Development of a prognostic index for predicting disease progression in non-muscle invasive bladder cancer

Although recent advances in high-throughput technology and data-driven approach have provided many insights into non-muscle invasive bladder cancer (NMIBC), previous studies are still limited in their ability to predict the clinical behavior of NMIBC including response to intravesical therapy. We aim to develop a prognostic index (PI) consisting of a small gene group that predicts the NMIBC progression and response to intravesical bacillus calmette-guérin (BCG) therapy. We analyzed progression-associated genes using Cox regression analysis and validated their predictive values using a fully connected neural network (FNN) algorithm. By applying a pathway enrichment analysis to these genes, a PI system consisting of small core genes for NMIBC progression was developed. Gene expression profiling in NMIBC patients identified a prognostic gene set for predicting NMIBC progression in multiple patient cohorts. Pathway enrichment analysis revealed a 23-gene signature. We incorporated these genes into the PI system, which was a significant prognostic indicator of NMIBC progression. The PI system was shown to be an independent risk factor by a multivariate analysis and subset stratification according to stage and grade. The subset analysis also revealed that the PI system could identify patients who would benefit from BCG immunotherapy. The 23-gene-based PI represents a promising diagnostic tool for identifying high-risk NMIBC patients who would display different clinical behaviors and response to BCG immunotherapy. Overall design: We generated an RNA-seq data set of 49 samples with non-muscle-invasive bladder cancer. Total RNA was isolated from tissue using TRI-reagent based method. Total RNA (500 ng) was processed for preparing whole transcriptome sequencing library. Enrichment of whole transcriptome RNA by depleting ribosomal RNA (rRNA) was processed for preparing whole transcriptome sequencing library using MGIEasy RNA Directional Library Prep Kit (MGI) according to manufacturer's instruction. After the rRNA is depleted, the remaining RNA is fragmented into small pieces using divalent cations under elevated temperature. The cleaved RNA fragments are copied into first strand cDNA using reverse transcriptase and random primers. Strand specificity is achieved in the RT directional buffer, followed by second strand cDNA synthesis. These cDNA fragments then have the addition of a single 'A' base and subsequent ligation of the adapter. The products are then purified and enriched with PCR to create the final cDNA library.The double stranded library is quantified using QauntiFluor ONE dsDNA System (Promega) and equal 330 ng in a total volume of 60 ml or less. The library is cyclized at 37 °C for 60 min, and then digested at 37 °C for 30 min, followed by cleanup of circularization product. To make DNA nanoball (DNB), the library is incubated at 30 °C for 25 min using DNB enzyme. Finally, Library was quantified by QauntiFluor ssDNA System (Promega). Sequencing of the prepared DNB was conducted on the MGIseq system (MGI) with 150 bp paired-end reads.