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. Pan, H, Renaud, L, Chaligne, R, Bloehdorn, J, Tausch, E, Mertens, D et al.. Discovery of candidate DNA methylation cancer driver genes. Cancer Discov. 2021; :. doi: 10.1158/2159-8290.CD-20-1334. PubMed PMID:33972312 .
  2. Al Zoughbi, W, Kim, D, Alperstein, SA, Ohara, K, Manohar, J, Greco, N et al.. Incorporating cytologic adequacy assessment into precision oncology workflow using telepathology: An institutional experience. Cancer Cytopathol. 2021; :. doi: 10.1002/cncy.22441. PubMed PMID:33929788 .
  3. Melms, JC, Biermann, J, Huang, H, Wang, Y, Nair, A, Tagore, S et al.. A molecular single-cell lung atlas of lethal COVID-19. Nature. 2021; :. doi: 10.1038/s41586-021-03569-1. PubMed PMID:33915568 .
  4. Elkhader, J, Elemento, O. Artificial intelligence in oncology: From bench to clinic. Semin Cancer Biol. 2021; :. doi: 10.1016/j.semcancer.2021.04.013. PubMed PMID:33915289 .
  5. Manohar, J, Abedian, S, Martini, R, Kulm, S, Salvatore, M, Ho, K et al.. Social and Clinical Determinants of COVID-19 Outcomes: Modeling Real-World Data from a Pandemic Epicenter. medRxiv. 2021; :. doi: 10.1101/2021.04.06.21254728. PubMed PMID:33851193 PubMed Central PMC8043490.
  6. Dixon, G, Pan, H, Yang, D, Rosen, BP, Jashari, T, Verma, N et al.. QSER1 protects DNA methylation valleys from de novo methylation. Science. 2021;372 (6538):. doi: 10.1126/science.abd0875. PubMed PMID:33833093 .
  7. Kassambara, A, Herviou, L, Ovejero, S, Jourdan, M, Thibaut, C, Vikova, V et al.. RNA-sequencing data-driven dissection of human plasma cell differentiation reveals new potential transcription regulators. Leukemia. 2021;35 (5):1451-1462. doi: 10.1038/s41375-021-01234-0. PubMed PMID:33824465 .
  8. Bhinder, B, Gilvary, C, Madhukar, NS, Elemento, O. Artificial Intelligence in Cancer Research and Precision Medicine. Cancer Discov. 2021;11 (4):900-915. doi: 10.1158/2159-8290.CD-21-0090. PubMed PMID:33811123 PubMed Central PMC8034385.
  9. Rendeiro, AF, Ravichandran, H, Bram, Y, Chandar, V, Kim, J, Meydan, C et al.. The spatial landscape of lung pathology during COVID-19 progression. Nature. 2021; :. doi: 10.1038/s41586-021-03475-6. PubMed PMID:33780969 .
  10. Park, J, Foox, J, Hether, T, Danko, D, Warren, S, Kim, Y et al.. Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps. bioRxiv. 2021; :. doi: 10.1101/2021.03.08.434433. PubMed PMID:33758858 PubMed Central PMC7987017.
  11. Khosravi, P, Lysandrou, M, Eljalby, M, Li, Q, Kazemi, E, Zisimopoulos, P et al.. A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology-Radiology Fusion. J Magn Reson Imaging. 2021; :. doi: 10.1002/jmri.27599. PubMed PMID:33719168 .
  12. Elemento, O. The road from Rous sarcoma virus to precision medicine. J Exp Med. 2021;218 (4):. doi: 10.1084/jem.20201754. PubMed PMID:33710257 PubMed Central PMC7961594.
  13. Wolujewicz, P, Aguiar-Pulido, V, AbdelAleem, A, Nair, V, Thareja, G, Suhre, K et al.. Genome-wide investigation identifies a rare copy-number variant burden associated with human spina bifida. Genet Med. 2021; :. doi: 10.1038/s41436-021-01126-9. PubMed PMID:33686259 .
  14. Guo, C, Crespo, M, Gurel, B, Dolling, D, Rekowski, J, Sharp, A et al.. CD38 in Advanced Prostate Cancers. Eur Urol. 2021; :. doi: 10.1016/j.eururo.2021.01.017. PubMed PMID:33678520 .
  15. Carrot-Zhang, J, Yao, X, Devarakonda, S, Deshpande, A, Damrauer, JS, Silva, TC et al.. Whole-genome characterization of lung adenocarcinomas lacking alterations in the RTK/RAS/RAF pathway. Cell Rep. 2021;34 (8):108784. doi: 10.1016/j.celrep.2021.108784. PubMed PMID:33626341 .
  16. Woo, XY, Giordano, J, Srivastava, A, Zhao, ZM, Lloyd, MW, de Bruijn, R et al.. Author Correction: Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts. Nat Genet. 2021;53 (5):761. doi: 10.1038/s41588-021-00811-4. PubMed PMID:33608693 .
  17. Carrot-Zhang, J, Yao, X, Devarakonda, S, Deshpande, A, Damrauer, JS, Silva, TC et al.. Whole-genome characterization of lung adenocarcinomas lacking the RTK/RAS/RAF pathway. Cell Rep. 2021;34 (5):108707. doi: 10.1016/j.celrep.2021.108707. PubMed PMID:33535033 PubMed Central PMC8009291.
  18. Montrose, DC, Saha, S, Foronda, M, McNally, EM, Chen, J, Zhou, XK et al.. Exogenous and Endogenous Sources of Serine Contribute to Colon Cancer Metabolism, Growth, and Resistance to 5-Fluorouracil. Cancer Res. 2021; :. doi: 10.1158/0008-5472.CAN-20-1541. PubMed PMID:33526512 .
  19. Bruno, NE, Nwachukwu, JC, Srinivasan, S, Nettles, CC, Izard, T, Jin, Z et al.. Chemical systems biology reveals mechanisms of glucocorticoid receptor signaling. Nat Chem Biol. 2021;17 (3):307-316. doi: 10.1038/s41589-020-00719-w. PubMed PMID:33510451 .
  20. Rivas, MA, Meydan, C, Chin, CR, Challman, MF, Kim, D, Bhinder, B et al.. Smc3 dosage regulates B cell transit through germinal centers and restricts their malignant transformation. Nat Immunol. 2021;22 (2):240-253. doi: 10.1038/s41590-020-00827-8. PubMed PMID:33432228 PubMed Central PMC7855695.
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