Peter Karl Sorger

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Peter Karl Sorger
<headshot of Peter Sorger circa 2014 wearing glasses and blue button-down shirt>
Sorger in 2014
Born1961 (age 62–63)
Halifax Nova Scotia, Canada
TitleOtto Krayer Professor of Systems Pharmacology, Harvard Medical School
SpouseCaroline Shamu
Awards
Academic background
Alma mater
ThesisThe transcriptional regulation of heat shock genes (1988)
Doctoral advisorHugh Pelham
Other advisors
Academic work
Discipline
Institutions

Peter Karl Sorger (born February 13, 1961, in Halifax Nova Scotia, Canada) is a systems and cancer biologist and Otto Krayer Professor of Systems Pharmacology in the Department of Systems Biology at Harvard Medical School.[1] Sorger is the founding head of the Harvard Program in Therapeutic Science (HiTS), director of its Laboratory of Systems Pharmacology (LSP), and co-director of the Harvard MIT Center for Regulatory Science. He was previously a Professor of Biology and Biological Engineering at the Massachusetts Institute of Technology where he co-founded its program on Computational and Systems Biology (CSBi). Sorger is known for his work in the field of systems biology and for having helped launch the field of computational and systems pharmacology. His research focuses on the molecular origins of cancer and approaches to accelerate the development of new medicines. Sorger teaches Principles and Practice of Drug Development at Massachusetts Institute of Technology and Harvard University.

Early life

Sorger was born on February 13, 1961, in Halifax Nova Scotia, Canada to Scottish and Austrian parents. His family immigrated to the US in 1963. He graduated summa cum laude from Harvard College in 1983 (in Biochemistry) where he studied the assembly of icosahedral viruses under the supervision of Stephen C. Harrison. He received his PhD for Biochemistry as a Marshall Scholar from Trinity College, Cambridge for research on the transcriptional regulation of heat shock genes[2][3] under the supervision of Hugh Pelham at the Medical Research Council Laboratory of Molecular Biology in Cambridge, England. He then trained as a Richard Childs Fellow and Lucille P. Markey Scholar with Harold Varmus and Andrew Murray at the University of California, San Francisco.

Career

Sorger joined the MIT Department of Biology in 1994 following a year as a visiting scientist with Anthony A. Hyman at the European Molecular Biology Laboratory, Heidelberg, Germany. Sorger became a full Professor in the MIT Biology and Biological Engineering Departments in 2004.

Sorger's postdoctoral and early faculty research led to the first reconstitution of a chromosome-microtubule attachment (a yeast kinetochore) and the subsequent identification of multiple kinetochore proteins.[4][5] His group identified mammalian homologs of the checkpoint proteins that regulate entry into mitosis, and showed that mutations in these genes can be oncogenic because they cause chromosome instability.[6][7][8] This work contributed to the understanding of the faithful transmission of chromosomes from mother to daughter cells. Defects in these mechanisms cause aneuploidy that plays a major role in oncogenic transformation.

Working closely with Doug Lauffenburger and funded by the Defense Advanced Research Projects Agency and the National Institutes of Health's National Centers for Systems Biology program,[9] Sorger's work in the 1990s increasingly focused on oncogenesis itself and on mammalian signal transduction.[10] Sorger and Lauffenburger's approach combined molecular genetics, live-cell microscopy and mechanistic computational modeling.[11][12] Their focus on biochemistry REF was unusual in an era dominated by genomics and ultimately led Sorger to co-found the software company Glencoe Software and the biotech company Merrimack Pharmaceuticals.[13] Subsequent work by Sorger' group led to a new understanding of stochastic fluctuation in cellular responses to natural ligands and drugs[14][15] and to the development of a range of innovative computational methods, including the biochemistry-specific Python PySB[16] and the natural language processing and knowledge assembly system INDRA.[17][18]

In 2011, Sorger was active in the development of the discipline of Quantitative Systems Pharmacology, including overseeing the preparation of a widely cited white paper for the NIH entitled "Quantitative and Systems Pharmacology in the Post-genomic Era: New Approaches to Discovering Drugs and Understanding Therapeutic Mechanisms".[19] This white paper envisioned the emergence of an empirically based but computationally sophisticated approach to the science underlying development of innovative new medicines. Sorger moved to Harvard Medical School[20] to pursue these approaches by establishing the Laboratory of Systems Pharmacology, which merges laboratory experiments, computer science, and medicine to fundamentally improve drug discovery.[21] Funding from the Massachusetts Life Sciences Center in 2014[22] and 2017[23][24] made the lab a reality and it now has 150 faculty trainees and staff from Boston-area institutions including Harvard University, MIT, Tufts University, Northeastern University and Harvard-affiliated Hospitals.

Sorger's research involves multiple systems pharmacology approaches to cancer. The first focuses on preclinical pharmacology, the stage at which the molecular mechanisms of disease are studied and new drugs sought. An investigation into the causes of irreproducibility drug-response measurements[25] led to a series of conceptual,[26] computational,[27] and experimental improvements[28] in scoring drug action that are now widely used in academe and industry and have enabled the discovery of new mechanisms of action for existing drugs.[29] Recent work has focused on deep learning as means to further understand complex protein networks and drug mechanisms.[30][31] The second project involves developing methods to study drug mechanism at scale in patients through highly multiplexed tissue imaging[32][33] of the biopsies routinely acquired from patients (particularly cancer patients).[34] This has led to a very rapidly growing tissue imaging and digital histology program[35] that is part of the US National Cancer Institute Moonshot and promises to substantially advance precision cancer care.[36] The third project involves studying the clinical trial record to understand how successful and failed trials differ. An early success was the discovery that the great majority of approved combination cancer therapies exhibit independent action – not synergy.[37][38] As Merck & Co. investigators subsequently realized, this fundamentally changes how immunotherapy combinations should be developed.[39] The group is now engaged in a large-scale effort[40] to digitize and make freely available all survival data from Phase 3 clinical trials.[41]

COVID-19 pandemic research

To address the need for face masks, respirators and other personal protective equipment for healthcare workers in the early COVID-19 pandemic, Sorger, physician Nicole LeBoeuf and MD-PhD student Deborah Plana established the Boston Area Pandemic Fabrication team (PanFab).[42][43] This team of students and alumni from MIT and Harvard teamed up with local industry and led a series of 3D printing and rapid-turn manufacturing projects to make face shields,[44] mask frames,[45] powered air purifying respirators[46] and new ways to sterilize and reuse 95 respirators.[47] PanFab led to over a dozen open access publications and designs, including a thorough review of lessons learned[48] and a hope that we can be better prepared for future pandemics.

References

  1. ^ "Peter Sorger". sysbio.med.harvard.edu. Retrieved 18 December 2021.
  2. ^ Sorger, P. K.; Pelham, H. R. (9 September 1988). "Yeast heat shock factor is an essential DNA-binding protein that exhibits temperature-dependent phosphorylation". Cell. 24 (6): 855–864. doi:10.1016/S0092-8674(88)91219-6. PMID 3044613. S2CID 45178990. Retrieved 29 November 2021.
  3. ^ Sorger, P. K.; Lewis, M. J.; Pelham, H. R. (September 3, 1987). "Heat shock factor is regulated differently in yeast and HeLa cells". Nature. 329 (6134): 81–84. Bibcode:1987Natur.329...81S. doi:10.1038/329081a0. PMID 3306402. S2CID 4315665. Retrieved 29 November 2021.
  4. ^ He, X.; Rines, D. R.; Espelin, C. W.; Sorger, P. K. (2001). "Molecular analysis of kinetochore-microtubule attachment in budding yeast". Cell. 106 (2): 195–206. doi:10.1016/S0092-8674(01)00438-X. PMID 11511347. S2CID 15917728.
  5. ^ Kaplan, K. B.; Hyman, A. A.; Sorger, P. K. (1997). "Regulating the yeast kinetochore by ubiquitin-dependent degradation and Skp1p-mediated phosphorylation". Cell. 91 (4): 491–500. doi:10.1016/s0092-8674(00)80435-3. PMID 9390558. S2CID 9159412.
  6. ^ Foijer, F.; Albacker, L. A.; Bakker, B.; Spierings, D.C.; Yue, Y.; Xie, S. Z.; Davis, S.; Lutum-Jehle, A.; Takemoto, D. (2017). "Deletion of the MAD2L1 spindle assembly checkpoint gene is tolerated in mouse models of acute T-cell lymphoma and hepatocellular carcinoma". eLife. 6: e20873. doi:10.7554/eLife.20873. PMC 5400506. PMID 28318489.
  7. ^ Dobles, M.; Liberal, V.; Scott, M. L.; Benezra, R.; Sorger, P. K. (2000). "Chromosome missegregation and apoptosis in mice lacking the mitotic checkpoint protein Mad2". Cell. 101 (6): P635-645. doi:10.1016/S0092-8674(00)80875-2. PMID 10892650. S2CID 12738892.
  8. ^ Michel, L. S.; Liberal, V.; Chatterjee, A.; Kirchwegger, R.; Pasche, B.; Gerald, W.; Dobles, M.; Sorger, P. K.; Murty, V. V. V. S.; Benzra, R. (2001). "MAD2 haplo-insufficiency causes premature anaphase and chromosome instability in mammalian cells". Nature. 409 (6818): 355–359. doi:10.1038/35053094. PMID 11201745. S2CID 4417961. Retrieved 16 December 2021.
  9. ^ "NIH grant aids MIT systems biology". MIT News. 15 September 2003. Retrieved 17 December 2021.
  10. ^ Janes, K. A.; Albeck, J. G.; Gaudet, S.; Sorger, P. K.; Lauffenburger, D. A.; Yaffe, M. B. (2005-12-09). "A systems model of signaling identifies a molecular basis set for cytokine-induced apoptosis". Science. 310 (5754): 1646–53. Bibcode:2005Sci...310.1646J. doi:10.1126/science.1116598. PMID 16339439. S2CID 22495219. Retrieved 16 December 2021.
  11. ^ Janes, K. A.; Gaudet, S.; Albeck, J. G.; Nielsen, U. B.; Lauffenburger, D. A.; Sorger, P. K. (2006-03-24). "The response of human epithelial cells to TNF involves an inducible autocrine cascade". Cell. 124 (6): 1225–1239. doi:10.1016/j.cell.2006.01.041. PMID 16564013. S2CID 540286.
  12. ^ Albeck, J. G.; Burke, J. M.; Spencer, S. L.; Lauffenburger, D. A.; Sorger, P. K. (2008-12-02). "Modeling a Snap-Action, Variable-Delay Switch Controlling Extrinsic Cell Death". PLOS Biology. 6 (12): 2831–2852. doi:10.1371/journal.pbio.0060299. PMC 2592357. PMID 19053173.
  13. ^ "Friendster for Proteins". Forbes. Feb 23, 2007. Retrieved 17 December 2021.
  14. ^ Spencer, S. L.; Gaudet, S.; Albeck, J. G.; Burke, J. M.; Sorger, P. K. (2009-05-21). "Non-genetic origins of cell-to-cell variability in TRAIL-induced apoptosis". Nature. 459 (7245): 428–32. Bibcode:2009Natur.459..428S. doi:10.1038/nature08012. PMC 2858974. PMID 19363473.
  15. ^ Spencer, S. L.; Sorger, P. K. (2011-03-18). "Measuring and modeling apoptosis in single cells". Cell. 144 (6): 926–39. doi:10.1016/j.cell.2011.03.002. PMC 3087303. PMID 21414484.
  16. ^ Lopez, C. F.; Muhlich, J. L.; Bachman, J. A.; Sorger, P. K. (2013-02-19). "Programming biological models in Python using PySB". Molecular Systems Biology. 9: 646. doi:10.1038/msb.2013.1. PMC 3588907. PMID 23423320.
  17. ^ Prabhakar, Arati. "The merging of humans and machines is happening now". WIRED. Retrieved 17 December 2021.
  18. ^ Gyori, B. M.; Bachman, J. A.; Subramanian, K.; Muhlich, J. L.; Galescu, L.; Sorger, P. K. (2017-11-24). "From word models to executable models of signaling networks using automated assembly". Molecular Systems Biology. 13 (11): 954. doi:10.15252/msb.20177651. PMC 5731347. PMID 29175850.
  19. ^ Sorger, P. K.; Allerheiligen, S.R.B. (October 2011). "Quantitative and Systems Pharmacology in the Post-genomic Era: New Approaches to Discovering Drugs and Understanding Therapeutic Mechanisms" (PDF). An NIH White Paper by the QSP Workshop Group: 1–47.
  20. ^ Xie, K. (17 June 2013). "Systematic Drug Discovery". Harvard Magazine. Retrieved 17 December 2021.
  21. ^ Bebinger, M. (August 10, 2015). "State-Funded Lab At Harvard Medical Aims To Reinvent Drug Discovery". WBUR. Retrieved 17 December 2021.
  22. ^ "Harvard Medical School Opens Laboratory of Systems Pharmacology". Massachusetts Life Sciences Center. 24 September 2014. Retrieved 17 December 2021.
  23. ^ "Investing in Innovation: Massachusetts Life Sciences Center gives Boston biomedicine an $18 million boost". HMS News. 19 May 2017. Retrieved 17 December 2021.
  24. ^ "HARVARD MEDICAL SCHOOL LABORATORY OF SYSTEMS PHARMACOLOGY". BDS Architects. Retrieved 17 December 2021.
  25. ^ Niepel, M.; Hafner, M.; Mills, C. E.; Subramanian, K.; Williams, E. H.; Chung, M.; Gaudio, B.; Barrette, A. M.; Stern, A. D.; Hu, B.; Korkola, J. E.; LINCS Consortium; Gray, J. W.; Birtwistle, M. R.; Heiser, L. M.; Sorger, P. K. (2019-07-05). "A Multi-center Study on the Reproducibility of Drug-Response Assays in Mammalian Cell Lines". Cell Systems. 9 (1): 35–48.e5. doi:10.1016/j.cels.2019.06.005. PMC 6700527. PMID 31302153.
  26. ^ Fallahi-Sichani, M.; Honarnejad, S.; Heiser, L. M.; Gray, J. W.; Sorger, P. K. (2013-11-01). "Metrics other than potency reveal systematic variation in responses to cancer drugs". Nature Chemical Biology. 9 (11): 708–14. doi:10.1038/nchembio.1337. PMC 3947796. PMID 24013279.
  27. ^ Hafner, M.; Niepel, M.; Chung, M.; Sorger, P. K. (2016-06-01). "Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs". Nature Methods. 13 (6): 521–527. doi:10.1038/nmeth.3853. PMC 4887336. PMID 27135972.
  28. ^ Mills, C. E.; Subramanian, K.; Hafner, M.; Niepel, M.; Gerosa, L.; Chung, M.; Victor, C.; Gaudio, B.; Yapp, C.; Sorger, P. K. (2021-08-28). "Multiplexed and reproducible high content screening of live and fixed cells using the Dye Drop method". doi:10.1101/2021.08.27.457854. S2CID 237356861. Retrieved 2021-09-27. {{cite journal}}: Cite journal requires |journal= (help)
  29. ^ Hafner, M.; Mills, C. E.; Subramanian, K.; Chen, C.; Chung, M.; Boswell, S. A.; Everley, R. A.; Liu, C.; Walmsley, C. S.; Juric, D.; Sorger, P. K. (2019-08-15). "Multiomics Profiling Establishes the Polypharmacology of FDA-Approved CDK4/6 Inhibitors and the Potential for Differential Clinical Activity". Cell Chemical Biology. 26 (8): 1067–1080.e8. doi:10.1016/j.chembiol.2019.05.005. PMC 6936329. PMID 31178407.
  30. ^ AlQuraishi, M.; Sorger, P. K. (2021-10-04). "Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms". Nature Methods. 18 (10): 1169–1180. doi:10.1038/s41592-021-01283-4. ISSN 1548-7091. PMC 8793939. PMID 34608321.
  31. ^ Cunningham, J. M.; Koytiger, G.; Sorger, P. K.; AlQuraishi, M. (2020-02-06). "Biophysical prediction of protein-peptide interactions and signaling networks using machine learning". Nature Methods. 17 (2): 175–183. doi:10.1038/s41592-019-0687-1. PMC 7004877. PMID 31907444.
  32. ^ Lin, J.-R.; Izar, B.; Wang, S.; Yapp, C.; Mei, S.; Shah, P. M.; Santagata, S.; Sorger, P. K. (2018-07-11). "Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes". eLife. 7. doi:10.7554/eLife.31657. ISSN 2050-084X. PMC 6075866. PMID 29993362.
  33. ^ Rashid, R.; Chen, Y.-A.; Hoffer, J.; Muhlich, J. L.; Lin, J.-R.; Krueger, R.; Pfister, H.; Mitchell, R.; Santagata, S.; Sorger, P. K. (2021-11-08). "Narrative online guides for the interpretation of digital-pathology images and tissue-atlas data". Nature Biomedical Engineering. 6 (5): 515–526. doi:10.1038/s41551-021-00789-8. PMC 9079188. PMID 34750536.
  34. ^ "Atlas maker: Q&A with Peter Sorger". Ludwig Cancer Research. Retrieved 16 December 2021.
  35. ^ "CyCIF - Cyclic Immunofluorescence". Retrieved 17 December 2021.
  36. ^ Liu, D.; Lin, J.-R.; Robitschek, E. J.; Kasumova, G. G.; Heyde, A.; Shi, A.; Kraya, A.; Zhang, G.; Moll, T.; Frederick, D. T.; Chen, Y.-A.; Wang, S.; Schapiro, D.; Ho, L.-L.; Bi, K.; Sahu, A.; Mei, S.; Miao, B.; Sharova, T.; Alvarez-Breckenridge, C.; Stocking, J. H.; Kim, T.; Fadden, R.; Lawrence, D.; Hoang, M. P.; Cahill, D. P.; Malehmir, M.; Nowak, M. A.; Brastianos, P. K.; Lian, C. G.; Ruppin, E.; Izar, B.; Herlyn, M.; Van Allen, E. M.; Nathanson, K.; Flaherty, K. T.; Sullivan, R. J.; Kellis, M; Sorger, P. K.; Boland, G. M. (2021-05-03). "Evolution of delayed resistance to immunotherapy in a melanoma responder". Nature Medicine. 27 (6): 985–992. doi:10.1038/s41591-021-01331-8. PMC 8474080. PMID 33941922.
  37. ^ Palmer, A. C.; Sorger, P. K. (2017-12-14). "Combination Cancer Therapy Can Confer Benefit via Patient-to-Patient Variability without Drug Additivity or Synergy". Cell. 171 (7): 1678–1691.e13. doi:10.1016/j.cell.2017.11.009. ISSN 1097-4172. PMC 5741091. PMID 29245013.
  38. ^ Palmer, A. C; Izar, B.; Sorger, P. K (2020-02-04). "Combinatorial benefit without synergy in recent clinical trials of immune checkpoint inhibitors". pp. 2020–01.31.20019604. medRxiv 10.1101/2020.01.31.20019604v2.
  39. ^ Chen, C.; Liu, F.; Ren, Y.; Suttner, L.; Sun, Z.; Shentu, Y.; Schmidt, E. V. (2020-11-01). "Independent drug action and its statistical implications for development of combination therapies". Contemporary Clinical Trials. 98: 106126. doi:10.1016/j.cct.2020.106126. PMID 32853780. S2CID 221359327. Retrieved 17 December 2021.
  40. ^ "Cancer Trials". CANCERTRIALS.io. Retrieved 17 December 2021.
  41. ^ Plana, D.; Fell, G.; Alexander, B. M.; Palmer, A. C.; Sorger, P. K. (2021-05-17). "Cancer patient survival can be accurately parameterized, revealing time-dependent therapeutic effects and doubling the precision of small trials". doi:10.1101/2021.05.14.442837. S2CID 234785442. Retrieved 2021-05-18. {{cite journal}}: Cite journal requires |journal= (help)
  42. ^ Sinha, M. S.; Bourgeois, F.T.; Sorger, Peter K. (2020-06-18). "Personal Protective Equipment for COVID-19: Distributed Fabrication and Additive Manufacturing". American Journal of Public Health. 110 (8): 1162–1164. doi:10.2105/AJPH.2020.305753. PMC 7349433. PMID 32552025.
  43. ^ "PanFab News". PanFab. Retrieved 17 December 2021.
  44. ^ Mostaghimi, A.; Antonini, M.-J.; Plana, D.; Anderson, P. D.; Beller, B.; Boyer, E. W.; Fannin, A.; Freake, J.; Oakley, R.; Sinha, M. S.; Smith, L.; Van, C.; Yang, H.; Sorger, P. K.; LeBoeuf, N. R.; Yu, S. H. (2020-12-18). "Regulatory and Safety Considerations in Deploying a Locally Fabricated, Reusable Face Shield in a Hospital Responding to the COVID-19 Pandemic". Med. 1 (1): 139–151.e4. doi:10.1016/j.medj.2020.06.003. hdl:1721.1/128858. PMC 7304404. PMID 32838357.
  45. ^ McAvoy, M.; Bui, A.-T. N.; Hansen, C.; Plana, D.; Said, J. T.; Yu, Z.; Yang, H.; Freake, J.; Van, C.; Krikorian, D.; Cramer, A.; Smith, L.; Jiang, L.; Lee, K. J.; Li, S. J.; Beller, B.; Huggins, K.; Short, M. P.; Yu, S. H.; Mostaghimi, A.; Sorger, P. K.; LeBoeuf, N. R. (2021-06-07). "3D Printed frames to enable reuse and improve the fit of N95 and KN95 respirators". BMC Biomedical Engineering. 3 (1): 10. doi:10.1186/s42490-021-00055-7. PMC 8182357. PMID 34099062.
  46. ^ Kothakonda, A.; Atta, L.; Plana, D.; Ward, F.; Davis, C.; Cramer, A.; Moran, R.; Freake, J.; Tian, E.; Mazor, O.; Gorelik, P.; Van, C.; Hansen, C.; Yang, H.; Sinha, M. S.; Li, J.; Yu, S. H.; LeBoeuf, N. R.; Sorger, P. K. (2021-03-29). "De novo Powered Air-Purifying Respirator Design and Fabrication for Pandemic Response". medRxiv 10.1101/2021.03.25.21252076.
  47. ^ Cramer, A. K.; Plana, D.; Yang, H.; Carmack, M. M.; Tian, E.; Sinha, M. S.; Krikorian, D.; Turner, D.; Mo, J.; Li, J.; Gupta, R.; Manning, H.; Bourgeois, F. T.; Yu, S. H.; Sorger, P. K.; LeBoeuf, N. R. (2021-01-21). "Analysis of SteraMist ionized hydrogen peroxide technology in the sterilization of N95 respirators and other PPE". Scientific Reports. 11 (1): 2051. doi:10.1038/s41598-021-81365-7. PMC 7819989. PMID 33479334.
  48. ^ Antonini, M.-J.; Plana, D.; Srinivasan, S.; Atta, L.; Achanta, A.; Yang, H.; Cramer, A.; Freake, J.; Sinha, M. S.; Yu, S. H.; LeBoeuf, N. R.; Linville-Engler, B.; Sorger, P. K. (2020-09-24). "A Crisis-Responsive Framework for Medical Device Development during the COVID-19 Pandemic". doi:10.20944/preprints202009.0577.v1. S2CID 224873745. Retrieved 2020-12-01. {{cite journal}}: Cite journal requires |journal= (help)
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