Matthew J. Niederst

6.2k total citations · 2 hit papers
11 papers, 1.6k citations indexed

About

Matthew J. Niederst is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology and Oncology. According to data from OpenAlex, Matthew J. Niederst has authored 11 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Pulmonary and Respiratory Medicine, 6 papers in Molecular Biology and 6 papers in Oncology. Recurrent topics in Matthew J. Niederst's work include Lung Cancer Treatments and Mutations (7 papers), HER2/EGFR in Cancer Research (4 papers) and PI3K/AKT/mTOR signaling in cancer (4 papers). Matthew J. Niederst is often cited by papers focused on Lung Cancer Treatments and Mutations (7 papers), HER2/EGFR in Cancer Research (4 papers) and PI3K/AKT/mTOR signaling in cancer (4 papers). Matthew J. Niederst collaborates with scholars based in United States. Matthew J. Niederst's co-authors include Jeffrey A. Engelman, Lecia V. Sequist, Matthew G. Oser, Zofia Piotrowska, Elizabeth L. Lockerman, Angel R. Garcia, Hillary E. Mulvey, Haichuan Hu, Alexandra C. Newton and Audrey O’Neill and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and Blood.

In The Last Decade

Matthew J. Niederst

11 papers receiving 1.6k citations

Hit Papers

Transformation from non-small-cell lung cancer to small-c... 2015 2026 2018 2022 2015 2015 200 400 600
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. Transformation from non-small-cell lung cancer to small-cell lung cancer: molecular drivers and cells of origin
    2015 712 citations Matthew G. Oser, Matthew J. Niederst et al. The Lancet Oncology profile →
  2. The Allelic Context of the C797S Mutation Acquired upon Treatment with Third-Generation EGFR Inhibitors Impacts Sensitivity to Subsequent Treatment Strategies
    2015 441 citations Matthew J. Niederst, Haichuan Hu et al. Clinical Cancer Research profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew J. Niederst United States 9 938 859 850 400 156 11 1.6k
Rintaro Noro Japan 25 811 0.9× 697 0.8× 978 1.2× 531 1.3× 109 0.7× 95 1.8k
Fabrice Branle Switzerland 15 796 0.8× 951 1.1× 578 0.7× 209 0.5× 219 1.4× 36 1.5k
Zhenfan Yang China 19 1.2k 1.3× 1.1k 1.2× 549 0.6× 308 0.8× 57 0.4× 39 1.8k
Roberta Caputo Italy 13 664 0.7× 805 0.9× 612 0.7× 317 0.8× 94 0.6× 27 1.4k
Katherine E. Hutchinson United States 19 536 0.6× 920 1.1× 972 1.1× 595 1.5× 152 1.0× 48 1.8k
Yongchang Shi United States 7 447 0.5× 535 0.6× 578 0.7× 211 0.5× 80 0.5× 9 1.3k
Donata Vitagliano Italy 19 390 0.4× 1.0k 1.2× 920 1.1× 228 0.6× 144 0.9× 29 1.9k
Marileila Varella‐Garcia United States 13 860 0.9× 623 0.7× 618 0.7× 277 0.7× 67 0.4× 16 1.4k
Claire Crafter United Kingdom 16 361 0.4× 650 0.8× 918 1.1× 175 0.4× 87 0.6× 26 1.5k
Richeng Jiang China 19 1.0k 1.1× 600 0.7× 952 1.1× 390 1.0× 96 0.6× 48 1.8k

Countries citing papers authored by Matthew J. Niederst

Since Specialization
Citations

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

Fields of papers citing papers by Matthew J. Niederst

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew J. Niederst. 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 Matthew J. Niederst. The network helps show where Matthew J. Niederst may publish in the future.

Co-authorship network of co-authors of Matthew J. Niederst

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

All Works

11 of 11 papers shown
1.
Engels, Boris, Andrew Price, Andrew M. Stein, et al.. (2021). Preservation of T-Cell Stemness with a Novel Expansionless CAR-T Manufacturing Process, Which Reduces Manufacturing Time to Less Than Two Days, Drives Enhanced CAR-T Cell Efficacy. Blood. 138(Supplement 1). 2848–2848. 19 indexed citations
2.
Gainor, Justin F., Matthew J. Niederst, Jochen K. Lennerz, et al.. (2016). Dramatic Response to Combination Erlotinib and Crizotinib in a Patient with Advanced, EGFR -Mutant Lung Cancer Harboring De Novo MET Amplification. Journal of Thoracic Oncology. 11(7). e83–e85. 55 indexed citations
3.
Niederst, Matthew J., Jeffrey A. Engelman, & Aaron N. Hata. (2016). Distinct evolutionary paths to TKI resistance in NSCLC. Cell Cycle. 17(3). 298–299. 4 indexed citations
4.
Niederst, Matthew J., Haichuan Hu, Hillary E. Mulvey, et al.. (2015). The Allelic Context of the C797S Mutation Acquired upon Treatment with Third-Generation EGFR Inhibitors Impacts Sensitivity to Subsequent Treatment Strategies. Clinical Cancer Research. 21(17). 3924–3933. 441 indexed citations breakdown →
5.
Oser, Matthew G., Matthew J. Niederst, Lecia V. Sequist, & Jeffrey A. Engelman. (2015). Transformation from non-small-cell lung cancer to small-cell lung cancer: molecular drivers and cells of origin. The Lancet Oncology. 16(4). e165–e172. 712 indexed citations breakdown →
6.
Piotrowska, Zofia, Daniel B. Costa, Mark S. Huberman, et al.. (2015). Activity of AUY922 in NSCLC patients with EGFR exon 20 insertions.. Journal of Clinical Oncology. 33(15_suppl). 8015–8015. 13 indexed citations
7.
Piotrowska, Zofia, Matthew J. Niederst, Mari Mino–Kenudson, et al.. (2014). Variation in Mechanisms of Acquired Resistance Among EGFR-Mutant NSCLC Patients With More Than 1 Postresistant Biopsy. International Journal of Radiation Oncology*Biology*Physics. 90(5). S6–S7. 12 indexed citations
8.
Piotrowska, Zofia, Matthew J. Niederst, Mari Mino–Kenudson, et al.. (2014). Variation in mechanisms of acquired resistance (AR) among EGFR-mutant NSCLC patients with more than one post-resistant biopsy.. Journal of Clinical Oncology. 32(15_suppl). 8053–8053. 7 indexed citations
9.
Niederst, Matthew J. & Jeffrey A. Engelman. (2013). Bypass Mechanisms of Resistance to Receptor Tyrosine Kinase Inhibition in Lung Cancer. Science Signaling. 6(294). re6–re6. 202 indexed citations
10.
O’Neill, Audrey, Matthew J. Niederst, & Alexandra C. Newton. (2012). Suppression of survival signalling pathways by the phosphatase PHLPP. FEBS Journal. 280(2). 572–583. 88 indexed citations
11.
Brognard, John, Matthew J. Niederst, Gloria Reyes, Noel A. Warfel, & Alexandra C. Newton. (2009). Common Polymorphism in the Phosphatase PHLPP2 Results in Reduced Regulation of Akt and Protein Kinase C. Journal of Biological Chemistry. 284(22). 15215–15223. 34 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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