Bladder cancer is the most common malignant tumour of the urinary system that is characterised by significant intra-tumoural heterogeneity. While large-scale sequencing projects have provided a preliminary understanding of tumour heterogeneity, these findings are based on the average signals obtained from the pooled populations of diverse cells. Recent advances in single-cell sequencing (SCS) technologies have been critical in this regard, opening up new ways of understanding the nuanced tumour biology by identifying distinct cellular subpopulations, dissecting the tumour microenvironment, and characterizing cellular genomic mutations. By integrating these novel insights, SCS technologies are expected to make powerful and meaningful changes to the current diagnosis and treatment of bladder cancer through the identification and usage of novel biomarkers as well as targeted therapeutics. SCS can discriminate complex heterogeneity in a large population of tumour cells and determine the key molecular properties that influence clinical outcomes. Here, we review the advances in single-cell technologies and discuss their applications in cancer research and clinical practice, with a specific focus on bladder cancer.

In this study we compared the amplitude, latency, and spatial distribution of the mismatch negativity (MMN), elicited by tones deviating in either frequency, intensity, stimulus-onset asynchrony (SOA) or location, and assessed inter- and intra-subject variability. Cross-dimensional comparisons were facilitated by adjusting the magnitude of deviance individually, so that the detection rates were similar, both across dimensions (within subject) and across subjects (within dimension). Despite similar detection rates, the MMN elicited by frequency deviance was larger, and the MMN elicited by SOA deviance was earlier than the other types of MMN. The reliability of frequency-related MMN was better than that of the other types of MMN. The results highlight the problems of comparing MMN across dimensions, especially in clinical populations.