Fig 1.
Schematic image of the gene expression-based strategy for identification of prognostic markers and subsequent IHC evaluation.
For each probe (matching to a gene) in the four discovery data sets, the median gene expression value was used to divide the samples into two groups (high/low). The log-rank test was employed to identify probes significantly associated with OS (P-value < 0.05). Results from the four discovery data sets were then compared and probes that were significantly associated with OS in all four data sets were tested in the same manner in two validation data sets. The genes significantly associated with OS in both data sets were classified as potential prognostic markers. Out of these genes, three were selected for IHC evaluation in two patient cohorts. One of the cohorts was used as an IHC discovery cohort were optimal cut-offs for each markers were selected. These cut-offs were then applied to the cases in the IHC validation cohort. * Only the U133 2plus array subset (n = 102) from Chitale et al. was included. Abbreviations: OS = overall survival, IHC = immunohistochemistry.
Table 1.
Genes with prognostic potential identified in the gene expression-based discovery and validation step.
Fig 2.
Spearman correlation of gene expression levels of the 19 candidate genes in the two validation data sets.
(A) Tomida et al. [15], (B) Tang et al [14]. If multiple probes were available for a gene then the probes with largest standard deviation was chosen to represent the gene. Area of the circles show the absolute value of corresponding correlation coefficients.
Fig 3.
Prognostic value of Ki67 (A), MCM4 (B), TYMS (C), and combined score (D), on overall survival in the IHC discovery cohort.
Fig 4.
Prognostic value of Ki67 (A), MCM4 (B), TYMS (C), and combined score (D), on overall survival in the IHC validation cohort.