[A single center study：An analysis of the safety and validity of delaying repeated biopsy for patients with atypical small acinar proliferation].

Objective: To explore the association between atypical small acinar proliferation (ASAP) and subsequent diagnosis of intermediate and high risk prostate cancer (PCa), and analyze whether delaying repeat biopsy timing is safe and effective.

Methods: From June 2000 to June 2022, we retrospectively analyzed the clinical data of 276 patients accepting prostatic biopsy and diagnosed with ASAP in China-Japan Union Hospital of Jilin University. 54.

The Origin and Evolution of Bladder Cancer Stem Cells.

Bladder cancer is the most common malignant tumor of the urinary system. Bladder cancer stem cells (BCSCs) play key roles in tumor initiation, metastasis, relapse and drug-resistance. Investigation of BCSCs is of great value.

Targeting mTOR signaling overcomes acquired resistance to combined BRAF and MEK inhibition in BRAF-mutant melanoma.

Targeting MAPK pathway using a combination of BRAF and MEK inhibitors is an efficient strategy to treat melanoma harboring BRAF-mutation. The development of acquired resistance is inevitable due to the signaling pathway rewiring. Combining western blotting, immunohistochemistry, and reverse phase protein array (RPPA), we aim to understanding the role of the mTORC1 signaling pathway, a center node of intracellular signaling network, in mediating drug resistance of BRAF-mutant melanoma to the combination of BRAF inhibitor (BRAFi) and MEK inhibitor (MEKi) therapy.

Targeting Extracellular Matrix Remodeling Restores BRAF Inhibitor Sensitivity in BRAFi-resistant Melanoma.

Purpose: The extracellular matrix (ECM) is an intriguing, yet understudied component of therapy resistance. Here, we investigated the role of ECM remodeling by the collagenase, MT1-MMP, in conferring resistance of v-Raf murine sarcoma viral oncogene homolog B1 (BRAF)-mutant melanoma to BRAF inhibitor (BRAFi) therapy.

Experimental Design: Publicly available RNA-sequencing data and reverse phase protein array were used to determine the relevance of MT1-MMP upregulation in BRAFi-resistant melanoma in patients, patient-derived xenografts, and cell line-derived tumors.

Comprehensive Gene Expression Analysis in NMIBC Using RNA-seq Reveals New Therapy Strategies.

Non-muscle invasive bladder cancer (NMIBC) patients often have fewer treatment options, and suffer the progression of disease due to mechanisms that are not clear, as well as due to its diversity. This study was designed to explore the molecular mechanism of bladder cancer through an RNA-seq. In addition to conventional analyses, we also simplified the network through modularization using the WGCNA algorithm, with the help of the topological overlapping matrix and hierarchical cluster tree, which are based on the PPI network of STRING.

BRAF Targeting Sensitizes Resistant Melanoma to Cytotoxic T Cells.

Purpose: BRAF and MEK inhibitors (BRAFi and MEKi) are actively used for the treatment of metastatic melanoma in patients with BRAF mutation in their tumors. However, the development of resistance to BRAFi and MEKi remains a difficult clinical challenge with limited therapeutic options available to these patients. In this study, we investigated the mechanism and potential therapeutic utility of combination BRAFi and adoptive T-cell therapy (ACT) in melanoma resistant to BRAFi.

Induction of Telomere Dysfunction Prolongs Disease Control of Therapy-Resistant Melanoma.

Telomerase promoter mutations are highly prevalent in human tumors including melanoma. A subset of patients with metastatic melanoma often fail multiple therapies, and there is an unmet and urgent need to prolong disease control for those patients. Numerous preclinical therapy-resistant models of human and mouse melanoma were used to test the efficacy of a telomerase-directed nucleoside, 6-thio-2'-deoxyguanosine (6-thio-dG).

Integrated Bioinformatics Analysis of Potential Biomarkers for Prostate Cancer.

The aim was to expound the pathogenesis of prostate cancer and to identify the potentially biomarkers for prostate cancer (PC). DNA methylation microarray data GSE38240 containing 8 prostate cancer metastases and 4 normal prostate samples as well as gene expression profile data GSE26910 containing 6 prostate primary tumors and 6 normal samples were used. Differentially expressed genes (DEGs) and differently methylated sites of PC were screened and the regulatory network was constructed with DEGs-related transcription factors (TFs).

Biomarker identification in clear cell renal cell carcinoma based on miRNA-seq and digital gene expression-seq data.

This study aimed to explore the underlying microRNA (miRNA) targets in clear cell renal cell carcinoma (ccRCC). The expression profile with accession number GSE24952 was downloaded from the Gene Expression Omnibus database. Based on the dataset, the differentially expressed genes (DEGs) and miRNAs in ccRCC tissues and matched normal adjacent tissues were analyzed.

Screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles.

The aim of the present study was to analyze potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles. First, gene expression profiles GSE38241 and GSE3933 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between prostate cancer and normal control samples were identified using the Linear Models for Microarray Data package.

Beneficial effect of T follicular helper cells on antibody class switching of B cells in prostate cancer.

Prostate cancer is the most common malignancy in males and easily develops to be aggressive which is closely related to the chronic inflammatory tumor microenvironment in situ. This study aimed to assess the immunoglobulin G (IgG) subclass of B cells and explore their interactions with T follicular helper (Tfh) subsets in prostate cancer patients. The percentages of peripheral blood naïve B cells, memory B cells and mature B cells, as well as Tfh1, Tfh2 and Tfh17 cells were analyzed or sorted by FACSAria.