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SCLC cell line profiling on HG-U133A arrays set 2

GSE10841 Homo sapiens (human) Expression microarray 46 samples Submitted 2008/05/01 Platform GPL571
At a glance

Expression microarray · human · 46 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Homo sapiens (human)
Topic
Small cell lung cancerThis series is part of our curated briefing on it.
Samples
46 samples: 46 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
RNA expression analysis was performed to compare patterns to sensitivity to BCL2 inhibitors (ABT-263). Overexpression of the prosurvival Bcl-2 family members (Bcl-2, Bcl-xL and Mcl-1) is commonly associated with tumor maintenance, progression and chemoresistance. We previously reported the discovery of ABT-737, a potent, small molecule Bcl-2 family protein inhibitor.
Read the full summary ↓
A major limitation of ABT-737 is that it is not orally bioavailable. This may limit its use for chronic single agent treatment and the flexibility to dose in combination with parenteral chemotherapy. Here we report the discovery and biological properties of ABT-263, a potent, orally bioavailable Bad-like BH3 mimetic (Kiâ??s of < 1 nM for Bcl-2, Bcl-xL and Bcl-w). The oral bioavailability of ABT-263 in preclinical animal models is 20% - 50%, depending on formulation. ABT-263 disrupts Bcl-2/Bcl-xL interactions with pro-death proteins (e.g., Bim) in cells leading to the initiation of apoptosis within 2 hr post-treatment. In human tumor cells, ABT-263 rapidly induces Bax translocation, cytochrome c release and subsequent programmed cell death. Oral administration of ABT-263 alone induces complete tumor regressions in xenograft models of small cell lung cancer and acute lymphoblastic leukemia. In xenograft models of aggressive B-cell lymphoma and multiple myeloma where ABT-263 exhibits modest or no single agent activity, it significantly enhances the efficacy of clinically relevant therapeutic regimens. These data provide the rationale for clinical trials evaluating ABT-263 in SCLC and B-cell malignancies. The oral efficacy of ABT-263 should provide dosing flexibility to maximize clinical utility as both a single agent and in combination with standard chemotherapeutic regimens. Keywords: cell line comparison
This dataset
Open GSE10841 in finder → Find more human microarray datasets → Small cell lung cancer landscape →
Download · which file do I need?

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 (GSE10841_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 ↓

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA107325. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 18451170) ↗
Study design
46 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 46 sample titles: 46 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 6 more — browse all 46 samples with per-sample file links →

More Small cell lung cancer datasets

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.