High-throughput analysis of gene expression data is subject to technological and statistical issues that confuse the underlying expression-condition associations. In this contribution a network-based candidate gene prioritization strategy was applied to the enrichment of a publicly available gene expression dataset, focused on the study of the mechanosensitivity of genes exposed to altered pulmonary matrix stiffness. Results suggested that some genes which had not been taken into account in the original study could have an important role in the processes causing, or affected by, pulmonary fibrosis.