Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of human primary lung adenocarcinomas

ABSTRACT: We have investigated whether the early dissemination of tumor cells into bone marrow is associated with a specific molecular pattern in primary lung cancer Experiment Overall Design: two groups of primary lung adenocarcinomas were compared differentiating in the metastatic potential

ORGANISM(S): Homo sapiens

SUBMITTER: Thomas Streichert

PROVIDER: E-GEOD-10799 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Genomic profiles associated with early micrometastasis in lung cancer: relevance of 4q deletion.

Wrage Michaela M Ruosaari Salla S Eijk Paul P PP Kaifi Jussuf T JT Hollmén Jaakko J Yekebas Emre F EF Izbicki Jakob R JR Brakenhoff Ruud H RH Streichert Thomas T Riethdorf Sabine S Glatzel Markus M Ylstra Bauke B Pantel Klaus K Wikman Harriet H

Clinical cancer research : an official journal of the American Association for Cancer Research 20090210 5

<h4>Purpose</h4>Bone marrow is a common homing organ for early disseminated tumor cells (DTC) and their presence can predict the subsequent occurrence of overt metastasis and survival in lung cancer. It is still unclear whether the shedding of DTC from the primary tumor is a random process or a selective release driven by a specific genomic pattern.<h4>Experimental design</h4>DTCs were identified in bone marrow from lung cancer patients by an immunocytochemical cytokeratin assay. Genomic aberrat ...[more]

PMID: 19208797

Similar Datasets

Project description:The diagnosis of primary lung adenocarcinomas with intestinal or mucinous differentiation (PAIM) remains challenging due to the overlapping histomorphological, immunohistochemical and genetic characteristics with lung metastatic colorectal cancer (lmCRC). This study aimed to explore the protein biomarkers that could distinguish between PAIM and lmCRC. To uncover differences between the two diseases, we used tandem mass tagging (TMT)-based shotgun proteomics to characterize proteomes of formalin-fixed paraffin-embedded (FFPE) tumor samples of PAIM (n = 22) and lmCRC (n = 17). Then three machine learning algorithms, namely support vector machine (SVM), random forest and the Least Absolute Shrinkage and Selection Operator (LASSO), were utilized to select protein features with diagnostic significance. These candidate proteins were further validated in an independent cohort (PAIM, n = 11; lmCRC, n = 19) by immunochemistry (IHC) to confirm their diagnostic performance. In total, 105 proteins out of 7871 proteins were significantly dysregulated between PAIM and lmCRC samples and well-separated two groups by Uniform Manifold Approximation and Projection (UMAP). The upregulated proteins in PAIM were involved in actin cytoskeleton organization, platelet degranulation, and regulation of leukocyte chemotaxis, while downregulated ones were involved in mitochondrial transmembrane transport, vasculature development, and stem cell proliferation. A set of 10 candidate proteins (high-level expression in lmCRC: CDH17, ATP1B3, GLB1, OXNAD1, LYST, FABP1; high-level expression in PAIM: NARR, MLPH, S100A14, CK7) was ultimately selected to distinguish PAIM from lmCRC by machine learning algorithms. We further confirmed using IHC that the five protein biomarkers including CDH17, CK7, MLPH, FABP1 and NARR were effective biomarkers for distinguishing PAIM from lmCRC. Our study depicts PAIM-specific proteomic characteristics and demonstrates the potential utility of new protein biomarkers for the differential diagnosis of PAIM and lmCRC. These findings may contribute to improving the diagnostic accuracy and guide appropriate treatments for these patients.

Dataset Information

Transcription profiling of human primary lung adenocarcinomas

Publications

Genomic profiles associated with early micrometastasis in lung cancer: relevance of 4q deletion.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets