Department of Radiation Oncology

Andy J. Minn

faculty photo

Andy J. Minn, MD, PhD

Associate Professor of Radiation Oncology
Department: Radiation Oncology

Contact information
Abramson Family Cancer Research Institute
421 Curie Blvd
BRB II/III, Room 510
Philadelphia, PA 19104
BA (Biology)
The University of Chicago, Chicago, IL, 1992.
PhD (Immunology)
The University of Chicago, Chicago, IL, 1999.
MD (Medicine)
The University of Chicago, Chicago, IL, 2000.
Permanent link
> Perelman School of Medicine   > Faculty   > Details

Description of Research Expertise

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, Senior lab manager
Lex Johnson, Graduate student
Bihui Xu, Graduate student
Barzin Nabet, Graduate student
Erica Dhuey, Graduate student
Joseph Benci, Postdoc
Lisa Cucolo, Graduate student
Jacob Shabason, Instructor
Shetal Patel, Fellow
Brian Kim, Undergraduate student

Selected Publications

Ishwaran Hemant, Kogalur Udaya B, Chen Xi, Minn Andy J : Random survival forests for high-dimensional data. Statistical Analysis and Data Mining 4: 115-32, Jan 2011.

Ishwaran Hemant, Kogalur Udaya B, Gorodeski Eiran Z, Minn Andy J, Lauer Michael S: High dimensional variable selection for survival data. Journal of the American Statistical Association 105: 205-17, Mar 2010.

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Last updated: 07/16/2017
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