Tcga prostate

OBJECTIVE: This work aimed to investigate the expression of acidic leucine-rich nuclear protein phosphatase 32B (ANP32B) in prostate adenocarcinoma (PRAD) and evaluate the effect of ANP32B on the proliferation of prostate adenocarcinoma cells. METHODS: We evaluated the expression of ANP32B in PRAD tissues and cells compared to the controls obtained from The Cancer Genome Atlas (TCGA). siRNA targeting ANP32B was transfected into DU145 cells to knockdown the ANP32B expression and plasmids carrying ANP32B coding region were used to overexpress ANP32B in PC3 cells...

BACKGROUND: Anoikis is a distinctive type of apoptosis. It is involved in tumor progression and metastasis. But its function in castration-resistant prostate cancer remains veiled. We aimed to develop a prognostic indicator based on anoikis-related long non-coding RNAs (arlncRNAs) and to investigate their biological function in castration-resistant prostate cancer (CRPC). MATERIAL AND METHOD: Differentially expressed anoikis-related genes were extracted from two CRPC datasets, GSE51873, and GSE78201...

Methyltransferase-like protein 7A (METTL7A) is an m6A RNA methyltransferase that has been linked to cancer prognosis and drug resistance. However, a comprehensive analysis of METTL7A is lacking. The expression of METTL7A, prognostic performance, correlation with microsatellite instability (MSI), tumor mutational burden (TMB), and immune infiltration was investigated in The Cancer Genome Atlas (TCGA). Immunohistochemistry staining was applied to detect METTL7A in 6 tumors. METTL7A was significantly decreased in 19 cancers in TCGA including LUAD...

BACKGROUND: TMPRSS2-ERG (T2E) fusion is highly related to aggressive clinical features in prostate cancer (PC), which guides individual therapy. However, current fusion prediction tools lacked enough accuracy and biomarkers were unable to be applied to individuals across different platforms due to their quantitative nature. This study aims to identify a transcriptome signature to detect the T2E fusion status of PC at the individual level. METHODS: Based on 272 high-throughput mRNA expression profiles from the Sboner dataset, we developed a rank-based algorithm to identify a qualitative signature to detect T2E fusion in PC...

Progesterone and AdipoQ Receptor 3 (PAQR3) is a member of the AdipoQ receptor. Our previous studies have found that PAQR3 plays a role as a candidate inhibitor in cardiac adenocarcinoma, breast cancer, gastric cancer and colorectal cancer, but the systematic analysis of PAQR3 in tumors is currently lacking. The objective of this study was to investigate the prognostic and therapeutic value of PAQR3 in 31 tumors. Through the analysis of TCGA, UALCAN, GEO, GEPIA2, TIMER, Kaplan-Meier plotter, TISIDB and other databases, it was found that the expression level of PAQR3 changed significantly in different tumor types, and the expression level of Neuroblastoma was very high...

BACKGROUND: Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics...

BACKGROUND: Prostate cancer (PCa) is the most prevalent genitourinary malignancy in men, with a significant proportion of patients developing biochemical recurrence (BCR) after treatment. The immune microenvironment and metabolic alterations have crucial implications for the tumorigenesis and progression of PCa. Therefore, identifying metabolic genes associated with the immune microenvironment holds promise for predicting BCR and improving PCa prognosis. METHODS: In this study, ssGSEA and hierarchical clustering analysis were first conducted to evaluate and group PCa samples, followed by the use of the ESTIMATE and CIBERSORT algorithms to characterize the immunophenotypes and tumor microenvironment...

BACKGROUND: Prostate cancer (PCa) is a widespread malignancy, predominantly affecting elderly males, and current methods for diagnosis and treatment of this disease continue to fall short. The marker Ki-67 (MKI67) has been previously demonstrated to correlate with the proliferation and metastasis of various cancer cells, including those of PCa. Hence, verifying the association between MKI67 and the diagnosis and prognosis of PCa, using bioinformatics databases and clinical data analysis, carries significant clinical implications...

Prostate cancer (PCa) harbors several genetic alterations, the most prevalent of which is TMPRSS2:ERG gene fusion, affecting nearly half of all cases. Capitalizing on the increasing availability of whole-slide images (WSIs), this study introduces a deep learning (DL) model designed to detect TMPRSS2:ERG fusion from H&E-stained WSIs of radical prostatectomy specimens. Leveraging the TCGA prostate adenocarcinoma cohort, which comprises 436 WSIs from 393 patients, we developed a robust DL model, trained across ten different splits, each consisting of distinct training, validation, and testing sets...

BACKGROUND: Cancer stem cells (CSCs) have been implicated in prostate cancer (PCA) progression and therapeutic resistance. This study aimed to compare the expression levels of CSC CD (CD 44, CD 133, and CD 24) markers in treatment-naive patients with metastatic PCA before and after treatment. METHODS: The study included 60 treatment-naïve patients with metastatic PCA who received androgen deprivation therapy (ADT) alone (n = 30) and ADT plus chemotherapy (n = 30)...

ANP32B is a histone chaperone that interacts with various transcription factors that regulate cancer cell proliferation, immigration, and apoptosis. c-Myc, a well-known oncogenic protein, is a principal player in the initiation and progression of prostate cancer (PC). The means by which ANP32B and c-Myc act remain unknown. We downloaded clinical data from the GEO, TCGA, and other databases to explore ANP32B expression and its effects on the survival of PC and normal tissues. ANP32B-knockdown cell lines were used to evaluate how ANP32B affected cell proliferation in vitro and in vivo...

RATIONALE: The emerging evidence suggested that senescence regulator genes were involved in multi cancers, which may be utilized as new targets for cancers. However, the dysregulation and clinical impact of senescence regulator genes in clear cell renal cell cancer (ccRCC) were still in foggy. METHODS: Using multiomics data from TCGA-KIRC and other datasets, we comprehensively investigated the function of senescence regulator genes in ccRCC. ccRCC patients could be remodeled into 2 significant different groups basing on senescence regulators expression: senescence-pattern cancer subtype1 (SPCS1) and subtype2 (SPCS2)...

BACKGROUND: Ovarian cancer (OV) is a prevalent and deadly disease with high mortality rates. The development of accurate prognostic tools and personalized therapeutic strategies is crucial for improving patient outcomes. METHODS: A graph-based deep learning model, the Ovarian Cancer Digital Pathology Index (OCDPI), was introduced to predict prognosis and response to adjuvant therapy using hematoxylin and eosin (H&E)-stained whole-slide images (WSIs). The OCDPI was developed using formalin-fixed, paraffin-embedded (FFPE) WSIs from the TCGA-OV cohort, and was externally validated in two independent cohorts from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and Harbin Medical University Cancer Hospital (HMUCH)...

Basement membrane plays an important role in tumor invasion and metastasis, which is closely related to prognosis. However, the prognostic value and biology of basement membrane genes (BMGs) in prostate cancer (PCa) remain unknown. In the TCGA training set, we used differentially expressed gene analysis, protein-protein interaction networks, univariate and multivariate Cox regression, and least absolute shrinkage and selection operator regression to construct a basement membrane-related risk model (BMRM) and validated its effectiveness in the MSKCC validation set...

BACKGROUND: Currently, prostate-specific antigen (PSA) is commonly used as a prostate cancer (PCa) biomarker. PSA is linked to some factors that frequently lead to erroneous positive results or even needless biopsies of elderly people. OBJECTIVES: In this pilot study, we undermined the potential genes and mutations from several databases and checked whether or not any putative prognostic biomarkers are central to the annotation. The aim of the study was to develop a risk prediction model that could help in clinical decision-making...

BACKGROUND: Prostate adenocarcinoma (PRAD) is a common cancer diagnosis among men globally, yet large gaps in our knowledge persist with respect to the molecular bases of its progression and aggression. It is mostly indolent and slow-growing, but aggressive prostate cancers need to be recognized early for optimising treatment, with a view to reducing mortality. METHODS: Based on TCGA transcriptomic data pertaining to PRAD and the associated clinical metadata, we determined the sample Gleason grade, and used it to execute: (i) Gleason-grade wise linear modeling, followed by five contrasts against controls and ten contrasts between grades; and (ii) Gleason-grade wise network modeling via weighted gene correlation network analysis (WGCNA)...

Colon adenocarcinoma (COAD) is the predominant type of colorectal cancer. Early diagnosis and treatment can significantly improve the prognosis of COAD patients. Anoctamin 7 (ANO7), an anion channel protein, has been implicated in prostate cancer and other types of cancer. In this study, we analyzed the expression of ANO7 and its correlation with clinicopathological characteristics among COAD patients using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and the University of Alabama at Birmingham CANcer (UALCAN) databases...

BACKGROUND: Cancer-associated fibroblasts (CAFs) are heterogeneous and can influence the progression of prostate cancer in multiple ways; however, their capacity to present and process antigens in PRAD has not been investigated. In this study, antigen presentation and process-related CAFs (APPCAFs) were identified using bioinformatics, and the clinical implications of APPCAF-related signatures in PRAD were investigated. METHODS: SMART technology was used to sequence the transcriptome of primary CAFs isolated from patients undergoing different treatments...

Prostate cancer (PRAD) is one of the common malignant tumors of the urinary system. In order to predict the treatment results for PRAD patients, this study proposes to develop a risk profile based on endoplasmic reticulum stress (ERS). Based on the Memorial Sloan-Kettering Cancer Center (MSKCC) cohort and the Gene Expression Omnibus database (GSE70769), we verified the predictive signature. Using a random survival forest analysis, prognostically significant ERS-related genes were found. An ERS-related risk score (ERscore) was created using multivariable Cox analysis...

Prostate cancer (PCa) represents a substantial global health concern and a prominent contributor to male cancer-related mortality. The aim of this study is to explore the role of B-type endothelin receptor (EDNRB) in PCa and evaluate its therapeutic potential. The investigation employed predictive methodologies encompassing data acquisition from the GEO and TCGA databases, gene screening, enrichment analysis, in vitro experiments involving PCR, Western blotting, wound healing, and Transwell assays, as well as animal experiments...