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. 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 .
  2. 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; :. doi: 10.1038/s41588-021-00811-4. PubMed PMID:33608693 .
  3. 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 .
  4. 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 .
  5. 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 .
  6. 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.
  7. Woo, XY, Giordano, J, Srivastava, A, Zhao, ZM, Lloyd, MW, de Bruijn, R et al.. Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts. Nat Genet. 2021;53 (1):86-99. doi: 10.1038/s41588-020-00750-6. PubMed PMID:33414553 PubMed Central PMC7808565.
  8. Li, J, Duran, MA, Dhanota, N, Chatila, WK, Bettigole, SE, Kwon, J et al.. Metastasis and immune evasion from extracellular cGAMP hydrolysis. Cancer Discov. 2020; :. doi: 10.1158/2159-8290.CD-20-0387. PubMed PMID:33372007 .
  9. Rendeiro, AF, Casano, J, Vorkas, CK, Singh, H, Morales, A, DeSimone, RA et al.. Profiling of immune dysfunction in COVID-19 patients allows early prediction of disease progression. Life Sci Alliance. 2021;4 (2):. doi: 10.26508/lsa.202000955. PubMed PMID:33361110 PubMed Central PMC7768198.
  10. Marderstein, AR, Davenport, ER, Kulm, S, Van Hout, CV, Elemento, O, Clark, AG et al.. Leveraging phenotypic variability to identify genetic interactions in human phenotypes. Am J Hum Genet. 2021;108 (1):49-67. doi: 10.1016/j.ajhg.2020.11.016. PubMed PMID:33326753 PubMed Central PMC7820920.
  11. Yusufova, N, Kloetgen, A, Teater, M, Osunsade, A, Camarillo, JM, Chin, CR et al.. Histone H1 loss drives lymphoma by disrupting 3D chromatin architecture. Nature. 2021;589 (7841):299-305. doi: 10.1038/s41586-020-3017-y. PubMed PMID:33299181 PubMed Central PMC7855728.
  12. Vosoughi, A, Zhang, T, Shohdy, KS, Vlachostergios, PJ, Wilkes, DC, Bhinder, B et al.. Common germline-somatic variant interactions in advanced urothelial cancer. Nat Commun. 2020;11 (1):6195. doi: 10.1038/s41467-020-19971-8. PubMed PMID:33273457 PubMed Central PMC7713129.
  13. Chu, CS, Hellmuth, JC, Singh, R, Ying, HY, Skrabanek, L, Teater, MR et al.. Unique Immune Cell Coactivators Specify Locus Control Region Function and Cell Stage. Mol Cell. 2020;80 (5):845-861.e10. doi: 10.1016/j.molcel.2020.10.036. PubMed PMID:33232656 PubMed Central PMC7737631.
  14. Xie, XP, Laks, DR, Sun, D, Poran, A, Laughney, AM, Wang, Z et al.. High-resolution mouse subventricular zone stem-cell niche transcriptome reveals features of lineage, anatomy, and aging. Proc Natl Acad Sci U S A. 2020;117 (49):31448-31458. doi: 10.1073/pnas.2014389117. PubMed PMID:33229571 PubMed Central PMC7733854.
  15. Kolin, DA, Kulm, S, Christos, PJ, Elemento, O. Clinical, regional, and genetic characteristics of Covid-19 patients from UK Biobank. PLoS One. 2020;15 (11):e0241264. doi: 10.1371/journal.pone.0241264. PubMed PMID:33201886 PubMed Central PMC7671499.
  16. Beg, S, Bareja, R, Ohara, K, Eng, KW, Wilkes, DC, Pisapia, DJ et al.. Integration of whole-exome and anchored PCR-based next generation sequencing significantly increases detection of actionable alterations in precision oncology. Transl Oncol. 2021;14 (1):100944. doi: 10.1016/j.tranon.2020.100944. PubMed PMID:33190043 PubMed Central PMC7674614.
  17. Curchoe, CL, Malmsten, J, Bormann, C, Shafiee, H, Flores-Saiffe Farias, A, Mendizabal, G et al.. Predictive modeling in reproductive medicine: Where will the future of artificial intelligence research take us?. Fertil Steril. 2020;114 (5):934-940. doi: 10.1016/j.fertnstert.2020.10.040. PubMed PMID:33160516 .
  18. Hajirasouliha, I, Elemento, O. Precision medicine and artificial intelligence: overview and relevance to reproductive medicine. Fertil Steril. 2020;114 (5):908-913. doi: 10.1016/j.fertnstert.2020.09.156. PubMed PMID:33160512 .
  19. Rendeiro, AF, Ravichandran, H, Bram, Y, Salvatore, S, Borczuk, A, Elemento, O et al.. The spatio-temporal landscape of lung pathology in SARS-CoV-2 infection. medRxiv. 2020; :. doi: 10.1101/2020.10.26.20219584. PubMed PMID:33140072 PubMed Central PMC7605585.
  20. Hadi, K, Yao, X, Behr, JM, Deshpande, A, Xanthopoulakis, C, Tian, H et al.. Distinct Classes of Complex Structural Variation Uncovered across Thousands of Cancer Genome Graphs. Cell. 2020;183 (1):197-210.e32. doi: 10.1016/j.cell.2020.08.006. PubMed PMID:33007263 .
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