Publications by authors named "Youhuang Liu"

Background: Circular RNAs (circRNAs) have significant roles in tumor progression. The role of circRNA derived from ARP2 actin-related protein 2 homolog (circACTR2) has been reported in various human diseases. However, the functions and regulatory mechanisms of circACTR2 in Bladder Cancer (BCa) remain unknown.

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Article Synopsis
  • The study aims to examine how consistent Gleason scores from preoperative biopsies are with postoperative pathology scores in prostate cancer patients and to develop a risk scoring model.
  • Researchers analyzed demographic and clinical data of patients who underwent radical prostatectomy and found significant differences in Gleason scores between biopsy and surgery results, highlighting factors like weight, BMI, and PSA levels.
  • They successfully created an 8-factor predictive model to assess the consistency of Gleason scores, showing its effectiveness through various statistical evaluations.
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Objective: To construct and verify a key gene signature of the basement membrane of prostate cancer (PCa) to predict the progression and biochemical recurrence of the malignancy after radical prostatectomy.

Methods: Based on the PCa-related transcriptome, gene mutation and clinical data from the Cancer Genome Atlas Project (TCGA) database, we analyzed the differentially expressed genes (DEG) related to the basement membrane in the PCa and adjacent normal prostate tissues, and subjected them to GO function enrichment and KEGG pathway enrichment analyses. We identified prognosis-related genes from the DEGs and analyzed their mutations.

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Neuropilin-1 (NRP-1) overexpression has been reported in a variety of human cancers. However, the role of NRP-1 in bladder cancer (BC) remains unclear. The aim of present study was to analyze NRP-1 protein expression in BC tissues and to assess its prognostic significance for BC.

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This study aimed to investigate infiltration related microRNAs (miRNAs) in bladder urothelial carcinoma (BUC). Twenty patients with BUC were enrolled and divided into 2 groups according to infiltration or not: infiltrating BUC group (n=12) and non-infiltrating BUC group (n=8). Gene chip was used to detect infiltration related miRNAs in the BUC samples.

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