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Last update 23 Jan 2025

PCLAF

Last update 23 Jan 2025

Basic Info

Synonyms

HCV NS5A-transactivated protein 9, Hepatitis C virus NS5A-transactivated protein 9, KIAA0101

+ [12]

Introduction

PCNA-binding protein that acts as a regulator of DNA repair during DNA replication. Following DNA damage, the interaction with PCNA is disrupted, facilitating the interaction between monoubiquitinated PCNA and the translesion DNA synthesis DNA polymerase eta (POLH) at stalled replisomes, facilitating the bypass of replication-fork-blocking lesions. Also acts as a regulator of centrosome number.

Drugs associated with PCLAF

SM-1044

Target

PCLAF

Mechanism

PCLAF modulators

Active Org.

Guizhou Medical University

Originator Org.

Guizhou Medical University

Active Indication

Neoplasms

Inactive Indication-

Drug Highest PhasePreclinical

First Approval Ctry. / Loc.-

First Approval Date20 Jan 1800

AD-4

Target

PCLAF

Mechanism

PCLAF modulators

Active Org.

Guizhou Medical University

Originator Org.

Guizhou Medical University

Active Indication

Neoplasms

Inactive Indication-

Drug Highest PhasePreclinical

First Approval Ctry. / Loc.-

First Approval Date20 Jan 1800

CN118291393

Patent Mining

Target

PCLAF

Mechanism-

Active Org.

Xiangya Hospital Central South University

Originator Org.

Xiangya Hospital Central South University

Active Indication

Neoplasms [+1]

Inactive Indication-

Drug Highest PhaseDiscovery

First Approval Ctry. / Loc.-

First Approval Date20 Jan 1800

100 Clinical Results associated with PCLAF

100 Translational Medicine associated with PCLAF

0 Patents (Medical) associated with PCLAF

8,240

Literatures (Medical) associated with PCLAF

01 Dec 2025·Medical Microbiology and Immunology

Significance of diagnostic and therapeutic potential of serum endothelial and inflammatory biomarkers in defining disease severity of dengue infected patients

Article

Author: Ghosh, Priyanka ; Kaveri, Krishnasamy ; Saha, Bibhuti ; Tripathi, Anusri

Dengue virus (DENV) mediated disease severity leads to fatality among infected patients. Immune sentinels recognize DENV thereby secreting inflammatory mediators, endothelial biomarkers and anticoagulation factors. Absence of any diagnostic biomarkers for early identification of severe dengue (SD) patients has hindered disease management. Present study is aimed to evaluate diagnostic potential of these biomarkers along with their therapeutic targets for disease severity. Dengue infection was screened among 214 symptomatic patients and 25 healthy individuals by qRT-PCR, NS1-antigen, anti-dengue-IgM, anti-dengue-IgG ELISA and categorized them according to WHO-classification, 2009. Dengue viral-load and serotypes were determined by qRT-PCR. Serum-protein concentrations of inflammatory mediators (MIF, PAF, MMP2, MMP9, MCP1, RANTES, STNFRI, ST2, EOTAXIN), endothelial biomarkers (SDC1, VEGF, ANGPT2), anticoagulation factors (sTM, vWF, TF, PAI) were determined by sandwich ELISA. Statistical, PPI-network, hub-proteins, drug prediction analysis were performed by GraphPad-Prism⁹, STRING, Cytoscape-cytoHubba, DrugBank online, TTD, respectively. Among 81 dengue infected patients, significantly higher levels of MIF, PAF, sTNFRI, MMP9, VEGF, ANGPT2, MMP2, RANTES, SDC1 were detected among SD patients compared to non-severe ones, with excellent and good diagnostic potential of first (> 77.11, > 57.57 ng/ml, > 3226 pg/ml) and next three (> 105.3 ng/ml, > 12,380, > 8284 pg/ml) biomarkers, respectively. Serum MIF, PAF, MMP9, sTNFRI levels were significantly higher among hospitalized (p-value: 0.0081-0.0499), high-viral-load (p-value: 0.0266-0.0466) and DENV-2, 4 (p-value: < 0.0001-0.0298) infected patients. PPI-network analysed MMP9, PAI, vWF, ANGPT2, sTM, sTNFRI, MIF as hub-proteins targeted by FDA-approved/experimental drugs. This study recognized serum-biomarkers: MIF, PAF, sTNFRI, MMP9, VEGF, ANGPT2 to have significant diagnostic potential for identification of SD cases.

01 Feb 2025·Translational Oncology

MAZ-mediated tumor progression and immune evasion in hormone receptor-positive breast cancer: Targeting tumor microenvironment and PCLAF+ subtype-specific therapy

Article

Author: Sun, Yuwei ; Li, Yumeng ; Xiahou, Zhikai ; Jia, Hongling ; Ni, Gaofeng ; Zang, Hongyan ; Zhao, Fu

BACKGROUNDBreast cancer had been the most frequently diagnosed cancer among women, making up nearly one-third of all female cancers. Hormone receptor-positive breast cancer (HR+BC) was the most prevalent subtype of breast cancer and exhibited significant heterogeneity. Despite advancements in endocrine therapies, patients with advanced HR+BC often faced poor outcomes due to the development of resistance to treatment. Understanding the molecular mechanisms behind this resistance, including tumor heterogeneity and changes in the tumor microenvironment, was crucial for overcoming resistance, identifying new therapeutic targets, and developing more effective personalized treatments.METHODSThe study utilized single-cell RNA sequencing (scRNA-seq) data sourced from the Gene Expression Omnibus database and The Cancer Genome Atlas to analyze HR+BC and identify key cellular characteristics. Cell type identification was achieved through Seurat's analytical tools, and subtype differentiation trajectories were inferred using Slingshot. Cellular communication dynamics between tumor cell subtypes and other cells were analyzed with the CellChat. The pySCENIC package was utilized to analyze transcription factors regulatory networks in the identified tumor cell subtypes. The results were verified by in vitro experiments. A risk scoring model was developed to assess patient outcomes.RESULTSThis study employed scRNA-seq to conduct a comprehensive analysis of HR+BC tumor subtypes, identifying the C3 PCLAF+ tumor cells subtype, which demonstrated high proliferation and differentiation potential. C3 PCLAF+ tumor cells subtype was found to be closely associated with cancer-associated fibroblasts through the MK signaling pathway, facilitating tumor progression. Additionally, we discovered that MAZ was significantly expressed in C3 PCLAF+ tumor cells subtype, and in vitro experiments confirmed that MAZ knockdown inhibited tumor growth, accentuating its underlying ability as a therapeutic target. Furthermore, we developed a novel prognostic model based on the expression profile of key prognostic genes within the PCLAF+/MAZ regulatory network. This model linked high PCLAF+ tumor risk scores with poor survival outcomes and specific immune microenvironment characteristics.CONCLUSIONThis study utilized scRNA-seq to reveal the role of the C3 PCLAF+ tumor cells subtype in HR+BC, emphasizing its association with poor prognosis and resistance to endocrine therapies. MAZ, identified as a key regulator, contributed to tumor progression, while the tumor microenvironment had a pivotal identity in immune evasion. The findings underscored the importance of overcoming drug resistance, recognizing novel treatment targets, and crafting tailored diagnosis regimens.

01 Jan 2025·Neuroscience

Pigs as a translational animal model for the study of peak alpha frequency

Article

Author: Andreis, Felipe Rettore ; Nørgaard Dos Santos Nielsen, Thomas Gomes ; Muhammadee Janjua, Taha Al ; Jensen, Winnie ; Meijs, Suzan ; Mazhari-Jensen, Daniel Skak

The most characteristic feature of the human electroencephalogram is the peak alpha frequency (PAF). While PAF has been proposed as a biomarker in several diseases and disorders, the disease mechanisms modulating PAF, as well as its physiological substrates, remain elusive. This has partly been due to challenges related to experimental manipulation and invasive procedures in human neuroscience, as well as the scarcity of animal models where PAF is consistently present in resting-state. With the potential inclusion of PAF in clinical screening and decision-making, advancing the mechanistic understanding of PAF is warranted. In this paper, we propose the female Danish Landrace pig as a suitable animal model to probe the mechanisms of PAF and its feature as a biomarker. We show that somatosensory alpha oscillations are present in anesthetized pigs using electrocorticography and intracortical electrodes located at the sensorimotor cortex. This was evident when looking at the time-domain as well as the spectral morphology of spontaneous recordings. We applied the FOOOF-algorithm to extract the spectral characteristics and implemented a robustness threshold for any periodic component. Using this conservative threshold, PAF was present in 18/20 pigs with a normal distribution of the peak frequency between 8-12 Hz, producing similar findings to human recordings. We show that PAF was present in 69.6 % of epochs of approximately six-minute-long resting-state recordings. In sum, we propose that the pig is a suitable candidate for investigating the neural mechanisms of PAF as a biomarker for disease and disorders such as pain, neuropsychiatric disorders, and response to pharmacotherapy.

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PCLAF

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