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Mario Niepel

Systems Biology / Systems Pharmacology

200 Longwood Ave
Boston, MA 02445
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Mario Niepel

I am a instructor-level faculty member at the Department of Systems Biology and Laboratory of Systems Pharmacology at Harvard Medical School. My research focuses on investigating the mechanisms of how cancer cell lines respond to small molecule inhibitors. I am combining large scale phenotypic, biochemical, and transcriptional measurements with both proteomic and genomic profiling of cells to understand the determinants of drug responses.

 

  • Quantifying drug sensitivity

    The GR50 drug sensitivity shows that paclitaxel has the same potency in virtually all breast cancer cell lines.

  • RTK network predicts drug responses

    Receptor tyrosine kinases in bresat cancer cell lines can be used to predict the cell’s response to therapeutic drugs.

  • Responses of cancer lines to growth factors

    In a BMC Biology publication we identified potential molecular underpinnings of growth factor responses in breast cancer.

  • Modeling Signaling Transduction

    Building statistical and ODE models of how receptor tyrosine kinases signal down to the MAPK and AKT pathway.

  • Mlp proteins and the nuclear pore

    Investigations of how the Mlp proteins link the nuclear pores with other structures of the nuclear envelope.

  • Translational control of viral RNAs

    Viral RNAs can often initiate translation while bypassing the common CAP/polyA-dependent cellular translation machinery.

  • Research
    • Drug Response
    • Cancer Profiling
    • Signal Transduction
    • Nuclear Pores
    • Translational Control
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Latest News

  • Proteomic Mapping of the EGFR/MAPK pathway published.
  • Nature Methods paper published
  • Conference on Phenotypic Drug Discovery
  • Two posters at AACR Targets and Therapeutics in Boston
  • Advances in Breast Cancer Research
  • LSP on NPR
More

Recent Publications

  • L1000CDS2: LINCS L1000 characteristic direction signatures search engine.
  • Conservation of protein abundance patterns reveals the regulatory architecture of the EGFR-MAPK pathway
  • Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs
  • Systematic analysis of BRAFV600E melanomas reveals a role for JNK/c-Jun pathway in adaptive resistance to drug-induced apoptosis
  • Analysis of growth factor signaling in genetically diverse breast cancer lines.
  • LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures.
More
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