scTumorDrug: predicting cell-type-specific drug responses for heterogeneous tumors

It is important to predict cell-type-specific drug responses within the heterogeneous tumors for precision medicine. The single-cell RNA sequencing (scRNA-seq) technique together with drug responses data provides opportunities for this mission. The previous methods were mainly evaluated in datasets derived from cancer cell lines, lacking direct validations on the real tumors derived from mouse models and clinical human samples. In this work, we integrated the labeled scRNA-seq, bulk RNA, and drug response data to develop the computational tool scTumorDrug to predict cell-type-specific drug responses for heterogeneous tumors. Overall, scTumorDrug achieved accurate predictions in public datasets derived from cell lines, mouse models, and clinical human samples, and outperformed previous methods in the selected datasets. Since there is no available experimental validation on drug responses from tumor subpopulations, we established the mouse bladder tumor model to investigate the cell-type-specific drug responses for the small molecule JQ1 by performing single nucleus RNA sequencing and spatial transcriptomics. The mouse model showed that the JQ1 treatment delayed the tumor progression though it did not completely eliminate the bladder tumors. The scTumorDrug found that the Mki67+ urothelial subpopulation was sensitive to JQ1, which was cross-validated by spatial transcriptomics. This observation also provided an explanation for JQ1 efficacy. To summarize, the scTumorDrug can be used in broad application scenarios and we provided cell-type-specific drug response prediction and validation.