Natalie Davidson, Ph.D. Weill Cornell Medicine
Extraordinary claims require extraordinary evidence. -Carl Sagan
- natalie.davidson@ inf.ethz.ch
- +41 43 254 0224
Biomedical Informatics Group
- SHM 26 B 3
I am interested in extending statistical models to gain deeper understanding of transcriptional dysregulation in cancer.
I am interested in understanding the role transcriptional dysregulation plays in cancer. Through my collaborations during my Ph.D., I have been able to conduct single cancer and pan-cancer analyses using RNA-Seq and Ribosome Profiling data. I typically use generalized linear models and generalized linear mixed models, but I am interested in extending to other models as the numbers of samples in cancer analyses grow. I am currently a part of the International Cancer Genome Consortium, where I integrate multiple transcriptional aberrations such as splicing, fusions, over/under expression, allele specific expression, and others in over 1,000 samples to identify cancer relevant genes and alteration patterns. I received my B.Sc. in computer science and minor in mathematics from University of California, Santa Barbara. I received my M.Sc. in computer science from University of California, Los Angeles under the advisement of Dr. Jason Ernst. I am currently obtaining my Ph.D from Tri-Institutional Program for Computational Biology and Medicine in New York, while conducting research at ETH Zürich.
Abstract We call upon the research community to standardize efforts to use daily self-reported data about COVID-19 symptoms in the response to the pandemic and to form a collaborative consortium to maximize global gain while protecting participant privacy. The rapid and global spread of COVID-19 led the World Health Organization to declare it a pandemic on 11 March 2020. One factor contributing to the spread of the pandemic is the lack of information about who is infected, in large part because of the lack of testing. This facilitated the silent spread of the causative coronavirus (SARS-CoV-2), which led to delays in public-health and government responses and an explosion in cases. In countries that have tested more aggressively and that had the capacity to transparently share this data, such as South Korea and Singapore, the spread of disease has been greatly slowed1. Although efforts are underway around the world to substantially ramp up testing capacity, technology-driven approaches to collecting self-reported information can fill an immediate need and complement official diagnostic results. This type of approach has been used for tracking other diseases, notably influenza2. The information collected may include health status that is self-reported through surveys, including those from mobile apps; results of diagnostic laboratory tests; and other static and real-time geospatial data. The collection of privacy-protected information from volunteers about health status over time may enable researchers to leverage these data to predict, respond to and learn about the spread of COVID-19. Given the global nature of the disease, we aim to form an international consortium, tentatively named the ‘Coronavirus Census Collective’, to serve as a hub for amassing this type of data and to create a unified platform for global epidemiological data collection and analysis.
Authors Segal E, Zhang F, Lin X, King G, Shalem O, Shilo S, Allen WE, Alquaddoomi F, Altae-Tran H, Anders S, Balicer R, Bauman T, Bonilla X, Booman G, Chan AT, Cohen O, Coletti S, Natalie R Davidson, Dor Y, Drew DA, Elemento O, Evans G, Ewels P, Gale J, Gavrieli A, Geiger B, Grad YH, Greene CS, Hajirasouliha I, Jerala R, Kahles A, Kallioniemi O, Keshet A, Kocarev L, Landua G, Meir T, Muller A, Nguyen LH, Oresic M, Ovchinnikova S, Peterson H, Prodanova J, Rajagopal J, Rätsch G, Rossman H, Rung J, Sboner A, Sigaras A, Spector T, Steinherz R, Stevens I, Vilo J, Wilmes P.
Submitted Nature Medicine
Abstract Transcript alterations often result from somatic changes in cancer genomes. Various forms of RNA alterations have been described in cancer, including overexpression, altered splicing and gene fusions; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed ‘bridged’ fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.
Authors PCAWG Transcriptome Core Group, Claudia Calabrese, Natalie R Davidson, Deniz Demircioğlu, Nuno A. Fonseca, Yao He, André Kahles, Kjong-Van Lehmann, Fenglin Liu, Yuichi Shiraishi, Cameron M. Soulette, Lara Urban, Liliana Greger, Siliang Li, Dongbing Liu, Marc D. Perry, Qian Xiang, Fan Zhang, Junjun Zhang, Peter Bailey, Serap Erkek, Katherine A. Hoadley, Yong Hou, Matthew R. Huska, Helena Kilpinen, Jan O. Korbel, Maximillian G. Marin, Julia Markowski, Tannistha Nandi, Qiang Pan-Hammarström, Chandra Sekhar Pedamallu, Reiner Siebert, Stefan G. Stark, Hong Su, Patrick Tan, Sebastian M. Waszak, Christina Yung, Shida Zhu, Philip Awadalla, Chad J. Creighton, Matthew Meyerson, B. F. Francis Ouellette, Kui Wu, Huanming Yang, PCAWG Transcriptome Working Group, Alvis Brazma, Angela N. Brooks, Jonathan Göke, Gunnar Rätsch, Roland F. Schwarz, Oliver Stegle, Zemin Zhang & PCAWG Consortium- Show fewer authors Nature volume 578, pages129–136(2020)Cite this article
Abstract Intra-tumor hypoxia is a common feature in many solid cancers. Although transcriptional targets of hypoxia-inducible factors (HIFs) have been well characterized, alternative splicing or processing of pre-mRNA transcripts which occurs during hypoxia and subsequent HIF stabilization is much less understood. Here, we identify HIF-dependent alternative splicing events after whole transcriptome sequencing in pancreatic cancer cells exposed to hypoxia with and without downregulation of the aryl hydrocarbon receptor nuclear translocator (ARNT), a protein required for HIFs to form a transcriptionally active dimer. We correlate the discovered hypoxia-driven events with available sequencing data from pan-cancer TCGA patient cohorts to select a narrow set of putative biologically relevant splice events for experimental validation. We validate a small set of candidate HIF-dependent alternative splicing events in multiple human cancer cell lines as well as patient-derived human pancreatic cancer organoids. Lastly, we report the discovery of a HIF-dependent mechanism to produce a hypoxia-dependent, long and coding isoform of the UDP-N-acetylglucosamine transporter SLC35A3.
Authors Philipp Markolin, Natalie R Davidson, Christian K. Hirt, Christophe D. Chabbert, Nicola Zamboni, Gerald Schwank, Wilhelm Krek, Gunnar Rätsch
Abstract Translation initiation is orchestrated by the cap binding and 43S pre-initiation complexes (PIC). Eukaryotic initiation factor 1A (EIF1A) is essential for recruitment of the ternary complex and for assembling the 43S PIC. Recurrent EIF1AX mutations in papillary thyroid cancers are mutually exclusive with other drivers, including RAS. EIF1AX is enriched in advanced thyroid cancers, where it displays a striking co-occurrence with RAS, which cooperates to induce tumorigenesis in mice and isogenic cell lines. The C-terminal EIF1AX-A113splice mutation is the most prevalent in advanced thyroid cancer. EIF1AX-A113spl variants stabilize the PIC and induce ATF4, a sensor of cellular stress, which is co-opted to suppress EIF2α phosphorylation, enabling a general increase in protein synthesis. RAS stabilizes c-MYC, an effect augmented by EIF1AX-A113spl. ATF4 and c-MYC induce expression of aminoacid transporters and enhance sensitivity of mTOR to aminoacid supply. These mutually reinforcing events generate therapeutic vulnerabilities to MEK, BRD4 and mTOR kinase inhibitors.
Authors Gnana P. Krishnamoorthy, Natalie R Davidson, Steven D Leach, Zhen Zhao, Scott W. Lowe, Gina Lee, Iñigo Landa, James Nagarajah, Mahesh Saqcena, Kamini Singh, Hans-Guido Wendel, Snjezana Dogan, Prasanna P. Tamarapu, John Blenis, Ronald Ghossein, Jeffrey A. Knauf, Gunnar Rätsch and James A. Fagin
Submitted Cancer Discovery
Abstract We present the most comprehensive catalogue of cancer-associated gene alterations through characterization of tumor transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes project. Using matched whole-genome sequencing data, we attributed RNA alterations to germline and somatic DNA alterations, revealing likely genetic mechanisms. We identified 444 associations of gene expression with somatic non-coding single-nucleotide variants. We found 1,872 splicing alterations associated with somatic mutation in intronic regions, including novel exonization events associated with Alu elements. Somatic copy number alterations were the major driver of total gene and allele-specific expression (ASE) variation. Additionally, 82% of gene fusions had structural variant support, including 75 of a novel class called "bridged" fusions, in which a third genomic location bridged two different genes. Globally, we observe transcriptomic alteration signatures that differ between cancer types and have associations with DNA mutational signatures. Given this unique dataset of RNA alterations, we also identified 1,012 genes significantly altered through both DNA and RNA mechanisms. Our study represents an extensive catalog of RNA alterations and reveals new insights into the heterogeneous molecular mechanisms of cancer gene alterations.
Authors Claudia Calabrese, Natalie R Davidson, Nuno A Fonseca, Yao He, André Kahles, Kjong-Van Lehmann, Fenglin Liu, Yuichi Shiraishi, Cameron M Soulette, Lara Urban, Deniz Demircioğlu, Liliana Greger, Siliang Li, Dongbing Liu, Marc D Perry, Linda Xiang, Fan Zhang, Junjun Zhang, Peter Bailey, Serap Erkek, Katherine A Hoadley, Yong Hou, Helena Kilpinen, Jan O Korbel, Maximillian G Marin, Julia Markowski, Tannistha Nandi, Qiang Pan-Hammarström, Chandra S Pedamallu, Reiner Siebert, Stefan G Stark, Hong Su, Patrick Tan, Sebastian M Waszak, Christina Yung, Shida Zhu, Philip Awadalla, Chad J Creighton, Matthew Meyerson, B Francis F Ouellette, Kui Wu, Huanming Yang, Alvis Brazma, Angela N Brooks, Jonathan Göke, Gunnar Rätsch, Roland F Schwarz, Oliver Stegle, Zemin Zhang
Authors N Davidson, Kjong-Van Lehmann, Andre Kahles, A Perez, Gunnar Rätsch