Tissue specificity of in vitro drug sensitivity

Abstract

Objectives: We sought to investigate the tissue specificity of drug sensitivities in large-scale pharmacological studies and compare these associations to those found in drug clinical indications.

Materials and methods: We leveraged the curated cell line response data from PharmacoGx and applied an enrichment algorithm on drug sensitivity values' area under the drug dose-response curves (AUCs) with and without adjustment for general level of drug sensitivity.

Results: We observed tissue specificity in 63% of tested drugs, with 8% of total interactions deemed significant (false discovery rate <0.05). By restricting the drug-tissue interactions to those with AUC > 0.2, we found that in 52% of interactions, the tissue was predictive of drug sensitivity (concordance index > 0.65). When compared with clinical indications, the observed overlap was weak (Matthew correlation coefficient, MCC = 0.0003, P > .10).

Discussion: While drugs exhibit significant tissue specificity in vitro, there is little overlap with clinical indications. This can be attributed to factors such as underlying biological differences between in vitro models and patient tumors, or the inability of tissue-specific drugs to bring additional benefits beyond gold standard treatments during clinical trials.

Conclusion: Our meta-analysis of pan-cancer drug screening datasets indicates that most tested drugs exhibit tissue-specific sensitivities in a large panel of cancer cell lines. However, the observed preclinical results do not translate to the clinical setting. Our results suggest that additional research into showing parallels between preclinical and clinical data is required to increase the translational potential of in vitro drug screening.

Figure 1.

Schematic representation of data input and analysis pipeline.

Figure 2.

Composition and overlap of our compendium of pharmacogenomic datasets. (A) Number of cell lines representing each tissue type with respect to their source dataset. Tissue types represented by <5 cell lines in a given dataset were removed for the dataset. (B) Overlap for drugs, cell lines, and tissue types across datasets.

Figure 3.

Distribution of in vitro drug-tissue associations. Number of significantly associated drugs for each tissue type in our compendium.

Figure 4.

Number of in vitro drug-tissue associations in each pharmacogenomic dataset and meta-analysis. The associations that are significant in a dataset and in the meta-analysis are in blue. The associations found significant in a dataset but not selected after meta-analysis are in red. The associations found nonsignificant in a dataset but ending up selected after meta-analysis are in green.

Figure 5.

Circos plot representing the significant associations for drugs with clinical trial evidence. Light blue and orange boxes represent drugs and tissues, respectively. Red lines represent drug-tissue associations observed only in vitro (referred to as experimental). Pink lines indicate experimental relationships with no clinical relevance. Green lines indicate a clinical application not recognized in preclinical analysis. Blue lines indicate in vitro drug-tissue associations supported by clinical indications.