(2024) William Kepler Whiteford Faculty Fellow.
(2024) Young Innovator in Cellular and Molecular Bioengineering.
(2024) NSF Career.
(2024) CMBE BMES Rising Star.
(2020 - 2021) Hillman Early-career Fellow for Innovative Cancer Research.
(2017 - 2022) NIH Pathway to Independence Award (K99/R00).
PhD, Massachusetts Institute of Technology, 2007 - 2013
MSc, Technical University Munich, 2003 - 2005
BSc/MSc, National Technical University of Athens, 2001 - 2006
McDonald, T.O., Bruno, S., Roney, J.P., Zervantonakis, I.K., & Michor, F. (2025). BESTDR: Bayesian quantification of mechanism-specific drug response in cell culture. In bioRxiv. doi: 10.1101/2025.02.05.636681.
Carleton, N., Lee, S., Li, R., Zou, J., Brown, D.D., Hooda, J., Chang, A., Kumar, R., Klei, L.R., Rigatti, L.H., Newsome, J., John Mary, D.J.S., Atkinson, J.M., West, R.E., Nolin, T.D., Oberly, P.J., Huang, Z., Poirier, D., Diego, E.J., Lucas, P.C., Tseng, G., Lotze, M.T., McAuliffe, P.F., Zervantonakis, I.K., Oesterreich, S., & Lee, A.V. (2024). Systemic and local chronic inflammation and hormone disposition promote a tumor-permissive environment for breast cancer in older women. bioRxiv, 2024.10.18.616978.Cold Spring Harbor Laboratory. doi: 10.1101/2024.10.18.616978.
Cho, Y., Laird, M., Bishop, T., Li, R., Ruffo, E., Lohmueller, J., & Zervantonakis, I.K. (2024). CAR T cell infiltration and cytotoxic killing within the core of 3D breast cancer spheroids under control of antigen sensing in microwell arrays. bioRxiv, 2024.03.14.585033.Cold Spring Harbor Laboratory. doi: 10.1101/2024.03.14.585033.
Cho, Y., Laird, M.S., Bishop, T., Li, R., Jazwinska, D.E., Ruffo, E., Lohmueller, J., & Zervantonakis, I.K. (2024). CAR T cell infiltration and cytotoxic killing within the core of 3D breast cancer spheroids under the control of antigen sensing in microwell arrays. APL Bioeng, 8(3), 036105.AIP Publishing. doi: 10.1063/5.0207941.
Jazwinska, D.E., Cho, Y., & Zervantonakis, I.K. (2024). Enhancing PKA-dependent mesothelial barrier integrity reduces ovarian cancer transmesothelial migration via inhibition of contractility. iScience, 27(6), 109950.Elsevier. doi: 10.1016/j.isci.2024.109950.
Lee, S., Cho, Y., Li, Y., Li, R., Brown, D., McAuliffe, P., Lee, A.V., Oesterreich, S., Zervantonakis, I.K., & Osmanbeyoglu, H.U. (2024). Cancer-cell derived S100A11 promotes macrophage recruitment in ER+ breast cancer. bioRxiv, 2024.03.21.586041.Cold Spring Harbor Laboratory. doi: 10.1101/2024.03.21.586041.
Lee, S., Cho, Y., Li, Y., Li, R., Lau, A.W., Laird, M.S., Brown, D., McAuliffe, P., Lee, A.V., Oesterreich, S., Zervantonakis, I.K., & Osmanbeyoglu, H.U. (2024). Cancer-cell derived S100A11 promotes macrophage recruitment in ER+ breast cancer. Oncoimmunology, 13(1), 2429186.Taylor & Francis. doi: 10.1080/2162402X.2024.2429186.
Poskus, M.D., McDonald, J., Laird, M., Li, R., Norcoss, K., & Zervantonakis, I.K. (2024). Rational design of HER2-targeted combination therapies to reverse drug resistance in fibroblast-protected HER2+ breast cancer cells. bioRxiv, 2024.05.18.594826.Cold Spring Harbor Laboratory. doi: 10.1101/2024.05.18.594826.
Poskus, M.D., McDonald, J., Laird, M., Li, R., Norcoss, K., & Zervantonakis, I.K. (2024). Rational Design of HER2-Targeted Combination Therapies to Reverse Drug Resistance in Fibroblast-Protected HER2+ Breast Cancer Cells. Cell Mol Bioeng, 17(5), 491-506.Springer Nature. doi: 10.1007/s12195-024-00823-0.
Scott, A.L., Jazwinska, D.E., Kulawiec, D.G., & Zervantonakis, I.K. (2024). Paracrine Ovarian Cancer Cell-Derived CSF1 Signaling Regulates Macrophage Migration Dynamics in a 3D Microfluidic Model that Recapitulates In Vivo Infiltration Patterns in Patient-Derived Xenografts. Adv Healthc Mater, 13(28), e2401719.Wiley. doi: 10.1002/adhm.202401719.
Adler, F.R., Anderson, A.R.A., Bhushan, A., Bogdan, P., Bravo-Cordero, J.J., Brock, A., Chen, Y., Cukierman, E., DelGiorno, K.E., Denis, G.V., Ferrall-Fairbanks, M.C., Gartner, Z.J., Germain, R.N., Gordon, D.M., Hunter, G., Jolly, M.K., Karacosta, L.G., Mythreye, K., Katira, P., Kulkarni, R.P., Kutys, M.L., Lander, A.D., Laughney, A.M., Levine, H., Lou, E., Lowenstein, P.R., Masters, K.S., Pe'er, D., Peyton, S.R., Platt, M.O., Purvis, J.E., Quon, G., Richer, J.K., Riddle, N.C., Rodriguez, A., Snyder, J.C., Lee Szeto, G., Tomlin, C.J., Yanai, I., Zervantonakis, I.K., & Dueck, H. (2023). Modeling collective cell behavior in cancer: Perspectives from an interdisciplinary conversation. Cell Syst, 14(4), 252-257.Elsevier. doi: 10.1016/j.cels.2023.03.002.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Figure S1 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505637.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Figure S5 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505622.v1.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Figure S4 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505628.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Figure S2 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505634.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Figure S1 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505637.v1.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Figure S2 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505634.v1.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Figure S3 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505631.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Table 1 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505619.v1.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Figure S3 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505631.v1.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Figure S4 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505628.v1.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Data from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.c.6538137.v1.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Table 1 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505619.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Supplementary Figure S5 from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.22505622.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2023). Data from Combined MEK and BCL-2/X<sub>L</sub> Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. doi: 10.1158/1535-7163.c.6538137.
Jazwinska, D.E., Kulawiec, D.G., & Zervantonakis, I.K. (2023). Cancer-mesothelial and cancer-macrophage interactions in the ovarian cancer microenvironment. Am J Physiol Cell Physiol, 325(3), C721-C730.American Physiological Society. doi: 10.1152/ajpcell.00461.2022.
Kalli, M., Poskus, M.D., Stylianopoulos, T., & Zervantonakis, I.K. (2023). Beyond matrix stiffness: targeting force-induced cancer drug resistance. Trends Cancer, 9(11), 937-954.Elsevier. doi: 10.1016/j.trecan.2023.07.006.
Kong, S., Moharil, P., Handly-Santana, A., Boehnke, N., Panayiotou, R., Gomerdinger, V., Covarrubias, G., Pires, I.S., Zervantonakis, I., Brugge, J., & Hammond, P.T. (2023). Synergistic combination therapy delivered via layer-by-layer nanoparticles induces solid tumor regression of ovarian cancer. Bioeng Transl Med, 8(2), e10429.Wiley. doi: 10.1002/btm2.10429.
Poskus, M.D., Wang, T., Deng, Y., Borcherding, S., Atkinson, J., & Zervantonakis, I.K. (2023). Fabrication of 3D-printed molds for polydimethylsiloxane-based microfluidic devices using a liquid crystal display-based vat photopolymerization process: printing quality, drug response and 3D invasion cell culture assays. Microsyst Nanoeng, 9(1), 140.Springer Nature. doi: 10.1038/s41378-023-00607-y.
Kalli, M., Li, R., Mills, G.B., Stylianopoulos, T., & Zervantonakis, I.K. (2022). Mechanical Stress Signaling in Pancreatic Cancer Cells Triggers p38 MAPK- and JNK-Dependent Cytoskeleton Remodeling and Promotes Cell Migration via Rac1/cdc42/Myosin II. Mol Cancer Res, 20(3), 485-497.American Association for Cancer Research (AACR). doi: 10.1158/1541-7786.MCR-21-0266.
Labrie, M., Brugge, J.S., Mills, G.B., & Zervantonakis, I.K. (2022). Therapy resistance: opportunities created by adaptive responses to targeted therapies in cancer. Nat Rev Cancer, 22(6), 323-339.Springer Nature. doi: 10.1038/s41568-022-00454-5.
Mohammad Mirzaei, N., Changizi, N., Asadpoure, A., Su, S., Sofia, D., Tatarova, Z., Zervantonakis, I.K., Chang, Y.H., & Shahriyari, L. (2022). Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model. In Gallo, J. (Ed.). PLoS Comput Biol, 18(3), e1009953.Public Library of Science (PLoS). doi: 10.1371/journal.pcbi.1009953.
Mohammad Mirzaei, N., Tatarova, Z., Hao, W., Changizi, N., Asadpoure, A., Zervantonakis, I.K., Hu, Y., Chang, Y.H., & Shahriyari, L. (2022). A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice. J Pers Med, 12(5), 807.MDPI. doi: 10.3390/jpm12050807.
Poskus, M.D., Wang, T., Deng, Y., Borcherding, S., Atkinson, J., & Zervantonakis, I.K. (2022). Digital Light Processing 3D printing for biological applications of polydimethylsiloxane-based microfluidics. 2022.09.28.509779.Cold Spring Harbor Laboratory. doi: 10.1101/2022.09.28.509779.
Scott, A.L., Kulawiec, D., Jazwinska, D., & Zervantonakis, I.K. (2022). Paracrine CSF1 signaling regulates macrophage migration dynamics towards ovarian cancer cells in a 3D microfluidic model that recapitulates in vivo infiltration patterns in patient-derived xenograft models. 2022.09.27.509704.Cold Spring Harbor Laboratory. doi: 10.1101/2022.09.27.509704.
Stahlberg, E.A., Abdel-Rahman, M., Aguilar, B., Asadpoure, A., Beckman, R.A., Borkon, L.L., Bryan, J.N., Cebulla, C.M., Chang, Y.H., Chatterjee, A., Deng, J., Dolatshahi, S., Gevaert, O., Greenspan, E.J., Hao, W., Hernandez-Boussard, T., Jackson, P.R., Kuijjer, M., Lee, A., Macklin, P., Madhavan, S., McCoy, M.D., Mohammad Mirzaei, N., Razzaghi, T., Rocha, H.L., Shahriyari, L., Shmulevich, I., Stover, D.G., Sun, Y., Syeda-Mahmood, T., Wang, J., Wang, Q., & Zervantonakis, I. (2022). Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation. Front Digit Health, 4, 1007784.Frontiers. doi: 10.3389/fdgth.2022.1007784.
Hamalian, S., Güth, R., Runa, F., Sanchez, F., Vickers, E., Agajanian, M., Molnar, J., Nguyen, T., Gamez, J., Humphries, J.D., Nayak, A., Humphries, M.J., Tchou, J., Zervantonakis, I.K., & Kelber, J.A. (2021). A SNAI2-PEAK1-INHBA stromal axis drives progression and lapatinib resistance in HER2-positive breast cancer by supporting subpopulations of tumor cells positive for antiapoptotic and stress signaling markers. Oncogene, 40(33), 5224-5235.Springer Nature. doi: 10.1038/s41388-021-01906-2.
Kalli, M., Li, R., Mills, G.B., Stylianopoulos, T., & Zervantonakis, I.K. (2021). Mechanical stress in pancreatic cancer: Signaling pathway adaptation activates cytoskeletal remodeling and enhances cell migration. 2021.06.11.448065.Cold Spring Harbor Laboratory. doi: 10.1101/2021.06.11.448065.
Mohammad Mirzaei, N., Su, S., Sofia, D., Hegarty, M., Abdel-Rahman, M.H., Asadpoure, A., Cebulla, C.M., Chang, Y.H., Hao, W., Jackson, P.R., Lee, A.V., Stover, D.G., Tatarova, Z., Zervantonakis, I.K., & Shahriyari, L. (2021). A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration. J Pers Med, 11(10), 1031.MDPI. doi: 10.3390/jpm11101031.
Correa, S., Boehnke, N., Barberio, A.E., Deiss-Yehiely, E., Shi, A., Oberlton, B., Smith, S.G., Zervantonakis, I., Dreaden, E.C., & Hammond, P.T. (2020). Tuning Nanoparticle Interactions with Ovarian Cancer through Layer-by-Layer Modification of Surface Chemistry. ACS Nano, 14(2), 2224-2237.American Chemical Society (ACS). doi: 10.1021/acsnano.9b09213.
Hamalian, S., Güth, R., Runa, F., Molnar, J., Vickers, E., Agajanian, M., Humphries, J., Humphries, M.J., Tchou, J., Zervantonakis, I.K., & Kelber, J.A. (2020). A SNAI2-PEAK1 stromal axis drives progression and lapatinib resistance in HER2-positive breast cancer by supporting a cytokine expression profile that converges on PI3K/Akt signaling. 2020.05.15.098772.Cold Spring Harbor Laboratory. doi: 10.1101/2020.05.15.098772.
Nyman, E., Stein, R.R., Jing, X., Wang, W., Marks, B., Zervantonakis, I.K., Korkut, A., Gauthier, N.P., & Sander, C. (2020). Perturbation biology links temporal protein changes to drug responses in a melanoma cell line. In Faeder, J.R. (Ed.). PLoS Comput Biol, 16(7), e1007909.Public Library of Science (PLoS). doi: 10.1371/journal.pcbi.1007909.
Sarkizova, S., Klaeger, S., Le, P.M., Li, L.W., Oliveira, G., Keshishian, H., Hartigan, C.R., Zhang, W., Braun, D.A., Ligon, K.L., Bachireddy, P., Zervantonakis, I.K., Rosenbluth, J.M., Ouspenskaia, T., Law, T., Justesen, S., Stevens, J., Lane, W.J., Eisenhaure, T., Lan Zhang, G., Clauser, K.R., Hacohen, N., Carr, S.A., Wu, C.J., & Keskin, D.B. (2020). A large peptidome dataset improves HLA class I epitope prediction across most of the human population. Nat Biotechnol, 38(2), 199-209.Springer Nature. doi: 10.1038/s41587-019-0322-9.
Zervantonakis, I. (2020). Improving cancer combination therapy by timing drug administration. Science Translational Medicine, 12(539).American Association for the Advancement of Science (AAAS). doi: 10.1126/scitranslmed.abb5671.
Zervantonakis, I. (2020). Cancer-immune topology influences lung cancer evolution. Science Translational Medicine, 12(547).American Association for the Advancement of Science (AAAS). doi: 10.1126/scitranslmed.abc8944.
Zervantonakis, I. (2020). Not all fibroblasts are equal in cancer. Science Translational Medicine, 12(555).American Association for the Advancement of Science (AAAS). doi: 10.1126/scitranslmed.abd4769.
Zervantonakis, I. (2020). Uncovering metabolic states in cytotoxic T cells, one cell at a time. Science Translational Medicine, 12(563).American Association for the Advancement of Science (AAAS). doi: 10.1126/scitranslmed.abe6027.
Zervantonakis, I.K., Poskus, M.D., Scott, A.L., Selfors, L.M., Lin, J.R., Dillon, D.A., Pathania, S., Sorger, P.K., Mills, G.B., & Brugge, J.S. (2020). Fibroblast-tumor cell signaling limits HER2 kinase therapy response via activation of MTOR and antiapoptotic pathways. Proc Natl Acad Sci U S A, 117(28), 16500-16508.Proceedings of the National Academy of Sciences. doi: 10.1073/pnas.2000648117.
Zhao, W., Li, J., Chen, M.J.M., Luo, Y., Ju, Z., Nesser, N.K., Johnson-Camacho, K., Boniface, C.T., Lawrence, Y., Pande, N.T., Davies, M.A., Herlyn, M., Muranen, T., Zervantonakis, I.K., von Euw, E., Schultz, A., Kumar, S.V., Korkut, A., Spellman, P.T., Akbani, R., Slamon, D.J., Gray, J.W., Brugge, J.S., Lu, Y., Mills, G.B., & Liang, H. (2020). Large-Scale Characterization of Drug Responses of Clinically Relevant Proteins in Cancer Cell Lines. Cancer Cell, 38(6), 829-843.e4.Elsevier. doi: 10.1016/j.ccell.2020.10.008.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U.A., Hallberg, D., Velculescu, V.E., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2019). Combined MEK and BCL-2/XL Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient-Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. Mol Cancer Ther, 18(3), 642-655.American Association for Cancer Research (AACR). doi: 10.1158/1535-7163.MCT-18-0413.
Stover, E.H., Baco, M.B., Cohen, O., Li, Y.Y., Christie, E.L., Bagul, M., Goodale, A., Lee, Y., Pantel, S., Rees, M.G., Wei, G., Presser, A.G., Gelbard, M.K., Zhang, W., Zervantonakis, I.K., Bhola, P.D., Ryan, J., Guerriero, J.L., Montero, J., Liang, F.J., Cherniack, A.D., Piccioni, F., Matulonis, U.A., Bowtell, D.D.L., Sarosiek, K.A., Letai, A., Garraway, L.A., Johannessen, C.M., & Meyerson, M. (2019). Pooled Genomic Screens Identify Anti-apoptotic Genes as Targetable Mediators of Chemotherapy Resistance in Ovarian Cancer. Mol Cancer Res, 17(11), 2281-2293.American Association for Cancer Research (AACR). doi: 10.1158/1541-7786.MCR-18-1243.
Najafov, A., Zervantonakis, I.K., Mookhtiar, A.K., Greninger, P., March, R.J., Egan, R.K., Luu, H.S., Stover, D.G., Matulonis, U.A., Benes, C.H., & Yuan, J. (2018). BRAF and AXL oncogenes drive RIPK3 expression loss in cancer. In Green, D. (Ed.). PLoS Biol, 16(8), e2005756.Public Library of Science (PLoS). doi: 10.1371/journal.pbio.2005756.
Funamoto, K., Yoshino, D., Matsubara, K., Zervantonakis, I.K.Funamoto, K., Nakayama, M., Masamune, J., Kimura, Y., & Kamm, R.D. (2017). Endothelial monolayer permeability under controlled oxygen tension. Integr Biol (Camb), 9(6), 529-538.Oxford University Press (OUP). doi: 10.1039/c7ib00068e.
Liu, J.F., Palakurthi, S., Zeng, Q., Zhou, S., Ivanova, E., Huang, W., Zervantonakis, I.K., Selfors, L.M., Shen, Y., Pritchard, C.C., Zheng, M., Adleff, V., Papp, E., Piao, H., Novak, M., Fotheringham, S., Wulf, G.M., English, J., Kirschmeier, P.T., Velculescu, V.E., Paweletz, C., Mills, G.B., Livingston, D.M., Brugge, J.S., Matulonis, U.A., & Drapkin, R. (2017). Establishment of Patient-Derived Tumor Xenograft Models of Epithelial Ovarian Cancer for Preclinical Evaluation of Novel Therapeutics. Clin Cancer Res, 23(5), 1263-1273.American Association for Cancer Research (AACR). doi: 10.1158/1078-0432.CCR-16-1237.
Zervantonakis, I.K., Iavarone, C., Chen, H.Y., Selfors, L.M., Palakurthi, S., Liu, J.F., Drapkin, R., Matulonis, U., Leverson, J.D., Sampath, D., Mills, G.B., & Brugge, J.S. (2017). Systems analysis of apoptotic priming in ovarian cancer identifies vulnerabilities and predictors of drug response. Nat Commun, 8(1), 365.Springer Nature. doi: 10.1038/s41467-017-00263-7.
Gallegos, L.L., Ng, M.R., Sowa, M.E., Selfors, L.M., White, A., Zervantonakis, I.K., Singh, P., Dhakal, S., Harper, J.W., & Brugge, J.S. (2016). A protein interaction map for cell-cell adhesion regulators identifies DUSP23 as a novel phosphatase for β-catenin. Sci Rep, 6(1), 27114.Springer Nature. doi: 10.1038/srep27114.
Iwanicki, M.P., Chen, H.Y., Iavarone, C., Zervantonakis, I.K., Muranen, T., Novak, M., Ince, T.A., Drapkin, R., & Brugge, J.S. (2016). Mutant p53 regulates ovarian cancer transformed phenotypes through autocrine matrix deposition. JCI Insight, 1(10), e86829.American Society for Clinical Investigation. doi: 10.1172/jci.insight.86829.
Kobus, T., Zervantonakis, I.K., Zhang, Y., & McDannold, N.J. (2016). Growth inhibition in a brain metastasis model by antibody delivery using focused ultrasound-mediated blood-brain barrier disruption. J Control Release, 238, 281-288.Elsevier. doi: 10.1016/j.jconrel.2016.08.001.
Spiegel, A., Brooks, M.W., Houshyar, S., Reinhardt, F., Ardolino, M., Fessler, E., Chen, M.B., Krall, J.A., DeCock, J., Zervantonakis, I.K., Iannello, A., Iwamoto, Y., Cortez-Retamozo, V., Kamm, R.D., Pittet, M.J., Raulet, D.H., & Weinberg, R.A. (2016). Neutrophils Suppress Intraluminal NK Cell-Mediated Tumor Cell Clearance and Enhance Extravasation of Disseminated Carcinoma Cells. Cancer Discov, 6(6), 630-649.American Association for Cancer Research (AACR). doi: 10.1158/2159-8290.CD-15-1157.
Zervantonakis, I.K., & Arvanitis, C.D. (2016). Controlled Drug Release and Chemotherapy Response in a Novel Acoustofluidic 3D Tumor Platform. Small, 12(19), 2616-2626.Wiley. doi: 10.1002/smll.201503342.
Kandela, I., Zervantonakis, I., Reproducibility Project: Cancer Biology, & Reproducibility Project Cancer Biology. (2015). Registered report: Discovery and preclinical validation of drug indications using compendia of public gene expression data. Elife, 4(MAY), e06847.eLife. doi: 10.7554/eLife.06847.
Pavesi, A., Adriani, G., Rasponi, M., Zervantonakis, I.K., Fiore, G.B., & Kamm, R.D. (2015). Controlled electromechanical cell stimulation on-a-chip. Sci Rep, 5(1), 11800.Springer Nature. doi: 10.1038/srep11800.
Schuessler, T.K., Chan, X.Y., Chen, H.J., Ji, K., Park, K.M., Roshan-Ghias, A., Sethi, P., Thakur, A., Tian, X., Villasante, A., Zervantonakis, I.K., Moore, N.M., Nagahara, L.A., & Kuhn, N.Z. (2014). Biomimetic tissue-engineered systems for advancing cancer research: NCI Strategic Workshop report. Cancer Res, 74(19), 5359-5363.American Association for Cancer Research (AACR). doi: 10.1158/0008-5472.CAN-14-1706.
Srinivasan, P., Zervantonakis, I.K., & Kothapalli, C.R. (2014). Synergistic effects of 3D ECM and chemogradients on neurite outgrowth and guidance: a simple modeling and microfluidic framework. In Weaver, A.M. (Ed.). PLoS One, 9(6), e99640.Public Library of Science (PLoS). doi: 10.1371/journal.pone.0099640.
Aref, A.R., Huang, R.Y.J., Yu, W., Chua, K.N., Sun, W., Tu, T.Y., Bai, J., Sim, W.J., Zervantonakis, I.K., Thiery, J.P., & Kamm, R.D. (2013). Screening therapeutic EMT blocking agents in a three-dimensional microenvironment. Integr Biol (Camb), 5(2), 381-389.Oxford University Press (OUP). doi: 10.1039/c2ib20209c.
Jeon, J.S., Zervantonakis, I.K., Chung, S., Kamm, R.D., & Charest, J.L. (2013). In vitro model of tumor cell extravasation. In Koutsopoulos, S. (Ed.). PLoS One, 8(2), e56910.Public Library of Science (PLoS). doi: 10.1371/journal.pone.0056910.
Polacheck, W.J., Zervantonakis, I.K., & Kamm, R.D. (2013). Tumor cell migration in complex microenvironments. Cell Mol Life Sci, 70(8), 1335-1356.Springer Nature. doi: 10.1007/s00018-012-1115-1.
Chan, J.M., Zervantonakis, I.K., Rimchala, T., Polacheck, W.J., Whisler, J., & Kamm, R.D. (2012). Engineering of in vitro 3D capillary beds by self-directed angiogenic sprouting. In Kirchmair, R. (Ed.). PLoS One, 7(12), e50582.Public Library of Science (PLoS). doi: 10.1371/journal.pone.0050582.
Farahat, W.A., Wood, L.B., Zervantonakis, I.K., Schor, A., Ong, S., Neal, D., Kamm, R.D., & Asada, H.H. (2012). Ensemble analysis of angiogenic growth in three-dimensional microfluidic cell cultures. In Egles, C. (Ed.). PLoS One, 7(5), e37333.Public Library of Science (PLoS). doi: 10.1371/journal.pone.0037333.
Funamoto, K., Zervantonakis, I.K., Liu, Y., Ochs, C.J., Kim, C., & Kamm, R.D. (2012). A novel microfluidic platform for high-resolution imaging of a three-dimensional cell culture under a controlled hypoxic environment. Lab Chip, 12(22), 4855-4863.Royal Society of Chemistry (RSC). doi: 10.1039/c2lc40306d.
Shin, Y., Han, S., Jeon, J.S., Yamamoto, K., Zervantonakis, I.K., Sudo, R., Kamm, R.D., & Chung, S. (2012). Microfluidic assay for simultaneous culture of multiple cell types on surfaces or within hydrogels. Nat Protoc, 7(7), 1247-1259.Springer Nature. doi: 10.1038/nprot.2012.051.
Zervantonakis, I.K., Hughes-Alford, S.K., Charest, J.L., Condeelis, J.S., Gertler, F.B., & Kamm, R.D. (2012). Three-dimensional microfluidic model for tumor cell intravasation and endothelial barrier function. Proc Natl Acad Sci U S A, 109(34), 13515-13520.Proceedings of the National Academy of Sciences. doi: 10.1073/pnas.1210182109.
Kothapalli, C.R., van Veen, E., de Valence, S., Chung, S., Zervantonakis, I.K., Gertler, F.B., & Kamm, R.D. (2011). A high-throughput microfluidic assay to study neurite response to growth factor gradients. Lab Chip, 11(3), 497-507.Royal Society of Chemistry (RSC). doi: 10.1039/c0lc00240b.
Luo, Y., Zervantonakis, I.K., Oh, S.B., Kamm, R.D., & Barbastathis, G. (2011). Spectrally resolved multidepth fluorescence imaging. J Biomed Opt, 16(9), 096015.SPIE, the international society for optics and photonics. doi: 10.1117/1.3626211.
Zervantonakis, I.K., Kothapalli, C.R., Chung, S., Sudo, R., & Kamm, R.D. (2011). Microfluidic devices for studying heterotypic cell-cell interactions and tissue specimen cultures under controlled microenvironments. Biomicrofluidics, 5(1), 13406.AIP Publishing. doi: 10.1063/1.3553237.
Chung, S., Sudo, R., Zervantonakis, I.K., Rimchala, T., & Kamm, R.D. (2009). Microfluidics: surface-treatment-induced three-dimensional capillary morphogenesis in a microfluidic platform (adv. Mater. 47/2009). Adv Mater, 21(47).Wiley. doi: 10.1002/adma.200990175.
Chung, S., Sudo, R., Zervantonakis, I.K., Rimchala, T., & Kamm, R.D. (2009). Surface-treatment-induced three-dimensional capillary morphogenesis in a microfluidic platform. Adv Mater, 21(47), 4863-4867.Wiley. doi: 10.1002/adma.200901727.
Sudo, R., Chung, S., Zervantonakis, I.K., Vickerman, V., Toshimitsu, Y., Griffith, L.G., & Kamm, R.D. (2009). Transport-mediated angiogenesis in 3D epithelial coculture. FASEB J, 23(7), 2155-2164.Wiley. doi: 10.1096/fj.08-122820.
Das, S.K., Chung, S., Zervantonakis, I., Atnafu, J., & Kamm, R.D. (2008). A microfluidic platform for studying the effects of small temperature gradients in an incubator environment. Biomicrofluidics, 2(3), 34106.AIP Publishing. doi: 10.1063/1.2988313.
Zervantonakis, I.K., Fung-Kee-Fung, S.D., Lee, W.N., & Konofagou, E.E. (2007). A novel, view-independent method for strain mapping in myocardial elastography: eliminating angle and centroid dependence. Phys Med Biol, 52(14), 4063-4080.IOP Publishing. doi: 10.1088/0031-9155/52/14/004.
Cho, Y., Li, R., & Zervantonakis, I. (2023). Inhibition of myosin II in triple-negative breast cancer cells limits macrophage recruitment in a 3D environment. In CANCER RESEARCH, 83(7), (p. 4613).American Association for Cancer Research (AACR). doi: 10.1158/1538-7445.AM2023-4613.
Kalli, M., Li, R., Zervantonakis, I., & Stylianopoulos, T. (2022). Mechanical stress activates autophagy to induce drug resistance in pancreatic cancer cells. In CANCER RESEARCH, 82(12).
Kalli, M., Li, R., Zervantonakis, I., & Stylianopoulos, T. (2022). Mechanical stress activates autophagy to induce drug resistance in pancreatic cancer cells. In CANCER RESEARCH, 82(12).
Scott, A.L., Ayoola, O., & Zervantonakis, I.K. (2021). Microfluidic modeling of tumor-macrophage signaling in ovarian cancer. In CANCER RESEARCH, 81(5), (p. po042).American Association for Cancer Research (AACR). doi: 10.1158/1538-7445.TME21-PO042.
Rosenbluth, J.M., Zervantonakis, I., Boedicker, M., Wagle, N., Dillon, D., Nakhlis, F., Brugge, J.S., & Overmoyer, B. (2019). Patient-derived organoid models of inflammatory breast cancer. In CANCER RESEARCH, 79(4), (p. p5-17-01-p5-17-01).American Association for Cancer Research (AACR). doi: 10.1158/1538-7445.SABCS18-P5-17-01.
Stover, E.H., Baco, M.B., Cohen, O., Li, Y., Christie, E., Bagul, M., Goodale, A., Lee, Y., Pantel, S., Rees, M., Wei, G., Presser, A., Zervantonakis, I., Bhola, P., Ryan, J., Guerriero, J., Liang, F., Cherniack, A., Piccioni, F., Matulonis, U.A., Bowtell, D.D.L., Letai, A., Sarosiek, K., Garraway, L., Johannessen, C.M., & Meyerson, M. (2019). POOLED GENOMIC SCREENS IDENTIFY ANTI-APOPTOTIC GENES AS MEDIATORS OF CHEMOTHERAPY RESISTANCE IN OVARIAN CANCER. In CLINICAL CANCER RESEARCH, 25(22), (p. 74).
Hamalian, S., Guth, R., Zervantonakis, I., Duell, E., Lin, J.R., Shisgal, P., Molnar, J., Geller, C., Agajanian, M., Tchou, J., Sorger, P.K., Brugge, J.S., & Kelber, J.A. (2018). Mesenchymal stromal cells expressing a PEAK1/Cripto axis sustain pro-survival NF-κB signaling in adjacent tumor cells to promote disease progression and therapy resistance. In CANCER RESEARCH, 78(13), (p. 2140).American Association for Cancer Research (AACR). doi: 10.1158/1538-7445.AM2018-2140.
Iavarone, C., Zervantonakis, I.K., Selfors, L.M., Palakurthi, S.S., Liu, J.F., Drapkin, R., Mills, G.B., Leverson, J.D., Sampath, D., Matulonis, U.A., & Brugge, J.S. (2018). Combined MEK and BCL-2/XL inhibition as a potential drug combination for the treatment of high-grade serous ovarian cancer. In CLINICAL CANCER RESEARCH, 24(15), (pp. 31-+).
Iavarone, C., Zervantonakis, I., Selfors, L.M., Palakurthi, S., Liu, J.F., Matulonis, U.A., Drapkin, R.I., Mills, G.B., Leverson, J.D., Sampath, D., & Brugge, J.S. (2017). Combined MEK and BCL-2/XL inhibition as a potential drug combination for the treatment of high-grade serous ovarian cancer. In CANCER RESEARCH, 77(13_Supplement), (p. 4033).American Association for Cancer Research (AACR). doi: 10.1158/1538-7445.AM2017-4033.
Zervantonakis, I.K., Iavarone, C., Chen, H.Y., Leverson, J., Sampath, D., Palakurthi, S., Drapkin, R., Liu, J.F., Matulonis, U., Mills, G., & Brugge, J.S. (2017). Systems analysis of signaling pathway adaptation to design effective PI3K-based combination therapies using ovarian cancer patient-derived xenografts. In CANCER RESEARCH, 77(2_Supplement), (p. pr01).American Association for Cancer Research (AACR). doi: 10.1158/1538-7445.EPSO16-PR01.
Iavarone, C., Zervantonakis, I., Chen, H.Y., Palakurthi, S.S., Liu, J.F., Matulonis, U., Drapkin, R., Mills, G., Leverson, J., Sampath, D., & Brugge, J. (2016). Design of effective combination therapies for high-grade serous ovarian cancer using patient -derived xenograft models. In CANCER RESEARCH, 76(14_Supplement), (p. 3843).American Association for Cancer Research (AACR). doi: 10.1158/1538-7445.AM2016-3843.
Iavarone, C., Zervantonakis, I., Chen, H.Y., Palakurthi, S.S., Liu, J.F., Matulonis, U.A., Drapkin, R.I., Mills, G.B., Leverson, J.D., Sampath, D., & Brugge, J.S. (2016). Design of effective combination therapies for high-grade serous ovarian cancer using patient-derived xenograft models. In CLINICAL CANCER RESEARCH, 22(2_Supplement), (p. b48).American Association for Cancer Research (AACR). doi: 10.1158/1557-3265.OVCA15-B48.
Iwanicki, M.P., Chen, H.Y., Zervantonakis, I., Novak, M., Muranen, T., Ince, T.A., Drapkin, R., & Brugge, J.S. (2016). Mutant p53 drives early events in fallopian tube tumorigenesis through mesenchyme-associated autocrine production of matrix that supports survival and mesothelial intercalation. In CLINICAL CANCER RESEARCH, 22(2_Supplement), (p. pr12).American Association for Cancer Research (AACR). doi: 10.1158/1557-3265.OVCA15-PR12.
Zervantonakis, I., Chen, H.Y., Muranen, T., Liu, J., Drapkin, R., Matulonis, U., & Brugge, J. (2015). Adaptive resistance of patient-derived ovarian cancer cells to PI3K/mTOR inhibition. In CLINICAL CANCER RESEARCH, 21(4_Supplement), (p. pr01).American Association for Cancer Research (AACR). doi: 10.1158/1557-3265.PMS14-PR01.
Gallegos, L.L., Ng, M.R., Sowa, M.E., White, A., Selfors, L., Zervantonakis, I., Dhakal, S., Singh, P., Harper, J.W., & Brugge, J.S. (2014). A functional proteomic study identifies multiple novel regulators of epithelial cell-cell adhesion. In MOLECULAR BIOLOGY OF THE CELL, 25.
Srinivasan, P., Zervantonakis, I.K., & Kothapalli, C.R. (2014). Theoretical and Experimental Framework of Neurite Response to Chemical Gradients in 3D Matrices. In BIOPHYSICAL JOURNAL, 106(2), (p. 572A).Elsevier. doi: 10.1016/j.bpj.2013.11.3172.
Iwanicki, M.P., Novak, M., Zervantonakis, I.K., Ince, T.A., Drapkin, R., & Brugge, J.S. (2013). Targeting mutant p53 and cell-cell adhesion in ovarian cancer. In CLINICAL CANCER RESEARCH, 19(19_Supplement), (p. a7).American Association for Cancer Research (AACR). doi: 10.1158/1078-0432.OVCA13-A7.
Luo, Y., Zervantonakis, I., Oh, B., Kamm, R., & Barbastathis, G. (2011). Spectrum resolved fluorescence imaging in multi-focal volume holographic microscopy. In Raghavachari, R., & Liang, R. (Eds.). In Proceedings of SPIE--the International Society for Optical Engineering, 7891, (p. 78910c-78910c-5).SPIE, the international society for optics and photonics. doi: 10.1117/12.874570.
Chung, S., Sudo, R., Vickerman, V., Zervantonakis, I.K., & Kamm, R.D. (2010). Microfluidic platforms for studies of angiogenesis, cell migration, and cell-cell interactions. Sixth International Bio-Fluid Mechanics Symposium and Workshop March 28-30, 2008 Pasadena, California. In Ann Biomed Eng, 38(3), (pp. 1164-1177).Springer Nature.United States. doi: 10.1007/s10439-010-9899-3.
Zervantonakis, I., Sudo, R., Rimchala, T., Polacheck, W., Chung, S., & Kamm, R. (2009). A physiological relevant 3D in vitro model of cancer cell migration and interactions with endothelium. In CANCER RESEARCH, 69.
Chung, S., Sudo, R., Zervantonakis, I., Rimchala, T., Mack, P.J., Wan, C.R., Vickerman, V., & Kamm, R.D. (2008). Microfluidic platform to study three dimensional cell migration & capillary morphogenesis. In 12th International Conference on Miniaturized Systems for Chemistry and Life Sciences - The Proceedings of MicroTAS 2008 Conference, (pp. 24-26).