GEO series

SMO variants explain the majority of drug resistance in basal cell carcinoma [Target Sequencing]

GSE58376 Homo sapiens (human) Other 66 samples Submitted 2015/03/16 Platform GPL15520

At a glance

human · 66 samples

Organism: Homo sapiens (human)
Samples: 66 samples
Data you can get: A processed table (series matrix) and supplementary files from NCBI.

Summary (written by the submitters)

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.

Read the full summary ↓

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

This dataset

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Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE58376_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

Also filed as BioProject PRJNA252375 and SRA study SRP043088. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 25759020) ↗

Samples in this study

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