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Series GSE58375 Query DataSets for GSE58375
Status Public on Mar 16, 2015
Title SMO variants explain the majority of drug resistance in basal cell carcinoma [RNA-Seq]
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary Advanced basal cell carcinomas (BCCs) frequently acquire resistance to Smoothened (SMO) inhibitors through unknown mechanisms, providing a unique opportunity to study human tumor evolution. Here, we identify SMO mutations in 50% (22/44) of resistant BCCs compared with 5.6% (2/36) of untreated BCCs (p<0.0001), and show that these mutations maintain Hedgehog signaling in the presence of SMO inhibitors. Alterations include four ligand binding pocket (LBP) mutations that define sites of inhibitor binding and four variants that confer constitutive activity and inhibitor resistance, thus defining pivotal residues of SMO that ensure receptor autoinhibition. Finally, we show that both classes of SMO variants respond to the aPKC-ι/λ inhibitor PSI and GLI2 antagonist ATO that operate downstream of SMO
Overall design Genome-wide gene expression profiling of 8 normal skin biopsies, 9 resistant basal cell cancers and 4 sensitive basal cell cancers.
Contributor(s) Atwood SX, Sarin KY, Li J, Kim G, Rezaee M, Ally MS, Kim J, Yao C, Whitson RJ, Chang AS, Oro AE, Tang JY
Citation(s) 25759020
Submission date Jun 10, 2014
Last update date May 15, 2019
Contact name Jiang Li
Phone 6507258839
Organization name Stanford University
Department Dermatology
Lab Tony Oro
Street address 269 Campus Drive, Stanford University
City Stanford
State/province CA
ZIP/Postal code 94305
Country USA
Platforms (1)
GPL16791 Illumina HiSeq 2500 (Homo sapiens)
Samples (21)
GSM1409334 RNASeq_Normal1
GSM1409335 RNASeq_Normal2
GSM1409336 RNASeq_Normal3
This SubSeries is part of SuperSeries:
GSE58377 SMO variants explain the majority of drug resistance in basal cell carcinoma
BioProject PRJNA252377
SRA SRP043085

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SOFT formatted family file(s) SOFTHelp
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Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE58375_RNAseq_Expression_Matrix.xlsx.gz 7.9 Mb (ftp)(http) XLSX
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Raw data are available in SRA
Processed data are available on Series record

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