Natalie Proost

4.8k total citations
32 papers, 1.8k citations indexed

About

Natalie Proost is a scholar working on Molecular Biology, Oncology and Epidemiology. According to data from OpenAlex, Natalie Proost has authored 32 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 14 papers in Oncology and 6 papers in Epidemiology. Recurrent topics in Natalie Proost's work include Cancer Cells and Metastasis (7 papers), Epigenetics and DNA Methylation (6 papers) and Lung Cancer Research Studies (6 papers). Natalie Proost is often cited by papers focused on Cancer Cells and Metastasis (7 papers), Epigenetics and DNA Methylation (6 papers) and Lung Cancer Research Studies (6 papers). Natalie Proost collaborates with scholars based in Netherlands, United States and Russia. Natalie Proost's co-authors include Anton Berns, Ji‐Ying Song, Dirk Adriaensen, Inge Brouns, John Zevenhoven, Erwin van Montfort, Joaquim Calbó, Ralph Meuwissen, H. Berna Beverloo and Ellen van Drunen and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Natalie Proost

28 papers receiving 1.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Natalie Proost Netherlands 18 1.0k 994 431 374 353 32 1.8k
Fréderic Fina France 27 893 0.9× 687 0.7× 506 1.2× 389 1.0× 262 0.7× 87 2.2k
Carl M. Gay United States 20 780 0.8× 995 1.0× 151 0.4× 294 0.8× 342 1.0× 60 1.6k
Christopher E. Pelloski United States 17 1.1k 1.1× 532 0.5× 540 1.3× 439 1.2× 187 0.5× 35 2.2k
Benjamin T. Spike United States 23 1.6k 1.6× 1.0k 1.0× 563 1.3× 231 0.6× 314 0.9× 44 2.4k
Bodour Salhia United States 26 914 0.9× 580 0.6× 483 1.1× 358 1.0× 115 0.3× 69 2.0k
Véronique Quillien France 27 1.0k 1.0× 665 0.7× 562 1.3× 325 0.9× 214 0.6× 71 2.2k
David Tran United States 20 528 0.5× 485 0.5× 255 0.6× 253 0.7× 139 0.4× 39 1.4k
Qian Zhan United States 21 948 0.9× 729 0.7× 262 0.6× 155 0.4× 133 0.4× 36 1.6k
Gayatry Mohapatra United States 14 743 0.7× 517 0.5× 320 0.7× 486 1.3× 92 0.3× 26 1.4k
Jonathan M. Lehman United States 14 748 0.7× 857 0.9× 145 0.3× 220 0.6× 510 1.4× 26 1.5k

Countries citing papers authored by Natalie Proost

Since Specialization
Citations

This map shows the geographic impact of Natalie Proost's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Natalie Proost with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natalie Proost more than expected).

Fields of papers citing papers by Natalie Proost

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Natalie Proost. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Natalie Proost. The network helps show where Natalie Proost may publish in the future.

Co-authorship network of co-authors of Natalie Proost

This figure shows the co-authorship network connecting the top 25 collaborators of Natalie Proost. A scholar is included among the top collaborators of Natalie Proost based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Natalie Proost. Natalie Proost is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Bhin, Jinhyuk, Eline van der Burg, Anne Paulien Drenth, et al.. (2025). C-Terminal Truncation and Fusion Partner Determine Oncogenicity of FGFR3. Cancer Research. 86(6). 1372–1391.
3.
Aslam, Muhammad Assad, Teun van den Brand, Bram van den Broek, et al.. (2025). Histone methyltransferase DOT1L maintains cell state and restricts cytotoxic potential of CD8 T cells. Science Advances. 11(50). eadw1289–eadw1289.
4.
Nagel, Remco, Onno B. Bleijerveld, Natalie Proost, et al.. (2024). Chemotherapeutic agents and leucine deprivation induce codon-biased aberrant protein production in cancer. Nucleic Acids Research. 52(22). 13964–13979. 2 indexed citations
5.
Drakaki, Alexandra, Natalie Proost, Cor Lieftink, et al.. (2024). ADARp150 counteracts whole genome duplication. Nucleic Acids Research. 52(17). 10370–10384. 1 indexed citations
6.
Morales-Rodriguez, Francisco, Esther A. Zaal, Natalie Proost, et al.. (2024). Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors. Cell Reports Medicine. 6(1). 101878–101878. 3 indexed citations
7.
Nagel, Remco, Nanne Aben, Natalie Proost, et al.. (2019). Inhibition of the Replication Stress Response Is a Synthetic Vulnerability in SCLC That Acts Synergistically in Combination with Cisplatin. Molecular Cancer Therapeutics. 18(4). 762–770. 25 indexed citations
8.
Sun, Jianhui, Remco Nagel, Esther A. Zaal, et al.. (2019). SLC 1A3 contributes to L‐asparaginase resistance in solid tumors. The EMBO Journal. 38(21). e102147–e102147. 48 indexed citations
9.
Barazas, Marco, Alessia Gasparini, Yike Huang, et al.. (2018). Radiosensitivity Is an Acquired Vulnerability of PARPi-Resistant BRCA1-Deficient Tumors. Cancer Research. 79(3). 452–460. 36 indexed citations
10.
Serresi, Michela, Bjørn Siteur, Danielle Hulsman, et al.. (2018). Ezh2 inhibition in Kras-driven lung cancer amplifies inflammation and associated vulnerabilities. The Journal of Experimental Medicine. 215(12). 3115–3135. 31 indexed citations
11.
Serresi, Michela, Gaetano Gargiulo, Natalie Proost, et al.. (2016). Polycomb Repressive Complex 2 Is a Barrier to KRAS-Driven Inflammation and Epithelial-Mesenchymal Transition in Non-Small-Cell Lung Cancer. Cancer Cell. 29(2). 241–241. 5 indexed citations
12.
Semenova, Ekaterina A., Min‐Chul Kwon, Kim Monkhorst, et al.. (2016). Transcription Factor NFIB Is a Driver of Small Cell Lung Cancer Progression in Mice and Marks Metastatic Disease in Patients. Cell Reports. 16(3). 631–643. 106 indexed citations
13.
Ferone, Giustina, Ji‐Ying Song, Rajith Bhaskaran, et al.. (2016). SOX2 Is the Determining Oncogenic Switch in Promoting Lung Squamous Cell Carcinoma from Different Cells of Origin. Cancer Cell. 30(4). 519–532. 156 indexed citations
14.
Kwon, Min‐Chul, et al.. (2015). Paracrine signaling between tumor subclones of mouse SCLC: a critical role of ETS transcription factor Pea3 in facilitating metastasis. Genes & Development. 29(15). 1587–1592. 55 indexed citations
15.
Heideman, Marinus R., et al.. (2014). Sin3a-associated Hdac1 and Hdac2 are essential for hematopoietic stem cell homeostasis and contribute differentially to hematopoiesis. Haematologica. 99(8). 1292–1303. 47 indexed citations
16.
Krimpenfort, Paul, Ji‐Ying Song, Natalie Proost, et al.. (2012). Deleted in colorectal carcinoma suppresses metastasis in p53-deficient mammary tumours. Nature. 482(7386). 538–541. 67 indexed citations
17.
Calbó, Joaquim, Erwin van Montfort, Natalie Proost, et al.. (2011). A Functional Role for Tumor Cell Heterogeneity in a Mouse Model of Small Cell Lung Cancer. Cancer Cell. 19(2). 244–256. 258 indexed citations
18.
Proost, Natalie, et al.. (2011). Cell of Origin of Small Cell Lung Cancer: Inactivation of Trp53 and Rb1 in Distinct Cell Types of Adult Mouse Lung. Cancer Cell. 19(6). 754–764. 365 indexed citations
19.
Amerongen, Renée van, et al.. (2009). Frat oncoproteins act at the crossroad of canonical and noncanonical Wnt-signaling pathways. Oncogene. 29(1). 93–104. 33 indexed citations
20.
Calbó, Joaquim, et al.. (2009). Immune response in lung cancer mouse model mimics human anti-Hu reactivity. Journal of Neuroimmunology. 217(1-2). 38–45. 17 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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