Tumor relapse-free survival prognosis related consistency between cancer tissue and adjacent normal tissue in drug repurposing for solid tumor via connectivity map

Abstract Traditional drug discovery encounters challenges, including high costs, time-intensive processes, and inherent risks. Drug repurposing emerges as a compelling alternative strategy to identify new indications for investigational or approved drugs, circumventing these obstacles. Among the various drug repurposing methods, the Disease-specific Signature-based Connectivity Map (Cmap) approach is widely utilized. However, the commonly employed method for constructing disease-specific signatures, known as Differentially Expressed Genes (DEG), faces issues related to inconsistencies between dysregulated genes and the prognosis of genes in tumor tissue, as well as discrepancies in prognosis genes between tumor and normal tissues. In this study, we propose a novel approach, Prognosis Consistency Scoring (PCS), aimed at addressing these inconsistencies. PCS measures the consistency of gene prognosis between tumor and normal tissues by combining the Recurrence-Free Survival (RFS) prognosis power of genes in both contexts. Disease-specific signatures are then constructed based on PCS, and drug repurposing is performed using the Cmap and Lincs Unified Environment (CLUE). Validation of predicted drugs is conducted using data from DrugBank and ClinicalTrials databases. Our findings reveal that the aforementioned inconsistencies are pervasive. Compared to signatures based on DEGs, PCS-based signatures exhibit superior performance, identifying more drugs with higher prediction accuracy, as confirmed by DrugBank annotations. Notably, a significant proportion of predicted drugs without corresponding indications were subsequently validated in the ClinicalTrials database. Additionally, PCS-based signatures demonstrate elevated disease specificity and association with Drug Related Gene (DRG). Competing Interest Statement The authors have declared no competing interest. Footnotes List of abbreviations - BRCA - Breast invasive carcinoma - CLUE - Cmap and Lincs Unified Environment - Cmap - Connectivity Map - DEGs - Differential expressed genes - DGS - Disease gene score - DRG - Disease-related genes - FDR - False discovery rates - GWAS - Genome-wide association studies - HNSC - Head and neck squamous cell carcinoma - HSP - Heat shock protein - LIHC - Lung adenocarcinoma - LINCS-L1000 - Library of Integrated Network-Based Cellular Signatures L1000 - LUAD - Lung adenocarcinoma - LUSC - Lung squamous cell carcinoma - MODZ - Moderated z-score - NN - Normal Cox negative coefficient - NP - Normal Cox positive coefficient - PCS - Prognosis consistency score - PPI - Protein-protein interaction - RFS - Relapse-free survival - RNA-seq - RNA-sequencing - TCGA - The Cancer Genome Atlas - TD - Tumor down-regulated genes set - THCA - Thyroid carcinoma - TN - Tumor Cox negative coefficient - TP - Tumor RFS Cox positive coefficient - TPM - Transcripts per million - TRFSN - Tumor RFS Cox negative coefficient set - TRFSP - Tumor RFS Cox positive coefficient set - TU - Tumor up-regulated genes set - TWAS - Transcriptome-wide association studies - UCRDP - Unconsistency ratio of dysregulation and RFS prognosis - UCRTPNP - Unconsistency ratio between tumor RFS prognosis and normal RFS prognosis.