Our research focus

The primary focus of the Li Lab is on assessing the performance of next-generation sequencing techniques in accurate genome/epigenome/transcriptome profiling and understanding the clinical and functional role of epigenome heterogeneity in the cancer evolution. The Li laboratory utilizes computational and sequencing methodologies to identify and characterize the essential epigenetic lesions that guide cancer cells to evolve and escape from therapy. Our research interest is to understand the inner workings of cancer cells – the genetic and epigenetic heterogeneity that drive cancer initiation and progression. Specifically, the research involves (1) determining the drivers of epigenetic heterogeneity; (2) evaluating the functional impact of the cross-talk among epigenetic modifications on transcriptome; (3) assessing epigenetic heterogeneity/subpopulations in treatment resistance.

Dr. Li has developed a series of computational methods and software for the epigenome sequencing data analysis, to comprehensively detect the significant DNA methylation aberration and epigenetic heterogeneity during disease progression. Dr. Li's work has helped to establish the first principles and metrics for examining changes in RNA splicing and expression profiling and set standards at the FDA for clinical-grade RNA-sequencing. Dr. Li further applied these approaches to study the epigenetic heterogeneity and dynamics using acute myeloid leukemia (AML) as a model. Dr. Li found that epigenetic allele burden was linked to inferior clinical outcome, and epigenetic dynamics was related to hypervariable transcriptional regulation and was divergent from the genetic burden.

Highlighted Abstract

Genetic heterogeneity contributes to clinical outcome and progression of most tumors, but little is known about allelic diversity for epigenetic compartments, and almost no data exist for acute myeloid leukemia (AML). We examined epigenetic heterogeneity as assessed by cytosine methylation within defined genomic loci with four CpGs (epialleles), somatic mutations, and transcriptomes of AML patient samples at serial time points. We observed that epigenetic allele burden is linked to inferior outcome and varies considerably during disease progression. Epigenetic and genetic allelic burden and patterning followed different patterns and kinetics during disease progression. We observed a subset of AMLs with high epiallele and low somatic mutation burden at diagnosis, a subset with high somatic mutation and lower epiallele burdens at diagnosis, and a subset with a mixed profile, suggesting distinct modes of tumor heterogeneity. Genes linked to promoter-associated epiallele shifts during tumor progression showed increased single-cell transcriptional variance and differential expression, suggesting functional impact on gene regulation. Thus, genetic and epigenetic heterogeneity can occur with distinct kinetics likely to affect the biological and clinical features of tumors.

The Li Lab

Principal Investigator: Sheng Li, Ph.D.

Our research focus

Open Positions

Selected Publications

Highlighted Abstract

The rapid evolution of cancer cells under attack

Data provides new hope for pediatric brain tumor patients

Precision medicine and making sense of data

A RACIPE for success

Working with uncertainty in cell populations

Stuck in a dangerous cycle

Using mathematical modeling to target infections

Developing new therapies for Alzheimer’s disease