Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
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A unique gene expression signature is significantly differentially expressed in tumor-positive or tumor-negative sentinel lymph nodes in patients with melanoma.

Melanoma Research 2017 October
The purpose of this study was to learn whether molecular characterization through gene expression profiling of node-positive and node-negative sentinel lymph nodes (SLNs) in patients with clinical stage I and II melanoma may improve the understanding of mechanisms of metastasis and identify gene signatures for SLNs/SLNs that correlate with diagnosis or clinical outcome. Gene expression profiling was performed on SLN biopsies of 48 (24 SLN and 24 SLN) patients (T3a/b-T4a/b) who underwent staging of SLNs using transcriptome profiling analysis on 5 μm sections of fresh SLNs. U133A 2.0 Affymetrix gene chips were used. Significance analysis of microarrays was used to test the association between gene expression level and SLN status. Genes with fold change more than 1.5 and q value less than 0.05 were considered differentially expressed. Pathway analysis was performed using Ingenuity Pathway Analysis. The Benjamini and Hochberg method was used to adjust for multiple testing in pathway analysis. We identified 89 probe sets that were significantly differentially expressed (1.5-27-fold; q<0.05). Upon performing the pathway analysis, it was found that 25 genes were common among the most significant and biologically relevant canonical pathways. The molecules and pathways that achieved differential expression of highest statistical significance were notably related to melanoma and its microenvironment and to signaling pathways implicated in immunosuppression and development of cancer. A 25-gene signature is significantly differentially expressed between SLN and SLN and is related to melanoma oncogenesis and immunosuppression. The identified expression profile provides a signature of melanoma nodal involvement. These findings warrant further investigation into the mechanisms of metastasis, melanoma metastasis diagnosis, and prediction of outcome.

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