Non-muscle-invasive bladder cancer (NMIBC) is a heterogeneous disease with widely different outcomes. We performed a comprehensive transcriptional analysis of 460 early-stage urothelial carcinomas and showed that NMIBC can be subgrouped into three major classes with basal- and luminal-like characteristics and different clinical outcomes. Large differences in biological processes such as the cell cycle, epithelial-mesenchymal transition, and differentiation were observed. Analysis of transcript variants revealed frequent mutations in genes encoding proteins involved in chromatin organization and cytoskeletal functions. Furthermore, mutations in well-known cancer driver genes (e.g., TP53 and ERBB2) were primarily found in high-risk tumors, together with APOBEC-related mutational signatures. The identification of subclasses in NMIBC may offer better prognostication and treatment selection based on subclass assignment.
PURPOSE Novel sensitive methods for early detection of relapse and for monitoring therapeutic efficacy may have a huge impact on risk stratification, treatment, and ultimately outcome for patients with bladder cancer. We addressed the prognostic and predictive impact of ultra-deep sequencing of cell-free DNA in patients before and after cystectomy and during chemotherapy. PATIENTS AND METHODS We included 68 patients with localized advanced bladder cancer. Patient-specific somatic mutations, identified by whole-exome sequencing, were used to assess circulating tumor DNA (ctDNA) by ultra-deep sequencing (median, 105,000×) of plasma DNA. Plasma samples (n = 656) were procured at diagnosis, during chemotherapy, before cystectomy, and during surveillance. Expression profiling was performed for tumor subtype and immune signature analyses. RESULTS Presence of ctDNA was highly prognostic at diagnosis before chemotherapy (hazard ratio, 29.1; P = .001). After cystectomy, ctDNA analysis correctly identified all patients with metastatic relapse during disease monitoring (100% sensitivity, 98% specificity). A median lead time over radiographic imaging of 96 days was observed. In addition, for high-risk patients (ctDNA positive before or during treatment), the dynamics of ctDNA during chemotherapy was associated with disease recurrence ( P = .023), whereas pathologic downstaging was not. Analysis of tumor-centric biomarkers showed that mutational processes (signature 5) were associated with pathologic downstaging ( P = .024); however, no significant correlation for tumor subtypes, DNA damage response mutations, and other biomarkers was observed. Our results suggest that ctDNA analysis is better associated with treatment efficacy compared with other available methods. CONCLUSION ctDNA assessment for early risk stratification, therapy monitoring, and early relapse detection in bladder cancer is feasible and provides a basis for clinical studies that evaluate early therapeutic interventions.
Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for clinical research. However, nucleic acids extracted from FFPE tissues are fragmented and chemically modified making them challenging to use in molecular studies. We analysed 23 fresh-frozen (FF), 35 FFPE and 38 paired FF/FFPE specimens, representing six different human tissue types (bladder, prostate and colon carcinoma; liver and colon normal tissue; reactive tonsil) in order to examine the potential use of FFPE samples in next-generation sequencing (NGS) based retrospective and prospective clinical studies. Two methods for DNA and three methods for RNA extraction from FFPE tissues were compared and were found to affect nucleic acid quantity and quality. DNA and RNA from selected FFPE and paired FF/FFPE specimens were used for exome and transcriptome analysis. Preparations of DNA Exome-Seq libraries was more challenging (29.5% success) than that of RNA-Seq libraries, presumably because of modifications to FFPE tissue-derived DNA. Libraries could still be prepared from RNA isolated from two-decade old FFPE tissues. Data were analysed using the CLC Bio Genomics Workbench and revealed systematic differences between FF and FFPE tissue-derived nucleic acid libraries. In spite of this, pairwise analysis of DNA Exome-Seq data showed concordance for 70–80% of variants in FF and FFPE samples stored for fewer than three years. RNA-Seq data showed high correlation of expression profiles in FF/FFPE pairs (Pearson Correlations of 0.90 +/- 0.05), irrespective of storage time (up to 244 months) and tissue type. A common set of 1,494 genes was identified with expression profiles that were significantly different between paired FF and FFPE samples irrespective of tissue type. Our results are promising and suggest that NGS can be used to study FFPE specimens in both prospective and retrospective archive-based studies in which FF specimens are not available.
The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we perform an integrative multi-omics analysis of patients diagnosed with NMIBC (n = 834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations are significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration is associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirms the higher infiltration of class 2b tumors and demonstrates an association between higher immune cell infiltration and lower recurrence rates. Finally, the independent prognostic value of the transcriptomic classes is documented in 1228 validation samples using a single sample classification tool. The classifier provides a framework for biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.
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