Transitional cell carcinoma matrix stiffness regulates the osteopontin and YAP expression in recurrent patients

Modulating extracellular matrix stiffness: a strategic approach to boost cancer immunotherapy

The interplay between extracellular matrix (ECM) stiffness and the tumor microenvironment is increasingly recognized as a critical factor in cancer progression and the efficacy of immunotherapy. This review comprehensively discusses the key factors regulating ECM remodeling, including the activation of cancer-associated fibroblasts and the accumulation and crosslinking of ECM proteins. Furthermore, it provides a detailed exploration of how ECM stiffness influences the behaviors of both tumor and immune cells. Significantly, the impact of ECM stiffness on the response to various immunotherapy strategies, such as immune checkpoint blockade, adoptive cell therapy, oncolytic virus therapy, and therapeutic cancer vaccines, is thoroughly examined. The review also addresses the challenges in translating research findings into clinical practice, highlighting the need for more precise biomaterials that accurately mimic the ECM and the development of novel therapeutic strategies. The insights offered aim to guide future research, with the potential to enhance the effectiveness of cancer immunotherapy modalities.

Apoptosis related genes mediated molecular subtypes depict the hallmarks of the tumor microenvironment and guide immunotherapy in bladder cancer

Apoptosis has been discovered as a mechanism of cell death. The purpose of this study is to identify the diagnostic signature factors related to bladder cancer (BLCA) through apoptosis related genes (ARGs). Clinicopathological parameters and transcriptomics data of 1,440 BLCA patients were obtained from 7 datasets (GSE13507, GSE31684, GSE32548, GSE32894, GSE48075, TCGA-BLCA, and IMvigor210). We first identified prognosis-related ARGs in BLCA and used them to construct two ARGs molecular subtypes by using consensus clustering algorithm. By using principal component analysis algorithms, a ARGscore was constructed to quantify the index of individualized patient. High ARGscore correlated with progressive malignancy and poor outcomes in BLCA patients. High ARGscore was associated with higher immune cell, higher estimate scores, higher stromal scores, higher immune scores, higher immune checkpoint, and lower tumor purity, which was consistent with the "immunity tidal model theory". Preclinically, BLCA immunotherapy cohorts confirmed patients with low ARGscore demonstrated significant therapeutic advantages and clinical benefits. These findings contribute to our understanding of ARGs and immunotherapy in BLCA. The ARGscore is a potentially useful tool to predict the prognosis and immunotherapy in BLCA.

Gender, Bladder Cancer Healthcare and Burden of COVID-19

Bladder cancer as one of the main comorbid diseases might be more susceptible to develop COVID-19 infection with a higher mortality risk during the COVID-19 pandemic. The European Association of Urology (EAU) recommended a comprehensive panel for bladder cancer diagnosis and treatment during this global health problem. The urgent need for treatments of COVID-19 during the pandemic has persuaded researchers to evaluate the different medications, which may lead to drug shortages. Therefore, in this review paper, we have focused on the least recommendations of EAU about bladder cancer during of COVID-19 pandemic to provide a comprehensive panel for high-risk patients.

Trends in extracellular matrix biology

Extracellular matrixes (ECMs) are intricate 3-dimensional macromolecular networks of unique architectures with regulatory roles in cell morphology and functionality. As a dynamic native biomaterial, ECM undergoes constant but tightly controlled remodeling that is crucial for the maintenance of normal cellular behavior. Under pathological conditions like cancer, ECM remodeling ceases to be subjected to control resulting in disease initiation and progression. ECM is comprised of a staggering number of molecules that interact not only with one another, but also with neighboring cells via cell surface receptors. Such interactions, too many to tally, are of paramount importance for the identification of novel disease biomarkers and more personalized therapeutic intervention. Recent advances in big data analytics have allowed the development of online databases where researchers can take advantage of a stochastic evaluation of all the possible interactions and narrow them down to only those of interest for their study, respectively. This novel approach addresses the limitations that currently exist in studies, expands our understanding on ECM interactions, and has the potential to advance the development of targeted therapies. In this article we present the current trends in ECM biology research and highlight its importance in tissue integrity, the main interaction networks, ECM-mediated cell functional properties and issues related to pharmacological targeting.

Mechanobiology of solid tumors

Mechanical features of cancer cells emerge as a distinct trait during development and progression of solid tumors. Herein, we discuss recent key findings regarding the impact of various types of mechanical stresses on cancer cell properties. Data suggest that different mechanical forces, alterations of matrix rigidity and tumor microenvironment facilitate cancer hallmarks, especially invasion and metastasis. Moreover, a subset of mechanosensory proteins are responsible for mediating mechanically induced oncogenic signaling and response to chemotherapy. Delineating cancer dynamics and decoding of respective signal transduction mechanisms will provide new therapeutic strategies against solid tumors in the future.

An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

Simple Summary

Bladder cancer is evidently a challenge as far as its prognosis and treatment are concerned. The investigation of potential biomarkers and therapeutic targets is indispensable and still in progress. Most studies attempt to identify differential signatures between distinct molecular tumor subtypes. Therefore, keeping in mind the heterogeneity of urinary bladder tumors, we attempted to identify a consensus gene-related signature between the common expression profile of bladder cancer and control samples. In the quest for substantive features, we were able to identify key hub genes, whose signatures could hold diagnostic, prognostic, or therapeutic significance, but, primarily, could contribute to a better understanding of urinary bladder cancer biology.

Abstract

Bladder cancer (BCa) is one of the most prevalent cancers worldwide and accounts for high morbidity and mortality. This study intended to elucidate potential key biomarkers related to the occurrence, development, and prognosis of BCa through an integrated bioinformatics analysis. In this context, a systematic meta-analysis, integrating 18 microarray gene expression datasets from the GEO repository into a merged meta-dataset, identified 815 robust differentially expressed genes (DEGs). The key hub genes resulted from DEG-based protein–protein interaction and weighted gene co-expression network analyses were screened for their differential expression in urine and blood plasma samples of BCa patients. Subsequently, they were tested for their prognostic value, and a three-gene signature model, including COL3A1, FOXM1, and PLK4, was built. In addition, they were tested for their predictive value regarding muscle-invasive BCa patients’ response to neoadjuvant chemotherapy. A six-gene signature model, including ANXA5, CD44, NCAM1, SPP1, CDCA8, and KIF14, was developed. In conclusion, this study identified nine key biomarker genes, namely ANXA5, CDT1, COL3A1, SPP1, VEGFA, CDCA8, HJURP, TOP2A, and COL6A1, which were differentially expressed in urine or blood of BCa patients, held a prognostic or predictive value, and were immunohistochemically validated. These biomarkers may be of significance as prognostic and therapeutic targets for BCa.