Loss of cellular identity in common pre-clinical models of serine‑threonine kinase 11 (Liver kinase B1) loss

Abstract

Nearly 1/3 of lung adenocarcinomas have loss of STK11 (LKB1) function. Herein, a bioinformatics approach was used to determine how accurately preclinical model systems reflect the in vivo biology of STK11 loss in human patients. Hierarchical and K-mean clustering, principle component, and gene set enrichment analyses were employed to model gene expression due to STK11 loss in patient cohorts representing nearly 1000 lung adenocarcinoma patients. K-means clustering classified STK11 loss patient tumors into three distinct sub-groups; positive (54%), neuroendocrine (NE) (35%) and negative (11%). The positive and NE groups are both defined by the expression of NKX2–1. In addition to NKX2–1, NE patients express neuroendocrine markers such as ASCL1 and CALCA. In contrast, the negative group does not express NKX2–1 (or neuroendocrine markers) and is characterized by significantly reduced survival relative to the two other groups. Two gene expression signatures were derived to explain both neuroendocrine features and differentiation (NKX2–1 loss) and were validated through two public datasets involving chemical differentiation (DCI) and NKX2–1 reconstitution. Patients results were then compared with established cell lines, transgenic mice, and patient-derived xenograft models of STK11 loss. Interestingly, all cell line and PDX models cluster and show expression patterns similar with the NKX2–1 negative subset of STK11-loss human tumors. Surprisingly, even mouse models of STK11 loss do not resemble patient tumors based on gene expression patterns. Results suggest pre-clinical models of STK11 loss are pronounced by marked elimination of type II pneumocyte identity, opposite of most in vivo human tumors.