Biomarkers associated with metastasis of lung cancer to brain predict patient survival

Sara Nasser; Aarati R. Ranade; Shravan Sridhar; Lisa Haney; Ronald L. Korn; Michael B. Gotway; Glen J. Weiss; Seungchan Kim

doi:10.1504/IJDMB.2011.040385

Biomarkers associated with metastasis of lung cancer to brain predict patient survival

Sara Nasser, Aarati R. Ranade, Shravan Sridhar, Lisa Haney, Ronald L. Korn, Michael B. Gotway, Glen J. Weiss, Seungchan Kim

Diagnostic Radiology

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

MicroRNAs influence cell physiology; alteration in miRNA regulation can be implicated in carcinogenesis and disease progression. Generally, one miRNA is predicted to regulate several hundred genes, and as a result, miRNAs could serve as a better classifier than gene expression. We combine validated miRNA expression values with imaging features to classify NSCLC brain mets from non-brain mets and identify possible biomarkers of brain mets. This research involves comprehensive miRNA expression profiling, evaluation of normalisation techniques and combination of miRNA with imaging features FDG-PET/CT and CT Scan. The biomarkers were validated on an independent data set to predict potential brain mets.

Original language	English (US)
Pages (from-to)	287-307
Number of pages	21
Journal	International Journal of Data Mining and Bioinformatics
Volume	5
Issue number	3
DOIs	https://doi.org/10.1504/IJDMB.2011.040385
State	Published - May 2011

Keywords

Bioinformatics
Data mining
FDG-PET/CT scan
In-silico conditioning
Lung cancer
Microrna biomarkers

ASJC Scopus subject areas

Information Systems
General Biochemistry, Genetics and Molecular Biology
Library and Information Sciences

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10.1504/IJDMB.2011.040385

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title = "Biomarkers associated with metastasis of lung cancer to brain predict patient survival",

abstract = "MicroRNAs influence cell physiology; alteration in miRNA regulation can be implicated in carcinogenesis and disease progression. Generally, one miRNA is predicted to regulate several hundred genes, and as a result, miRNAs could serve as a better classifier than gene expression. We combine validated miRNA expression values with imaging features to classify NSCLC brain mets from non-brain mets and identify possible biomarkers of brain mets. This research involves comprehensive miRNA expression profiling, evaluation of normalisation techniques and combination of miRNA with imaging features FDG-PET/CT and CT Scan. The biomarkers were validated on an independent data set to predict potential brain mets.",

keywords = "Bioinformatics, Data mining, FDG-PET/CT scan, In-silico conditioning, Lung cancer, Microrna biomarkers",

author = "Sara Nasser and Ranade, {Aarati R.} and Shravan Sridhar and Lisa Haney and Korn, {Ronald L.} and Gotway, {Michael B.} and Weiss, {Glen J.} and Seungchan Kim",

year = "2011",

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AU - Nasser, Sara

AU - Ranade, Aarati R.

AU - Sridhar, Shravan

AU - Haney, Lisa

AU - Korn, Ronald L.

AU - Gotway, Michael B.

AU - Weiss, Glen J.

AU - Kim, Seungchan

PY - 2011/5

Y1 - 2011/5

N2 - MicroRNAs influence cell physiology; alteration in miRNA regulation can be implicated in carcinogenesis and disease progression. Generally, one miRNA is predicted to regulate several hundred genes, and as a result, miRNAs could serve as a better classifier than gene expression. We combine validated miRNA expression values with imaging features to classify NSCLC brain mets from non-brain mets and identify possible biomarkers of brain mets. This research involves comprehensive miRNA expression profiling, evaluation of normalisation techniques and combination of miRNA with imaging features FDG-PET/CT and CT Scan. The biomarkers were validated on an independent data set to predict potential brain mets.

AB - MicroRNAs influence cell physiology; alteration in miRNA regulation can be implicated in carcinogenesis and disease progression. Generally, one miRNA is predicted to regulate several hundred genes, and as a result, miRNAs could serve as a better classifier than gene expression. We combine validated miRNA expression values with imaging features to classify NSCLC brain mets from non-brain mets and identify possible biomarkers of brain mets. This research involves comprehensive miRNA expression profiling, evaluation of normalisation techniques and combination of miRNA with imaging features FDG-PET/CT and CT Scan. The biomarkers were validated on an independent data set to predict potential brain mets.

KW - Bioinformatics

KW - Data mining

KW - FDG-PET/CT scan

KW - In-silico conditioning

KW - Lung cancer

KW - Microrna biomarkers

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Biomarkers associated with metastasis of lung cancer to brain predict patient survival

Abstract

Keywords

ASJC Scopus subject areas

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