Sia V. Lindskrog

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.

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.

Overtreatment with cisplatin-based chemotherapy is a major issue in the management of muscle-invasive bladder cancer (MIBC), and currently none of the reported biomarkers for predicting response have been implemented in the clinic. Here we perform a comprehensive multi-omics analysis (genomics, transcriptomics, epigenomics and proteomics) of 300 MIBC patients treated with chemotherapy (neoadjuvant or first-line) to identify molecular changes associated with treatment response. DNA-based associations with response converge on genomic instability driven by a high number of chromosomal alterations, indels, signature 5 mutations and/or BRCA2 mutations. Expression data identifies the basal/squamous gene expression subtype to be associated with poor response. Immune cell infiltration and high PD-1 protein expression are associated with treatment response. Through integration of genomic and transcriptomic data, we demonstrate patient stratification to groups of low and high likelihood of cisplatin-based response. This could pave the way for future patient selection following validation in prospective clinical trials.

PURPOSE: To investigate the use of plasma and urine DNA mutation analysis for predicting neoadjuvant chemotherapy (NAC) response and oncological outcome in patients with muscle-invasive bladder cancer. EXPERIMENTAL DESIGN: Whole-exome sequencing of tumor and germline DNA was performed for 92 patients treated with NAC followed by radical cystectomy (RC). A custom NGS-panel capturing approximately 50 mutations per patient was designed and used to track mutated tumor DNA in plasma and urine. A total of 447 plasma samples, 281 urine supernatants, and 123 urine pellets collected before, during, and after treatment were analyzed. Patients were enrolled from 2013 to 2019, with a median follow-up time of 41.3 months after RC. RESULTS: We identified tumor DNA before NAC in 89% of urine supernatants, 85% of urine pellets, and 43% of plasma samples. Tumor DNA levels were higher in urine supernatants and urine pellets compared with plasma samples (P < 0.001). In plasma, detection of circulating tumor DNA (ctDNA) before NAC was associated with a lower NAC response rate (P < 0.001). Detection of tumor DNA after NAC was associated with lower response rates in plasma, urine supernatant, and urine pellet (P < 0.001, P = 0.03, P = 0.002). Tumor DNA dynamics during NAC was predictive of NAC response and outcome in urine supernatant and plasma (P = 0.006 and P = 0.002). A combined measure from plasma and urine supernatant tumor DNA dynamics stratified patients by outcome (P = 0.003). CONCLUSIONS: Analysis of tumor DNA in plasma and urine samples both separately and combined has a potential to predict treatment response and outcome.