Pan-cancer analysis identifies telomerase-associated signatures and cancer subtypes

Zhenhua Luo,Xuyang Feng,Changchang Xin,Zhou Songyang,Yuanyan Xiong,Zhiming Dai,Feng Li,Weixu Wang

doi:10.1186/s12943-019-1035-x

Abstract

BackgroundCancer cells become immortalized through telomere maintenance mechanisms, such as telomerase reverse transcriptase (TERT) activation. In addition to maintaining telomere length, TERT activates manifold cell survival signaling pathways. However, telomerase-associated gene signatures in cancer remain elusive.MethodsWe performed a systematic analysis of TERT high (TERThigh) and low (TERTlow) cancers using multidimensional data from The Cancer Genome Atlas (TCGA). Multidimensional data were analyzed by propensity score matching weight algorithm. Coexpression networks were constructed by weight gene coexpression network analysis (WGCNA). Random forest classifiers were generated to identify cancer subtypes.ResultsThe TERThigh-specific mRNA expression signature is associated with cell cycle-related coexpression modules across cancer types. Experimental screening of hub genes in the cell cycle module suggested TPX2 and EXO1 as potential regulators of telomerase activity and cell survival. MiRNA analysis revealed that the TERThigh-specific miR-17-92 cluster can target biological processes enriched in TERTlow cancer and that its expression is negatively correlated with the tumor/normal telomere length ratio. Intriguingly, TERThigh cancers tend to have mutations in extracellular matrix organization genes and amplify MAPK signaling. By mining the clinical actionable gene database, we uncovered a number of TERThigh-specific somatic mutations, amplifications and high expression genes containing therapeutic targets. Finally, a random forest classifier integrating telomerase-associated multi-omics signatures identifies two cancer subtypes showed profound differences in telomerase activity and patient survival.ConclusionsIn summary, our results depict a telomerase-associated molecular landscape in cancers and provide therapeutic opportunities for cancer treatment.

Highlights

Cancer cells become immortalized through telomere maintenance mechanisms, such as telomerase reverse transcriptase (TERT) activation
To identify telomerase-associated molecular signatures, we first defined two cancer types based on TERT expression: 1) patients with high expression of TERT (TERThigh) and 2) patients with low expression of TERT (TERTlow)
To investigate telomerase-associated molecular signatures across cancers, we developed an analytic pipeline by integrating multi-omics data and experimental studies (Fig. 1a)

Summary

Introduction

Cancer cells become immortalized through telomere maintenance mechanisms, such as telomerase reverse transcriptase (TERT) activation. In addition to maintaining telomere length, TERT activates manifold cell survival signaling pathways. Telomerase-associated gene signatures in cancer remain elusive. Results: The TERThigh-specific mRNA expression signature is associated with cell cycle-related coexpression modules across cancer types. Experimental screening of hub genes in the cell cycle module suggested TPX2 and EXO1 as potential regulators of telomerase activity and cell survival. MiRNA analysis revealed that the TERThigh-specific miR-17-92 cluster can target biological processes enriched in TERTlow cancer and that its expression is negatively correlated with the tumor/ normal telomere length ratio. A random forest classifier integrating telomerase-associated multi-omics signatures identifies two cancer subtypes showed profound differences in telomerase activity and patient survival. Most cancers activate telomerase to maintain telomere length [7].

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Results

Discussion

Conclusion