Starting with the discovery that genetic information is stored in the DNA, transcribed into RNA, and translated into proteins in the 1960s (central dogma of molecular biology), progressive innovations in molecular modalities has had a remarkable impact on cancer diagnostics and therapeutics [1]. RNA sequencing (RNA-seq), developed in recent years and focuses on analyzing differential gene expression, has become a key tool in identifying the differences between cells and their respective functions, aiding in the recognition of the functional elements disrupted during disease development. The term RNA-seq was traditionally applied to detecting gene expression regardless of the methodology used; however, the expansive application of RNA-seq has improved our understanding of the RNA as an imperial part of the central dogma and not merely a middle tool between DNA and protein. Hence, the term transcriptome is used collectively to define all the RNA transcripts, coding (mRNA) and noncoding (rRNA, tRNA, lncRNA, pri-miRNA) RNAs, their quantity, and interactions [[2], [3], [4]]. Similarly, cancer RNA-seq provides information about genetic dynamics in these malignant cells, thus providing more real-time information in terms of alternative gene splicing, posttranscriptional modifications, gene fusions, mutations, and expression profiles [5].

Clinically, RNA-seq has the potential of providing diagnostic, prognostic and therapy predictive insights in GU malignancies. For instance, RNA seq has facilitated the identification of TFE3 and TFEB rearranged renal cell carcinomas, providing a more sensitive alternative to fluorescence in situ hybridization (FISH) [6]. Similarly, RNA-seq has been instrumental to the luminal and basal classification of urothelial carcinoma, which had shown distinct clinical behavior and response to therapy [7]. Multiple RNA-seq methodologies were discovered and utilized in clinical research and diagnostics. For instance, poly(A)-enrichment RNA-Seq is a technology widely used for analyzing gene expression in tumors, however, it excludes the nonpolyadenylated transcripts, such as certain noncoding RNAs relevant in cancer. rRNA depletion RNA-Seq is another methodology used in RNA-seq, which provides a broader view of the transcriptome, capturing long noncoding RNAs and fusion transcripts critical in oncology, while the total RNA-Seq offers a wider, unbiased approach, making it valuable for detecting rare or aberrant transcripts.

Furthermore, long-read RNA-Seq (PacBio, Oxford Nanopore) enables full-length transcript characterization, enhancing fusion gene detection, though it has higher error rates. Meanwhile, bulk RNA-Seq remains the standard in clinical research for differential gene expression analysis but lacks single-cell resolution. Therefore, the choice of RNA-Seq method depends on clinical application, sample quality, and the need for high-resolution transcriptomic data to improve diagnostics and targeted therapies [[8], [9], [10]]. Although the detailed discussion of the different methodologies is beyond the scope of this review, they share the same basic outlines as RNA-seq: extracting the RNA, followed by RNA fragmentation, reverse transcription into complementary DNA (cDNA), and RNA sequencing (Fig. 1) [11].

In this review, we provide the current application of RNA-seq in the realm of common genitourinary malignancies and briefly discuss the future direction, irrespective of the RNA-seq methodology used.