Emerging biomarkers and targeted therapies in urothelial carcinoma

Abstract

The use of immunotherapy has revolutionized the management of patients with locally advanced, unresectable, and metastatic urothelial carcinoma (UC); however, platinum-based chemotherapy remains a therapeutic cornerstone both in localized muscle-invasive and advanced UC. There is still no predictive molecular biomarker with clinical utility to help guide treatment and select patients most likely to derive benefit from a particular therapeutic modality or regimen. However, recent research has further characterized the inherent biology and immunology landscapes of UC leading to the development of potential biomarkers and therapeutic targets that could be used upon further validation. Emerging interrogation of The Cancer Genome Atlas (TCGA) and other molecular profiling datasets has led to the identification of distinct molecular subtypes with diverse clinical behaviors with potential sensitivity to various therapies. It has also led to the discovery of multiple frequently altered genes and proteins that could lead to perturbation of intracellular signaling pathways and of the dynamic interactions between tumor cells, their "microenvironment", and the host "macro-environment". The advent of molecular profiling and deeper next-generation sequencing has the potential to change biomarker and "real time" drug sensitivity assessment, introducing and testing the premise of "precision oncology" and personalized medicine. Within this review, we summarize emerging biomarkers that may predict response to cisplatin-based chemotherapy, immunotherapy, emerging targeted therapies, and promising combination strategies. We also highlight a few examples of 'precision medicine' trials aiming to improve outcomes in UC. Since our review is not exhaustive we strongly recommend the readers to follow the continuously changing literature in the very interesting and dynamic field of UC.

Impact of performance status on treatment outcomes: A real‐world study of advanced urothelial cancer treated with immune checkpoint inhibitors

“…Although prognostic nomograms have been developed, composite predictive biomarkers (which can aid in decision making) need to demonstrate clinical utility via interrogation in clinical trials . Numerous putative biomarkers, such as PD‐L1 protein expression, the tumor mutational burden, T‐effector, TGF‐β, ΕΜΤ, and other gene signatures, DNA damage response gene and FGFR3 alterations, molecular subtypes, and T‐cell clonality/diversity, are under exploration; however, more work needs to be done to further validate clinically useful predictive biomarkers . Without the identification of such reliable and granular predictive tools, clinicians are left to use more blunt prognostic tools, such as the ECOG PS, to guide practice.…”

The Quest for an Ideal Neoadjuvant Systemic Therapy in Cisplatin-Ineligible Patients with Muscle-Invasive Localized Urothelial Carcinoma

“…Urothelial carcinoma has one of the highest mutation rates among solid tumors , which makes it ideal for investigation of agents targeting PD‐1/PD‐L1. Moreover, The Cancer Genome Atlas has reported potential therapeutic targets in 69% of the analyzed tumors, which provides the setting for evaluation of new therapeutic approaches .…”

“…For example, higher response rates to anti‐PD‐1/PD‐L1 have been associated with higher tumor tissue PD‐L1 expression in advanced urothelial carcinoma, but responses have also been seen with lower or no PD‐L1 expression . To make it more complicated, in the IMvigor211 phase III trial, tumor tissue PD‐L1 appeared overall favorably prognostic based on the SP142 assay used, but not predictive of response to atezolizumab . Widespread adoption of tumor mutational burden and PD‐L1 as biomarkers may be challenging because of variability of assays, methods, cutoffs, scoring systems, sampling bias, etc.…”

“…Widespread adoption of tumor mutational burden and PD‐L1 as biomarkers may be challenging because of variability of assays, methods, cutoffs, scoring systems, sampling bias, etc. . Other potential biomarkers include DNA damage response and mismatch repair gene defects, molecular subtypes based on gene expression profiling, T cell clonality and diversity, and cell‐free circulating tumor DNA, among others .…”

“…. Other potential biomarkers include DNA damage response and mismatch repair gene defects, molecular subtypes based on gene expression profiling, T cell clonality and diversity, and cell‐free circulating tumor DNA, among others .…”