Therapeutic significance of ARID1A mutation in bladder cancer

What's new about the tumor microenvironment of urothelial carcinoma?

Urothelial carcinoma is a significant global health concern that accounts for a substantial part of cancer diagnoses and deaths worldwide. The tumor microenvironment is a complex ecosystem composed of stromal cells, soluble factors, and altered extracellular matrix, that mutually interact in a highly immunomodulated environment, with a prominent role in tumor development, progression, and treatment resistance. This article reviews the current state of knowledge of the different cell populations that compose the tumor microenvironment of urothelial carcinoma, its main functions, and distinct interactions with other cellular and non-cellular components, molecular alterations and aberrant signaling pathways already identified. It also focuses on the clinical implications of these findings, and its potential to translate into improved quality of life and overall survival. Determining new targets or defining prognostic signatures for urothelial carcinoma is an ongoing challenge that could be accelerated through a deeper understanding of the tumor microenvironment.

Multiple programmed cell death patterns and immune landscapes in bladder cancer: Evidence based on machine learning and multi-cohorts

BACKGROUND

Bladder cancer (BLCA) is the most prevalent malignant neoplasm of the urinary tract, and ranks seventh as the most frequent systemic neoplasm in males. Dysregulation of programmed cell death (PCD) has been implicated in various stages of cancer progression, including tumorigenesis, invasion, and metastasis. However, the correlation between multiple PCD modes and BLCA is lacking. Thus, a risk prediction model was built based on 12 models of PCD to predict prognosis and immunotherapy response in patients with BLCA.

METHODS

The RNA sequencing transcriptome data of BLCA were collected from the Cancer Genome Atlas Program (TCGA) and GEO datasets. Univariate Cox and LASSO regression analyzes were performed to identify PCD-related genes (PCDRGs) significant for prognosis. Multivariate Cox regression analysis was used to develop a prognostic model for PCD. Survival analysis and chi-squared test were employed to analyze the survival variations between different risk groups. Univariate and multivariate Cox analyses were performed to evaluate the model as an independent prognostic predictor. A nomogram was formulated using both clinical data and the model to predict the survival rates of BLCA patients. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were performed to analyze and elucidate the molecular mechanisms and pathways operating within different risk score groups. Furthermore, the immune landscape was investigated and the efficacy of various anti-tumor drugs was evaluated for BLCA. Finally, consensus clustering analysis was adopted to explore the association between different PCD clusters and clinical characteristics.

RESULTS

Assessment of the public datasets and multivariate Cox analysis yielded 1254 PCDRGs, of which 10 PCDRGs for BLCA were identified. Based on the PCDRGs, a prognostic model was built for BLCA patient prognosis. Compared with the low-risk group, the high-risk group had a poorer prognosis. The model predicted area under the curve (AUC) values of 0.751, 0.753, and 0.763, respectively, for 1-, 3-, and 5-year survival of BLCA patients. The nomogram further demonstrated the credibility of the prognosis model. The low-risk group patients exhibited lower TIDE scores and higher TMB scores, implying better response of the low-risk group to immunotherapy. The consensus clustering analysis indicated that compared with PCD cluster A, PCD cluster B was significantly more expressed in PCDRGs, suggesting a closer relation of PCD cluster B to PCDRGs. Patients in PCD cluster B had lower risk scores.

CONCLUSION

To summarize, the effects of 12 PCD patterns on BLCA were synthesized and the correlation between PCD and BLCA was explored. These findings provide new and convincing evidence for individualized treatment of BLCA, and help guide the treatment strategy and improve the prognosis of BLCA patients.

ARID1A Inactivation Increases Expression of circ0008399 and Promotes Cisplatin Resistance in Bladder Cancer

OBJECTIVE

Cisplatin (CDDP)-based chemotherapy is a first-line, drug regimen for muscle-invasive bladder cancer (BC) and metastatic bladder cancer. Clinically, resistance to CDDP restricts the clinical benefit of some bladder cancer patients. AT-rich interaction domain 1A (ARID1A) gene mutation occurs frequently in bladder cancer; however, the role of CDDP sensitivity in BC has not been studied.

METHODS

We established ARID1A knockout BC cell lines using CRISPR/Cas9 technology. IC50 determination, flow cytometry analysis of apoptosis, and tumor xenograft assays were performed to verify changes in the CDDP sensitivity of BC cells losing ARID1A. qRT-PCR, Western blotting, RNA interference, bioinformatic analysis, and ChIP-qPCR analysis were performed to further explore the potential mechanism of ARID1A inactivation in CDDP sensitivity in BC.

RESULTS

It was found that ARID1A inactivation was associated with CDDP resistance in BC cells. Mechanically, loss of ARID1A promoted the expression of eukaryotic translation initiation factor 4A3 (EIF4A3) through epigenetic regulation. Increased expression of EIF4A3 promoted the expression of hsa_circ_0008399 (circ0008399), a novel circular RNA (circRNA) identified in our previous study, which, to some extent, showed that ARID1A deletion caused CDDP resistance through the inhibitory effect of circ0008399 on the apoptosis of BC cells. Importantly, EIF4A3-IN-2 specifically inhibited the activity of EIF4A3 to reduce circ0008399 production and restored the sensitivity of ARID1A inactivated BC cells to CDDP.

CONCLUSION

Our research deepens the understanding of the mechanisms of CDDP resistance in BC and elucidates a potential strategy to improve the efficacy of CDDP in BC patients with ARID1A deletion through combination therapy targeting EIF4A3.

A novel cuproptosis-related lncRNAs signature predicts prognostic and immune of bladder urothelial carcinoma

Bladder Urothelial Carcinoma (BLCA) remains the most common urinary system tumor, and its prognosis is poor. Cuproptosis is a recently discovered novel cell death involved in the development of tumor cells. However, the use of cuproptosis to predict the prognosis and immunity of Bladder Urothelial Carcinoma remains largely unclear, and this study was designed to verify cuproptosis-related long non-coding RNAs (lncRNAs) to estimate the prognosis and immunity of Bladder Urothelial Carcinoma. In our study, we first defined the expression of cuproptosis-related genes (CRGs) in BLCA, and 10 CRGs were up- or downregulated. We then constructed a co-expression network of cuproptosis-related mRNA and long non-coding RNAs using RNA sequence data from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA-BLCA), clinical features and mutation data from BLCA patients to obtain long non-coding RNAs by Pearson analysis. Afterward, univariate and multivariate COX analysis identified 21 long non-coding RNAs as independent prognostic factors and used these long non-coding RNAs to construct a prognostic model. Then, survival analysis, principal component analysis (PCA), immunoassay, and comparison of tumor mutation frequencies were performed to verify the accuracy of the constructed model, and GO and KEGG functional enrichment analysis was used to verify further whether cuproptosis-related long non-coding RNAs were associated with biological pathways. The results showed that the model constructed with cuproptosis-related long non-coding RNAs could effectively evaluate the prognosis of BLCA, and these long non-coding RNAs were involved in numerous biological pathways. Finally, we performed immune infiltration, immune checkpoint and drug sensitivity analyses on four genes (TTN, ARID1A, KDM6A, RB1) that were highly mutated in the high-risk group to evaluate the immune association of risk genes with BLCA. In conclusion, the cuproptosis-related lncRNA markers constructed in this study have evaluation value for prognosis and immunity in BLCA, which can provide a certain reference for the treatment and immunity of BLCA.

A new immune-related gene signature predicts the prognosis and immune escape of bladder cancer

BACKGROUND

The biological roles of immune-related genes (IRGs) in bladder cancer (BC) need to be further elucidated.

OBJECTIVE

To elucidate the predictive value of IRGs for prognosis and immune escape in BC.

METHODS

We comprehensively analyzed the transcriptomic and clinical information of 430 cases, including 19 normal and 411 BC patients from the TCGA database, and verified 165 BC cases in the GSE13507 dataset. The risk model was constructed based on IRGs by applying LASSO Cox regression and exploring the relationship between the risk score and prognosis, gene mutations, and immune escape in BC patients.

RESULTS

We identified 4 survival-related genes (PSMC1, RAC3, ROBO2 and ITGB3) among 6,196 IRGs in both the TCGA and GES13507 datasets,, which were used to establish a gene risk model by applying LASSO Cox regression. The results showed that the high-risk (HR) group was closely associated with poor survival or advanced pathological stage of BC. Furthermore, the risk score was found to be an independent risk factor for prognosis of BC patients. In addition, high-risk individuals showed a greater prevalence of TP53 mutations lower CD8+ T-cell and NK cell infiltration, higher Treg cell infiltration, higher expression of PD-L1, and higher immune exclusion scores than those in the low-risk (LR) group. Finally, the experimental verification shows that the model construction gene, especially PMSC1, plays an important role in the growth and metastasis of bladder cancer.

CONCLUSIONS

These evidences revealed the vital role of IRGs in predicting prognosis, TP53 mutation and immune escape in BC patients.

ML216-Induced BLM Helicase Inhibition Sensitizes PCa Cells to the DNA-Crosslinking Agent Cisplatin

Using standard DNA-damaging medicines with DNA repair inhibitors is a promising anticancer tool to achieve better therapeutic responses and reduce therapy-related side effects. Cell viability assay, neutral comet assay, western blotting (WB), and cell cycle and apoptosis analysis were used to determine the synergistic effect and mechanism of ML216, a Bloom syndrome protein (BLM) helicase inhibitor, and cisplatin (CDDP), a DNA-crosslinking agent, in PCa cells. Based on the online database research, our findings revealed that BLM was substantially expressed in PCa, which is associated with a bad prognosis for PCa patients. The combination of ML216 and CDDP improved the antiproliferative properties of three PCa cell lines. As indicated by the increased production of γH2AX and caspase-3 cleavage, ML216 significantly reduced the DNA damage-induced high expression of BLM, making PC3 more susceptible to apoptosis and DNA damage caused by CDDP. Furthermore, the combination of ML216 and CDDP increased p-Chk1 and p-Chk2 expression. The DNA damage may have triggered the ATR-Chk1 and ATM-Chk2 pathways simultaneously. Our results demonstrated that ML216 and CDDP combination therapy exhibited synergistic effects, and combination chemotherapy could be a novel anticancer tactic.