Sarcoidosis extent relates to molecular variability.

The molecular basis of sarcoidosis phenotype heterogeneity and its relationship to effective treatment of sarcoidosis have not been elucidated. Peripheral samples from sarcoidosis subjects who participated in a Phase II study of golimumab [anti-tumour necrosis factor (TNF)-α] and ustekinumab [anti-interleukin (IL)-12p40] were used to measure the whole blood transcriptome and levels of serum proteins. Differential gene and protein expression analyses were used to explore the molecular differences between sarcoidosis phenotypes as defined by extent of organ involvement. The same data were also used in conjunction with an enrichment algorithm to identify gene expression changes associated with treatment with study drugs compared to placebo. Our analyses revealed marked heterogeneity among the three sarcoidosis phenotypes included in the study cohort, including striking differences in enrichment of the interferon pathway. Conversely, enrichments of multiple pathways, including T cell receptor signalling, were similar among phenotypes. We also identify differences between treatment with golimumab and ustekinumab that may explain the differences in trends for clinical efficacy observed in the trial. We find that molecular heterogeneity is associated with sarcoidosis in a manner that may be related to the extent of organ involvement. These findings may help to explain the difficulty in identifying clinically efficacious sarcoidosis treatments and suggest hypotheses for improved therapeutic strategies.

Identifying Determinants of EGFR-Targeted Therapeutic Biochemical Efficacy Using Computational Modeling.

We modeled cellular epidermal growth factor receptor (EGFR) tyrosine phosphorylation dynamics in the presence of receptor-targeting kinase inhibitors (e.g., gefitinib) or antibodies (e.g., cetuximab) to identify systematically the factors that contribute most to the ability of the therapeutics to antagonize EGFR phosphorylation, an effect we define here as biochemical efficacy. Our model identifies distinct processes as controlling gefitinib or cetuximab biochemical efficacy, suggests biochemical efficacy is favored in the presence of certain EGFR ligands, and suggests new drug design principles. For example, the model predicts that gefitinib biochemical efficacy is preferentially sensitive to perturbations in the activity of tyrosine phosphatases regulating EGFR, but that cetuximab biochemical efficacy is preferentially sensitive to perturbations in ligand binding. Our results highlight numerous other considerations that determine biochemical efficacy beyond those reflected by equilibrium affinities. By integrating these considerations, our model also predicts minimum therapeutic combination concentrations to maximally reduce receptor phosphorylation.