Gene regulation plays a fundamental role in cellular development and cancer. Our lab uses genomics and systems biology approaches to understand the gene regulatory factors underlying cellular processes. We take snapshots of the regulatory systems using bulk and single-cell omics and imaging assays, and develop computational algorithms to integrate data and generate testable models of gene regulatory pathways in model systems.
Understanding the molecular basis of therapeutic resistance in cancer
We have 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
Unraveling the gene regulatory factors involved in cellular development
We are studying gene regulatory networks controlling the embryonic origin of hematopoietic stem cells, differentiation of T-cells, and pediatric cancers. Specific questions we 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?
Development of computational methods to interpret high-dimensional and single-cell transcriptomics, proteomics, and epigenomics data
We develop data-driven methods to integrate multi-omics data using network biology and principled machine learning. We generate large data sources using methods such as bulk and single-cell RNA-Seq, ATAC-Seq, Hi-C, and multiplexed fluorescent imaging. We 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
Melenhorst JJ*, Chen GM, Wang M, Porter DL, Chen C, Collins MA, Gao P, Bandyopadhyay S, Sun H, Zhao Z, Lundh S, Pruteanu-Malinici I, Nobles CL, Maji S, Frey NV, Gill SI, Tian L, Kulikovskaya I, Gupta M, Ambrose DE, Davis MM, Fraietta JA, Brogdon JL, Young RM, Chew A, Levine BL, Siegel DL, Alanio C, Wherry EJ, Bushman FD, Lacey SF, Tan K*, June CH*: Decade-long leukemia remissions with persistence of CD4+ CAR T-cells. Nature Feb 2022.
Chen C, Yu W, Alikarami F, Qiu Q, Chen C, Flournoy J, Gao P, Uzun Y, Fang L, Davenport JW, Hu Y, Zhu Q, Wang K, Libbrecht C, Felmeister A, Rozich I, Ding Y, Hunger SP, Felix CA, Wu H, Brown PA, Guest EM, Barrett DM*, Bernt KM*, Tan K*: Single-cell multiomics reveals increased plasticity, resistant populations and stem-cell-like blasts in KMT2A-rearranged leukemia. Blood Dec 2021.
Chen GM, Chen C, Das RK, Gao P, Chen C, Bandyopadhyay S, Ding Y, Uzun Y, Yu W, Zhu Q, Myers RM, Grupp SA, Barrett DM, Tan K
: Integrative bulk and single-cell profiling of pre-manufacture T-cell populations reveals factors mediating long-term persistence of CAR T-cell therapy. Cancer Discovery Apr 2021.
Ding YY, Kim H, Madden K, Loftus JP, Chen GM, Hottman Allen D, Zhang R, Xu J, Chen CH, Hu Y, Tasian SK*, Tan K*.: Network analysis reveals synergistic genetic dependencies for rational combination therapy in Philadelphia chromosome-like acute lymphoblastic leukemia. Clinical Cancer Research Jul 2021.
Hu Y, Peng T, Gao L, Tan K: CytoTalk: De novo construction of signal transduction networks using single-cell RNA-Seq data. Science Advances 7(16): eabf1356, Apr 2021.
Zhu Q, Gao P, Tober J, Bennett L, Chen C, Uzun Y, Li Y, Howell ED, Mumau M, Yu W, He B, Speck NA, Tan K: Developmental trajectory of pre-hematopoietic stem cell formation from endothelium. Blood 136(7): 845-856, May 2020.
He B, Gao P, Ding Y, Chen C, Chen GM, Chen C, Kim H, Tasian SK, Hunger SP, Tan K: Diverse noncoding mutations contribute to deregulation of cis-regulatory landscape in pediatric cancers. Science Advances 6(30): eaba3064, June 2020.
Gao P, Chen C, Howell ED, Li Y, Tober J, Uzun Y, He B, Gao L, Zhu Q, Siekmann A, Speck NA, Tan K: Transcriptional regulatory network controlling the ontogeny of hematopoietic stem cells. Genes & Development 34(13-14): 950-964, June 2020.
Hu Y, Gao L, Chen C, Ding Y, Wen X, Wang B, and Tan K: Optimal control nodes in disease-perturbed networks as targets for combination therapy. Nature Communications 10(1): 2180, May 2019.
Peng T, Zhu Q, Yin P, Tan K: Single-cell RNA-Seq imputation constrained by bulk RNA-Seq data. Genome Biology 20(1): 88, May 2019.
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Last updated: 01/10/2023
The Trustees of the University of Pennsylvania