Nowadays, a growing number of researches have indicated the important roles of LncRNA in bladder cancer, as LncRNA affects many physiological processes of bladder cancer, such as proliferation, migration, invasion, apoptosis and so on[20, 26]. This research aims to find new markers that can be used as noninvasive diagnosis of bladder cancer, leading to reduced compliance with cystoscopy, less patient distress, and lower financial burden for patients. LncRNA can be detected in blood, urine and tissues[27]. Many kinds of LncRNA are found to be different between healthy people and patients with bladder cancer. It can be used as a molecular marker for the early detection and treatment of bladder cancer[28, 29]. However, in order to apply LncRNA to clinical diagnosis, we need to establish standards, including sampling methods, sample processing, detection and analysis methods, and need to determine an optimal cut-off parameter.
To analyze the efficacy of LncRNA in the diagnosis of bladder cancer, 18 researches were included in this research. Our work found that the sensitivity and specificity of LncRNA were 0.72(0.70–0.73) and 0.76(0.75–0.78) respectively, and AUC was 0.82(0.78–0.85). The positive likelihood ratio of LncRNA in the diagnosis of bladder cancer was 3.09(2.66–3.58), the negative likelihood ratio was 0.37(0.33–0.42), and the combined diagnostic odds ratio was 9.43(7.30–12.20). The above data fully prove that LncRNA detection has a high application value in the diagnosis of bladder cancer. It can well replace the urine cytology diagnosis and become a new method of non-invasive diagnosis of bladder cancer. The researches data of Du et al[30] can also confirm this. Combined with its advantages of simple, fast and low cost, it is of great significance for the screening of early bladder cancer. At the same time, it can also be used as a monitoring means for patients with bladder cancer after the operation, which can relieve the pain of repeated cystoscopy and reduce the huge economic burden. Besides, it will improve the compliance and survival rate of patients along with improving the quality of life after operation.
We explored the impact of specimen from different sources on the diagnostic effect and found that detection of LncRNA expression in urine specimen has a better diagnostic effect than detection of LncRNA expression in blood and tissue. It may be due to the fact that bladder cancer cells are more likely to shed cells into the urine which further release LncRNA in it. The latest expert opinion also believes that urine markers for the diagnosis of bladder cancer are of great significance[28]. Therefore, in order to use LncRNA for clinical diagnosis in the future, we highly recommend to use urine as a standard sampling method.
At the same time, we are also very interested in whether there are differences in researches in different regions. Therefore, we conducted a subgroup analysis of China researches and researches from other countries. The results show that the diagnostic effect of LncRNA in researches from other countries is slightly higher than that in Chinese researches, but we still think that Chinese researches is closer to the real situation, because the sample size of Chinese researches is larger (1118 vs 469) However, the heterogeneity among all the researches in China is still very high. We think that the main source of heterogeneity is that we analyzed different LncRNAs together. In addition, all the researches did not clearly specify the cut-off value, which led to a high degree of heterogeneity.
The selection of different control types also has a certain impact on the final results. Our researches results show that the diagnosis effect of patients with benign diseases and healthy people as the control group is the best, and the use of benign diseases and healthy people as the control group is more in line with the clinical application scene. Therefore, in future researches, we suggest that researchers should use patients with benign diseases and healthy people as the control group.
Finally, some LncRNA markers have been studied by multiple authors, and we have analyzed these LncRNA individually as well. We analyzed a total of four LncRNA, UCA1, H19, HOTAIR, and MALAT1. Among them, UCA1 was the most reported, and 6 researchers reported it. Increasing evidence suggests that UCA1 has been highly expressed in bladder cancer cells [31, 32]. Moreover, UCA1 has the specificity of expression in bladder cancer tissues. Its expression in other urinary tumors is very low, while it does not express in corresponding para cancerous tissues, normal bladder tissues and normal kidney tissues[25, 33]. Therefore, it is very suitable as a diagnostic marker of bladder cancer. Our analysis also shows that UCA1 has a high diagnostic effect (Table 2), it has the highest sensitivity and specificity among the four markers we analyzed alone. we also analyzed H19, HOTAIR and MALAT1 separately, which showed good diagnostic performance. However, due to the limitation of sample size, more studies are needed to support our conclusion. In addition to single LncRNA, some LncRNA combinations can significantly improve the diagnostic performance. For example, Duan et al[34] found that the diagnostic performance of LncRNA combinations (MEG3, SNHG16 and MALAT1) for TA, T1 and T2-T4 was significantly higher than that of urine cytology. Therefore, based on the investigations of single LncRNA, it will be a more advanced research direction to explore the LncRNA combination that can be used for the diagnosis of bladder cancer.
Although our results are very encouraging, we should also consider several limitations of this study, such as since this meta-analysis revolved around the Asian countries notably China, the results discussed would not be an ideal reference for the other areas of the world. Besides, there was high heterogeneity between the included researches. We could not perform further analysis of the heterogeneity of the researches deeply. Furthermore, the cut-off point of the included references was not included due to the inconsistency of the cut-off point in each research. All included papers determined different types of LncRNA, thus contributing to the heterogeneity in the results analyzed. As some of the included studies did not provide sufficient data, we estimated the best sensitivity and specificity under the ROC curve using Engauge Digitizer 11 software. This could affect the reliability of finalized results.