The Liu Lab

Researching the fundamental genomics of breast cancer.

Principal Investigator

Edison T. Liu, M.D.


Farmington, CT


Research Focus Synopsis

We study the functional genomics of cancer, with a focus on breast cancer. We are currently investigating the systems genomics of breast cancer to better understand cancer maintenance and determine therapeutic sensitivity and resistance. We are also exploring how structural changes in the cancer genome determine primary cancer growth and affect therapeutic sensitivity and resistance.

Research focus

We have shown that specific gene combinatorics provide the molecular basis of a “systems” control of breast cancer biology (Low YL et al. PLoS Genet. 2010; Kong SL et al. Mol Syst Biol. 2011) and that uncovering these systems rules provides a strategy for cancer gene discovery (Soon WW et al. EMBO Mol Med. 2011). We have explored the role of structural genomic variations in coordinating the expression of gene cassettes that collectively drive cancer growth (Hillmer AM et al. Genome Res. 2011; Inaki K et al. Genome Res. 2011). Moreover, we showed that structural variations coordinately alter gene expression of driver genes that affect therapeutic response (Inaki K et al. Genome Res. 2014) and that these structural variations are generated by rearrangements at specific genomic regions defined by chromatin configurations (Grzeda KR et al. BMC Genomics. 2014).

Computationally, we now are pursuing the hypothesis that the structure of the human genome, as a result of evolutionary pressures, has an embedded organization that clusters genes with functions enhancing cellular autonomy from physiological controls and therefore facilitates cancer cell evolution. We speculate that the detailed analysis of a large cohort of human tumors will uncover blocks of genes that participate in structural variations as a unit, which we term Cancer Syntenic Blocks (CSBs). Similar to syntenic blocks in comparative evolution, these CSBs appear to change in copy number and engage in rearrangements as chromosomal blocks, suggesting a conservation of systems function.

Experimentally, we are focused on understanding how somatic structural variations contribute to the cancer cell robustness and therefore to its relative resistance to cancer therapeutics. We have found that specific genomic configurations are associated with chemotherapeutic sensitivities. These configurations drive the expression of several cancer genes from different regions of the genome but, at a higher ontological level, they result in the perturbation of similar cellular functions, leading to the activation of common oncogenic pathways.

For a better understanding of drug sensitivity and resistance, we have moved away from using established cancer cell lines and sought to establish experimental systems that reflect more closely the primary cancer state. To this end, we have pursued the optimization of in vivo Patient Derived Xenografts (PDXs) of primary breast tumors carried by NOD-scid-IL2 gamma KO (NSG) mice. PDXs’ histological and genomic configurations and their responses to therapeutic challenges resemble the behavior of their corresponding primary cancers, providing the most proximate experimental system to direct human clinical trials and allowing for a “primary-like” tumor to be expanded and reused experimentally. At The Jackson Laboratory, we have developed extensive experience in the establishment and use of this PDX system as a surrogate of primary tumors. Uniquely, we are coupling the PDX system with the in vitro culture of primary conditionally reprogrammed progenitor cells (CRPC) as an unlimited source of tumor cells, which are amenable to genetic-epigenetic reprogramming, fast drug response read-outs and sub-clonal dissection. We have optimized both systems to quantitatively interrogate relative drug sensitivity, so that the discovery of potential core drivers of cellular robustness generated by comprehensive genomic analyses can then be substantiated in this model system, via the precise editing of gene structures and gene expression.