Quantifying epigenetic reprogramming and cellular plasticity in preneoplastic lesions reveals dedifferentiation as a key precancer hallmark

Abstract

Epigenetic reprogramming and plasticity are two cancer hallmarks that increase the risk of carcinogenic transformation, yet quantifying these properties remains a fundamental challenge. Here we develop and validate a general pan-tissue computational framework called PLASTIC for quantifying cellular plasticity and epigenetic reprogramming from single-cell RNA-seq data. PLASTIC allows construction of Waddington-like landscapes allowing identification of high cancer risk states. When applied to a pan-preneoplastic tissue setting, PLASTIC reveals how the level of epigenetic reprogramming of precancerous cells correlates with cellular plasticity and cancer-risk, and that the high cancer risk state is characterized by increased dedifferentiation, even when compared to its fetal cell counterpart. Furthermore, PLASTIC predicts the emergence of metaplasia in normal lung cells from smokers, identifying a high cancer risk signature that we validate in independent data. In summary, PLASTIC can help quantify cellular plasticity and dedifferentiation of single cells in any tissue-type, opening up new strategies for cancer risk prediction and prevention.