KEYWORDS: Therapy resistance, metastasis, microenvironment, exosomes, immune checkpoint blockade, pattern recognition receptors, anti-viral signaling, NOTCH, breast cancer, glioblastoma multiforme, bioinformatics, genomics.
My laboratory is interested in gene programs and signaling pathways discovered through unbiased genomic approaches that regulate cancer metastasis and its resistance to either conventional treatment or immune therapies. In particular, we are focusing on 1) how stromal cells orchestrate cancer therapy resistance and growth in distant organs, and 2) how tumor cells regulate an immune suppressive microenvironment to influence response to immune checkpoint blockade.
The two most daunting obstacles in the clinical management of cancer are metastasis, or the spread of tumor cells from its origin to distant sites in the body, and resistance to chemotherapy and/or radiation, which are two primary means of treating the disease. Unfortunately, the molecular mechanisms that drive these central and elusive problems in oncology have remained poorly understood.
Our laboratory is focused on understanding how cancer cells acquire metastatic and treatment resistant phenotypes. Recent evidence suggests that these traits are acquired during tumorigenesis by antagonistic forces encountered as tumors grow and interact with their environment. Key among these selective pressures include inflammation, immune responses, and barriers imposed by surrounding stroma. Because the biology of these selective pressures can overlap with molecular mechanisms involved in metastasis and treatment resistance, genetic alterations that occur as a response to these pressures may predispose tumors to acquire a metastatic and/or treatment-resistant phenotype. Accordingly, we have a particular focus on how tumor cells interact with the microenvironment (stromal cells, immune cells) and the consequences of these interactions.
In order to better understand the basis for metastasis and treatment resistance, we utilize a multi-disciplinary approach towards both experimental and translational research goals. Hypothesis generation and testing relies on a systems biology paradigm that incorporates animal models, molecular biology, functional genomics, bioinformatics, and clinical correlation. Using these methods we and colleagues have identified gene programs and signaling pathways that not only predict but also regulate cancer phenotypes such as aggressive organ-selective metastasis, resistance to conventional therapies (chemotherapy and radiation), and resistance to immunotherapies. Some of these gene programs and pathways are expressed across multiple common human cancers including breast cancer, brain cancer, and melanoma, suggesting their disease relevance.
Mechanistic dissection of computational predictions have uncovered novel and complex signaling pathways on how tumor cells communicate with their microenvironment. One example includes how exosomes are transferred from stromal to breast cancer cells to engage therapy resistance pathways. These pathways include the activation of pattern recognition receptors in breast cancer cells by the transferred exosomes, and the activation of juxtacrine signaling through NOTCH receptors. Another example includes how tumor cells can alter the immune microenvironment to dictate the effectiveness of immune therapies such as immune checkpoint blockade. In all cases, the gene programs and pathways uncovered not only provide insight into important biological mechanisms but also provide potential biomarkers for prognosis, prediction, and therapy.
Many rotation projects related to the research interests described are available. Please contact Dr. Minn to inquire.
Taewon Yoon, Postdoctoral researcher
Yu Qiu, Postdoctoral researcher
Christina Twyman, Fellow
Tony Wu, Research specialist
Hannah Dada, Research specialist
Bihui Xu, Graduate student
Barzin Nabet, Graduate student
Erica Dhuey, Graduate student
Joseph Benci, Graduate student
Lisa Cucolo, Graduate student
Brian Kim, Undergraduate student
Benci Joseph L, Xu Bihui, Qiu Yu, Wu Tony J, Dada Hannah, Twyman-Saint Victor Christina, Cucolo Lisa, Lee David S M, Pauken Kristen E, Huang Alexander C, Gangadhar Tara C, Amaravadi Ravi K, Schuchter Lynn M, Feldman Michael D, Ishwaran Hemant, Vonderheide Robert H, Maity Amit, Wherry E John, Minn Andy J: Tumor Interferon Signaling Regulates a Multigenic Resistance Program to Immune Checkpoint Blockade. Cell 167(6): 1540-1554.e12, Dec 2016.
Twyman-Saint Victor C, Rech AJ, Maity A, Rengan R, Pauken KE, Stelekati E, Benci JL, Xu B, Dada H, Odorizzi PM, Herati RS, Mansfield KD, Patsch D, Amaravadi RK, Schuchter LM, Ishwaran H, Mick R, Pryma D, Xu X, Feldman MD, Gangadhar TC, Hahn SM, Wherry EJ, Vonderheide RH, Minn AJ: Radiation and Dual Checkpoint Blockade Activates Non-Redundant Immune Mechanisms in Cancer. Nature 520(7547): 373-7, Apr 2015.
Boelens MC, Wu TJ, Nabet BY, Xu B, Qiu Y, Yoon T, Azzam DJ, Twyman-Saint Victor C, Wiemann BZ, Ishwaran H, ter Brugge PJ, Jonkers J, Slingerland J, Minn AJ: Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways
Cell 159(3): 499-413, Oct 2014.
Minn Andy J, Wherry E John: Combination Cancer Therapies with Immune Checkpoint Blockade: Convergence on Interferon Signaling. Cell 165(2): 272-5, Apr 2016.
Jiang Yuchao, Qiu Yu, Minn Andy J, Zhang Nancy R: Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing. Proceedings of the National Academy of Sciences of the United States of America 113(37): E5528-37, Sep 2016.
Ishwaran H, Kogalur UB, Chen X, Minn AJ : Random survival forests for high-dimensional data. Statistical Analysis and Data Mining 4: 115-32, Jan 2011.
Ishwaran H, Kogalur UB, Gorodeski EZ, Minn AJ, Lauer MS: High dimensional variable selection for survival data. Journal of the American Statistical Association 105: 205-17, Mar 2010.
Weichselbaum RR, Ishwaran H, Yoon T, Nuyten DS, Baker SW, Khodarev N, Su AW, Shaikh AY, Roach P, Kreike B, Roizman B, Bergh J, Pawitan Y, van de Vijver MJ, Minn AJ: An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer. Proc Natl Acad Sci U S A 105(47): 18490-5, Nov 2008.
Minn AJ, Gupta GP, Padua D, Bos P, Nguyen DX, Nuyten D, Kreike B, Zhang Y, Wang Y, Ishwaran H, Foekens JA, van de Vijver M, Massagué J: Lung metastasis genes couple breast tumor size and metastatic spread. Proc Natl Acad Sci U S A 104(16): 6740-5, Apr 2007.
Minn AJ, Gupta GP, Siegel PM, Bos PD, Shu W, Giri DD, Viale A, Olshen AB, Gerald WL, Massagué J: Genes that mediate breast cancer metastasis to lung. Nature 436(7050): 518-24, Jul 2005.
Yun J, Frankenberger CA, Kuo WL, Boelens MC, Eves EM, Cheng N, Liang H, Li WH, Ishwaran H, Minn AJ*, Rosner MR* (* equal contribution and co-corresponding author): Signalling pathway for RKIP and Let-7 regulates and predicts metastatic breast cancer. EMBO J 30(21): 4500-14, Nov 2011.
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Last updated: 12/21/2016
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