David Nittner

3.4k total citations · 1 hit paper
18 papers, 1.7k citations indexed

About

David Nittner is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, David Nittner has authored 18 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 8 papers in Oncology and 8 papers in Cancer Research. Recurrent topics in David Nittner's work include Epigenetics and DNA Methylation (4 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Pancreatic and Hepatic Oncology Research (3 papers). David Nittner is often cited by papers focused on Epigenetics and DNA Methylation (4 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Pancreatic and Hepatic Oncology Research (3 papers). David Nittner collaborates with scholars based in Belgium, United States and Netherlands. David Nittner's co-authors include Adrian Liston, Kathleen Van den Eynde, Diether Lambrechts, Sara Aibar, Bernard Thienpont, Stein Aerts, Andreas Pircher, Els Wauters, Bram Boeckx and Erik Verbeken and has published in prestigious journals such as Nature Medicine, Nature Communications and Blood.

In The Last Decade

David Nittner

17 papers receiving 1.7k citations

Hit Papers

Phenotype molding of stromal cells in the lung tumor micr... 2018 2026 2020 2023 2018 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Nittner Belgium 13 1.1k 753 657 490 264 18 1.7k
John Lövrot Sweden 13 714 0.7× 923 1.2× 566 0.9× 466 1.0× 220 0.8× 21 1.6k
Hae‐Ock Lee South Korea 20 1.5k 1.4× 759 1.0× 854 1.3× 474 1.0× 230 0.9× 44 2.1k
Chongbiao Huang China 26 824 0.8× 765 1.0× 598 0.9× 439 0.9× 261 1.0× 49 1.7k
Guichun Huang China 24 959 0.9× 655 0.9× 636 1.0× 279 0.6× 239 0.9× 53 1.7k
Ayse Bassez Belgium 4 815 0.8× 842 1.1× 462 0.7× 659 1.3× 255 1.0× 8 1.5k
Stefanie Avril United States 22 649 0.6× 801 1.1× 418 0.6× 415 0.8× 189 0.7× 45 1.7k
Diego M. Marzese United States 25 1.2k 1.1× 507 0.7× 608 0.9× 203 0.4× 276 1.0× 75 1.7k
Janna Paulsson Sweden 19 748 0.7× 703 0.9× 398 0.6× 217 0.4× 292 1.1× 21 1.5k
Tina El Rayes United States 7 1.0k 0.9× 1.1k 1.4× 648 1.0× 319 0.7× 247 0.9× 7 1.8k
Molly A. Taylor United States 18 970 0.9× 624 0.8× 510 0.8× 432 0.9× 146 0.6× 30 1.7k

Countries citing papers authored by David Nittner

Since Specialization
Citations

This map shows the geographic impact of David Nittner'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 David Nittner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Nittner more than expected).

Fields of papers citing papers by David Nittner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Nittner. 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 David Nittner. The network helps show where David Nittner may publish in the future.

Co-authorship network of co-authors of David Nittner

This figure shows the co-authorship network connecting the top 25 collaborators of David Nittner. A scholar is included among the top collaborators of David Nittner 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 David Nittner. David Nittner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Venken, Tom, David Nittner, Jelle Verbeeck, et al.. (2023). Transcription factor NKX2–1 drives serine and glycine synthesis addiction in cancer. British Journal of Cancer. 128(10). 1862–1878. 14 indexed citations
2.
Bempt, Marlies Vanden, Koen Debackere, Sofie Demeyer, et al.. (2022). Aberrant MYCN expression drives oncogenic hijacking of EZH2 as a transcriptional activator in peripheral T-cell lymphoma. Blood. 140(23). 2463–2476. 12 indexed citations
3.
Riva, Mattéo, David Nittner, Jolien Ceusters, et al.. (2022). Radiation dose-escalation and dose-fractionation modulate the immune microenvironment, cancer stem cells and vasculature in experimental high-grade gliomas. Journal of Neurosurgical Sciences. 67(1). 55–65. 6 indexed citations
4.
Izci, Mukaddes, Christy Maksoudian, Tianjiao Chu, et al.. (2022). Gold nanoparticle delivery to solid tumors: a multiparametric study on particle size and the tumor microenvironment. Journal of Nanobiotechnology. 20(1). 518–518. 9 indexed citations
5.
Prieto, Cristina, Olga Gielen, Kris Jacobs, et al.. (2021). PSEN1-selective gamma-secretase inhibition in combination with kinase or XPO-1 inhibitors effectively targets T cell acute lymphoblastic leukemia. Journal of Hematology & Oncology. 14(1). 97–97. 12 indexed citations
6.
Dekervel, Jeroen, et al.. (2020). <p>Anti-Cancer Activity of Acriflavine as Metabolic Inhibitor of OXPHOS in Pancreas Cancer Xenografts</p>. OncoTargets and Therapy. Volume 13. 6907–6916. 15 indexed citations
7.
Dekervel, Jeroen, David Nittner, Louis Libbrecht, et al.. (2020). Gemcitabine Recruits M2-Type Tumor-Associated Macrophages into the Stroma of Pancreatic Cancer. Translational Oncology. 13(3). 100743–100743. 44 indexed citations
8.
Dekervel, Jeroen, Louis Libbrecht, David Nittner, et al.. (2019). Gemcitabine induces Epithelial-to-Mesenchymal Transition in patient-derived pancreatic ductal adenocarcinoma xenografts.. PubMed. 11(2). 765–779. 19 indexed citations
9.
Riva, Mattéo, Akila Weerasekera, Sarah Belderbos, et al.. (2019). CT-2A neurospheres-derived high-grade glioma in mice: a new model to address tumor stem cells and immunosuppression. Biology Open. 8(9). 12 indexed citations
10.
Habets, R., Charles E. de Bock, Lutgarde Serneels, et al.. (2019). Safe targeting of T cell acute lymphoblastic leukemia by pathology-specific NOTCH inhibition. Science Translational Medicine. 11(494). 77 indexed citations
11.
Bonvin, Elise, Enrico Radaelli, Martin Bizet, et al.. (2018). TET2-Dependent Hydroxymethylome Plasticity Reduces Melanoma Initiation and Progression. Cancer Research. 79(3). 482–494. 22 indexed citations
12.
Lambrechts, Diether, Els Wauters, Bram Boeckx, et al.. (2018). Phenotype molding of stromal cells in the lung tumor microenvironment. Nature Medicine. 24(8). 1277–1289. 1037 indexed citations breakdown →
13.
Talebi, Ali, Jonas Dehairs, Florian Rambow, et al.. (2018). Sustained SREBP-1-dependent lipogenesis as a key mediator of resistance to BRAF-targeted therapy. Nature Communications. 9(1). 2500–2500. 105 indexed citations
14.
Nittner, David, Florian Rambow, Enrico Radaelli, et al.. (2017). Mouse Cutaneous Melanoma Induced by Mutant BRaf Arises from Expansion and Dedifferentiation of Mature Pigmented Melanocytes. Cell stem cell. 21(5). 679–693.e6. 70 indexed citations
16.
Ghahremani, Morvarid Farhang, Steven Goossens, David Nittner, et al.. (2013). p53 promotes VEGF expression and angiogenesis in the absence of an intact p21-Rb pathway. Cell Death and Differentiation. 20(7). 888–897. 92 indexed citations
17.
Nittner, David, Irina Lambertz, Frederic F. Clermont, et al.. (2012). Synthetic lethality between Rb, p53 and Dicer or miR-17–92 in retinal progenitors suppresses retinoblastoma formation. Nature Cell Biology. 14(9). 958–965. 64 indexed citations
18.
Lambertz, Isabel, David Nittner, Pieter Mestdagh, et al.. (2009). Monoallelic but not biallelic loss of Dicer1 promotes tumorigenesis in vivo. Cell Death and Differentiation. 17(4). 633–641. 125 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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