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: 3122
Function: getPubMedXML

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

The analysis of N6-methyladenosine regulators impacting the immune infiltration in clear cell renal cell carcinoma. | LitMetric

The tumor immune microenvironment (TIME) and N6-methyladenosine (m6A) are related to the progression of several types of cancer. Nevertheless, the impact of m6A on the TIME of clear cell renal cell carcinoma (ccRCC) remains unclear. This study used an unsupervised clustering algorithm to divide the samples into distinct subgroups. The single sample gene set enrichment analysis (ssGSEA) algorithm to estimate the TIME. The correlation between m6A regulators and immune cells in different subgroups was calculated using Spearman analysis. At last, the relationship between IGF2BP2 and HMGA2 was validated in several datasets, including TCGA-KIRC, GEO, and HPA datasets. We found that m6A regulators were differently expressed in several clinical groups. Based on the expression of m6A regulators, we divided the samples into three subgroups. Then, the survival analysis for these three subgroups showed that the cluster 2 subgroup had poor overall survival (OS). Further, we found that IGF2BP2 and IGF2BP3 were essential components in the cluster 2 subgroup using the principal component analysis (PCA) algorithm. In addition, the expression of these two genes was significantly correlated with survival time. At last, we found that HMGA2 was significantly correlated with IGF2BP2 in several datasets, which indicated that HMGA2 is an essential role in affecting IGF2BP2 regulating the TIME. There is a close correlation between m6A regulators and TIME. Moreover, IGF2BP2 is related to the progression of ccRCC and plays an essential role in affecting the TIME.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s12032-021-01645-0DOI Listing

Publication Analysis

Top Keywords

m6a regulators
16
clear cell
8
cell renal
8
renal cell
8
cell carcinoma
8
correlation m6a
8
three subgroups
8
cluster subgroup
8
essential role
8
time
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!