ArrayVigil: a methodology for statistical comparison of gene signatures using segregated-one-tailed (SOT) Wilcoxon's signed-rank test

Age-related transcriptome changes in melanoma patients with tumor-positive sentinel lymph nodes

Age is an important factor for determining the outcome of melanoma patients. Sentinel lymph node (SLN) status is also a strong predictor of survival for melanoma. Paradoxically, older melanoma patients have a lower incidence of SLN metastasis but a higher mortality rate when compared with their younger counterparts. The mechanisms that underlie this phenomenon remain unknown. This study uses three independent datasets of RNA samples from patients with melanoma metastatic to the SLN to identify age-related transcriptome changes in SLNs and their association with outcome. Microarray was applied to the first dataset of 97 melanoma patients. NanoString was performed in the second dataset to identify the specific immune genes and pathways that are associated with recurrence in younger versus older patients. qRT-PCR analysis was used in the third dataset of 36 samples to validate the differentially expressed genes (DEGs) from microarray and NanoString. These analyses show that FOS, NR4A, and ITGB1 genes were significantly higher in older melanoma patients with positive SLNs. IRAK3- and Wnt10b-related genes are the major pathways associated with recurrent melanoma in younger and older patients with tumor-positive SLNs, respectively. This study aims to elucidate age-related differences in SLNs in the presence of nodal metastasis.

A novel gene expression index (GEI) with software support for comparing microarray gene signatures

This study was aimed to examine the validity of commonly used statistical tests for comparison of expression data from simulated and real gene signatures as well as pathway-characterized gene sets. A novel algorithm based on 10 sub-gradations (5 for up- and 5 for down-regulation) of fold-changes has been designed and testified using an Excel add-in software support. Our findings showed the limitations of conventional statistics for comparing the microarray gene expression data. However, the newly introduced Gene Expression Index (GEI) appeared to be more robust and straightforward for two-group comparison of normalized data. The software automation simplifies the task and the results are displayed in a comprehensive format including a color-coded bar showing the intensity of cumulative gene expression.

SCEW: a Microsoft Excel add-in for easy creation of survival curves

Survival curves are frequently used for reporting survival or mortality outcomes of experimental pharmacological/toxicological studies and of clinical trials. Microsoft Excel is a simple and widely used tool for creation of numerous types of graphic presentations however it is difficult to create step-wise survival curves in Excel. Considering the familiarity of clinicians and biomedical scientists with Excel, an algorithm survival curves in Excel worksheet (SCEW) has been developed for easy creation of survival curves directly in Excel worksheets. The algorithm has been integrated in the form of Excel add-in for easy installation and usage. The program is based on modification of frequency data for binary break-up using the spreadsheet formula functions whereas a macro subroutine automates the creation of survival curves. The advantages of this program are simple data input, minimal procedural steps and the creation of survival curves in the familiar confines of Excel.