 and SPRY4IT1 in UEs (Additional file 6: Figure S3 g-i). Collectively, our data indicated that the exosomal membrane can protect lncRNAs from being degraded, and their excellent stability makes exosomal lncRNAs ideal biomarkers for tumor diagnosis.

7Considering that combinations of tumor markers can improve the diagnostic accuracy, multivariate logistic regression model was performed in the training set to establish the selected exosomal lncRNA panel. The predictive probability of being diagnosed with BC was calculated using the equation as follows: Logit (P) = 0.6577–0.0695 × MALAT1–0.0686 × PCAT-1 – 0.0015 × SPRY4-IT1. The AUC of the panel was 0.854 (95% CI = 0.799–0.899, sensitivity = 70.2% and specificity =85.6%, Fig. 2a).

8To further verify the diagnostic performance of the panel, ROC analysis was performed in the validation set. Results showed that the AUC of the panel was 0.813 (95% CI = 0.744–0.870, sensitivity =62.5% and specificity = 85.0%) (Fig. 2b). Currently, urine cytology is widely used in clinical practice, but it has relatively poor sensitivity. Therefore, we compared the diagnostic performance between the panel and urine cytology. As expected, the AUC of urine cytology for BC detection was 0.619 (95% CI =0.539–0.694, sensitivity = 25% and specificity = 98.7%) (Fig. 2c), which was significantly lower than that of the panel.

9Next, we analyzed the correlation between the three UE-derived lncRNAs and clinicopathological characteristics of the BC patients. Results demonstrated overexpression of UE-derived PCAT-1 and SPRY4-IT1 were correlated with advanced TNM stage (all at p < 0.05). However, we did not find any significant association between the three lncRNAs and age, sex, tumor grade or positive lymph node metastasis (all at p > 0.05) (Additional file 7: Table S3).

10To explore prognostic value of the three lncRNAs, BC patients were followed-up in the validation set. In the NMIBC group, results showed that patients with up-regulated MALAT1 and PCAT-1 had a significantly lower RFS (p = 0.002 and p < 0.001, respectively, Fig. 3a-b) compared with their corresponding counterparts. Afterwards, univariate Cox proportional hazards regression showed that there was a significant correlation between RFS of NMIBC and PCAT-1 (p = 0.001), MALAT1 (p = 0.005) or tumor stage (p = 0.001). Multivariate analysis revealed that PCAT-1 (p = 0.018) and tumor stage (p = 0.036) were independent prognostic factors for the RFS of NMIBC (Additional file 8: Table S4). However, none of the three lncRNAs were correlated with the recurrence of MIBC patients (all at p > 0.05, Additional file 9: Table S5).

11Researchers have revealed UE-derived HOTAIR could serve as a biomarker for BC. However, their study are only conducted in a very small amount of urine samples, which are not verified in a larger population. Moreover, considering that the progression of BC is a complex pathophysiological process, thus no single lncRNA can stand alone as a biomarker, but instead panel consisting of several lncRNAs will be necessary for BC diagnosis.

12We established a three-lncRNA panel for BC diagnosis through analyzing UE-derived lncRNAs, and identified that PCAT-1 could act as an independent risk factor for RFS of NMIBC. Further multi-center studies are necessary to verify the diagnostic efficiency of such panel before it could be adopted into clinical practice.