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Prostate cancer is one of the most prevalent forms of cancer around the world. Androgen-deprivation treatment and chemotherapy are the curative approaches used to suppress prostate cancer progression. However, drug resistance is extensively and hard to overcome even though remarkable progress has been made in recent decades. Noncoding RNAs, such as miRNAs, lncRNAs, and circRNAs, are a group of cellular RNAs which participate in various cellular processes and diseases. Recently, accumulating evidence has highlighted the vital role of non-coding RNA in the development of drug resistance in prostate cancer. In this review, we summarize the important roles of these three classes of noncoding RNA in drug resistance and the potential therapeutic applications in this disease.

Nerves are important pathological elements of the microenvironment of tumors, including those in pancreatic, colon and rectal, prostate, head and neck, and breast cancers. Recent studies have associated perineural invasion with tumor progression and poor outcomes. In turn, tumors drive the reprogramming of neurons to recruit new nerve fibers. Therefore, the crosstalk between nerves and tumors is the hot topic and trend in current cancer investigations. Herein, we reviewed recent studies presenting direct supporting evidences for a better understanding of nerve–tumor interactions.

The antiandrogen enzalutamide (Enz) has improved survival in castration resistant prostate cancer (CRPC) patients. However, most patients eventually develop Enz resistance that may involve inducing the androgen receptor (AR) splicing variant 7 (ARv7). Here we report that high expression of monoamine oxidase-A (MAO-A) is associated with positive ARv7 detection in CRPC patients following Enz treatment. Targeting MAO-A with phenelzine or clorgyline, the FDA-approved drugs for antidepression, resensitize the Enz resistant (EnzR) cells to Enz treatment and further suppress EnzR cell growth in vitro and in vivo. Our findings suggest that Enz-increased ARv7 expression can transcriptionally enhance MAO-A expression resulting in Enz resistance via altering the hypoxia HIF-1α signals. Together, our results show that targeting the Enz/ARv7/MAO-A signaling with the antidepressants phenelzine or clorgyline can restore Enz sensitivity to suppress EnzR cell growth, which may indicate that these antidepression drugs can overcome the Enz resistance to further suppress the EnzR CRPC. Castration resistant prostate cancer patients treated with enzalutamide may develop resistance to the drug. Here, the authors report that monoamine oxidase-A expression is increased in these resistant tumors and that the antidepressants phenelzine/clorgyline can reverse such resistance to further suppress tumor growth

Background Circular RNA (circRNA) is a type of circular endogenous RNA produced by special selective splicing and participates in progression of diverse diseases. However, the role of circRNA in clear cell renal cell carcinoma (ccRCC) is still rarely reported. Methods We detected lower circ-AKT3 expression in ccRCC using the circular RNA microarray. Then, qPCR array was applied to verify the expression of circ-AKT3 in between 60 ccRCC tissues and adjacent normal tissues, as well as ccRCC cell lines and human normal kidney cell (HK-2). We investigated the function of circ-AKT3 in ccRCC in vitro and in vivo and detected underlying mechanisms by Western blotting, bioinformatic analysis, RNA pull-down assay and luciferase reporter assay. Results Circ-AKT3 was verified significantly downregulated in ccRCC. Knockdown of circ-AKT3 promoted ccRCC migration and invasion, while overexpression of circ-AKT3 suppressed ccRCC metastasis. Further, circ-AKT3/miR-296-3p/E-cadherin axis was shown responsible for circ-AKT3 inhibiting ccRCC metastasis. Conclusion Circ-AKT3 suppresses ccRCC metastasis by enforcing E-cadherin expression through competitively binding miR-296-3p. Circ-AKT3 may therefore serve as a novel therapeutic to better suppress ccRCC metastasis.

Background Sunitinib resistance can be classified into primary and secondary resistance. While accumulating research has indicated several underlying factors contributing to sunitinib resistance, the precise mechanisms in renal cell carcinoma are still unclear. Methods RNA sequencing and m6A sequencing were used to screen for functional genes involved in sunitinib resistance. In vitro and in vivo experiments were carried out and patient samples and clinical information were obtained for clinical analysis. Results We identified a tumor necrosis factor receptor-associated factor, TRAF1, that was significantly increased in sunitinib-resistant cells, resistant cell-derived xenograft (CDX-R) models and clinical patients with sunitinib resistance. Silencing TRAF1 increased sunitinib-induced apoptotic and antiangiogenic effects. Mechanistically, the upregulated level of TRAF1 in sunitinib-resistant cells was derived from increased TRAF1 RNA stability, which was caused by an increased level of N6-methyladenosine (m6A) in a METTL14-dependent manner. Moreover, in vivo adeno-associated virus 9 (AAV9) -mediated transduction of TRAF1 suppressed the sunitinib-induced apoptotic and antiangiogenic effects in the CDX models, whereas knockdown of TRAF1 effectively resensitized the sunitinib-resistant CDXs to sunitinib treatment. Conclusions Overexpression of TRAF1 promotes sunitinib resistance by modulating apoptotic and angiogenic pathways in a METTL14-dependent manner. Targeting TRAF1 and its pathways may be a novel pharmaceutical intervention for sunitinib-treated patients.

The methyltransferase Wilms’ tumor 1-associated protein (WTAP) has been reported to be dysregulated in various tumors. However, its role in renal cell carcinoma (RCC) remains elusive. Here, we explored whether WTAP was upregulated in RCC specimens compared to normal tissues. Functionally, WTAP promoted RCC cell proliferation and metastasis in vivo and in vitro. Mechanistically, WTAP act as an N6-methyladenosine transferase to regulate the m 6 A modification of long noncoding RNA TEX41. Then, the upregulated m 6 A modification destabilized TEX41 in a YTHDF2-dependent manner. Furthermore, TEX41 interacted with the SUZ12 protein and increased the histone methyltransferase activity of SUZ12, resulting in HDAC1 silencing. Totally, our study demonstrated the oncogenic the role of WTAP/TEX41/SUZ12/HDAC1 axis in RCC progression.

Androgen-deprivation therapy (ADT) via targeting androgens/androgen receptor (AR) signals may suppress cell proliferation in both prostate cancer (PCa) and bladder cancer (BCa), yet its impact on the cell invasion of these two urological cancers remains unclear. Here we found targeting androgens/AR with either the recently developed antiandrogen Enzalutamide (Enz) or AR-shRNAs led to increase PCa cell invasion, yet decrease BCa cell invasion. Mechanistic dissection revealed that suppressing androgens/AR signals could result in differential alterations of the selective circular RNAs (circRNAs) as a result of differential endogenous AR transcription. A negative autoregulation in PCa, yet a positive autoregulation in BCa, as a result of differential binding of AR to different androgen-response elements (AREs) and a discriminating histone H3K4 methylation, likely contributes to this outcome between these two urological tumors. Further mechanistic studies indicated that AR-encoded circRNA-ARC1 might sponge/alter the availability of the miRNAs miR-125b-2-3p and/or miR-4736, to impact the metastasis-related PPARγ/MMP-9 signals to alter the PCa vs. BCa cell invasion. The preclinical study using the in vivo mouse model confirms in vitro cell lines data, showing that Enz treatment could increase PCa metastasis, which can be suppressed after suppressing circRNA-ARC1 with sh-circRNA-ARC1. Together, these in vitro/in vivo results demonstrate that antiandrogen therapy with Enz via targeting AR may lead to either increase PCa cell invasion or decrease BCa cell invasion. Targeting these newly identified AR/circRNA-ARC1/miR-125b-2-3p and/or miR-4736/PPARγ/MMP-9 signals may help in the development of new therapies to better suppress the Enz-altered PCa vs. BCa metastasis.

To assess shifts in long-term survival outcomes for prostate cancer patients, the present study conducted conditional survival (CS) analysis and developed a personalized CS-nomogram to provide dynamic prognostic predictions. Data from 301,441 prostate cancer patients in the Surveillance, epidemiology, and end results (SEER) database were analyzed, with cancer-specific survival (CSS) estimated using the Aalen Johansen estimator. Key predictive factors, including tumor size, lymph node involvement, distant metastasis, and histological grade, were identified via LASSO and multivariable Cox regression analyses to construct the nomogram. Results showed an increase in 12-year CSS from 94.3% at diagnosis to 99.4% for those surviving more than 5 years, with prostate cancer-specific mortality falling below 5% after 5–6 years of survival. The CS-nomogram demonstrated high predictive accuracy, achieving a concordance index (C-index) of 0.869 and area under the curve (AUC) values between 0.847 and 0.904 over a 12-year follow-up period, which provides dynamic, individualized prognostic estimates, supporting the long-term management of prostate cancer patients.

Lactylation, a post-translational modification characterized by the attachment of lactate to protein lysine residues on proteins, plays a pivotal role in cancer progression and immune evasion. However, its implications in immunity regulation and prostate cancer prognosis remains poorly understood. This study aims to systematically examine the impact of lactylation-related genes (LRGs) on prostate cancer. Single-cell and bulk RNA sequencing data from patients with prostate cancer were analyzed. Data were sourced from TCGA-PRAD, GSE116918, and GSE54460, with batch effects mitigated using the ComBat method. LRGs were identified from exisiting literature, and unsupervised clustering was applied to assess their prognostic siginificance. The tumor microenvironment and functional enrichment of relevant pathways were also evaluated. A prognostic model was developed using integrative machine learning techniques, with drug sensitivy analysis included. The mRNA expression profiles of the top ten genes were validated in clinical samples. Single-cell RNA sequencing revealed distinct lactylation signatures across various cell types. Bulk RNA-seq analysis identified 56 prognostic LRGs, classifying patients into two distinct clusters with divergent prognoses. The high-risk cluster exhibited reduced immune cell infiltration and increased resistance to specific targeted therapies. A machine learning-based prognostic signature was developed, demonstrating robust predictive accuracy for treatment responses and disease outcomes. This study offers a comprehensive analysis of lactylation in prostate cancer, identifying potential prognostic biomarkers. The proposed prognostic signature provides a novel approach to personalized treatment strategies, deepening our understanding of the molecular mechanisms driving prostate cancer and offering a tool for predicting therapeutic responses and clinical outcomes.