Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA392410 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5819020.fastq.gz | Fastqsanger.gz | |||
| SRR5819021.fastq.gz | Fastqsanger.gz | |||
| SRR5819022.fastq.gz | Fastqsanger.gz | |||
| SRR5819023.fastq.gz | Fastqsanger.gz | |||
| SRR5819024.fastq.gz | Fastqsanger.gz |
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Project description:Background: The Ras pathway genes KRAS, BRAF or ERBBs have somatic mutations in ~60% of human colorectal carcinomas. At present, it is unknown whether the remaining cases lack mutations activating the Ras pathway, or whether they have acquired mutations in genes hitherto not known to belong to the pathway. Methods: To address the second possibility, and extend the compendium of Ras pathway genes, we used genome-wide transposon mutagenesis of two human colorectal cancer cell systems deprived of their activating KRAS or BRAF allele to identify genes enabling growth in low glucose, a Ras pathway phenotype, when targeted. Results: Of the 163 recurrently targeted genes in the two different genetic backgrounds, one third were known cancer genes and one-fifth had links to the EGFR/Ras/MAPK pathway. When compared to cancer genome sequencing datasets, 9 genes also mutated in human colorectal cancers were identified. Among these, stable knock-down of FOXO3, NCOA3, and TCF7L2 restored growth in low glucose but reduced MEK/MAPK phosphorylation, reduced anchorage-independent growth, and modulated expressions of GLUT1 and Ras pathway related proteins. Knock-down of NCOA3 and FOXO3 significantly decreased the sensitivity to cetuximab of KRAS mutant but not wild-type cells. Conclusions: This work establishes a proof-of-concept that human cell based genome-wide forward genetic screens can assign genes to pathways with clinical importance in human colorectal cancer.
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Project description:Recent genome sequencing efforts have identified millions of somatic mutations in cancer. However, the functional impact of most variants is poorly understood. Here we characterize 194 somatic mutations identified in primary lung adenocarcinomas using L1000 high-throughput gene-expression assays followed by expression-based variant impact phenotyping (eVIP), a method that uses gene expression changes to distinguish impactful from netural somatic mutations. This series represents the main experiment of the study where 8 replicates of wild-type and mutant ORFs are introduced into A549 cell lines. An ORF library containing wild-type and mutated versions of genes found to be mutated in lung cancer are introduced in A549 cell lines and measurements are made using the L1000 high-throughput gene-expression assay. These are done with 8 replicate experiemnts. The data are processed through a computational system, that converts raw fluorescence intensities into differential gene expression signatures. The data at each stage of the pre-processing are available: (LXB) - raw, unprocessed flow cytometry data from Luminex scanners. One LXB file is generated for each well of a 384-well plate, and each file contains a fluorescence intensity value for every observed analyte in the well. (Q2NORM) - gene expression profiles of directly measured landmark transcripts. Normalized using invariant set scaling followed by quantile normalization. (Z-SCORES) - signatures with differentially expressed genes computed by robust z-scores for each profile relative to control (relative to plate population as control)
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