The tumor therapy landscape of synthetic lethality

Biyu Zhang,Lan Chen,Chi Zhou,Yanli Yao,Chen Tang,Qi Liu,Xiang Cai,Shuyang Sun,Zhiting Wei,Xiaohan Chen,Zhiyuan Zhang,Feiyang Xing

doi:10.1038/s41467-021-21544-2

Abstract

Synthetic lethality is emerging as an important cancer therapeutic paradigm, while the comprehensive selective treatment opportunities for various tumors have not yet been explored. We develop the Synthetic Lethality Knowledge Graph (SLKG), presenting the tumor therapy landscape of synthetic lethality (SL) and synthetic dosage lethality (SDL). SLKG integrates the large-scale entity of different tumors, drugs and drug targets by exploring a comprehensive set of SL and SDL pairs. The overall therapy landscape is prioritized to identify the best repurposable drug candidates and drug combinations with literature supports, in vitro pharmacologic evidence or clinical trial records. Finally, cladribine, an FDA-approved multiple sclerosis treatment drug, is selected and identified as a repurposable drug for treating melanoma with CDKN2A mutation by in vitro validation, serving as a demonstrating SLKG utility example for novel tumor therapy discovery. Collectively, SLKG forms the computational basis to uncover cancer-specific susceptibilities and therapy strategies based on the principle of synthetic lethality.

Highlights

Synthetic lethality is emerging as an important cancer therapeutic paradigm, while the comprehensive selective treatment opportunities for various tumors have not yet been explored
We developed Synthetic Lethality Knowledge Graph (SLKG), which presents the comprehensive tumor therapy landscape of synthetic lethality (SL) and synthetic dosage lethality (SDL) from a drug repositioning perspective
These results form a comprehensive reference for exploiting the tumor therapy landscape to uncover cancer-specific susceptibilities based on the principle of SL

Summary

Introduction

Synthetic lethality is emerging as an important cancer therapeutic paradigm, while the comprehensive selective treatment opportunities for various tumors have not yet been explored. The best-studied example of targeted therapies exploiting the synthetic lethality (SL) principle is the use of poly-ADP ribose polymerase (PARP) inhibitors in breast and ovarian cancer harboring mutations in BReast CAncer gene (BRCA). Various methods have been proposed to identify SL and SDL interactions based on these data, the selective treatment opportunities for various tumors have not yet been explored To this end, we developed the Synthetic Lethality Knowledge Graph (SLKG, https://www.slkg.net/), which presents the comprehensive tumor therapy landscape of SL and SDL from a drug repositioning perspective. Cladribine, which is a FDA-approved multiple sclerosis treatment drug, was selected and identified as a repurposable drug for treating melanoma with CDKN2A mutation by a comprehensive in vitro validation, serving as a demonstrating experimental protocol to utilize SLKG for novel tumor therapy discovery. SLKG forms the computational basis for exploiting the tumor therapy landscape and repurposing known drugs based on the principle of SL to uncover cancer-specific susceptibilities

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Results

Conclusion