A combined gene expression data analysis approach has been employed to investigate the impact of VDAC1 expression on survival, which was statistically significant in all individual datasets examined. Several recent studies analysing microarray data for prognostic Doxorubicin Topoisomerase inhibitor markers in NSCLC have produced inconsistent results. The distinct lack of overlap associated between these signatures reflects instability and is attributed to small sample sizes with less than 200 samples used per study. Analysis of multiple datasets, for example combined analysis of microarray gene expression datasets addressing similar biological questions conducted at an interpretational level by meta-analysis, can enable more accurate results. Many studies propose methods for meta-analysis of microarray data with the aim of identifying significantly differentially expressed genes across studies using statistical techniques that avoid the direct comparison of gene expression values. The evaluation of multiple datasets as employed in this study has been shown to yield more reliable and valid results, because they are based on large sample numbers and the individual bias caused by each study is weakened. It is not known why VDAC1 correlates with poor survival outcomes. To understand the most relevant genetic features of VDAC1 overexpressing NSCLC, we conducted a gene expression meta-analysis to identify a subset of genes that were significantly enriched. We employed stringent statistical criteria, combined with a large sample size to support the identification of these VDAC1-covariant genes. VDAC1 and 6 gene signature was then validated across breast, myeloma and NCI-60 datasets, suggesting enrichment of genes which were independent of the type of cancer. Interestingly, of the 6 genes identified as being conserved and significantly differentially regulated in the high VDAC1 expressing group, most were functionally linked to the regulation of protein turnover. These genes included heat shock 70kDa protein 4, ubiquitin-conjugating enzyme E2D 2, and heat shock 70kDa protein 9, encoding a glucose regulated 75 kilodalton protein previously reported as correlating with poor survival in colorectal cancer. HSPA9 also binds and inactivates wild type p53, and regulates the RAS RAF MEK pathway. Similarly, p53 and RAS are targets of GTPase activating protein binding protein 1, and shown to predict shorter survival in oesophageal cancer. Casein kinase 1, alpha 1 regulates protein turnover via initiation of translation via EIF2 and participates in wnt signalling; a homologue CSKNK2A1 has been previously identified as an independent predictor of survival in squamous cell lung cancer. Like G3BP1, heterogeneous nuclear ribonucleoprot.