A systematic atlas of chaperome deregulation topologies across the human cancer landscape

Abstract

Proteome balance is safeguarded by the proteostasis network (PN), an intricately regulated network of conserved processes that evolved to maintain native function of the diverse ensemble of protein species, ensuring cellular and organismal health. Proteostasis imbalances and collapse are implicated in a spectrum of human diseases, from neurodegeneration to cancer. The characteristics of PN disease alterations however have not been assessed in a systematic way. Since the chaperome is among the central components of the PN, we focused on the chaperome in our study by utilizing a curated functional ontology of the human chaperome that we connect in a high-confidence physical protein-protein interaction network. Challenged by the lack of a systems-level understanding of proteostasis alterations in the heterogeneous spectrum of human cancers, we assessed gene expression across more than 10,000 patient biopsies covering 22 solid cancers. We derived a novel customized Meta-PCA dimension reduction approach yielding M-scores as quantitative indicators of disease expression changes to condense the complexity of cancer transcriptomics datasets into quantitative functional network topographies. We confirm upregulation of the HSP90 family and also highlight HSP60s, Prefoldins, HSP100s, ER- and mitochondria-specific chaperones as pan-cancer enriched. Our analysis also reveals a surprisingly consistent strong downregulation of small heat shock proteins (sHSPs) and we stratify two cancer groups based on the preferential upregulation of ATP-dependent chaperones. Strikingly, our analyses highlight similarities between stem cell and cancer proteostasis, and diametrically opposed chaperome deregulation between cancers and neurodegenerative diseases. We developed a web-based Proteostasis Profiler tool (Pro2) enabling intuitive analysis and visual exploration of proteostasis disease alterations using gene expression data. Our study showcases a comprehensive profiling of chaperome shifts in human cancers and sets the stage for a systematic global analysis of PN alterations across the human diseasome towards novel hypotheses for therapeutic network re-adjustment in proteostasis disorders.

Pan-cancer characterization of immune-related lncRNAs identifies potential oncogenic biomarkers

“…P-values were adjusted using the FDR. Moreover, following a previous study 58 , we combined the P-value and the ES score to an lncRES score, i.e.,…”

Mitochondrial stress-dependent regulation of cellular protein synthesis

“…As individual components of this highly interconnected proteostasis network are affected during stress conditions, other components adjust accordingly to maintain normal cellular function (Klaips et al, 2018;Sala et al, 2017;Schneider and Bertolotti, 2015). A dysregulation of one or more components of proteostasis can lead to pathological conditions, such as neurodegenerative diseases, diabetes and cancer (Hadizadeh Esfahani et al, 2018;Labbadia and Morimoto, 2015;Mukherjee et al, 2015). The expression of many proteins is regulated in a post-transcriptional manner, which explains observed discrepancies between the transcriptome and proteome (Ghazalpour et al, 2011;Schwanhäusser et al, 2011).…”

Multiple functionalities of molecular chaperones revealed through systematic mapping of their interaction networks

“…With the extraordinary efficiency and relatively low cost of applying high-throughput genomic and proteomic techniques, large interaction data are currently available that have not been fully analyzed especially from mammalian cells. Indeed, proteome imbalance in cancer has recently been evaluated by Hadizadeh Esfahani et al (30) using gene expression profiling and protein-protein interaction (PPI) datasets that are publicly available (Fig. 1).…”

“…This tissue is optimal for CCo GCN analyses because of its highly pronounced aging dynamics. A much larger GCN dataset was used to study CCo changes in cancer by Hadizadeh Esfahani et al (30) using The Cancer Genome Atlas compendium. The authors mapped CCo expression changes across 22 cancers compared with their healthy counterpart from thousands of publicly available patient biopsies.…”