A unique gene expression signature is significantly differentially expressed in tumor-positive or tumor-negative sentinel lymph nodes in patients with melanoma.

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.

A four-marker signature of TNF-RII, TGF-α, TIMP-1 and CRP is prognostic of worse survival in high-risk surgically resected melanoma.

BACKGROUND: E1694 tested GM2-KLH-QS21 vaccine versus high-dose interferon-α2b (HDI) as adjuvant therapy for operable stage IIB-III melanoma. We tested banked serum specimens from patients in the vaccine arm of E1694 for prognostic biomarkers. METHODS: Aushon Multiplex Platform was used to quantitate baseline serum levels of 115 analytes from 40 patients. Least absolute shrinkage and selection operator proportional hazard regression (Lasso PH) was used to select markers that are most informative for relapse-free survival (RFS) and overall survival (OS). Regular Cox PH models were then fit with the markers selected by the Lasso PH. Survival receiver operating characteristic (ROC) analysis was used to evaluate the ability of the models to predict 1-year RFS and 5-year OS. RESULTS: Four markers that include Tumor Necrosis Factor alpha Receptor II (TNF-RII), Transforming Growth Factor alpha (TGF-α), Tissue Inhibitor of Metalloproteinases 1 (TIMP-1), and C-reactive protein (CRP) were found to be most informative for the prediction of OS (high levels correlate with worse prognosis). The dichotomized risk score based on the four markers could significantly separate the OS curves (p = 0.0005). When using the four-marker PH model to predict 5-year OS, we achieved an area under the curve (AUC) of 89% (cross validated AUC = 72%). High baseline TNF-RII was also significantly associated with worse RFS. The RFS with high (above median) TNF-RII was significantly lower than low TNF-RII (p = 0.01). CONCLUSIONS: The biomarker signature consisting of TNFR-II, TGF-α, TIMP-1 and CRP is significantly prognostic of survival in patients with high-risk melanoma and warrants further investigation.