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
Glioblastoma (GBM) is a devastating adult brain cancer with high rates of recurrence and treatment resistance. Cellular heterogeneity and extensive invasion of surrounding brain tissues are characteristic features of GBM that contribute to its intractability. Current GBM model systems do not recapitulate some of the complex features of GBM and have not produced sufficiently-effective treatments. This has cast doubt on the effectiveness of current GBM models and drug discovery paradigms. In search of alternative pre-clinical GBM models, various 3D organoid-based GBM model systems have been developed using human cells. The scalability of these systems and potential to more accurately model characteristic features of GBM, provide promising new avenues for pre-clinical GBM research and drug discovery efforts. Here, we review the current suite of organoid-GBM models, their individual strengths and weaknesses, and discuss their future applications with an emphasis on compound screening.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892608 | PMC |
http://dx.doi.org/10.3389/fncel.2021.605255 | DOI Listing |
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