A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

HPV-driven heterogeneity in cervical cancer: study on the role of epithelial cells and myofibroblasts in the tumor progression based on single-cell RNA sequencing analysis. | LitMetric

AI Article Synopsis

  • The study investigates the tumor microenvironment in cervical cancer (CC) to understand how HPV status influences treatment options.
  • Using data from the Gene Expression Omnibus and single-cell RNA sequencing, researchers identified distinct cell clusters and noted that HPV-negative samples had increased immune infiltration while HPV-positive samples showed higher cell proliferation.
  • The findings suggest that HPV infection alters immune responses and tumor behavior, indicating new pathways for developing personalized cancer therapies.

Article Abstract

Background: Cervical cancer (CC) is a neoplasia with a high heterogeneity. We aimed to explore the characteristics of tumor microenvironment (TME) for CC treatment.

Methods: HPV positive (+) and negative (-) samples from cervical cancer (CC) patients were sourced from the Gene Expression Omnibus (GEO) database. The single-cell RNA sequencing (scRNA-seq) data were processed and annotated for cell types utilizing the Seurat package. Following this, the expression levels and biological roles of the marker genes were analyzed applying real-time PCR (RT-PCR) and transwell assays. Furthermore, the enrichment of genes with significantly differential expressions and copy number variations was assessed by the ClusterProlifer and inferCNV software packages.

Results: Seven main cell clusters were classified based on a total of 12,431 cells. The HPV- CC samples exhibited a higher immune cell infiltration level, while epithelial cells and myofibroblasts had higher proportion in the HPV+ CC samples with extensive heterogeneity. Immune pathways including antigen treatment and presentation, immunoglobulin production and T cell mediated immunity were significantly activated in the HPV- CC group with lower cell cycle and proliferation activity. However, the anti-tumor immunity of these cells was inhibited in HPV+ CC group with higher cell proliferation activity. Moreover, the amplification and loss of CNVs also supported that these cells in HPV- CC samples were prone to anti-tumor activation. Further cell validation results showed that except GZMA, the levels of APOC1, CEACAM6, FOXP3, SFRP4 and TFF3 were all higher in CC cells Hela, and that silencing TFF3 could inhibit the migration and invasion of CC cells .

Conclusion: This study highlighted the critical role of HPV infection in CC progression, providing a novel molecular basis for optimizing the current preventive screening and personalized treatment for the cancer.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438433PMC
http://dx.doi.org/10.7717/peerj.18158DOI Listing

Publication Analysis

Top Keywords

cervical cancer
12
epithelial cells
8
cells myofibroblasts
8
single-cell rna
8
rna sequencing
8
cells hpv-
8
hpv- samples
8
proliferation activity
8
cells
7
cell
7

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!