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. Cho, BA, Iyengar, NM, Zhou, XK, Morrow, M, Giri, DD, Verma, A et al.. Blood Biomarkers Reflect the Effects of Obesity and Inflammation on the Human Breast Transcriptome. Carcinogenesis. 2021; :. doi: 10.1093/carcin/bgab066. PubMed PMID:34314488 .
  2. Zoughbi, WA, Fox, J, Beg, S, Papp, E, Hissong, E, Ohara, K et al.. Validation of a ctDNA-based next-generation sequencing assay in a cohort of solid tumor patients: a proposed solution for decentralized plasma testing. Oncologist. 2021; :. doi: 10.1002/onco.13905. PubMed PMID:34286887 .
  3. Jobanputra, V, Wrzeszczynski, KO, Buttner, R, Caldas, C, Cuppen, E, Grimmond, S et al.. Clinical interpretation of whole-genome and whole-transcriptome sequencing for precision oncology. Semin Cancer Biol. 2021; :. doi: 10.1016/j.semcancer.2021.07.003. PubMed PMID:34256129 .
  4. Cox, N, Crozet, L, Holtman, IR, Loyher, PL, Lazarov, T, White, JB et al.. Diet-regulated production of PDGFcc by macrophages controls energy storage. Science. 2021;373 (6550):. doi: 10.1126/science.abe9383. PubMed PMID:34210853 .
  5. Croker, JA, Patel, R, Campbell, KS, Barton-Baxter, M, Wallet, S, Firestein, GS et al.. Building biorepositories in the midst of a pandemic. J Clin Transl Sci. 2021;5 (1):e92. doi: 10.1017/cts.2021.6. PubMed PMID:34192049 PubMed Central PMC8134891.
  6. Rosenquist, R, Cuppen, E, Buettner, R, Caldas, C, Dreau, H, Elemento, O et al.. Clinical utility of whole-genome sequencing in precision oncology. Semin Cancer Biol. 2021; :. doi: 10.1016/j.semcancer.2021.06.018. PubMed PMID:34175442 .
  7. Napoli, S, Cascione, L, Rinaldi, A, Spriano, F, Guidetti, F, Zhang, F et al.. Characterization of GECPAR, a noncoding RNA that regulates the transcriptional program of diffuse large B cell lymphoma. Haematologica. 2021; :. doi: 10.3324/haematol.2020.267096. PubMed PMID:34162177 .
  8. Meggendorfer, M, Jobanputra, V, Wrzeszczynski, KO, Roepman, P, de Bruijn, E, Cuppen, E et al.. Analytical demands to use whole-genome sequencing in precision oncology. Semin Cancer Biol. 2021; :. doi: 10.1016/j.semcancer.2021.06.009. PubMed PMID:34119643 .
  9. Brady, NJ, Bagadion, AM, Singh, R, Conteduca, V, Van Emmenis, L, Arceci, E et al.. Temporal evolution of cellular heterogeneity during the progression to advanced AR-negative prostate cancer. Nat Commun. 2021;12 (1):3372. doi: 10.1038/s41467-021-23780-y. PubMed PMID:34099734 PubMed Central PMC8185096.
  10. Sugita, M, Wilkes, DC, Bareja, R, Eng, KW, Nataraj, S, Jimenez-Flores, RA et al.. Targeting the epichaperome as an effective precision medicine approach in a novel PML-SYK fusion acute myeloid leukemia. NPJ Precis Oncol. 2021;5 (1):44. doi: 10.1038/s41698-021-00183-2. PubMed PMID:34040147 PubMed Central PMC8155064.
  11. Elemento, O. Towards artificial intelligence-driven pathology assessment for hematological malignancies. Blood Cancer Discov. 2021;2 (3):195-197. doi: 10.1158/2643-3230.bcd-21-0048. PubMed PMID:34027414 PubMed Central PMC8133372.
  12. Altorki, NK, McGraw, TE, Borczuk, AC, Saxena, A, Port, JL, Stiles, BM et al.. Neoadjuvant durvalumab with or without stereotactic body radiotherapy in patients with early-stage non-small-cell lung cancer: a single-centre, randomised phase 2 trial. Lancet Oncol. 2021;22 (6):824-835. doi: 10.1016/S1470-2045(21)00149-2. PubMed PMID:34015311 .
  13. Xu, Z, Verma, A, Naveed, U, Bakhoum, SF, Khosravi, P, Elemento, O et al.. Deep learning predicts chromosomal instability from histopathology images. iScience. 2021;24 (5):102394. doi: 10.1016/j.isci.2021.102394. PubMed PMID:33997679 PubMed Central PMC8099498.
  14. 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 .
  15. 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 .
  16. 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;595 (7865):114-119. doi: 10.1038/s41586-021-03569-1. PubMed PMID:33915568 .
  17. 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 .
  18. 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.
  19. 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 PubMed Central PMC8185639.
  20. 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 PubMed Central PMC8102200.
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