Targeting molecular aberrations in urothelial carcinoma: are we almost there?

Viable tumor volume: Volume of interest within segmented metastatic lesions, a pilot study of proposed computed tomography response criteria for urothelial cancer

OBJECTIVES

To evaluate the ability of new computed tomography (CT) response criteria for solid tumors such as urothelial cancer (VTV; viable tumor volume) to predict overall survival (OS) in patients with metastatic bladder cancer treated with cabozantinib.

MATERIALS AND METHODS

We compared the relative capabilities of VTV, RECIST, MASS (morphology, attenuation, size, and structure), and Choi criteria, as well as volume measurements, to predict OS using serial follow-up contrast-enhanced CT exams in patients with metastatic urothelial carcinoma. Kaplan-Meier curves and 2-tailed log-rank tests compared OS based on early RECIST 1.1 response against each of the other criteria. A Cox proportional hazards model assessed response at follow-up exams as a time-varying covariate for OS.

RESULTS

We assessed 141 lesions in 55CT scans from 17 patients with urothelial metastasis, comparing VTV, RECIST, MASS, and Choi criteria, and volumetric measurements, for response assessment. Median follow-up was 4.5 months, range was 2-14 months. Only the VTV criteria demonstrated a statistical association with OS (p=0.019; median OS 9.7 vs. 3.5 months).

CONCLUSION

This pilot study suggests that VTV is a promising tool for assessing tumor response and predicting OS, using criteria that incorporate tumor volume and density in patients receiving antiangiogenic therapy for urothelial cancer. Larger studies are warranted to further validate these findings.

Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data

BACKGROUND

Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis.

METHODS

In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Illumina Bead arrays (165 samples) and Affymetrix Oligo microarrays (188 samples). We investigated the structural and functional properties of GRNs for the identification of molecular targets associated to urothelial cancer.

RESULTS

We found that the urothelial cancer (UC) GRNs show a significant enrichment of subnetworks that are associated with known cancer hallmarks including cell cycle, immune response, signaling, differentiation and translation. Interestingly, the most prominent subnetworks of co-located genes were found on chromosome regions 5q31.3 (RNAseq), 8q24.3 (Oligo) and 1q23.3 (Bead), which all represent known genomic regions frequently deregulated or aberated in urothelial cancer and other cancer types. Furthermore, the identified hub genes of the individual GRNs, e.g., HID1/DMC1 (tumor development), RNF17/TDRD4 (cancer antigen) and CYP4A11 (angiogenesis/ metastasis) are known cancer associated markers. The GRNs were highly dataset specific on the interaction level between individual genes, but showed large similarities on the biological function level represented by subnetworks. Remarkably, the RNAseq UC GRN showed twice the proportion of significant functional subnetworks. Based on our analysis of inferential and experimental networks the Bead UC GRN showed the lowest performance compared to the RNAseq and Oligo UC GRNs.

CONCLUSION

To our knowledge, this is the first study investigating genome-scale UC GRNs. RNAseq based gene expression data is the data platform of choice for a GRN inference. Our study offers new avenues for the identification of novel putative diagnostic targets for subsequent studies in bladder tumors.