Olivier Elemento, Ph.D.

Professor of Physiology and Biophysics

  • Walter B. Wriston Research Scholar
  • Professor of Computational Genomics in Computational Biomedicine and Associate Director of the Institute for Computational Biomedicine
  • Director of the Englander Institute for Precision Medicine
  • Associate Director of the Institute for Computational Biomedicine


1305 York Avenue, Room Y-13.13
New York, NY 10021


Research Areas

Research Summary:

The Elemento lab combines Big Data analytics with experimentation to develop entirely new ways to help prevent, diagnose, understand, treat and ultimately cure cancer. Our research involves routine use of ultrafast DNA sequencing, proteomics, high-performance computing, mathematical modeling, and artificial intelligence/machine learning.

More specifically, we are working on :

  • Systems biology of regulatory networks in normal and malignant cells, with a strong focus on blood cancers (lymphomas and leukemias). We use ChIP-seq, RNA-seq, computational modeling to investigate how genes are regulated in cancer cells and how gene regulation in cancer cells differs from normal cells.
  • Cancer genomics and precision medicine. Using novel computational algorithms, we seek to identify new cancer mutations and understand why and where cancer mutations occur. We work on determining whether 3D chromatin architecture predicts where mutations are most likely to occur.
  • Epigenomics of cancer. Genes coding for proteins that modify, maintain or read the epigenome (DNA methylation and histone modifications) and are among the most frequently mutated genes in cancer. We use high-throughput experimental approaches and pattern detection techniques to investigate what these genes do and the genomewide epigenomic patterns they mediate.
  • Tumor genome evolution, anticancer drug resistance. Cancer is a fundamentally evolutionary disease. Using high-throughput sequencing, we are investigating how the tumor genome (and epigenome) evolves in time and particularly upon drug treatment.
  • Early cancer detection using machine learning. We use advanced machine learning approaches (artificial intelligence techniques) to detect cancer as early as possible and help guide treatment accordingly. One of our algorithms for thyroid cancer detection, based on Support Vector Machines, was recently licensed by Prolias Technologies.
  • Development of innovative computational approaches for analysis of high-throughput experiments (metabolomics, proteomics, high-throughout sequencing, etc) performed on cancer cells. For example we have developed ChIPseeqer, a broadly used ChIPseq data analysis framework.


Recent Publications:

  1. Wagner, AH, Walsh, B, Mayfield, G, Tamborero, D, Sonkin, D, Krysiak, K et al.. A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer. Nat. Genet. 2020;52 (4):448-457. doi: 10.1038/s41588-020-0603-8. PubMed PMID:32246132 .
  2. Hwang, I, Pan, H, Yao, J, Elemento, O, Zheng, H, Paik, J et al.. CIC is a critical regulator of neuronal differentiation. JCI Insight. 2020; :. doi: 10.1172/jci.insight.135826. PubMed PMID:32229723 .
  3. Lehmann, GL, Hanke-Gogokhia, C, Hu, Y, Bareja, R, Salfati, Z, Ginsberg, M et al.. Single-cell profiling reveals an endothelium-mediated immunomodulatory pathway in the eye choroid. J. Exp. Med. 2020;217 (6):. doi: 10.1084/jem.20190730. PubMed PMID:32196081 .
  4. Bhinder, B, Elemento, O. Computational methods in tumor immunology. Meth. Enzymol. 2020;636 :209-259. doi: 10.1016/bs.mie.2020.01.001. PubMed PMID:32178820 .
  5. De Micheli, AJ, Laurilliard, EJ, Heinke, CL, Ravichandran, H, Fraczek, P, Soueid-Baumgarten, S et al.. Single-Cell Analysis of the Muscle Stem Cell Hierarchy Identifies Heterotypic Communication Signals Involved in Skeletal Muscle Regeneration. Cell Rep. 2020;30 (10):3583-3595.e5. doi: 10.1016/j.celrep.2020.02.067. PubMed PMID:32160558 PubMed Central PMC7091476.
  6. Dalton, T, Doubrovina, E, Pankov, D, Reynolds, RC, Scholze, H, Selvakumar, A et al.. Epigenetic reprogramming sensitizes immunologically silent EBV+ lymphomas to viral directed immunotherapy. Blood. 2020; :. doi: 10.1182/blood.2019004126. PubMed PMID:32157281 .
  7. Conteduca, V, Ku, SY, Puca, L, Slade, M, Fernandez, L, Hess, J et al.. SLFN11 expression in advanced prostate cancer and response to platinum-based chemotherapy. Mol. Cancer Ther. 2020; :. doi: 10.1158/1535-7163.MCT-19-0926. PubMed PMID:32127465 .
  8. Verma, A, Muthukumar, T, Yang, H, Lubetzky, M, Cassidy, MF, Lee, JR et al.. Urinary cell transcriptomics and acute rejection in human kidney allografts. JCI Insight. 2020;5 (4):. doi: 10.1172/jci.insight.131552. PubMed PMID:32102984 PubMed Central PMC7101135.
  9. Ge, Y, Miao, Y, Gur-Cohen, S, Gomez, N, Yang, H, Nikolova, M et al.. The aging skin microenvironment dictates stem cell behavior. Proc. Natl. Acad. Sci. U.S.A. 2020;117 (10):5339-5350. doi: 10.1073/pnas.1901720117. PubMed PMID:32094197 PubMed Central PMC7071859.
  10. Beltran, H, Romanel, A, Conteduca, V, Casiraghi, N, Sigouros, M, Franceschini, GM et al.. Circulating tumor DNA profile recognizes transformation to castration-resistant neuroendocrine prostate cancer. J. Clin. Invest. 2020;130 (4):1653-1668. doi: 10.1172/JCI131041. PubMed PMID:32091413 PubMed Central PMC7108892.
  11. Park, K, Tran, H, Eng, KW, Ramazanoglu, S, Marrero Rolon, RM, Scognamiglio, T et al.. Performance Characteristics of a Targeted Sequencing Platform for Simultaneous Detection of Single Nucleotide Variants, Insertions/Deletions, Copy Number Alterations, and Gene Fusions in Cancer Genome. Arch. Pathol. Lab. Med. 2020; :. doi: 10.5858/arpa.2019-0162-OA. PubMed PMID:32045275 .
  12. Yomtoubian, S, Lee, SB, Verma, A, Izzo, F, Markowitz, G, Choi, H et al.. Inhibition of EZH2 Catalytic Activity Selectively Targets a Metastatic Subpopulation in Triple-Negative Breast Cancer. Cell Rep. 2020;30 (3):755-770.e6. doi: 10.1016/j.celrep.2019.12.056. PubMed PMID:31968251 .
  13. Casiraghi, N, Orlando, F, Ciani, Y, Xiang, J, Sboner, A, Elemento, O et al.. ABEMUS: platform specific and data informed detection of somatic SNVs in cfDNA. Bioinformatics. 2020; :. doi: 10.1093/bioinformatics/btaa016. PubMed PMID:31922552 .
  14. Iaea, DB, Spahr, ZR, Singh, RK, Chan, RB, Zhou, B, Bareja, R et al.. Stable reduction of STARD4 alters cholesterol regulation and lipid homeostasis. Biochim Biophys Acta Mol Cell Biol Lipids. 2020;1865 (4):158609. doi: 10.1016/j.bbalip.2020.158609. PubMed PMID:31917335 PubMed Central PMC6996790.
  15. Madhukar, NS, Khade, PK, Huang, L, Gayvert, K, Galletti, G, Stogniew, M et al.. A Bayesian machine learning approach for drug target identification using diverse data types. Nat Commun. 2019;10 (1):5221. doi: 10.1038/s41467-019-12928-6. PubMed PMID:31745082 PubMed Central PMC6863850.
  16. Sivakumar, R, Chan, M, Shin, JS, Nishida-Aoki, N, Kenerson, HL, Elemento, O et al.. Organotypic tumor slice cultures provide a versatile platform for immuno-oncology and drug discovery. Oncoimmunology. 2019;8 (12):e1670019. doi: 10.1080/2162402X.2019.1670019. PubMed PMID:31741771 PubMed Central PMC6844320.
  17. Lourenco, AR, Ban, Y, Crowley, MJ, Lee, SB, Ramchandani, D, Du, W et al.. Differential Contributions of Pre- and Post-EMT Tumor Cells in Breast Cancer Metastasis. Cancer Res. 2020;80 (2):163-169. doi: 10.1158/0008-5472.CAN-19-1427. PubMed PMID:31704888 PubMed Central PMC6980649.
  18. Sailer, V, Eng, KW, Zhang, T, Bareja, R, Pisapia, DJ, Sigaras, A et al.. Integrative Molecular Analysis of Patients With Advanced and Metastatic Cancer. JCO Precis Oncol. 2019;3 :. doi: 10.1200/PO.19.00047. PubMed PMID:31592503 PubMed Central PMC6778956.
  19. Courtiol, P, Maussion, C, Moarii, M, Pronier, E, Pilcer, S, Sefta, M et al.. Deep learning-based classification of mesothelioma improves prediction of patient outcome. Nat. Med. 2019;25 (10):1519-1525. doi: 10.1038/s41591-019-0583-3. PubMed PMID:31591589 .
  20. Conteduca, V, Oromendia, C, Eng, KW, Bareja, R, Sigouros, M, Molina, A et al.. Clinical features of neuroendocrine prostate cancer. Eur. J. Cancer. 2019;121 :7-18. doi: 10.1016/j.ejca.2019.08.011. PubMed PMID:31525487 PubMed Central PMC6803064.
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