LHFPL2

Last update 08 May 2025

Basic Info

Synonyms

KIAA0206, LHFPL tetraspan subfamily member 2, LHFPL tetraspan subfamily member 2 protein

+ [2]

Introduction

Plays a role in female and male fertility. Involved in distal reproductive tract development.

100 Clinical Results associated with LHFPL2

100 Translational Medicine associated with LHFPL2

0 Patents (Medical) associated with LHFPL2

Literatures (Medical) associated with LHFPL2

16 Aug 2023·Aging

A novel hepatocellular carcinoma-specific mTORC1-related signature for anticipating prognosis and immunotherapy.

Article

Author: Zou, Zhilin ; Chen, Erbao ; Lin, Zewei ; Liu, Jikui ; Liu, Jie ; Luo, Ting ; Mo, Yuqian ; Yi, Jing ; Hu, Yibing ; Li, Zheng

Tumor oncogenesis, cancer metastasis, and immune evasion were substantially impacted by the mammalian target of the rapamycin complex 1 (mTORC1) pathway. However, in hepatocellular carcinoma (HCC), no mTORC1 signaling-based gene signature has ever been published. mTORC1 scores were computed employing a single sample gene set enrichment analysis based on databases including the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). The PAG1, LHFPL2, and FABP5 expression levels were obtained to construct a mTORC1 pathway-related model. In two databases, the overall survival (OS) rate was shorter for high-mTORC1 score patients compared to those with low scores. The activation of TFs in the group with high risk was enhanced, such as the HIF-1 pathway. Additionally, it was discovered that a high mTORC1 score was linked to an immune exclusion phenotype and enhanced immunosuppressive cell infiltration. Notably, it was discovered that high-mTORC1 scores patients had poorer immunotherapeutic results and might not gain benefit from immunotherapy. When compared to the low HCC metastatic cell lines, the high HCC metastatic cell lines have overexpressed levels of PAG1, LHFPL2, and FABP5 expression. The expression of PAG1, LHFPL2, and FABP5 was inhibited by the MAPK and mTORC1 pathway inhibitors. Our study identified mTORC1 score signature can aid in the development of individualized immunotherapy protocols and predict the HCC patients' prognoses.

01 Jan 2023·International journal of general medicine

TRIM5 Promotes Systemic Lupus Erythematosus Through CD4(+) T Cells and Macrophage.

Article

Author: Pan, Zhaobing ; Xu, Xiaoqing ; Sun, Yao ; Yang, Qiaoshan ; Zhou, Fusheng ; Zhang, Xiaojing ; Wen, Leilei

PurposeSystemic lupus erythematosus (SLE) is a typical autoimmune disease characterized by the involvement of multiple organs and the production of antinuclear antibodies. This study aimed to investigate the molecular mechanism of SLE.Patients and MethodsWe retrieved genome-wide gene expression levels from five public datasets with relatively large sample sizes from the Gene Expression Omnibus (GEO), and we compared the expression profiles of peripheral blood mononuclear cells (PBMCs) from SLE patients and healthy controls (HCs). The expression of seven target genes in PBMCs from 25 cases and 3 HCs was further validated by reverse-transcription quantitative PCR (RT‒qPCR). Flow cytometry was used for verifying the proportion of naive CD4(+) T cells and M2 macrophages in PBMCs from 5 cases and 4 HCs.ResultsWe found 14 genes (TRIM5, FAM8A1, SHFL, LHFPL2, PARP14, IFIT5, PARP12, DDX60, IRF7, IF144, OAS1, OAS3, RHBDF2, and RSAD2) that were differentially expressed among all five datasets. The heterogeneity test under the fixed effect model showed no obvious heterogeneity of TRIM5, FAM8A1, and SHFL across different populations. TRIM5 was positively correlated with the remaining 13 genes. By separating patient samples into TRIM5-high and TRIM5-low groups, we found that up-regulated genes in the TRIM5-high group were mainly enriched in virus-related pathways. Immune cell proportion analysis and flow cytometry revealed that naive CD4(+) T cells were significantly decreased while M2 macrophages were increased in the SLE group. TRIM5 expression levels were negatively correlated with naive CD4(+) T cells but positively correlated with M2 macrophages.ConclusionOur data indicated that TRIM5 might be a key factor that modulates SLE etiology, possibly through naive CD4(+) T cells and M2 macrophages.

01 Dec 2021·Annals of the Rheumatic Diseases

Development and initial validation of diagnostic gene signatures for systemic lupus erythematosus

Letter

Author: Zheng, Qing ; Xuan, Jingxiu ; Shi, Guixiu ; Wang, Bin ; Gao, Zhenyu ; Chen, Shiju ; Chen, Rongjuan ; Liu, Yuan

In this study, we aimed to develop a genetic signature for systemic lupus erythematosus (SLE) diagnosis through bioinformatic analyses of whole blood transcriptome data.Fourteen whole blood transcriptome datasets with at least 20 patients with SLE and 10 controls were integrated with RRA, which included GSE110685, GSE112087, GSE99967, GSE110169, GSE88884, GSE65391, GSE72509, GSE45291, GSE49454, GSE61635,GSE50635, GSE39088, GSE20864 and GSE17755.RRA outcomes suggested that most of those top 100 DEGs were from type I interferon-related pathways such as IFI44L, IFI27 and IFIT1. The top 10 upregulated genes included IFI44L, IFI27, RSAD2, IFIT1, HERC5, IFIT3, IFI44, OASL, CMPK2 and USP18 and were all from type I interferon-related pathways, which were preliminarily selected as one SLE diagnostic genetic signature referred to as RRAtop10 in this study.Based on the gene co-expression modules calculated above, a more complex gene signature was developed by selecting at most 10 genes from each upregulated co-expression module.This complex gene signature (referred to as RRAWGCNA10) consisted of 34 key genes from six independent co-expression modules and included IFI44L, IFI27, RSAD2, IFIT1, HERC5, IFIT3, IFI44, OASL, CMPK2, USP18, LHFPL2, RRM2, CEACAM6, CEACAM8, DEFA4, HP, LCN2, MMP8, OLFM4, OLR1, RNASE2, TCN1, ANKRD22, CASP5, CEACAM1, CLEC4D, DHRS9, DYNLT1, FCGR1B, TLR5, TNFAIP6, TNFSF13B, ANXA3 and SLC26A8.Among those 34 genes, the first 10 genes were identical to those genes in RRAtop10 and were all from the same co-expression module.In summary, this study developed useful gene signatures for SLE diagnosis through bioinformatic analyses of whole blood transcriptomic data, which could effectively differentiate SLE in different datasets and may provide some assistance in the classification of SLE.

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LHFPL2

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