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

646-962-5726

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


Techniques

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. 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 .
  2. 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 .
  3. 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 .
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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 .
  10. 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.
  11. Fernandez, EM, Eng, K, Beg, S, Beltran, H, Faltas, BM, Mosquera, JM et al.. Cancer-Specific Thresholds Adjust for Whole Exome Sequencing-based Tumor Mutational Burden Distribution. JCO Precis Oncol. 2019;3 :. doi: 10.1200/PO.18.00400. PubMed PMID:31475242 PubMed Central PMC6716608.
  12. Ma, J, Redmond, D, Miyaguchi, A, Nam, AS, Nie, K, Mathew, S et al.. Exploring tumor clonal evolution in bone marrow of patients with diffuse large B-cell lymphoma by deep IGH sequencing and its potential relevance in relapse. Blood Cancer J. 2019;9 (9):69. doi: 10.1038/s41408-019-0229-1. PubMed PMID:31434873 PubMed Central PMC6704167.
  13. Springer, NL, Iyengar, NM, Bareja, R, Verma, A, Jochelson, MS, Giri, DD et al.. Obesity-Associated Extracellular Matrix Remodeling Promotes a Macrophage Phenotype Similar to Tumor-Associated Macrophages. Am. J. Pathol. 2019;189 (10):2019-2035. doi: 10.1016/j.ajpath.2019.06.005. PubMed PMID:31323189 PubMed Central PMC6880774.
  14. Khosravi, P, Kazemi, E, Zhan, Q, Malmsten, JE, Toschi, M, Zisimopoulos, P et al.. Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization. NPJ Digit Med. 2019;2 :21. doi: 10.1038/s41746-019-0096-y. PubMed PMID:31304368 PubMed Central PMC6550169.
  15. Mueller, FB, Yang, H, Lubetzky, M, Verma, A, Lee, JR, Dadhania, DM et al.. Landscape of innate immune system transcriptome and acute T cell-mediated rejection of human kidney allografts. JCI Insight. 2019;4 (13):. doi: 10.1172/jci.insight.128014. PubMed PMID:31292297 PubMed Central PMC6629252.
  16. Robinson, BD, Vlachostergios, PJ, Bhinder, B, Liu, W, Li, K, Moss, TJ et al.. Upper tract urothelial carcinoma has a luminal-papillary T-cell depleted contexture and activated FGFR3 signaling. Nat Commun. 2019;10 (1):2977. doi: 10.1038/s41467-019-10873-y. PubMed PMID:31278255 PubMed Central PMC6611775.
  17. Gilvary, C, Madhukar, N, Elkhader, J, Elemento, O. The Missing Pieces of Artificial Intelligence in Medicine. Trends Pharmacol. Sci. 2019;40 (8):555-564. doi: 10.1016/j.tips.2019.06.001. PubMed PMID:31277839 .
  18. Zaninovic, N, Elemento, O, Rosenwaks, Z. Artificial intelligence: its applications in reproductive medicine and the assisted reproductive technologies. Fertil. Steril. 2019;112 (1):28-30. doi: 10.1016/j.fertnstert.2019.05.019. PubMed PMID:31277764 .
  19. Berger, A, Brady, NJ, Bareja, R, Robinson, B, Conteduca, V, Augello, MA et al.. N-Myc-mediated epigenetic reprogramming drives lineage plasticity in advanced prostate cancer. J. Clin. Invest. 2019;130 :3924-3940. doi: 10.1172/JCI127961. PubMed PMID:31260412 PubMed Central PMC6715370.
  20. Lhuillier, C, Rudqvist, NP, Elemento, O, Formenti, SC, Demaria, S. Radiation therapy and anti-tumor immunity: exposing immunogenic mutations to the immune system. Genome Med. 2019;11 (1):40. doi: 10.1186/s13073-019-0653-7. PubMed PMID:31221199 PubMed Central PMC6587285.
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