Intrinsic Molecular Subclassification of Urothelial Carcinoma of the Bladder: Are We Finally there?

The Reduction of PSMB4 in T24 and J82 Bladder Cancer Cells Inhibits the Angiogenesis and Migration of Endothelial Cells

Bladder cancer (BC) is a malignant tumor of the urinary system with high mortality and recurrence rates. Proteasome subunit type 4 (PSMB4) is highly expressed and has been identified as having oncogenic properties in a variety of cancer types. This study aimed to explore the effect of PSMB4 knockdown on the survival, migration, and angiogenesis of human bladder cancer cells with different degrees of malignancy. We analyzed the effects of PSMB4 knockdown in bladder cancer cells and endothelial cells in the tumor microenvironment. PSMB4 was highly expressed in patients with low- and high-grade urothelial carcinoma. Inhibition of PSMB4 reduced protein expression of focal adhesion kinase (FAK) and myosin light chain (MLC), leading to reduced migration. Furthermore, the suppression of PSMB4 decreased the levels of vascular endothelial factor B (VEGF-B), resulting in lower angiogenic abilities in human bladder cancer cells. PSMB4 inhibition affected the migratory ability of HUVECs and reduced VEGFR2 expression, consequently downregulating angiogenesis. In the metastatic animal model, PSMB4 knockdown reduced the relative volumes of lung tumors. Our findings suggest the role of PSMB4 as a potential target for therapeutic strategies against human bladder cancer.

Receptor Tyrosine Kinase Pathway and Infiltrating Urothelial Carcinoma

Receptor tyrosine kinase pathway is frequently searched for cancer causing mutations in tumors. Emerging targeted therapies are gleam of hope for them. Infiltrating urothelial carcinoma can have many morphological aspects according to their differentiation/variants. To evaluate KRAS, BRAF, and PIK3CA mutations and HER2, EGFR, and p16 expression, we divided urothelial carcinomas into two groups: differentiated/variants (n = 12) and conventional (n = 12). We compared results with clinical, demographic, histopathologic features and survival rates. No statistically significant results could be obtained in the comparison of histopathologic properties/survival rates with mutation analysis and EGFR, HER2, and p16 status. Differentiated/variants urothelial carcinoma showed higher EGFR expression (P < 0.001). Glandular differentiation was the most frequent type, followed by squamous and sarcomatoid differentiation. We observed the most common mutation at KRAS with a propensity for urothelial carcinoma with glandular differentiation. More than one mutation/high protein expression was seen in some tumors. Targeted therapies for KRAS mutation can be effective at urothelial carcinoma with glandular differentiation. Heterologous expression of relevant proteins and genes can be a cause for targeted treatment obstacle. The determination of the molecular characters of tumors is a guide in creating targeted treatment algorithms and in choosing the patient.

PXDNL activates the motility of urothelial bladder carcinoma cells through the Wnt/β-catenin pathway and has a prognostic value

AIMS

Although aberrant expression of peroxidasin-like (PXDNL) has been associated with carcinogenesis, its potential role in the Urothelial Carcinoma of the Bladder (UCB) remains unknown. The present study aimed to explore the role of PXDNL in UCB carcinogenesis and its potential clinical value.

MAIN METHODS

Based on The Cancer Genome Atlas (TCGA) data, bioinformatics was used to explore the potential clinical value of PXDNL. Wound healing and Transwell invasion assays were employed for the purpose of assessing the cell motility, while the Western Blotting experiments were utilized for investigating the protein expression pattern of PXDNL in UCB and investigating the Epithelial-to-Mesenchymal Transition (EMT) and Wnt/β-catenin pathways for understanding the probable mechanisms involved.

KEY FINDS

PXDNL mRNA was overexpressed in UCB tissues and indicated a poor prognosis. High PXDNL mRNA levels were also associated with advanced clinicopathological features and were regarded as independent prognostic factors for UCB. However, PXDNL showed a weak correlation with immune cell infiltration in UCB. In addition, the findings of the study verified that the existing form of the PXDNL protein was 57-kDa and it was upregulated in the UCB cell lines and tissue samples. Furthermore, silencing PXDNL inhibited, while overexpressing PXDNL promoted EMT and motility of UCB cells in vitro. Mechanistic studies showed that PXDNL activated UCB cell motility via the Wnt/β-catenin pathway.

SIGNIFICANCE

The results reveal a novel molecular target that could be further explored for developing preventive, predictive, and individualized treatment strategies for UCB.

A Novel Risk Model for lncRNAs Associated with Oxidative Stress Predicts Prognosis of Bladder Cancer

Background

Oxidative stress (OS) reactions are closely related to the development and progression of bladder cancer (BCa). This project aimed to identify new potential biomarkers to predict the prognosis of BCa and improve immunotherapy.

Methods

We downloaded transcriptomic information and clinical data on BCa from The Cancer Genome Atlas (TCGA). Screening for OS genes was statistically different between tumor and adjacent normal tissue. A coexpression analysis between lncRNAs and differentially expressed OS genes was performed to identify OS-related lncRNAs. Then, differentially expressed oxidative stress lncRNAs (DEOSlncRNAs) between tumors and normal tissues were identified. Univariate/multivariate Cox regression analysis was performed to select the lncRNAs for risk assessment. LASSO analysis was conducted to establish a prognostic model. The prognostic risk model could accurately predict BCa patient prognosis and reveal a close correlation with clinicopathological features. We analyzed the principal component analysis (PCA), immune microenvironment, and half-maximal inhibitory concentration (IC50) in the risk groups.

Results

We constructed a model containing eight DEOSlncRNAs (AC021321.1, AC068196.1, AC008750.1, SETBP1-DT, AL590617.2, THUMPD3-AS1, AC112721.1, and NR4A1AS). The prognostic risk model showed better results in predicting the prognosis of BCa patients and was strongly correlated with clinicopathological characteristics. We found great agreement between the calibration plots and prognostic predictions in this model. The areas under the receiver operating characteristic (ROC) curve (AUCs) at 1, 3, and 5 years were 0.792, 0.804, and 0.843, respectively. This model also showed good predictive ability regarding the tumor microenvironment and tumor mutation burden. In addition, the high-risk group was more sensitive to eight therapeutic agents, and the low-risk group was more responsive to five therapeutic agents. Sixteen immune checkpoints were significantly different between the two risk groups.

Conclusion

Our eight DEOSlncRNA risk models provide new insights into predicting prognosis and clinical progression in BCa patients.

Prognostic significance and identification of basement membrane-associated lncRNA in bladder cancer

Based on the importance of basement membrane (BM) in cancer invasion and metastasis, we constructed a BM-associated lncRNA risk model to group bladder cancer (BCa) patients. Transcriptional and clinical data of BCa patients were downloaded from The Cancer Genome Atlas (TCGA), and the expressed genes of BM-related proteins were obtained from the BM-BASE database. We download the GSE133624 chip data from the GEO database as an external validation dataset. We screened for statistically different BM genes between tumors and adjacent normal tissues. Co-expression analysis of lncRNAs and differentially expressed BM genes was performed to identify BM-related lncRNAs. Then, differentially expressed BM-related lncRNAs (DEBMlncRNAs) between tumor and normal tissues were identified. Univariate/multivariate Cox regression analysis was performed to select lncRNAs for risk assessment. LASSO analysis was performed to build a prognostic model. We constructed a model containing 8 DEBMlncRNAs (AC004034.1, AL662797.1, NR2F1-AS1, SETBP1-DT, AC011503.2, AC093010.2, LINC00649 and LINC02321). The prognostic risk model accurately predicted the prognosis of BCa patients and revealed that tumor aggressiveness and distant metastasis were associated with higher risk scores. In this model, we constructed a nomogram to assist clinical decision-making based on clinicopathological characteristics such as age, T, and N. The model also showed good predictive power for the tumor microenvironment and mutational burden. We validated the expression of eight lncRNAs using the dataset GSE133624 and two human bladder cancer cell lines (5637, BIU-87) and examined the expression and cellular localization of LINC00649 and AC011503.2 using a human bladder cancer tissue chip. We found that knockdown of LINC00649 expression in 5637 cells promoted the proliferation of 5637 cells.Our eight DEBMlncRNA risk models provide new insights into predicting prognosis, tumor invasion, and metastasis in BCa patients.

Are We Ready to Implement Molecular Subtyping of Bladder Cancer in Clinical Practice? Part 2: Subtypes and Divergent Differentiation

Following several attempts to achieve a molecular stratification of bladder cancer (BC) over the last decade, a "consensus" classification has been recently developed to provide a common base for the molecular classification of bladder cancer (BC), encompassing a six-cluster scheme with distinct prognostic and predictive characteristics. In order to implement molecular subtyping (MS) as a risk stratification tool in routine practice, immunohistochemistry (IHC) has been explored as a readily accessible, relatively inexpensive, standardized surrogate method, achieving promising results in different clinical settings. The second part of this review deals with the pathological and clinical features of the molecular clusters, both in conventional and divergent urothelial carcinoma, with a focus on the role of IHC-based subtyping.

Immunohistochemistry subtyping of urothelial carcinoma is feasible in the daily practice

The preferred treatment of choice in muscle-invasive bladder cancer (MIBC) is usually transurethral resection followed by cystectomy, with neoadjuvant chemotherapy being a second option. As the treatment is associated with relevant side effects, a great effort is being made to improve the selection of patients, with molecular subtyping being one of the main strategies. Our aim was to develop an immunohistochemical algorithm for subtyping MIBCs. After a literature review, we have developed a simple algorithm to subtype MIBCs based on their morphology and three common antibodies: GATA3, CK5/6, and p16. We applied it to 113 muscle-invasive carcinomas. The positivity threshold for GATA3 and CK5/6 was 20% with at least moderate intensity, while p16 was 70% with moderate to intense nuclear and cytoplasmic staining. Cases GATA3 + CK5/6 - were considered luminal, while cases GATA3 - CK5/6 + were classified as nonluminal/basal squamous. Luminal p16 + cases were labeled as genomically unstable and luminal p16 - as Uro-like. Cases GATA3 + CK5/6 + with a predominantly basal pattern were labeled luminal, while diffuse cases were labeled nonluminal/basal squamous. All GATA3-CK5/6 - cases were considered nonluminal and were divided into mesenchymal-like or neuroendocrine, depending on the morphology. We were able to classify the 113 cases as: 82 (72.57%) were luminal, being 47 Uro-like (41.59%) and 35 (30.97%) genomically unstable; 31 (27.43%) were nonluminal, being 24 basal/squamous (21.24%), two (1.76%) mesenchymal-like, and five (4.42%) neuroendocrine like. We have achieved a feasible and cost-effective algorithm to subtype MIBCs from morphological features and the use of three common antibodies. Further studies in external cohorts are necessary to validate these results.

N6-methyladenosine-related non-coding RNAs are potential prognostic and immunotherapeutic responsiveness biomarkers for bladder cancer

BACKGROUND

Bladder cancer (BC) is a commonly occurring malignant tumor of the urinary system, demonstrating high global morbidity and mortality rates. BC currently lacks widely accepted biomarkers and its predictive, preventive, and personalized medicine (PPPM) is still unsatisfactory. N6-methyladenosine (m6A) modification and non-coding RNAs (ncRNAs) have been shown to be effective prognostic and immunotherapeutic responsiveness biomarkers and contribute to PPPM for various tumors. However, their role in BC remains unclear.

METHODS

m6A-related ncRNAs (lncRNAs and miRNAs) were identified through a comprehensive analysis of TCGA, starBase, and m6A2Target databases. Using TCGA dataset (training set), univariate and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to develop an m6A-related ncRNA-based prognostic risk model. Kaplan-Meier analysis of overall survival (OS) and receiver operating characteristic (ROC) curves were used to verify the prognostic evaluation power of the risk model in the GSE154261 dataset (testing set) from Gene Expression Omnibus (GEO). A nomogram containing independent prognostic factors was developed. Differences in BC clinical characteristics, m6A regulators, m6A-related ncRNAs, gene expression patterns, and differentially expressed genes (DEGs)-associated molecular networks between the high- and low-risk groups in TCGA dataset were also analyzed. Additionally, the potential applicability of the risk model in the prediction of immunotherapeutic responsiveness was evaluated based on the "IMvigor210CoreBiologies" data set.

RESULTS

We identified 183 m6A-related ncRNAs, of which 14 were related to OS. LASSO regression analysis was further used to develop a prognostic risk model that included 10 m6A-related ncRNAs (BAALC-AS1, MIR324, MIR191, MIR25, AC023509.1, AL021707.1, AC026362.1, GATA2-AS1, AC012065.2, and HCP5). The risk model showed an excellent prognostic evaluation performance in both TCGA and GSE154261 datasets, with ROC curve areas under the curve (AUC) of 0.62 and 0.83, respectively. A nomogram containing 3 independent prognostic factors (risk score, age, and clinical stage) was developed and was found to demonstrate high prognostic prediction accuracy (AUC = 0.83). Moreover, the risk model could also predict BC progression. A higher risk score indicated a higher pathological grade and clinical stage. We identified 1058 DEGs between the high- and low-risk groups in TCGA dataset; these DEGs were involved in 3 molecular network systems, i.e., cellular immune response, cell adhesion, and cellular biological metabolism. Furthermore, the expression levels of 8 m6A regulators and 12 m6A-related ncRNAs were significantly different between the two groups. Finally, this risk model could be used to predict immunotherapeutic responses.

CONCLUSION

Our study is the first to explore the potential application value of m6A-related ncRNAs in BC. The m6A-related ncRNA-based risk model demonstrated excellent performance in predicting prognosis and immunotherapeutic responsiveness. Based on this model, in addition to identifying high-risk patients early to provide them with focused attention and targeted prevention, we can also select beneficiaries of immunotherapy to deliver personalized medical services. Furthermore, the m6A-related ncRNAs could elucidate the molecular mechanisms of BC and lead to a new direction for the improvement of PPPM for BC.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13167-021-00259-w.