Cell-type specific subtyping of epigenomes improves prognostic stratification of cancer
Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background
Most molecular classifications of cancer are based on bulk-tissue profiles that measure an average over many distinct cell-types. As such, cancer subtypes inferred from transcriptomic or epigenetic data are strongly influenced by cell-type composition and do not necessarily reflect subtypes defined by cell-type specific cancer-associated alterations, which could lead to suboptimal cancer classifications.
Methods
To address this problem, we here propose the novel concept of cell-type specific combinatorial clustering (CELTYC), which aims to group cancer samples by the molecular alterations they display in specific cell-types. We illustrate this concept in the context of DNA methylation data of liver and kidney cancer, deriving in each case novel cancer subtypes and assessing their prognostic relevance against current state-of-the-art prognostic models.
Results
In both liver and kidney cancer, we reveal improved cell-type specific prognostic models, not discoverable using standard methods. In the case of kidney cancer, we show how combinatorial indexing of epithelial and immune-cell clusters define improved prognostic models driven by synergy of high mitotic age and altered cytokine signaling. We validate the improved prognostic models in independent datasets, and identify underlying cytokine-immune-cell signatures driving poor outcome.
Conclusions
In summary, cell-type specific combinatorial clustering is a valuable strategy to help dissect and improve current prognostic classifications of cancer in terms of the underlying cell-type specific epigenetic and transcriptomic alterations.
