Wikipedia

Christina Curtis

Christina Curtis is an American scientist who is a Professor of Medicine, Genetics and Biomedical Data Science and an Endowed Scholar at Stanford University[1][3] where her research investigates the evolution of tumors.[4] She is director of Artificial Intelligence and Cancer Genomics at Stanford University School of Medicine and is on the board of directors of the American Association for Cancer Research.

Christina Curtis
Curtis in 2021
Alma materUniversity of California, Los Angeles
Heidelberg University
University of Southern California
Scientific career
FieldsCancer genomics
Tumor evolution
Computational biology
Early detection[1]
InstitutionsStanford University
University of Cambridge
ThesisAnalysis of high-density oligonucleotide gene expression data for dissecting aging pathways (2007)
Doctoral advisorSimon Tavaré[2]
Websiteprofiles.stanford.edu/christina-curtis Edit this at Wikidata

Early life and education edit

Curtis decided that she wanted to work on cancer treatments when she was a teenager.[5] She was an undergraduate student at the University of California, Los Angeles[6] and did a masters degree at Heidelberg University.[7] She moved to the University of Southern California for graduate studies, where she earned both a master's and a doctoral degree.[8] She completed her PhD in molecular and computational biology in 2007 supervised by Simon Tavaré.[2][9]

Research and career edit

Curtis was a postdoctoral researcher at the University of Cambridge, where she spent three years before returning to the faculty at the University of Southern California.[citation needed]

Curtis has leveraged computational modeling to better understand breast cancer, providing insight into the evolution and metastasization of tumors.[10] She established the Cancer Computational and Systems Biology group.

Curtis uses computer simulations to understand genetic mutations in tumor samples.[11] She believes that breast cancer tumors have genetic differences that respond differently to treatments.[11] In 2019, she combined molecular analysis and historical clinical data to create the largest breast cancer cohort. In this cohort she found four groups of tumors that occur later in life, up to 20 years after the initial cancer diagnosis. She also found a subset of breast cancer tumors that do not recur after five years.[12] To this end, Curtis believes that tumors with metastatic potential have this from the start – they are "born to be bad".[5]

In 2022, Curtis was appointed director of Artificial Intelligence and Cancer Genomics at the Stanford Cancer Institute.[citation needed]

Awards and honors edit

Selected publications edit

  • Curtis C; Shah SP; Chin SF; et al. (18 April 2012). "The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups". Nature. 486 (7403): 346–52. doi:10.1038/NATURE10983. ISSN 1476-4687. PMC 3440846. PMID 22522925. Wikidata Q29614700.
  • Jae-Ho Cheong (11 September 2014). "Comprehensive molecular characterization of gastric adenocarcinoma". Nature. 513 (7517): 202–9. doi:10.1038/NATURE13480. ISSN 1476-4687. PMC 4170219. PMID 25079317. Wikidata Q28244985.
  • Andrea Sottoriva; Haeyoun Kang; Zhicheng Ma; et al. (9 February 2015). "A Big Bang model of human colorectal tumor growth". Nature Genetics. 47 (3): 209–216. doi:10.1038/NG.3214. ISSN 1061-4036. PMC 4575589. PMID 25665006. Wikidata Q36074227.

References edit

  1. ^ a b Christina Curtis publications indexed by Google Scholar  
  2. ^ a b Christina Curtis at the Mathematics Genealogy Project  
  3. ^ Christina Curtis publications from Europe PubMed Central
  4. ^ "Q&A: Christina Curtis on Computational and Systems Biology". Cancer Discovery. 10 (2): 169. 22 January 2020. doi:10.1158/2159-8290.CD-ND2020-001. ISSN 2159-8274. PMID 31969324. Wikidata Q92858397.
  5. ^ a b "Christina Curtis, PhD, MSc: Researching Ways to Intercept Cancer at Its Earliest Stages". aacr.org. American Association for Cancer Research. Retrieved 2023-05-09.
  6. ^ Christina Curtis on LinkedIn  
  7. ^ "Christina Curtis". med.stanford.edu. Stanford Medicine. Retrieved 2023-05-09.
  8. ^ Curtis, Christina (2007). Analysis of high-density oligonucleotide gene expression data for dissecting aging pathways (PhD thesis). University of Southern California. ISBN 978-0-549-83622-3. ProQuest 304825898.
  9. ^ a b "Christina Curtis". bcrf.org. Breast Cancer Research Foundation. 2014-06-24. Retrieved 2023-05-09.
  10. ^ "Meet the Team". med.stanford.edu. Retrieved 2023-05-09.
  11. ^ a b c "Pioneer Award Program - Program Highlights". commonfund.nih.gov. 2013-06-26. Retrieved 2023-05-09.
  12. ^ Rueda, Oscar M.; Sammut, Stephen-John; Seoane, Jose A.; Chin, Suet-Feung; Caswell-Jin, Jennifer L.; Callari, Maurizio; Batra, Rajbir; Pereira, Bernard; Bruna, Alejandra; Ali, H. Raza; Provenzano, Elena; Liu, Bin; Parisien, Michelle; Gillett, Cheryl; McKinney, Steven (March 2019). "Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups". Nature. 567 (7748): 399–404. Bibcode:2019Natur.567..399R. doi:10.1038/s41586-019-1007-8. ISSN 1476-4687. PMC 6647838. PMID 30867590.
  13. ^ Fletcher, Alexandra (2012-10-30). "Christina Curtis wins young investigator award". stemcell.keck.usc.edu. University of Southern California. Retrieved 2023-05-09.
  14. ^ "Christina Curtis". nasonline.org. Retrieved 2023-05-09.
  15. ^ "Meet Our Scholars". komen.org. Susan G. Komen. Retrieved 2023-05-09.
  16. ^ Jarrett, Keke (2022-04-09). "AACR honors elite group with scientific achievement awards and lectureships". aacrmeetingnews.org. AACR Annual Meeting News. Retrieved 2023-05-09.
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