Cardiovascular health (CVH) is a well-known predictor of morbidity and mortality, while phenotypic age (PhenoAge) is a promising biomarker of aging. This study aimed to explore the association between Life's Essential 8 (LE8), a novel CVH measure, and PhenoAge acceleration (PhenoAgeAccel), as well as the potential mediating role of oxidative stress biomarkers in this relationship. A total of 23,896 individuals were included from the NHANES database (2005-2018). LE8 scores were categorized into low, moderate, and high groups. PhenoAge, measured through clinical laboratory blood chemistries, served as a marker of biological aging. Weighted linear regression analyses were performed to assess the association between LE8 scores and PhenoAgeAceel. In the multivariable linear regression, LE8 scores were significantly and inversely associated with PhenoAgeAccel, showing a decreased risk in the moderate CVH group (β -2.98; 95%CI -3.29, -2.66) and high CVH group (β -4.72; 95%CI -5.08, -4.35) compared to the low CVH group. When treated as a continuous variable, each 10-point increase in LE8 scores corresponded to a 1.14-year decrease in PhenoAge (β -1.14; 95%CI -1.21, -1.06). Among the eight individual components in LE8, seven exhibited a significant negative correlation with PhenoAgeAccel, except for blood lipids. Additionally, mediation analysis revealed that oxidative stress biomarkers, including γ-glutamyltransferase (GGT), bilirubin, and uric acid, collectively mediated 17.1% of the associations between LE8 scores and PhenoAgeAccel (P < 0.001). Higher LE8 scores, representing ideal CVH, are significantly related to a deceleration in PhenoAge, and oxidative stress biomarkers may play a mediating role in this relationship.

Androgen deprivation therapy (ADT) is a cornerstone treatment for locally advanced or metastatic prostate cancer (PCa). However, its potential effects on the tumor immune microenvironment (TIM) of PCa patients and the underlying mechanism remain largely unclear. To explore the effects of ADT on PCa TIM, RNA sequencing was performed on six paired pre-ADT biopsy and post-ADT PCa lesions, and five paired paracancerous benign tissues from patients receiving neoadjuvant ADT with locally advanced PCa. Bioinformatics methods including ESTIMATE and ssGSEA were used to evaluate the stromal immune score and immune cell infiltration in PCa and paracancerous tissues. Weighted correlation network analysis was used to screen hub genes in the ADT-induced immune remodeling process. The results showed differences exist between PCa and paracancerous tissues in response to ADT. Compared with paracancerous tissues, the immune remodeling effect of ADT in PCa was more intense. ZFP36, JUNB, and SOCS3 served as hub genes in the ADT-induced immune remodeling process and were associated with PSA recurrent-free survival in the TCGA and our neoadjuvant ADT cohort. To investigate the joint action of the above three hub genes, an immune signature score was constructed. The results showed that immune signature score-based immune subtypes reveal the heterogeneity of the immune microenvironment of PCa and showed significant differences in patient prognosis, tumor immune infiltration, mutation burden, and landscape.

Cancer-associated fibroblasts (CAFs), the central players in the tumor microenvironment (TME), can promote tumor progression and metastasis via various functions. However, the properties of CAFs in prostate cancer (PCa) have not been fully assessed. Therefore, we aimed to examine the CAF characteristics in PCa and construct a CAF-derived signature to predict PCa prognosis. CAFs were identified using single-cell RNA sequencing (scRNA-seq) data from 3 studies. We performed the FindAllMarkers function to extract CAF marker genes and constructed a signature to predict the biochemical relapse-free survival (bRFS) of PCa in the Cancer Genome Atlas (TCGA) cohort. Subsequently, different algorithms were applied to reveal the differences of the TME, immune infiltration, treatment responses in the high- and low-risk groups. Additionally, the CAF heterogeneity was assessed in PCa, which were confirmed by the functional enrichment analysis, gene set enrichment analysis (GSEA), and AUCell method. The scRNA-seq analysis identified a CAF cluster with 783 cells and determined 183 CAF marker genes. Cell-cell communication revealed extensive interactions between fibroblasts and immune cells. A CAF-related prognostic model, containing 7 genes (ASPN, AEBP1, ALDH1A1, BGN, COL1A1, PAGE4 and RASD1), was developed to predict bRFS and validated by 4 independent bulk RNA-seq cohorts. Moreover, the high-risk group of the signature score connected with an immunosuppressive TME, such as a higher level of M2 macrophages and lower levels of plasma cells and CD8⁺ T cells, and a reduced reaction rate for immunotherapy compared with low-risk group. After re-clustering CAFs via unsupervised clustering, we revealed 3 biologically distinct CAF subsets, namely myofibroblast-like CAFs (myCAFs), immune and inflammatory CAFs (iCAFs) and antigen-presenting CAFs (apCAFs). In conclusion, the CAF-derived signature, the first of its kind, can effectively predict PCa prognosis and serve as an indicator for immunotherapy. Furthermore, our study identified 3 CAF subpopulations with distinct functions in PCa.

Objective To assess the efficacy and safety of green-light laser photoselective vaporisation of the prostate (PVP) compared with transurethral resection of the prostate (TURP) for lower urinary tract symptoms (LUTS) secondary to benign prostatic hyperplasia (BPH). Design Systematic review and meta-analysis, conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement. Data sources PubMed, EMBASE, the Cochrane Library until October 2018. Eligibility criteria Randomised controlled trials and prospective studies comparing the safety and efficacy of PVP versus TURP for LUTS manifesting through BPH. Data extraction and synthesis Perioperative parameters, complications rates and functional outcomes including treatment-related adverse events such as International Prostate Symptom Score (IPSS), maximum flow rate (Qmax), postvoid residual (PVR), quality of life (QoL) and International Index of Erectile Function (IIEF). Results 22 publications consisting of 2665 patients were analysed. Pooled analysis revealed PVP is associated with reduced blood loss, transfusion, clot retention, TUR syndrome, capsular perforation, catheterisation time and hospitalisation, but also with a higher reintervention rate and longer intervention duration (all p<0.05). No significant difference in IPSS, Qmax, QoL, PVR or IIEF at 3, 24, 36 or 60 months was identified. There was a significant difference in QoL at 6 months (MD=−0.08; 95% CI −0.13 to −0.02; p=0.007), and IPSS (MD = −0.10; 95% CI −0.15 to −0.05; p<0.0001) and Qmax (MD=0.62; 95% CI 0.06 to 1.19; p=0.03) at 12 months, although these differences were not clinically relevant. Conclusion PVP is an effective alternative, holding additional safety benefits. PVP has equivalent long-term IPSS, Qmax, QoL, PVR, IIEF efficacy and fewer complications. The main drawbacks are dysuria and reintervention, although both can be managed with non-invasive techniques. The additional shortcoming is that PVP does not acquire histological tissue examination which removes an opportunity to identify prostate cancer.

Background: As a transcription factor, Zic family member 2 (ZIC2) has been involved in more and more studies of tumorigenesis, which has been proved by our research team to be an effective prognostic marker for Pan-cancer. However, the prognosis, tumor promoting effect and regulatory mechanism of ZIC2 in clear cell renal cell carcinoma (ccRCC) are still unknown.