Dataset Information

Profiling of human lung tissues on 11 normal control, 11 patient and 11 corresponding mouse xenograft tumours

ABSTRACT: The total protein expression level of 11 paired human normal, human lung cancer samples and correspoding mouse xenograft samples were analyzed by LC-MS/MS. These protein expression data were than compared with corresponding DNA copy number changes and mRNA expression level changes among these samples.

OTHER RELATED OMICS DATASETS IN: PRJNA263446

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Lung

DISEASE(S): Lung Benign Neoplasm

SUBMITTER: Jiefei Tong

LAB HEAD: Mike F. Moran

PROVIDER: PXD000853 | Pride | 2014-12-04

REPOSITORIES: Pride

ACCESS DATA

Publications

Integrated omic analysis of lung cancer reveals metabolism proteome signatures with prognostic impact.

Li Lei L Wei Yuhong Y To Christine C Zhu Chang-Qi CQ Tong Jiefei J Pham Nhu-An NA Taylor Paul P Ignatchenko Vladimir V Ignatchenko Alex A Zhang Wen W Wang Dennis D Yanagawa Naoki N Li Ming M Pintilie Melania M Liu Geoffrey G Muthuswamy Lakshmi L Shepherd Frances A FA Tsao Ming Sound MS Kislinger Thomas T Moran Michael F MF

Nature communications 20141128

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 ...[more]

PMID: 25429762

Similar Datasets

Project description:Osteosarcoma is the most common malignancy of bone, and occurs most frequently in children and adolescents. Currently, the most reliable technique for prognostication is measuring histopathologic tumor necrosis following preoperative chemotherapy, and favourable prognosis is signified by 90% or greater estimated necrosis of the tumour. Neither genetic testing nor molecular biomarkers have been described for this tumour. We used the novel nanoString mRNA expression analysis system to analyzed total RNA from 35 flash-frozen sporadic paediatric osteosarcoma biopsy and resection specimens to quantify mRNA expression for 17 oncogenes and tumour suppressor genes. Three oncogenes, cell cycle regulator gene CDC5L, the RecQ DNA helicase gene RECQL4, and the cyclin-dependent kinase gene CDK4, were more highly expressed (p<0.05) in tumours which responded poorly to neoadjuvant chemotherapy. A similar trend (p<0.10) was identified for the osteoblast-specific transcription factor gene RUNX2. No statistically significant difference existed in comparing expression of CDC5L, RECQL4, CDK4, and RUNX2 between biopsy and resection samples. Additionally, analysis of expression data in the context of histological subtype yielded preliminary results for deducing molecular subtypes of osteosarcomas. Osteoblastic osteosarcomas possessed higher expression of CDKN1A, PTEN, and RUNX2 relative to their fibroblastic counterparts (p<0.05). This research study shows that CDC5L, RECQL4, and CDK4 tumour expression levels may be useful for identifying patients who may not benefit from the current standardized chemotherapy regimen. Total RNA was isolated from 52 pediatric osteosarcoma samples (prechemotherapy biopsies and resections), 3 osteosarcoma cell lines, and normal human osteoblasts. nanoString mRNA expression analysis was applied to samples split between 3 batches to compare samples based on clinical and pathologic data reports, and to compare samples with normal human osteoblasts. For 43 samples, there were complete data and the RNA was successfully assayed. Analysis was performed using R.

Dataset Information

Profiling of human lung tissues on 11 normal control, 11 patient and 11 corresponding mouse xenograft tumours

Publications

Integrated omic analysis of lung cancer reveals metabolism proteome signatures with prognostic impact.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure