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
Purpose: Colon cancer is one of the leading causes of death worldwide, and screening of effective molecular markers for the diagnosis is prioritised for prevention and treatment. This study aimed to investigate the diagnostic and predictive potential of genes related to the lipid metabolism pathway, regulated by a protein called sterol-regulatory element-binding transcription Factor 2 (SREBF2), for colon cancer and patient outcomes.
Methods: We used machine-learning algorithms to identify key genes associated with SREBF2 in colon cancer based on a public database. A nomogram was created to assess the diagnostic value of these genes and validated in the Cancer Genome Atlas. We also analysed the relationship between these genes and the immune microenvironment of colon tumours, as well as the correlation between gene expression and clinicopathological characteristics and prognosis in the China Medical University (CMU) clinical cohort.
Results: Three genes, , and , were identified as hub genes related to SREBF2 and colon cancer. Using the TCGA dataset, receiver operating characteristic curve analysis showed the area under the curve values of 0.943, 0.976, and 0.868 for , and , respectively. In the CMU cohort, SREBF2 and DHCR7 expression levels were correlated with TNM stage and tumour invasion depth (P < 0.05), and high DHCR7 expression was related to poor prognosis of colon cancer (P < 0.05). Furthermore, gene expression was positively correlated with the abundance of M0 and M1 macrophages and inversely correlated with the abundance of M2 macrophages, suggesting that the immune microenvironment may play a role in colon cancer surveillance. There was a correlation between and expression across cancers in the TCGA database.
Conclusion: This study highlights the potential of as a diagnostic marker and therapeutic target for colon cancer.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10723182 | PMC |
http://dx.doi.org/10.2147/OTT.S428150 | DOI Listing |
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