Tan Laboratory Research Overview



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The Tan Lab has a number of ongoing projects investigating the molecular basis of oncogenesis and therapy resistance in cancer cells. Some highlights are:

  1. Generation of a bulk and single-cell multi-omic atlas of pediatric cancer at multiple therapeutic time points
  2. Identification of novel combination therapies by understanding disease-perturbed gene networks
  3. Understanding the cellular adaptations of cancer cells to targeted therapy and immunotherapy through novel systems biology approaches

Researchers in the Tan Lab are studying gene regulatory networks controlling the embryonic origin of hematopoietic stem cells, differentiation of T-cells, and pediatric cancers. Specific questions they ask include:

  1. What are the key regulators and cis-regulatory elements that control cell/tissue-specific gene expression in these systems?
  2. How does the 3-dimensional genome organization controls cell/tissue-specific gene expression in these systems?
  3. What are the mutations in the cis-regulatory DNA sequences that confer disease risk in these systems?
  4. What are the signaling pathways that mediate cell-cell communications in in these systems?

Researchers within the Tan Lab develop data-driven methods to integrate multi-omics data using network biology and principled machine learning. They generate large data sources using methods such as bulk and single-cell RNA-Seq, ATAC-Seq, Hi-C, and multiplexed fluorescent imaging. They also develop computational methods to integrate these data sources and model the gene regulatory architecture that underlies cellular fate and disease. Ongoing projects include:

  1. Development of network-based approaches to identify disease-perturbed pathways and critical regulatory nodes for the diagnosis and prognosis of diseases, and to identify candidates for novel therapeutics
  2. Integration of single-cell transcriptomics and epigenomics to characterize the sequence of gene regulatory events leading to cellular differentiation and cancer
  3. Understanding the impact of non-coding somatic variation, including copy number alterations and structural variation, in pediatric cancer"