My research interest is to understand the inner workings of cancer cells – the genetic and epigenetic heterogeneity that drive cancer initiation and progression. We utilize computational and sequencing methodologies to identify and characterize the essential epigenetic lesions that guide cancer cells to evolve and escape from anti-cancer therapy. The ultimate goal is to develop novel methods to predict and address tumor evolution.
TET2 somatic mutations occur in ∼10% of diffuse large B-cell lymphomas (DLBCL) but are of unknown significance. Herein, we show that TET2 is required for the humoral immune response and is a DLBCL tumor suppressor. TET2 loss of function disrupts transit of B cells through germinal centers (GC), causing GC hyperplasia, impaired class switch recombination, blockade of plasma cell differentiation, and a preneoplastic phenotype. TET2 loss was linked to focal loss of enhancer hydroxymethylation and transcriptional repression of genes that mediate GC exit, such as PRDM1. Notably, these enhancers and genes are also repressed in CREBBP-mutant DLBCLs. Accordingly, TET2 mutation in patients yields a CREBBP-mutant gene-expression signature, CREBBP and TET2 mutations are generally mutually exclusive, and hydroxymethylation loss caused by TET2 deficiency impairs enhancer H3K27 acetylation. Hence, TET2 plays a critical role in the GC reaction, and its loss of function results in lymphomagenesis through failure to activate genes linked to GC exit signals. SIGNIFICANCE: We show that TET2 is required for exit of the GC, B-cell differentiation, and is a tumor suppressor for mature B cells. Loss of TET2 phenocopies CREBBP somatic mutation. These results advocate for sequencing TET2 in patients with lymphoma and for the testing of epigenetic therapies to treat these tumors.See related commentary by Shingleton and Dave, p. 1515.This article is highlighted in the In This Issue feature, p. 1494.
Three-dimensional genomic compartments and sub-compartments help regulate gene expression across the genome. As more data comes out about 3D genomic structures, there is an increasing need to efficiently identify and characterize sub-compartments and their roles in genome function. Sheng Li and her team developed a new computational tool, SCI, that outperforms previously developed algorithms for this purpose.
Jackson Laboratory (JAX) Assistant Professor Sheng Li, Ph.D., was chosen as a 2020 NextGen Star by the American Association for Cancer Research (AACR). She is one of 12 early-career cancer researchers recognized for their outstanding work and future potential.
What if, much like screening through genetic testing, we could learn how to better treat individual patients through their unique epigenetic markers? This is the question that Assistant Professor Sheng Li, Ph.D. tackles in her lab every day.