Driving basal-like (triple-negative) breast cancer by N-Ras
To understand the cause of tumor initiation and progression, substantial efforts have been made to uncover all gene changes in the tumor. These discoveries require the subsequent classification of these changes as “drivers”, directly responsible for tumor formation and progression, as opposed to “passengers”, whose presence does not change the course of the disease. The overall objective of this project is to identify such drivers. It is known that a key driver for the luminal breast cancer is estrogen receptor (ER); however, basal-like breast cancer (BLBC) drivers remain largely unknown. BLBC is the most aggressive form of breast cancer and cannot be treated by the current targeted therapies against ER and HER2 as in luminal breast cancers. In this study, we present evidence that BLBCs may evolve from ER+ breast cancer and identify N-Ras as a major driver that promotes the change. The significance of these findings are that we will not only directly help BLBC patients but may also prevent luminal breast cancer from evolving into the more aggressive BLBC form.
DNA damage repair defects in estrogen receptor positive tumors and their role in endocrine therapy resistance
Disruptions in DNA damage repair (DDR) can promote tumor formation by predisposing cells to accumulate DNA aberrations, brought about by carcinogens or other cytotoxic events. These defects can also incline tumors to therapeutic resistance. Clinical trials have shown that approximately 30 percent of ER positive (ER+) patient tumors become resistant to endocrine therapy. While many mechanisms for intrinsic and acquired endocrine resistance in breast cancer have been explored, links between defects in DDR and endocrine therapy resistance are understudied. Preliminary analysis of two neoadjuvant aromatase inhibitor clinical trials show that DDR defective tumors have greater proliferation capacity at the conclusion of endocrine therapy. We hypothesize that defects in different DDR pathways have different impacts on the tumor genome which dictates its ability to respond to endocrine therapy. Hence, this study aims at unraveling the role of DDR pathways in endocrine therapy resistant ER+ tumors by bioinformatics classification of samples based on abnormalities across canonical DDR pathways, followed by investigating the relationship between endocrine therapy resistance to different DDR pathways and profiling their genomic aberration signatures.
Development of microscaled proteomic profiling to identify and target aberrant protein kinases within human breast tumors
The breast cancer research community has made substantial progress in analyzing the DNA and RNA of cancer patients. However, changes in DNA and RNA that ultimately affect protein activities are often very difficult to predict by analyzing only DNA and/or RNA. The resulting translated protein encoded by such DNA/RNA experiences post-translational modifications that sometimes deviate from their templates. In addition, kinases, an enzymatic classification of proteins, are regarded as the “molecular switches” that can turn cellular pathways on and off. A common cause of cancer occurs when these molecular switches become defective and remain “on”. These kinases are also highly-susceptible therapeutic candidates based on their well-defined molecular structures to which drugs can be designed to lodge within their catalytic core. Our team has developed a tool to directly profile changes in the protein kinases (kinome) using mass spectrometry technology. Furthermore, we employ existing protein kinase inhibitors as bait to fish these kinases out and subsequently analyze the amount of each kinase active in a particular patient. Through rigorous optimization, we can now use this innovative technology to analyze human breast tumor samples approximately the size of a grain of rice. This micro-scaling of our technology positions us within striking distance of surveying actual tumor biopsies for aberrant protein kinases that may be responsible for driving each tumor; thereby, exposing the faulty molecular switch for precision therapeutics. For instance, when comparing kinase networks across breast cancer subtypes, we have identified a key molecule that can drive the low expression of claudin which defines a very aggressive form of triple negative breast cancer that is currently without suitable targeted therapy. Thus, our kinomic profiling approach may shed light on how to treat this as well other forms of breast cancer.
Mutagenesis-induced endocrine resistance in estrogen receptor positive breast cancer
Breast cancer is one of the most common cancer diagnoses among women. The number of fatalities related to breast cancer is extraordinarily high: more than 40,000 women will die of the disease this year in the USA alone (NCI database). The most common type of breast cancer diagnosed is estrogen receptor (ER) positive breast cancer, accounting for >60 percent of breast cancer cases. ER+ breast cancer, by and large, has a good prognosis, because it is responsive to therapy that targets the ER pathway. However, about 1/3 of women diagnosed with ER+ breast cancer develop resistance to treatment with the risk of relapse persisting several decades after diagnosis. Despite recent advances, the majority of resistant cases remains unexplained. About 30 percent of ER+ tumors have 10-fold higher mutations. In an analysis of multiple human datasets we demonstrated that High Mutation Load tumors (HML) associated with significantly worse overall survival and response to endocrine treatment than ‘Low Mutation Load’ (LML) tumors. These data suggest a role for mutagenesis in regulating response to endocrine therapy. Therefore, the remaining challenge is to investigate whether mutagenesis causes endocrine therapy resistance in estrogen receptor positive breast tumors and whether discovery of alternative therapeutic strategies that can be used in high mutation load, treatment resistance subset of ER+ tumors will fundamentally change the way ER+ tumors are diagnosed, classified, and treated.
Investigation of metastatic potential from patient tumors utilizing a mouse intraductal model system
The current rate at which new drugs fail during clinical trials suggests that it is necessary to develop more robust preclinical models that can adequately translate the findings at the bench to effective treatments in the clinic. Recent studies have shown that xenograft models are valuable in maintaining the patient’s drug response when the human tumor cells are directly transplanted into mice. We have demonstrated the power of using patient-derived xenografts (PDXs) in the study of endocrine therapy resistance of ER+ breast cancer. (Li et al., Cell Reports, 2013) These PDX models were first generated at Washington University; hence their “WHIM” (Washington University Human in Mouse) nomenclature. We are now focused in further improving this PDX models by integrating the “Mouse INtraDuctal” (MIND) model, in which, the tumor cells are introduced into the milk ducts of mice (Behbod et al., Breast Cancer Res., 2009 & Sflomos et al., Cancer Cell, 2016). In addition, we will track injected human tumor cells in vivo via reporter gene(s). With this optimized model, we can thoroughly characterize each patient’s tumor, target aberrant pathways via personalized therapies, measure their response, and analyze metastasis.
Non-canonical HER2 activation in human cancer
Investigating the impact of HER-targeted drugs on HER2/EGFR non-amplified solid tumors
Targeting HER family members is one of the greatest successes in oncology. It is, therefore, essential to fully identify all cancers that are driven by these oncogenes in order to take full advantage of the wide array of HER targeting agents available. Until recently, HER-targeted therapy is only effective in HER2/EGFR-amplified cancers. However, using genome-sequencing approaches we showed that HER2-mutation status can predict response to HER-targeted therapy. We are currently using proteomic approaches to identify novel subsets of breast cancer patients who could benefit from HER-targeted therapy using patient-derived xenografts (PDXs), publicly available breast cancer datasets such as the Cancer Genome Atlas (TCGA), and our breast cancer patient sequencing studies. Additionally, our research focuses on understanding the biological underpinnings of sensitivity and resistant to HER-targeted therapy in breast and colorectal cancers.
To test the impact of tyrosine kinase (TK) mutations in human cancers
The Cancer Genome Atlas (TCGA) have identified several activating HER2 mutations in breast and colorectal cancers. We provided the functional and clinical impact of HER2 mutations in breast and colorectal cancer patients using cancer cell lines, PDX models, and in a clinical trials setting. Genome sequencing of ER+ breast cancer patients we have identified novel tyrosine kinase mutations that drive poor prognosis but our understanding of the biochemistry of these mutations in ER+ breast cancer is extremely limited. We will, therefore, study how specific poor prognosis tyrosine kinase mutations, discovered in our sequencing analysis, reprogram the kinome as a prelude to developing an effective therapeutic approach.
ESR1 gene fusion-induced therapeutic resistance and metastasis in estrogen receptor positive breast cancer
The majority of breast cancers express estrogen receptor alpha (ER), which respond to the hormone estrogen to drive the growth and/or progression of these ER-positive (ER+) breast tumors. Such estrogen-fueled tumors are likely to initially respond to standard-of-care hormonal therapeutics, which can either disrupt estrogen binding to the ER, block estrogen synthesis, or cause ER to be degraded all together. Despite the success of these anti-ER agents, about one-third of ER+ breast cancer patients will develop resistance to these targeted therapies. By the time such a diagnosis of therapeutic resistance is made, these tumors often represent potentially fatal, advanced stage (metastatic) disease for which there are very few treatment options. Our lab has recently discovered ESR1 (gene that encodes for ER) fusion events from both early and advanced stage disease, leading to production of chimeric proteins, containing half of one gene and half of another. My research focuses on identifying the underlying mechanisms of how these gene fusion products contribute to tumor growth and metastasis, a process in which cells spread to different parts of the body and is the main cause of death in patients with breast cancer. Such “accidents” in nature may not be unique to ER fusion biology, and could be more generally significant to tumor biology of ER expressing tumors. These results have the potential to improve survival rates for the vast numbers of women with ER-positive tumors that develop therapeutic resistant disease.