TY - GEN
T1 - Identifying miRNA and imaging features associated with metastasis of lung cancer to the brain
AU - Nasser, Sara
AU - Ranade, Aarati R.
AU - Sridhart, Shravan
AU - Haney, Lisa
AU - Korn, Ronald L.
AU - Gotway, Michael B.
AU - Weissy, Glen J.
AU - Kim, Seungchan
N1 - Funding Information:
* Units: 1.mole-'.sec-' (ko); sec-l (k"). Supported by refs. 117 and 119. E = 60 kcal./mole-' is an assumed value.
PY - 2009
Y1 - 2009
N2 - MicroRNAs are small non-coding RNAs of 21-25 nucleotides that might impact regulatory mechanisms in cancer. Due to their influence on cell physiology, alteration of miRNA regulation can be implicated in carcinogenesis and disease progression. In general, one miRNA is predicted to regulate several hundred genes, and as a result, miRNA profiling could serve as a better classifier than gene expression profiling. More than 50% of brain metastasis (brain mets) are associated with non-small cell lung cancer (NSCLC). As miRNAs can regulate certain genes, the presence or absence of certain miRNA could lead to oncogene potential for brain mets. In this study, we combine validated miRNA expression values with imaging features to separate NSCLC brain mets from non-brain mets and identify biomarkers that may indicate possibility of brain mets. This research involves comprehensive miRNA expression profiling, validation of miRNA with qRTPCR, correlation of miRNA with imaging features such as PET/CT and CT Scan. Eleven statistically significant miRNA were identified and matched with imaging features to yield a class separation of brain mets and non-brain mets.
AB - MicroRNAs are small non-coding RNAs of 21-25 nucleotides that might impact regulatory mechanisms in cancer. Due to their influence on cell physiology, alteration of miRNA regulation can be implicated in carcinogenesis and disease progression. In general, one miRNA is predicted to regulate several hundred genes, and as a result, miRNA profiling could serve as a better classifier than gene expression profiling. More than 50% of brain metastasis (brain mets) are associated with non-small cell lung cancer (NSCLC). As miRNAs can regulate certain genes, the presence or absence of certain miRNA could lead to oncogene potential for brain mets. In this study, we combine validated miRNA expression values with imaging features to separate NSCLC brain mets from non-brain mets and identify biomarkers that may indicate possibility of brain mets. This research involves comprehensive miRNA expression profiling, validation of miRNA with qRTPCR, correlation of miRNA with imaging features such as PET/CT and CT Scan. Eleven statistically significant miRNA were identified and matched with imaging features to yield a class separation of brain mets and non-brain mets.
KW - In-silico conditioning
KW - Non-small cell lung cancer
KW - PET/CT scan
KW - miRNA
UR - http://www.scopus.com/inward/record.url?scp=74549220389&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=74549220389&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2009.64
DO - 10.1109/BIBM.2009.64
M3 - Conference contribution
AN - SCOPUS:74549220389
SN - 9780769538853
T3 - 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009
SP - 246
EP - 251
BT - 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009
T2 - 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009
Y2 - 1 November 2009 through 4 November 2009
ER -