Laura van ‘t Veer

48.7k total citations · 4 hit papers
200 papers, 14.6k citations indexed

About

Laura van ‘t Veer is a scholar working on Cancer Research, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Laura van ‘t Veer has authored 200 papers receiving a total of 14.6k indexed citations (citations by other indexed papers that have themselves been cited), including 127 papers in Cancer Research, 96 papers in Oncology and 51 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Laura van ‘t Veer's work include Breast Cancer Treatment Studies (79 papers), Cancer Genomics and Diagnostics (56 papers) and HER2/EGFR in Cancer Research (32 papers). Laura van ‘t Veer is often cited by papers focused on Breast Cancer Treatment Studies (79 papers), Cancer Genomics and Diagnostics (56 papers) and HER2/EGFR in Cancer Research (32 papers). Laura van ‘t Veer collaborates with scholars based in United States, Netherlands and Belgium. Laura van ‘t Veer's co-authors include René Bernards, Marc J. van de Vijver, Anke Witteveen, Yudong D. He, Augustinus A. M. Hart, Stephen Friend, Mao Mao, Matthew J. Marton, Ron Kerkhoven and K van der Kooy and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Laura van ‘t Veer

185 papers receiving 14.2k citations

Hit Papers

Gene expression profiling predicts clinical outcome of br... 2002 2026 2010 2018 2002 2004 2013 2023 2.0k 4.0k 6.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Gene expression profiling predicts clinical outcome of breast cancer
    2002 7.0k citations Laura van ‘t Veer, Marc J. van de Vijver et al. profile →
  2. Bilateral Prophylactic Mastectomy Reduces Breast Cancer Risk in BRCA1 and BRCA2 Mutation Carriers: The PROSE Study Group
    2004 812 citations Laura van ‘t Veer et al. Journal of Clinical Oncology profile →
  3. Glutamine Sensitivity Analysis Identifies the xCT Antiporter as a Common Triple-Negative Breast Tumor Therapeutic Target
    2013 471 citations Laura van ‘t Veer et al. profile →
  4. Circulating tumor nucleic acids: biology, release mechanisms, and clinical relevance
    2023 148 citations Laura van ‘t Veer, Mark Jesus M. Magbanua et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Laura van ‘t Veer United States 46 7.9k 5.9k 5.1k 3.0k 1.5k 200 14.6k
Jeffrey R. Marks United States 66 9.3k 1.2× 4.6k 0.8× 5.6k 1.1× 2.5k 0.8× 1.4k 0.9× 222 16.1k
Alexander Pergamenschikov United States 6 9.2k 1.2× 6.7k 1.1× 6.5k 1.3× 2.7k 0.9× 1.9k 1.3× 9 16.3k
Stephanie Geisler Norway 21 7.5k 0.9× 7.2k 1.2× 7.4k 1.5× 2.5k 0.8× 1.7k 1.1× 36 14.5k
Christian A. Rees United States 9 9.1k 1.2× 6.7k 1.1× 6.6k 1.3× 2.7k 0.9× 1.9k 1.2× 10 16.0k
Lodewyk F.A. Wessels Netherlands 62 10.2k 1.3× 4.3k 0.7× 4.6k 0.9× 2.1k 0.7× 1.4k 0.9× 252 15.8k
Adam B. Olshen United States 51 8.6k 1.1× 4.7k 0.8× 4.9k 1.0× 2.8k 0.9× 2.8k 1.8× 152 15.7k
Øystein Fluge Norway 25 6.5k 0.8× 6.1k 1.0× 6.4k 1.3× 1.7k 0.6× 1.9k 1.2× 91 13.9k
Anne‐Lise Børresen‐Dale Norway 18 6.3k 0.8× 6.1k 1.0× 6.0k 1.2× 1.7k 0.6× 1.7k 1.1× 26 12.4k
Tomofumi Osako Japan 19 5.2k 0.7× 5.7k 1.0× 6.0k 1.2× 1.6k 0.5× 2.2k 1.5× 42 12.1k
Nobuyuki Arima Japan 26 5.7k 0.7× 6.0k 1.0× 6.3k 1.2× 1.7k 0.6× 2.4k 1.5× 86 13.4k

Countries citing papers authored by Laura van ‘t Veer

Since Specialization
Citations

This map shows the geographic impact of Laura van ‘t Veer'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 Laura van ‘t Veer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laura van ‘t Veer more than expected).

Fields of papers citing papers by Laura van ‘t Veer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Laura van ‘t Veer. 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 Laura van ‘t Veer. The network helps show where Laura van ‘t Veer may publish in the future.

Co-authorship network of co-authors of Laura van ‘t Veer

This figure shows the co-authorship network connecting the top 25 collaborators of Laura van ‘t Veer. A scholar is included among the top collaborators of Laura van ‘t Veer 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 Laura van ‘t Veer. Laura van ‘t Veer 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.
Li, Wen, Natsuko Onishi, Jessica Gibbs, et al.. (2025). MRI-Based Model for Personalizing Neoadjuvant Treatment in Breast Cancer. Tomography. 11(3). 26–26.
3.
Sayaman, Rosalyn W., Yizhuo Shen, Joseph A. Caruso, et al.. (2025). Super-enhancer profiling reveals ThPOK/ZBTB7B, a CD4+ cell lineage commitment factor, as a master regulator that restricts breast cancer cells to a luminal non-migratory phenotype. Cellular and Molecular Life Sciences. 82(1). 397–397.
4.
Ríos-Hoyo, Alejandro, Erin F. Cobain, Laura A. Huppert, et al.. (2024). Neoadjuvant Chemotherapy and Immunotherapy for Estrogen Receptor–Positive Human Epidermal Growth Factor 2–Negative Breast Cancer. Journal of Clinical Oncology. 42(22). 2632–2636. 10 indexed citations
5.
Ríos-Hoyo, Alejandro, Jiawei Dai, Christina Yau, et al.. (2024). Hormone Receptor–Positive HER2-Negative/MammaPrint High-2 Breast Cancers Closely Resemble Triple-Negative Breast Cancers. Clinical Cancer Research. 31(2). 403–413. 2 indexed citations
6.
Rastogi, Priya, Hanna Bandos, Peter C. Lucas, et al.. (2024). Utility of the 70-Gene MammaPrint Assay for Prediction of Benefit From Extended Letrozole Therapy in the NRG Oncology/NSABP B-42 Trial. Journal of Clinical Oncology. 42(30). 3561–3569. 3 indexed citations
7.
Thomas, Alexandra, Denise M. Wolf, Ronald Balassanian, et al.. (2024). Therapeutic response and outcomes with uncommon breast cancer subtypes in the I-SPY trial 2010-2022.. Journal of Clinical Oncology. 42(23_suppl). 1–1. 1 indexed citations
8.
Magbanua, Mark Jesus M., Wen Li, & Laura van ‘t Veer. (2024). Integrating Imaging and Circulating Tumor DNA Features for Predicting Patient Outcomes. Cancers. 16(10). 1879–1879. 8 indexed citations
9.
Hogarth, Michael, Allison Stover Fiscalini, Laura van ‘t Veer, et al.. (2023). Early Ascertainment of Breast Cancer Diagnoses Comparing Self-Reported Questionnaires and Electronic Health Record Data Warehouse: The WISDOM Study. JCO Clinical Cancer Informatics. 7(7). e2300019–e2300019.
10.
Sayaman, Rosalyn W., Leah Sabacan, Allison Stover Fiscalini, et al.. (2023). Abstract PD14-07: PD14-07 Associations of Breast Cancer Risk Level and Prediction of Tumor Aggressiveness in the Athena Breast Health Network. Cancer Research. 83(5_Supplement). PD14–7. 1 indexed citations
11.
Olow, Aleksandra, Laura van ‘t Veer, & Denise M. Wolf. (2021). Toward developing a metastatic breast cancer treatment strategy that incorporates history of response to previous treatments. BMC Cancer. 21(1). 2 indexed citations
12.
Magbanua, Mark Jesus M., Wen Li, Denise M. Wolf, et al.. (2021). Circulating tumor DNA and magnetic resonance imaging to predict neoadjuvant chemotherapy response and recurrence risk. npj Breast Cancer. 7(1). 32–32. 33 indexed citations
13.
Jacob, Laurent, Anke Witteveen, Leonie Delahaye, et al.. (2020). Controlling technical variation amongst 6693 patient microarrays of the randomized MINDACT trial. Communications Biology. 3(1). 397–397. 5 indexed citations
14.
Viale, Giuseppe, Femke A. de Snoo, Leen Slaets, et al.. (2017). Immunohistochemical versus molecular (BluePrint and MammaPrint) subtyping of breast carcinoma. Outcome results from the EORTC 10041/BIG 3-04 MINDACT trial. Breast Cancer Research and Treatment. 167(1). 123–131. 45 indexed citations
15.
Olow, Aleksandra, Zhongzhong Chen, R Niedner, et al.. (2016). An Atlas of the Human Kinome Reveals the Mutational Landscape Underlying Dysregulated Phosphorylation Cascades in Cancer. Cancer Research. 76(7). 1733–1745. 14 indexed citations
16.
Drukker, Caroline A., Jolien M. Bueno-de-Mesquita, Valesca P. Retèl, et al.. (2013). Comparing the 70-gene signature to the Dutch Breast Cancer guidelines in the prospective RASTER study. University of Twente Research Information. 49. 1 indexed citations
17.
Schmidt, Marcus, Alexandra J. van den Broek, Robert A.E.M. Tollenaar, F.E. van Leeuwen, & Laura van ‘t Veer. (2013). Breast cancer survival of BRCA1/2 carriers compared to non-BRCA1/2 carriers in a large breast cancer cohort.. Cancer Research. 73(8). 1 indexed citations
18.
Mook, Stella, Laura van ‘t Veer, Emiel J. Rutgers, et al.. (2011). Independent Prognostic Value of Screen Detection in Invasive Breast Cancer. JNCI Journal of the National Cancer Institute. 103(7). 585–597. 92 indexed citations
19.
Broeks, Annegien, Linde M. Braaf, Angelina Huseinovic, et al.. (2007). Identification of women with an increased risk of developing radiation-induced breast cancer: a case only study. Breast Cancer Research. 9(2). R26–R26. 62 indexed citations
20.
Veer, Laura van ‘t. (2006). Molecular Profiles Guide the Way to Improve Patient Management. Clinical Cancer Research. 12. 1 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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