Transcriptomics

Dataset Information

0

Integrinated Omic analysis of lung cancer reveals metabolism proteome signatures with prognostic impact


ABSTRACT: Cancer results from processes prone to selective pressure and dysregulation acting along the sequence-to-phenotype continuum DNA→RNA→Protein→Disease. However, the extent to which cancer is a manifestation of the proteome is unknown. Here we present an integrated omic map representing non-small cell lung carcinoma. Dysregulated proteins not previously implicated as cancer drivers are encoded throughout the genome including but not limited to regions of recurrent DNA amplification/deletion. Clustering reveals signatures composed of metabolism proteins particularly highly recapitulated between patient-matched primary and xenograft tumours. Interrogation of The Cancer Genome Atlas reveals cohorts of patients with lung and other cancers that have DNA alterations in genes encoding the signatures, and this was accompanied by differences in survival. The recognition of genome and proteome alterations as related products of selective pressure driving the disease phenotype may be a general approach to uncover and group together cryptic, polygenic disease drivers.

ORGANISM(S): Homo sapiens

PROVIDER: GSE62113 | GEO | 2014/10/09

SECONDARY ACCESSION(S): PRJNA263446

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2014-10-09 | E-GEOD-62113 | biostudies-arrayexpress
2024-04-29 | GSE167155 | GEO
2014-09-16 | E-GEOD-60753 | biostudies-arrayexpress
| MSV000082970 | MassIVE
| PRJNA263446 | ENA
2015-01-19 | E-GEOD-63452 | biostudies-arrayexpress
2013-01-02 | E-GEOD-42355 | biostudies-arrayexpress
2013-03-07 | E-GEOD-44929 | biostudies-arrayexpress
| PRJNA329139 | ENA
2014-09-16 | GSE60753 | GEO