Differences in protein-protein association networks for lung adenocarcinoma: A retrospective study

Abstract

Various methods to determine the connectivity scores between groups of proteins associated with lung adenocarcinoma are examined. Proteins act together to perform a wide range of functions within biological processes. Hence, identification of key proteins and their interactions within protein networks can provide invaluable information on disease mechanisms. Differential network analysis provides a means of identifying differences in the interactions among proteins between two networks. We use connectivity scores based on the method of partial least squares to quantify the strength of the interactions between each pair of proteins. These scores are then used to perform permutation-based statistical tests. This examines if there are significant differences between the network connectivity scores for individual proteins or classes of proteins. The expression data from a study on lung adenocarcinoma is used in this study. Connectivity scores are computed for a group of 109 subjects who were in the complete remission and as well as for a group of 51 subjects whose cancer had progressed. The distributions of the connectivity scores are similar for the two networks yet subtle but statistically significant differences have been identified and their impact discussed.

Patient-level proteomic network prediction by explainable artificial intelligence

“…The dominant network features in tumors of this cluster were formed by the proteins c-Met, ERCC1, Caspase-8, Snail, PARP, and RB. This expands the results of Datta et al who described this regulatory pattern for LUAD using a partial least squares method 40 . The largest regulatory network they found included ERCC1, PARP, Snail, c-Met, Caspase-8, and Rb, but connections to RB were reduced in a subgroup that showed tumor progression.…”

“…The most important network features were the proteins PARP, Caspase-8, Snail, c-Met, ERCC1, and RB. Importantly, these predicted network patterns that appear to be highly conserved across these samples have also been reported in a study that examined protein regulation in a cohort of LUAD (see also discussion) 40 . Further analysis showed that the inferred interaction strength between these proteins had a bimodal distribution in cancers of the gastrointestinal tract, the lung, and the uterus while LRP scores for other tumors only were distributed around the lower peak (see Supplementary Fig.…”