Request Demo

Last update 08 May 2025

PMEPA1

Last update 08 May 2025

Basic Info

Synonyms

PMEPA1, Prostate transmembrane protein androgen induced 1, prostate transmembrane protein, androgen induced 1

+ [5]

Introduction

Functions as a negative regulator of TGF-beta signaling and thereby probably plays a role in cell proliferation, differentiation, apoptosis, motility, extracellular matrix production and immunosuppression. In the canonical TGF-beta pathway, ZFYVE9/SARA recruits the intracellular signal transducer and transcriptional modulators SMAD2 and SMAD3 to the TGF-beta receptor. Phosphorylated by the receptor, SMAD2 and SMAD3 then form a heteromeric complex with SMAD4 that translocates to the nucleus to regulate transcription. Through interaction with SMAD2 and SMAD3, LDLRAD4 may compete with ZFYVE9 and SMAD4 and prevent propagation of the intracellular signal (PubMed:20129061, PubMed:24627487). Also involved in down-regulation of the androgen receptor (AR), enhancing ubiquitination and proteasome-mediated degradation of AR, probably by recruiting NEDD4 (PubMed:18703514).

Drugs associated with PMEPA1

WO2023097293

Patent Mining

Target

PMEPA1

Mechanism-

Active Org.

President & Fellows of Harvard College

Originator Org.

President & Fellows of Harvard College

Active Indication

Congenital Disorders [+2]

Inactive Indication-

Drug Highest PhaseDiscovery

First Approval Ctry. / Loc.-

First Approval Date20 Jan 1800

WO2024243545

Patent Mining

Target

PMEPA1

Mechanism-

Active Org.

President & Fellows of Harvard College

Originator Org.

President & Fellows of Harvard College

Active Indication

Cardiovascular Diseases [+13]

Inactive Indication-

Drug Highest PhaseDiscovery

First Approval Ctry. / Loc.-

First Approval Date20 Jan 1800

100 Clinical Results associated with PMEPA1

100 Translational Medicine associated with PMEPA1

0 Patents (Medical) associated with PMEPA1

146

Literatures (Medical) associated with PMEPA1

01 Dec 2025·Functional & Integrative Genomics

Heterogeneity analysis and prognostic model construction of HPV negative oral squamous cell carcinoma T cells using ScRNA-seq and bulk-RNA analysis

Article

Author: Li, Chongxin ; Luo, Huan ; Liu, Feineng ; Lv, Jialing ; Zhang, Chao ; Li, Chunyan ; Zhang, Wen ; Xu, Guoyu ; Yang, Shixuan ; Deng, Ruoyu ; Zhao, Yinhong ; Zhang, Tengfei ; Lv, Zengbo ; Wang, Lin

BACKGROUNDT cells are involved in every stage of tumor development and significantly influence the tumor microenvironment (TME). Our objective was to assess T-cell marker gene expression profiles, develop a predictive risk model for human papilloma virus (HPV)-negative oral squamous cell carcinoma (OSCC) utilizing these genes, and examine the correlation between the risk score and the immunotherapy response.METHODSWe acquired scRNA-seq data for HPV-negative OSCC from the GEO datasets. We performed cell‒cell communication, trajectory, and pathway enrichment analyses of T-cell-associated genes. In addition, we constructed and validated a T-cell-associated gene prognostic model for HPV-negative OSCC patients using TCGA and GEO data and assessed the immune infiltration status of HPV-negative OSCC patients .qRT-PCR was used to detect the expression level of prognosis-related genes in different risk groups.RESULTSScRNA-seq was conducted on 28,000 cells derived from 14 HPV-negative OSCC samples and 6 normal samples. We identified 4,635 T cells from these cells and identified 774 differentially expressed genes(DEGs) associated with T cells across five distinct T-cell subtypes. Through the integration of bulk-RNAseq data, we established a prognostic model based on DEGs related to T cells. By separating patients into high-risk and low-risk groups according to these prognostic related genes, we can accurately predict their survival rates and the immune infiltration status of the TME.qRT-PCR results showed that compared with the patients of low risk group, the expression of PMEPA1, SH2D2A, SMS and PRDX4 were significantly up-regulated in high risk group.CONCLUSIONThis study provides a resource for understanding the heterogeneity of T cells in HPV-negative OSCC patients and associated prognostic risk models. It provides new insights for predicting survival and level of immune infiltration in patients with HPV-negative OSCC.

01 May 2025·Journal of Ethnopharmacology

Root of Prunus persica (taoshugen) ameliorated renal fibrosis by inhibiting TGF-β signaling via upregulating Pmepa1 in mice with unilateral ureter obstruction

Article

Author: Zhang, Hong-Min ; Wang, Li ; Wang, Lu ; Shen, Hong-Chun ; Long, Wen ; Chen, Qiu-Wei ; Li, Yu-Qing ; Ren, Wei ; Lin, Jing-Yi ; Wang, Hong-Lian ; Shang, Xue-Mei ; Chen, Wen-Yan ; Wang, Yi-Xuan

ETHNOPHARMACOLOGICAL RELEVANCEVarious parts of Prunus persica (L.) Batsch (peach) exhibit medicinal properties and are utilized in traditional Chinese medicine (TCM) for therapeutic purposes. Notably, the root of P. persica, referred to as "taoshugen" in Chinese, is utilized by experienced TCM practitioners for the treatment of liver cirrhosis, suggesting its potential efficacy in mitigating organ fibrosis.AIM OF THE STUDYThe study aimed to investigate the potential protective role of the water extract of taoshugen (WE-TSG) against chronic kidney disease-associated renal fibrosis and the underlying mechanisms.MATERIALS AND METHODSThe chemical composition of WE-TSG was characterized using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The anti-renal fibrosis efficacy of WE-TSG was evaluated in vitro using TGF-β1-stimulated renal tubular TCMK1 cells and in vivo using a murine model of unilateral ureter obstruction (UUO). The underlying mechanisms were elucidated using RNA-seq and CRISPR/Cas9-mediated loss of function of candidate genes. The activity of TGF-β signaling and the extent of fibrosis were determined by luciferase reporter assays, histology, immunohistochemistry, RT-PCR, and Western blot.RESULTSLC-MS/MS analysis identified 14 major compounds in WE-TSG, primarily flavonoids and organooxygen compounds. In TCMK1 cells, WE-TSG significantly inhibited the activity of TGF-β-responsive luciferase reporters, CAGA-luc and CTGF-luc, and dose-dependently (3.125, 6.25, and 12.5 μg/mL) suppressed TGF-β1-induced Smad2/3 phosphorylation (p-Smad2/3) and fibrotic gene (fibronectin, Col1a1, and Ctgf) expression, without affecting total Smad2/3 protein levels. In vivo, oral administration of WE-TSG (1.4 and 2.8 g/kg) attenuated structural abnormalities, collagen deposition, and fibrotic gene (fibronectin, Col1a1, and α-SMA) expression, alongside reduced TGF-β signaling activity (TGF-β1 and p-Smad2/3) in the kidney tissues of UUO mice. RNA-seq in TCMK1 cells identified that Pmepa1, a negative-feedback regulator of TGF-β signaling, was significantly upregulated upon WE-TSG pretreatment. Importantly, knockout of Pmepa1 abolished the anti-TGF-β signaling and anti-fibrosis effects of WE-TSG in TGF-β1-stimulated TCMK1 cells. Moreover, kidney-targeted Pmepa1 knockdown also abrogated the anti-renal fibrosis role of WE-TSG in UUO mice.CONCLUSIONSOur findings demonstrate that WE-TSG inhibits TGF-β signaling and attenuates UUO-induced renal fibrosis by promoting Pmepa1 expression, highlighting the potential of herbal medicine taoshugen in the clinical treatment of CKD.

28 Jan 2025·ACS Omega

Transmembrane Prostate Androgen-Induced Protein 1 Molecular Modeling and Refinement Using Coarse-Grained Molecular Dynamics

Article

Author: Yusuf, Muhammad ; Wicaksono, Imam Adi ; Amalia, Riezki ; Milanda, Tiana ; Romadhon, Shidqi Fajri ; Nugraha, Bagas Adi Prasetya ; Destiarani, Wanda

Transmembrane prostate androgen-induced protein 1 (TMEPAI), a type 1b transmembrane protein, is highly expressed in many types of cancer and is involved in cancer signaling pathways. TMEPAI affects the TGF-β, androgen receptor, Wnt, and MAPK/ERK signaling pathways. Although TMEPAI interactions are known, information about their structure is limited. This study performed TMEPAI structure prediction via a computational approach with template-free modeling using multiple Web server and refining with coarse-grained molecular dynamics to improve the understanding of its characterization, mechanism, and interactions, followed by intensive server-based validation. As a result, the predicted TMEPAI isoform structure was validated for all parameters, and the trRosetta server provided the most reliable predicted structure. This research is expected to provide preliminary scientific information about the TMEPAI structure prediction and apply it to develop targeted cancer therapy drugs.

Analysis

Perform a panoramic analysis of this field.

view full example data

Hiro LS Researcher

The AI Search Engine Built to Accelerate Biopharma Decisions

Search across billion-scale life sciences data to uncover signals, validate evidence, and act with confidence.

Ask any biopharma research question→

Get started for free today!

Accelerate Strategic R&D decision making with Synapse, Patsnap’s AI-powered Connected Innovation Intelligence Platform Built for Life Sciences Professionals.

Discover Synapse Data Servers

Synapse data is now integrated into the PatSnap LS Model Context Protocol (MCP) service. Customize your LLM agent now using our MCP server!

Bio

Bio Sequences Search & Analysis

Chemical

Chemical Structures Search & Analysis

PMEPA1

Basic Info

Related

Analysis