Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285097015> ?p ?o ?g. }
- W4285097015 endingPage "e09616" @default.
- W4285097015 startingPage "e09616" @default.
- W4285097015 abstract "Discover potential biomarkers of the response for anti-cancer therapies, including traditional Chinese medicine (TCM), is a critical but much different task in the field of cancer research. Based on accumulated data and sophisticated methods, multi-omics analysis provides a feasible strategy for the discovery of potential therapeutic biomarkers. Here, we screened the potential therapeutic biomarkers for anti-cancer compounds in TCM through multi-omics data analysis. Firstly, compounds in TCM were collected from the public databases. Then, the molecules that those compounds can intervene on cell lines were carefully filtered out from existing drug bioactivity datasets. Finally, multi-omics analysis including gene mutation analysis, differential expression gene analysis, copy number variation analysis and clinical survival analysis for pan-cancer were conducted to screen potential therapeutic biomarkers for compounds in TCM. 13 molecules of compounds in TCM namely ERBB2, MYC, FLT4, TEK, GLI1, TOP2A, PDE10A, SLC6A3, GPR55, TERT, EGFR, KCNA3 and HDAC4 are differentially expressed, high frequently mutated, obtain high copy number variation rate and also significant in survival, are considered as the potential therapeutic biomarkers." @default.
- W4285097015 created "2022-07-14" @default.
- W4285097015 creator A5044708050 @default.
- W4285097015 creator A5079034229 @default.
- W4285097015 date "2022-09-01" @default.
- W4285097015 modified "2023-09-30" @default.
- W4285097015 title "Multi-omics analysis to screen potential therapeutic biomarkers for anti-cancer compounds" @default.
- W4285097015 cites W1975875968 @default.
- W4285097015 cites W1987710883 @default.
- W4285097015 cites W2010581642 @default.
- W4285097015 cites W2020026524 @default.
- W4285097015 cites W2020541351 @default.
- W4285097015 cites W2034197594 @default.
- W4285097015 cites W2035618305 @default.
- W4285097015 cites W2041440766 @default.
- W4285097015 cites W2043398720 @default.
- W4285097015 cites W2050113624 @default.
- W4285097015 cites W2075463771 @default.
- W4285097015 cites W2094678200 @default.
- W4285097015 cites W2108068107 @default.
- W4285097015 cites W2117660667 @default.
- W4285097015 cites W2121003886 @default.
- W4285097015 cites W2125789330 @default.
- W4285097015 cites W2126547130 @default.
- W4285097015 cites W2135989615 @default.
- W4285097015 cites W2148223818 @default.
- W4285097015 cites W2180481128 @default.
- W4285097015 cites W2230320310 @default.
- W4285097015 cites W2329659234 @default.
- W4285097015 cites W2460110786 @default.
- W4285097015 cites W2472042329 @default.
- W4285097015 cites W2570401594 @default.
- W4285097015 cites W2575837388 @default.
- W4285097015 cites W2599586112 @default.
- W4285097015 cites W2625559053 @default.
- W4285097015 cites W2766490148 @default.
- W4285097015 cites W2767090924 @default.
- W4285097015 cites W2767377392 @default.
- W4285097015 cites W2767891136 @default.
- W4285097015 cites W2797722903 @default.
- W4285097015 cites W2804524004 @default.
- W4285097015 cites W2806041148 @default.
- W4285097015 cites W2899291554 @default.
- W4285097015 cites W2900832683 @default.
- W4285097015 cites W2911482348 @default.
- W4285097015 cites W2918849193 @default.
- W4285097015 cites W2949066452 @default.
- W4285097015 cites W3011090040 @default.
- W4285097015 cites W3017710116 @default.
- W4285097015 cites W3071810363 @default.
- W4285097015 cites W3086660972 @default.
- W4285097015 cites W3090131714 @default.
- W4285097015 cites W3108958457 @default.
- W4285097015 cites W3113136031 @default.
- W4285097015 cites W3118808299 @default.
- W4285097015 cites W3133857097 @default.
- W4285097015 cites W3153612641 @default.
- W4285097015 cites W3170986249 @default.
- W4285097015 cites W4206841660 @default.
- W4285097015 doi "https://doi.org/10.1016/j.heliyon.2022.e09616" @default.
- W4285097015 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36091949" @default.
- W4285097015 hasPublicationYear "2022" @default.
- W4285097015 type Work @default.
- W4285097015 citedByCount "1" @default.
- W4285097015 countsByYear W42850970152022 @default.
- W4285097015 crossrefType "journal-article" @default.
- W4285097015 hasAuthorship W4285097015A5044708050 @default.
- W4285097015 hasAuthorship W4285097015A5079034229 @default.
- W4285097015 hasBestOaLocation W42850970151 @default.
- W4285097015 hasConcept C104317684 @default.
- W4285097015 hasConcept C121608353 @default.
- W4285097015 hasConcept C124535831 @default.
- W4285097015 hasConcept C157585117 @default.
- W4285097015 hasConcept C29537977 @default.
- W4285097015 hasConcept C46111723 @default.
- W4285097015 hasConcept C54355233 @default.
- W4285097015 hasConcept C60644358 @default.
- W4285097015 hasConcept C67082663 @default.
- W4285097015 hasConcept C70721500 @default.
- W4285097015 hasConcept C71924100 @default.
- W4285097015 hasConcept C86803240 @default.
- W4285097015 hasConceptScore W4285097015C104317684 @default.
- W4285097015 hasConceptScore W4285097015C121608353 @default.
- W4285097015 hasConceptScore W4285097015C124535831 @default.
- W4285097015 hasConceptScore W4285097015C157585117 @default.
- W4285097015 hasConceptScore W4285097015C29537977 @default.
- W4285097015 hasConceptScore W4285097015C46111723 @default.
- W4285097015 hasConceptScore W4285097015C54355233 @default.
- W4285097015 hasConceptScore W4285097015C60644358 @default.
- W4285097015 hasConceptScore W4285097015C67082663 @default.
- W4285097015 hasConceptScore W4285097015C70721500 @default.
- W4285097015 hasConceptScore W4285097015C71924100 @default.
- W4285097015 hasConceptScore W4285097015C86803240 @default.
- W4285097015 hasIssue "9" @default.
- W4285097015 hasLocation W42850970151 @default.
- W4285097015 hasLocation W42850970152 @default.
- W4285097015 hasLocation W42850970153 @default.
- W4285097015 hasOpenAccess W4285097015 @default.