N1-methyladenosine RNA methylation patterns are associated with an increased risk to biochemical recurrence in prostate cancer and serve as a potential novel biomarker for patient stratification.

Introduction: N1-methyladenosine (m1A) RNA methylation is an emerging epigenetic modification. Its potential role in lipid metabolism and prognosis of prostate cancer (PCa) remains unexplored.

Objectives: This study investigated the impact of m1A on lipid metabolism and PCa prognosis.

Evaluation of glucocorticoid-related genes reveals GPD1 as a therapeutic target and regulator of sphingosine 1-phosphate metabolism in CRPC.

Prostate cancer (PCa) is an androgen-dependent disease, with castration-resistant prostate cancer (CRPC) being an advanced stage that no longer responds to androgen deprivation therapy (ADT). Mounting evidence suggests that glucocorticoid receptors (GR) confer resistance to ADT in CRPC patients by bypassing androgen receptor (AR) blockade. GR, as a novel therapeutic target in CRPC, has attracted substantial attention worldwide.

RNA modification Regulators' Co-Expression Score (RMRCoeS) predicts biochemical recurrence and therapy response in prostate cancer: A multi-omics and experimental validation study.

Background: Owing to the heterogeneity of prostate cancer (PCa), the clinical indicators traditionally fall short of meeting the requirements for personalized medicine. The realm of RNA modification has emerged as an increasingly relevant domain, shedding light on its pivotal role in tumor heterogeneity. However, the specific contributions of RNA modification regulators within the context of PCa remain largely unexplored.

ACOX2 Serves as a Favorable Indicator Related to Lipid Metabolism and Oxidative Stress for Biochemical Recurrence in Prostate Cancer.

Given the heterogeneity of tumors, there is an urgent need for accurate prognostic parameters in prostate cancer (PCa) patients. Lipid metabolism (LM) reprogramming and oxidative stress (OS) play a vital role in the progression of PCa. In this work, we identified five LM-OS-related genes (including ACOX2, PPRAGC1A, PTGS1, PTGS2, and HAO1) associated with the biochemical recurrence (BCR) of PCa.

Machine learning-based integration develops a stress response stated T cell (Tstr)-related score for predicting outcomes in clear cell renal cell carcinoma.

Background: Establishment of a reliable prognostic model and identification of novel biomarkers are urgently needed to develop precise therapy strategies for clear cell renal cell carcinoma (ccRCC). Stress response stated T cells (Tstr) are a new T-cell subtype, which are related to poor disease stage and immunotherapy response in various cancers.

Methods: 10 machine-learning algorithms and their combinations were applied in this work.

Arginase 2 is a Diagnostic and Prognostic Marker for Prostate Cancer and Is Associated with Metabolism.

Objective: Metabolism, a basic need and biochemical process for cell survival and proliferation, is closely connected with the pathogenesis and progression of prostate cancer.

Methods: A four-gene signature construct that includes CKM (CKM), CD38, Enoyl Coenzyme A(EHHADH), and Arginase 2(ARG2) was created by bioinformatics. Finally, hub genes were validated by IHC and in vitro experiments.

Identification of a 9-gene signature to enhance biochemical recurrence prediction in primary prostate cancer: A benchmarking study using ten machine learning methods and twelve patient cohorts.

Prostate cancer (PCa) is a prevalent malignancy among men worldwide, and biochemical recurrence (BCR) after radical prostatectomy (RP) is a critical turning point commonly used to guide the development of treatment strategies for primary PCa. However, the clinical parameters currently in use are inadequate for precise risk stratification and informing treatment choice. To address this issue, we conducted a study that collected transcriptomic data and clinical information from 1662 primary PCa patients across 12 multicenter cohorts globally.

FKBP10 promotes clear cell renal cell carcinoma progression and regulates sensitivity to the HIF2α blockade by facilitating LDHA phosphorylation.

Renal cell carcinoma (RCC) is one of the three major malignant tumors of the urinary system and originates from proximal tubular epithelial cells. Clear cell renal cell carcinoma (ccRCC) accounts for approximately 80% of RCC cases and is recognized as a metabolic disease driven by genetic mutations and epigenetic alterations. Through bioinformatic analysis, we found that FK506 binding protein 10 (FKBP10) may play an essential role in hypoxia and glycolysis pathways in ccRCC progression.

Silencing HOXC13 exerts anti-prostate cancer effects by inducing DNA damage and activating cGAS/STING/IRF3 pathway.

Background: Advanced prostate cancer (PCa) will develop into castration-resistant prostate cancer (CRPC) and lead to poor prognosis. As the primary subtype of CRPC, CRPC-AR accounts for the major induction of PCa heterogeneity. CRPC-AR is mainly driven by 25 transcription factors (TFs), which we speculate may be the key factors driving PCa toward CRPC.

Metformin escape in prostate cancer by activating the PTGR1 transcriptional program through a novel super-enhancer.

The therapeutic efficacy of metformin in prostate cancer (PCa) appears uncertain based on various clinical trials. Metformin treatment failure may be attributed to the high frequency of transcriptional dysregulation, which leads to drug resistance. However, the underlying mechanism is still unclear.

A reactive oxygen species-related signature to predict prognosis and aid immunotherapy in clear cell renal cell carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is a malignant disease containing tumor-infiltrating lymphocytes. Reactive oxygen species (ROS) are present in the tumor microenvironment and are strongly associated with cancer development. Nevertheless, the role of ROS-related genes in ccRCC remains unclear.

Integrated high-throughput analysis identifies super enhancers in metastatic castration-resistant prostate cancer.

Metastatic castration-resistant prostate cancer (mCRPC) is a highly aggressive stage of prostate cancer, and non-mutational epigenetic reprogramming plays a critical role in its progression. Super enhancers (SE), epigenetic elements, are involved in multiple tumor-promoting signaling pathways. However, the SE-mediated mechanism in mCRPC remains unclear.

Identification and verification of an ALYREF-involved 5-methylcytosine based signature for stratification of prostate cancer patients and prediction of clinical outcome and response to therapies.

Objectives: Due to the heterogeneity of PCa, the clinical indicators used for PCa can't satisfy risk prognostication and personalized treatment. It is imperative to develop novel biomarkers for prognosis prediction and therapy response in PCa. Accumulating evidence shows that non-mutational epigenetic reprogramming, independent from genomic instability and mutation, serves as a newly added hallmark in cancer progression.

Development and validation of a tobacco smoking-related index for predicting overall survival and immunotherapy response in bladder cancer.

Bladder cancer is one of the top five most prevalent cancers in the United States and a major cause of cancer-related mortality worldwide. Meanwhile, tobacco smoking is a well-established modifiable risk factor for bladder cancer, with a population-attributable risk of approximately 50%. But the relationship between the prognosis of bladder cancer and tobacco smoking remains unclear.

A prognostic signature consisting of N6-methyladenosine modified mRNAs demonstrates clinical potential in prediction of biochemical recurrence and guidance on precision therapy in prostate cancer.

Novel biomarkers are urgently needed to improve the prediction of clinical outcomes and guide personalized treatment for prostate cancer (PCa) patients. However, the role of N6-methyladenosine (m6A) modifications in PCa initiation and progression remains largely elusive. In our study, we collected benign Prostate Hyperplasia (BPH), localized PCa, and metastatic PCa samples from patients and performed methylated RNA immunoprecipitation sequencing (MeRIP-Seq) to map m6A-methylated mRNAs.

Prognostic implication of heterogeneity and trajectory progression induced by enzalutamide in prostate cancer.

Background: Enzalutamide, as a second-generation endocrine therapy drug for prostate cancer (PCa), is prominent representative among the synthetic androgen receptor antagonists. Currently, there is lack of enzalutamide-induced signature (ENZ-sig) for predicting progression and relapse-free survival (RFS) in PCa.

Methods: Enzalutamide-induced candidate markers were derived from single-cell RNA sequencing analysis integrating three enzalutamide-stimulated models (0-, 48-, and 168-h enzalutamide stimulation).

Identification and Validation of FGF-Related Prognostic Signatures in Prostate Cancer.

Background: FGF signaling is critical to controlling various cancers. Nevertheless, the functions of FGF-related genes in PCa are still unknown.

Objective: The objective of this study is to build a FGF-related signature that was capable of accurately predicting PCa survival and prognosis for BCR.

Molecular predictors of metastasis in patients with prostate cancer.

Introduction: Prostate cancer is a serious threat to the health of older adults worldwide. The quality of life and survival time of patients sharply decline once metastasis occurs. Thus, early screening for prostate cancer is very advanced in developed countries.