Dataset Information

PSGL-1 is a novel tumor microenvironment prognostic biomarker with cervical high-grade squamous lesions and more.

ABSTRACT:

Background

Macrophages secrete many cytokines and chemokines, which can provoke either an anti-tumor or pro-tumor immune response. P-selectin glycoprotein ligand-1 (PSGL-1) is expressed in macrophages and plays a vital role in synergizing for a more robust anti-tumor response. However, there are few studies about PSGL-1 expression status and clinical value of biological function in cervical cancer.

Methods

In this study, 565 participants were enrolled. PSGL-1 mRNA was detected by real-time quantitative PCR (qPCR) with cervical cytology specimens. The relationship between PSGL-1 and cervical intraepithelial neoplasia in two grades and more (CIN2+) was analyzed, and the optimal cut-off values of PSGL-1 to predict CIN2+ were calculated. In addition, the clinical significance of PSGL-1 in cervical cancer was determined by Kaplan-Meier Cox regression based on the database.

Results

The mean PSGL-1 increased significantly with cervical lesion development, especially compared with CIN2+ (p<0.05). Moreover, the expression of PSGL-1 increased significantly in HPV-16/18 positive and HPV-18 positive, but not in HPV-16 positive and other HR-HPV positive. And then, it demonstrated that the area under the receiver operating characteristic curve (AUC) of PSGL-1 was 0.820, and an optimal cut-off 0.245. Furthermore, the PSGL-1 had the highest odds ratio and highest OR (OR= 8.707; 95% CI (.371-19.321)) for the detection of CIN 2+. In addition, our result also indicated that higher PSGL-1 expression was significantly related to a better prognosis in cervical cancer due to immune cell infiltration.

Conclusions

PSGL-1≥0.245 in cervical cytology specimens is a new auxiliary biomarker of CIN2+, and it may be a promising prognosis predictor and potential immunotherapy target linked with immune infiltration of cervical cancer.

SUBMITTER: Lin Y

PROVIDER: S-EPMC10030516 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

PSGL-1 is a novel tumor microenvironment prognostic biomarker with cervical high-grade squamous lesions and more.

Lin Yingying Y Huang Shan S Qi Yuanjie Y Xie Li L Jiang Junying J Li Hua H Chen Zhiwei Z

Frontiers in oncology 20230308

<h4>Background</h4>Macrophages secrete many cytokines and chemokines, which can provoke either an anti-tumor or pro-tumor immune response. P-selectin glycoprotein ligand-1 (PSGL-1) is expressed in macrophages and plays a vital role in synergizing for a more robust anti-tumor response. However, there are few studies about PSGL-1 expression status and clinical value of biological function in cervical cancer.<h4>Methods</h4>In this study, 565 participants were enrolled. PSGL-1 mRNA was detected by ...[more]

PMID: 36969026

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Project description:It is crucial to classify cervical lesions into high-grade squamous intraepithelial lesions (HSILs) and low-grade SILs (LSILs), as LSILs are conservatively treated by observation, based on an expectation of natural regression, whereas HSILs usually require electrosurgical excision. In the present study, peripheral blood gene expression profiles were analyzed to identify transcriptomic biomarkers distinguishing HSILs from LSILs. A total of 102 blood samples were collected from women with cervical SILs (66 HSIL and 36 LSIL) for microarray hybridization. Candidate gene signatures were identified using AdaBoost algorithms, and a predictive model was constructed using logistic regression to differentiate HSILs from LSILs. To correct for possible bias as a result of the limited sample size and to verify the stability of the predictive model, a two-fold cross validation and null set analysis was conducted over 1,000 iterations. The functions of the transcriptomic biomarkers were then analyzed to elucidate the pathogenesis of cervical SIL. A total of 10 transcriptomic genes (STMN3, TRPC4AP, DYRK2, AGK, KIAA0319L, GRPEL1, ZFC3H1, LYL1, ITGB1 and ARHGAP18) were identified. The predictive model based on the 10-gene panel exhibited well-discriminated power. A cross validation process using known disease status exhibited almost the same performance as that of the predictive model, whereas null-set analysis with randomly reassigned disease status exhibited much lower predictive performance for distinguishing HSILs from LSILs. These biomarkers were involved in the 'Rho GTPase cycle', 'mitochondrial protein import', 'oncogenic MAPK signaling', 'integrin cell surface interaction' and 'signaling by BRAF and RAF fusions'. In conclusion, peripheral blood gene expression analysis is a promising method for distinguishing HSILs from LSILs. The present study proposes 10 candidate genes that could be used in the future as diagnostic biomarkers and potential therapeutic targets for cervical SILs. A simple, non-invasive blood test would be clinically useful in the diagnosis and classification of patients with cervical SILs.

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Project description:Tumor microenvironment (TME) is emerging as an essential part of cervical cancer (CC) tumorigenesis and development, becoming a hotspot of research these years. However, comprehending the specific composition of TME is still facing enormous challenges, especially the immune and stromal components. In this study, we downloaded the RNA-seq profiles and somatic mutation data of 309 CC cases from The Cancer Genome Atlas (TCGA) database, which were analyzed by integrative bioinformatical methods. Initially, ESTIMATE computational method was employed to calculate the amount of immune and stromal components. Then, based on the high- and low-immunity cohorts, we recognized the differentially expressed genes (DEGs) as well as the differentially mutated genes (DMGs). Additionally, we conducted an intersection analysis of DEGs and DMGs, ultimately determining an immune-related prognostic signature, GTPase, IMAP Family Member 4 (GIMAP4). Moreover, sequential analyses demonstrated that GIMAP4 was a protective factor in CC, positively correlated with the overall survival (OS) and negatively with distant metastasis. Besides, we utilized the Gene Set Enrichment Analysis (GSEA) to explore the enrichment-pathways in high and low-expression cohorts of GIMAP4. The results indicated that the genes of the high-expression cohort had a high enrichment in immune-related biological processes and metabolic activities in the low one. Furthermore, CIBERSORT analysis was applied to evaluate the proportion of tumor-infiltrating immune cells (TICs), illustrating that several activated TICs were strongly associated with GIMAP4 expression, which suggested that GIMAP4 had the potential to be an indicator for the immune state in TME of CC. Hence, GIMAP4 contributed to predicting the CC patients' clinical outcomes, such as survival rate, distant metastasis and immunotherapy response. Moreover, GIMAP4 could serve as a promising biomarker for TME remodeling, suggesting the possible underlying mechanisms of tumorigenesis and CC progression, which may provide different therapeutic perceptions of CC, and therefore improve treatment.

Dataset Information

PSGL-1 is a novel tumor microenvironment prognostic biomarker with cervical high-grade squamous lesions and more.

Background

Methods

Results

Conclusions

Publications

PSGL-1 is a novel tumor microenvironment prognostic biomarker with cervical high-grade squamous lesions and more.

Similar Datasets

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