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
Intrinsic and acquired resistance limit the window of effectiveness for oncogene-targeted cancer therapies. Here, we describe an resistance assay (ISRA) that reliably models acquired resistance to RTK/RAS-pathway-targeted therapies across cell lines. Using osimertinib resistance in -mutated lung adenocarcinoma (LUAD) as a model system, we show that acquired osimertinib resistance can be significantly delayed by inhibition of proximal RTK signaling using SHP2 inhibitors. Isolated osimertinib-resistant populations required SHP2 inhibition to resensitize cells to osimertinib and reduce MAPK signaling to block the effects of enhanced activation of multiple parallel RTKs. We additionally modeled resistance to targeted therapies including the KRAS inhibitors adagrasib and sotorasib, the MEK inhibitor trametinib, and the farnesyl transferase inhibitor tipifarnib. These studies highlight the tractability of resistance assays to model acquired resistance to targeted therapies and provide a framework for assessing the extent to which synergistic drug combinations can target acquired drug resistance.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10788224 | PMC |
http://dx.doi.org/10.1016/j.isci.2023.108711 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!