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

ADME gene-driven prognostic model for bladder cancer: a breakthrough in predicting survival and personalized treatment

BACKGROUND

Genes that participate in the absorption, distribution, metabolism, excretion (ADME) processes occupy a central role in pharmacokinetics. Meanwhile, variability in clinical outcomes and responses to treatment is notable in bladder cancer (BLCA).

METHODS

Our study utilized expansive datasets from TCGA and the GEO to explore prognostic factors in bladder cancer. Utilizing both univariate Cox regression and the lasso regression techniques, we identified ADME genes critical for patient outcomes. Utilizing genes identified in our study, a model for assessing risk was constructed. The evaluation of this model's predictive precision was conducted using Kaplan-Meier survival curves and assessments based on ROC curves. Furthermore, we devised a predictive nomogram, offering a straightforward visualization of crucial prognostic indicators. To explore the potential factors mediating the differences in outcomes between high and low risk groups, we performed comprehensive analyses including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)-based enrichment analyses, immune infiltration variations, somatic mutation landscapes, and pharmacological sensitivity response assessment etc. Immediately following this, we selected core genes based on the PPI network and explored the prognostic potential of the core genes as well as immune modulation, and pathway activation. And the differential expression was verified by immunohistochemistry and qRT-PCR. Finally we explored the potential of the core genes as pan-cancer biomarkers.

RESULTS

Our efforts culminated in the establishment of a validated 17-gene ADME-centered risk prediction model, displaying remarkable predictive accuracy for BLCA prognosis. Through separate cox regression analyses, the importance of the model's risk score in forecasting BLCA outcomes was substantiated. Furthermore, a novel nomogram incorporating clinical variables alongside the risk score was introduced. Comprehensive studies established a strong correlation between the risk score and several key indicators: patterns of immune cell infiltration, reactions to immunotherapy, landscape of somatic mutation and profiles of drug sensitivity. We screened the core prognostic gene CYP2C8, explored its role in tumor bioregulation and validated its upregulated expression in bladder cancer. Furthermore, we found that it can serve as a reliable biomarker for pan-cancer.

CONCLUSION

The risk assessment model formulated in our research stands as a formidable instrument for forecasting BLCA prognosis, while also providing insights into the disease's progression mechanisms and guiding clinical decision-making strategies.

Development of a propionate metabolism-related gene-based molecular subtypes and scoring system for predicting prognosis in bladder cancer

PURPOSE

Bladder cancer (BLCA) is a prevalent malignancy. Dysregulated propionate metabolism, a key cancer factor, suggests a potential target for treating metastatic cancer. However, a complete understanding of the link between propionate metabolism-related genes (PMRGs) and bladder cancer is lacking.

METHODS

From the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we gathered BLCA patient data, which was classified into distinct subgroups using non-negative matrix factorization (NMF). Survival and pathway analyses were conducted between these clusters. The PMRGs model, created through univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses, was assessed for prognostic significance using Kaplan-Meier and receiver operating characteristic (ROC) curves. A comprehensive evaluation included clinical, tumor microenvironment (TME), drug sensitivity, and immunotherapy analyses. Finally, the expression of HSD17B1 essential genes was confirmed via quantitative real-time polymerase chain reaction (qRT-PCR), with further validation through Transwell, wound healing, colony-formation, and EDU assays.

RESULTS

We discovered two distinct subcategories (CA and CB) within BLCA using NMF analysis, with CA demonstrating significantly better overall survival compared to CB. Additionally, six PMRGs emerged as critical factors associated with propionate metabolism and prognosis. Kaplan-Meier analysis revealed that high-risk PMRGs were correlated with a poorer prognosis in BLCA patients. Moreover, significant differences were observed between the two groups in terms of infiltrated immune cells, immune checkpoint expression, TME scores, and drug sensitivity. Notably, we found that suppressing HSD17B1 gene expression inhibited the invasion of bladder cancer cells.

CONCLUSION

Our study proposes molecular subtypes and a PMRG-based score as promising prognostic indicators in BLCA. Additionally, cellular experiments underscore the pivotal role of HSD17B1 in bladder cancer metastasis and invasion, suggesting its potential as a novel therapeutic target.

Emerging strategy for the treatment of urothelial carcinoma: Advances in antibody-drug conjugates combination therapy

Urothelial carcinoma (UC) is a prevalent malignant tumor involving the urinary system. Although there are various treatment modalities, including surgery, chemotherapy, and immune checkpoint inhibitor (ICI) therapy, some patients experience disease recurrence and metastasis with poor prognosis and dismal long-term survival. Antibody-drug conjugates (ADCs), which combine the targeting ability of antibody drugs with the cytotoxicity of chemotherapeutic drugs, have recently emerged as a prominent research focus in the development of individualized precision cancer therapy. Although ADCs have improved the overall response rate in patients with UC, their effectiveness remains limited. Currently, ADC-based combination therapies, particularly ADC combined with ICIs, have demonstrated promising efficacy. This combination approach has advanced the treatment of UC, exhibiting the potential to become the standard first-line therapy for advanced UC in the future. This article reviewed clinical trials involving ADC-based combination therapy for UC and discussed the possible challenges and future perspectives to provide guidance for the clinical treatment of UC.

Immune Checkpoints Inhibitors and Chemotherapy as First-Line Treatment for Metastatic Urothelial Carcinoma: A Network Meta-Analysis of Randomized Phase III Clinical Trials

Simple Summary

On the basis of the efficacy and tolerable safety profiles of immune checkpoints inhibitors (ICIs) in second-line metastatic urothelial carcinoma (mUC) patients, some emerging clinical trials focus on the first-line treatment. Thus, we conducted a network meta-analysis (NMA) to assess and compare the response and toxicity of ICIs in naïve-chemotherapy mUC setting. According to our results, combination therapy (either ICIs plus chemotherapy (CTX) or ICIs plus ICIs) had a higher priority in terms of overall survival. Concerning monotherapy, ICIs are not inferior to CTX in terms of OS. In view of the adverse effect, ICIs are very tolerable, and combination therapy did not lead to a higher incidence of grade 3–5 AEs when compared with CTX.

Abstract

Immune checkpoints inhibitors (ICIs) were considered as second-line treatments in metastatic urothelial carcinoma (mUC) based on better survival benefit and safety profile than chemotherapy (CTX). We aimed to assess different ICIs regimens in the efficacy and safety for front-line treatments in mUC patients. A comprehensive literature search was performed and Phase II-III randomized controlled trials (RCTs) on ICIs for patients with mUC were included. The outcome was evaluated by overall survival (OS), progression of free survival (PFS), objective response rate (ORR), and grade 3–5 adverse events. Network meta-analysis was used to estimate the effect size. Surface under cumulative ranking curves (SUCRAs) were applied to rank the included treatments for each outcome. Results: The survival benefit of a single ICI was non-inferiority to chemotherapy (CTX). Although no superior effects were indicated, combination therapy (either ICIs plus CTX or ICIs plus ICIs) presented better OS compared with CTX alone. In terms of PFS, combination therapy produced a noticeable benefit over CTX. Regarding the SUCRA ranking, atezolizumab plus CTX was associated with the best ranking for OS and pembrolizumab plus CTX was the best in PFS. In terms of safety, a single ICI had better safety profile than CTX and combination therapy had a similar risk of grade 3–5 adverse events with CTX. Conclusions: Our NMA results revealed that combination therapy has better ranking compared with monotherapy in OS and acceptable AEs. ICIs alone present non-inferior OS but a lower incidence of AEs compared with CTX.