Transcriptional Profiling of Advanced Urothelial Cancer Predicts Prognosis and Response to Immunotherapy

Hippo signaling modulation and its biological implications in urological malignancies

Although cancer diagnosis and treatment have rapidly advanced in recent decades, urological malignancies, which have high morbidity and mortality rates, are among the most difficult diseases to treat. The Hippo signaling is an evolutionarily conserved pathway in organ size control and tissue homeostasis maintenance. Its downstream effectors, Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ), are key modulators of numerous physiological and pathological processes. Recent work clearly indicates that Hippo signaling is frequently altered in human urological malignancies. In this review, we discuss the disparate viewpoints on the upstream regulators of YAP/TAZ and their downstream targets and systematically summarize the biological implications. More importantly, we highlight the molecular mechanisms involved in Hippo-YAP signaling to improve our understanding of its role in every stage of prostate cancer, bladder cancer and kidney cancer progression. A better understanding of the biological outcomes of YAP/TAZ modulation will contribute to the establishment of future therapeutic approaches.

The role of DNA damage repair (DDR) system in response to immune checkpoint inhibitor (ICI) therapy

As our understanding of the mechanisms of cancer treatment has increased, a growing number of studies demonstrate pathways through which DNA damage repair (DDR) affects the immune system. At the same time, the varied response of patients to immune checkpoint blockade (ICB) therapy has prompted the discovery of various predictive biomarkers and the study of combination therapy. Here, our investigation explores the interactions involved in combination therapy, accompanied by a review that summarizes currently identified and promising predictors of response to immune checkpoint inhibitors (ICIs) that are useful for classifying oncology patients. In addition, this work, which discusses immunogenicity and several components of the tumor immune microenvironment, serves to illustrate the mechanism by which higher response rates and improved efficacy of DDR inhibitors (DDRi) in combination with ICIs are achieved.

YAP1 activation is associated with the progression and response to immunotherapy of non-muscle invasive bladder cancer

Background

Despite the availability of several treatments for non-muscle-invasive bladder cancer (NMIBC), many patients are still not responsive to treatments, and the disease progresses. A new prognostic classifier can differentiate between treatment response and progression, and it could be used as a very important tool in patient decision-making regarding treatment options. In this study, we focused on the activation of Yes-associated protein 1 (YAP1), which is known to play a pivotal role in tumour progression and serves as a factor contributing to the mechanism of resistance to various relevant therapeutic agents. We further evaluated its potential as a novel prognostic agent.

Methods

We identified YAP1-associated gene signatures based on UC3-siYAP1 cells (n=8) and NMIBC cohort (n=460). Cross-validation was performed using 5 independent bladder cancer patient cohorts (n=1006). We also experimentally validated the changes of gene expression levels representing each subgroup.

Findings

The 976-gene signature based on YAP1-activation redefined three subgroups and had the benefits of Bacillus Calmette-Guérin (BCG) treatment in patients with NMIBC (hazard ratio 3.32, 95% CI 1.29-8.56, p = 0.01). The integrated analysis revealed that YAP1 activation was associated with the characterization of patients with high-risk NMIBC and the response to immunotherapy.

Interpretation

This study suggests that YAP1 activation has an important prognostic effect on bladder cancer progression and might be useful in the selection of immunotherapy.

Funding

A funding list that contributed to this research can be found in the Acknowledgements section.

Prediction of the Immune Phenotypes of Bladder Cancer Patients for Precision Oncology

Bladder cancer (BC) is the most common urinary malignancy; however accurate diagnosis and prediction of recurrence after therapies remain elusive. This study aimed to develop a biosignature of immunotherapy-based responses using gene expression data. Publicly available BC datasets were collected, and machine learning (ML) approaches were applied to identify a novel biosignature to differentiate patient subgroups. Immune phenotyping of BC in the IMvigor210 dataset included three subtypes: inflamed, excluded, and desert immune. Immune phenotypes were analyzed with gene expressions using traditional but powerful classification methods such as random forests, Deep Neural Networks (DNN), Support Vector Machines (SVM) together with boosting and feature selection methods. Specifically, DNN yielded the highest area under the curve (AUC) with precision and recall (PR) curves and receiver operating characteristic (ROC) curves for each phenotype ([Formula: see text] and [Formula: see text], respectively) resulting in the identification of gene expression features useful for immune phenotype classification. Our results suggest significant potential to further develop and utilize machine learning algorithms for analysis of BC and its precaution. In conclusion, the findings from this study present a novel gene expression assay that can accurately discriminate BC patients from controls. Upon further validation in independent cohorts, this gene signature could be developed into a predictive test that can support clinical evaluation and patient care.

Subgroup Identification with Gene Expression Profiles of Adipose Tissue in Patients with Coronary Artery Disease

Among many diseases, coronary artery disease (CAD) is the primary cause of mortality and morbidity worldwide. With the aim of revealing the underlying genetic characteristics of the CAD subtypes, we recruited patients with CAD and categorized them into subgroups according to the transcriptome expression profiles of the adipose tissue.With the removal of the batch effect, consensus clustering was employed to determine the subgroup numbers. Subgroup-specific genes were determined to conduct analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Weighted gene co-expression network analysis (WGCNA) revealed the subgroup-specific WGCNA modules. Moreover, gene set enrichment analysis (GSEA) was conducted. Overrepresentation enrichment analysis (OEA) of subgroup-specific signatures was also conducted to reveal the significant gene module associated with the corresponding clinical characteristics.After the removal of the batch effect, 77 CAD objects were divided into three subgroups. It was observed that the patients in subgroup III tended to be fat. After analyzing the dominant pathways of each subgroup, we discovered that the protein digestion and absorption pathway was specifically upregulated in subgroup I, which might result from the lowest proportion of the epicardial adipose tissue (EAT) sample. Moreover, subgroup II patients had genetic characteristics of high expression of complement and coagulation cascades and TNF signaling pathway. Furthermore, Th17 cell differentiation was significantly upregulated in subgroup III, indicating that Th17 cell differentiation is related to the clinical characteristics of body mass index (BMI).In conclusion, the genetic classification of CAD subjects indicated that subjects from different subgroups may exhibit specific gene expression patterns, suggesting that more personalized treatment should be applied to patients in each subgroup.

From clinical trials to clinical use of checkpoint inhibitors for patients with metastatic urothelial cancer

Monoclonal antibodies targeting the checkpoint inhibitors (CPIs), programmed cell death protein-1 or programmed cell death ligand-1, are changing the landscape of urothelial carcinoma therapeutics. Overall, clinical studies in metastatic or advanced urothelial cancer showed that CPIs provided a slight improvement in survival and a relevant advantage in safety, compared with chemotherapy. After reviewing published and ongoing trials, the authors discuss expected answers to unmet needs, with a special attention to the research of biological markers for patients with urothelial cancer eligible for treatment with CPIs in this article.