Mark Ayers

15.8k total citations · 3 hit papers
56 papers, 7.8k citations indexed

About

Mark Ayers is a scholar working on Oncology, Cancer Research and Molecular Biology. According to data from OpenAlex, Mark Ayers has authored 56 papers receiving a total of 7.8k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Oncology, 27 papers in Cancer Research and 18 papers in Molecular Biology. Recurrent topics in Mark Ayers's work include Cancer Immunotherapy and Biomarkers (22 papers), Cancer Genomics and Diagnostics (18 papers) and Colorectal Cancer Treatments and Studies (10 papers). Mark Ayers is often cited by papers focused on Cancer Immunotherapy and Biomarkers (22 papers), Cancer Genomics and Diagnostics (18 papers) and Colorectal Cancer Treatments and Studies (10 papers). Mark Ayers collaborates with scholars based in United States, Japan and South Korea. Mark Ayers's co-authors include Lajos Pusztai, James Stec, Jared Lunceford, W. Fraser Symmans, Jeffrey S. Ross, Gabriel N. Hortobágyi, Andrey Loboda, Sarina A. Piha‐Paul, Andrew Albright and Michael Nebozhyn and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Journal of Clinical Oncology.

In The Last Decade

Mark Ayers

55 papers receiving 7.7k citations

Hit Papers

IFN-γ–related mRNA profile predicts ... 2005 2026 2012 2019 2017 2005 2018 500 1000 1.5k 2.0k
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. IFN-γ–related mRNA profile predicts clinical response to PD-1 blockade
    2017 2.3k citations Mark Ayers, Jared Lunceford et al. profile →
  2. Breast Cancer Molecular Subtypes Respond Differently to Preoperative Chemotherapy
    2005 1.4k citations Roman Rouzier, Charles M. Perou et al. Clinical Cancer Research profile →
  3. T-Cell–Inflamed Gene-Expression Profile, Programmed Death Ligand 1 Expression, and Tumor Mutational Burden Predict Efficacy in Patients Treated With Pembrolizumab Across 20 Cancers: KEYNOTE-028
    2018 656 citations Patrick A. Ott, Yung‐Jue Bang et al. Journal of Clinical Oncology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Ayers United States 33 5.2k 2.7k 2.5k 1.9k 1.6k 56 7.8k
Hartmut Koeppen United States 51 5.0k 1.0× 1.7k 0.6× 4.9k 2.0× 1.5k 0.8× 1.4k 0.9× 116 9.2k
Talia Golan Israel 39 5.4k 1.0× 2.3k 0.9× 2.0k 0.8× 1.7k 0.9× 1.1k 0.7× 170 7.2k
Shumei Kato United States 38 4.5k 0.9× 2.6k 1.0× 2.2k 0.9× 2.4k 1.3× 1.3k 0.8× 174 7.5k
Priti Lal United States 34 3.0k 0.6× 2.0k 0.7× 2.5k 1.0× 2.4k 1.2× 1.3k 0.8× 128 6.7k
Livio Trusolino Italy 51 4.4k 0.8× 2.2k 0.8× 4.9k 2.0× 1.7k 0.9× 905 0.6× 135 10.2k
Roberto Salgado Belgium 34 6.5k 1.2× 2.6k 1.0× 1.7k 0.7× 1.7k 0.9× 2.9k 1.8× 147 8.7k
Silvia Darb‐Esfahani Germany 35 3.3k 0.6× 1.9k 0.7× 2.1k 0.9× 865 0.4× 1.1k 0.7× 114 5.9k
Peter Schmid United Kingdom 44 8.3k 1.6× 3.2k 1.2× 2.1k 0.9× 3.5k 1.8× 2.6k 1.6× 207 11.0k
Luciana Molinero United States 37 6.6k 1.3× 2.1k 0.8× 1.6k 0.7× 2.2k 1.1× 3.4k 2.2× 102 9.2k
Robert Radinsky United States 45 6.3k 1.2× 2.2k 0.8× 4.5k 1.8× 2.5k 1.3× 999 0.6× 127 10.4k

Countries citing papers authored by Mark Ayers

Since Specialization
Citations

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

Fields of papers citing papers by Mark Ayers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Ayers

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Ayers. A scholar is included among the top collaborators of Mark Ayers 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 Mark Ayers. Mark Ayers 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.
Haddad, Robert I., Tanguy Y. Seiwert, Laura Q.M. Chow, et al.. (2022). Influence of tumor mutational burden, inflammatory gene expression profile, and PD-L1 expression on response to pembrolizumab in head and neck squamous cell carcinoma. Journal for ImmunoTherapy of Cancer. 10(2). e003026–e003026. 54 indexed citations
3.
Cristescu, Răzvan, Michael Nebozhyn, Chunsheng Zhang, et al.. (2021). Transcriptomic Determinants of Response to Pembrolizumab Monotherapy across Solid Tumor Types. Clinical Cancer Research. 28(8). 1680–1689. 40 indexed citations
4.
Garassino, Marina Chiara, Delvys Rodríguez‐Abreu, Shirish M. Gadgeel, et al.. (2019). OA04.06 Evaluation of TMB in KEYNOTE-189: Pembrolizumab Plus Chemotherapy vs Placebo Plus Chemotherapy for Nonsquamous NSCLC. Journal of Thoracic Oncology. 14(10). S216–S217. 66 indexed citations
5.
Herbst, Roy S., Gilberto Lopes, Dariusz M. Kowalski, et al.. (2019). LBA4 Association of KRAS mutational status with response to pembrolizumab monotherapy given as first-line therapy for PD-L1-positive advanced non-squamous NSCLC in Keynote-042. Annals of Oncology. 30. xi63–xi64. 79 indexed citations
6.
Ayers, Mark, Michael Nebozhyn, Răzvan Cristescu, et al.. (2018). Molecular Profiling of Cohorts of Tumor Samples to Guide Clinical Development of Pembrolizumab as Monotherapy. Clinical Cancer Research. 25(5). 1564–1573. 27 indexed citations
7.
Ott, Patrick A., Yung‐Jue Bang, Sarina A. Piha‐Paul, et al.. (2018). T-Cell–Inflamed Gene-Expression Profile, Programmed Death Ligand 1 Expression, and Tumor Mutational Burden Predict Efficacy in Patients Treated With Pembrolizumab Across 20 Cancers: KEYNOTE-028. Journal of Clinical Oncology. 37(4). 318–327. 656 indexed citations breakdown →
8.
Ott, Patrick A., Y-J. Bang, A.R. Abdul Razak, et al.. (2017). Relationship of PD-L1 and a T-cell inflamed gene expression profile (GEP) to clinical response in a multicohort trial of solid tumors (KEYNOTE [KN]028). Annals of Oncology. 28. v22–v22. 5 indexed citations
9.
Haddad, Robert I., Tanguy Y. Seiwert, Laura Q.M. Chow, et al.. (2017). Genomic determinants of response to pembrolizumab in head and neck squamous cell carcinoma (HNSCC).. Journal of Clinical Oncology. 35(15_suppl). 6009–6009. 40 indexed citations
10.
Patel, Viralkumar, Kumudha Balakrishnan, Mark Douglas, et al.. (2016). Duvelisib treatment is associated with altered expression of apoptotic regulators that helps in sensitization of chronic lymphocytic leukemia cells to venetoclax (ABT-199). Leukemia. 31(9). 1872–1881. 52 indexed citations
11.
Sclafani, Francesco, Tae‐Yop Kim, David Cunningham, et al.. (2015). A Randomized Phase II/III Study of Dalotuzumab in Combination With Cetuximab and Irinotecan in Chemorefractory,KRASWild-Type, Metastatic Colorectal Cancer. JNCI Journal of the National Cancer Institute. 107(12). djv258–djv258. 73 indexed citations
12.
Chung, Hyun Cheol, Veena Shankaran, Ravit Geva, et al.. (2015). LBA-04 Clinical outcomes and their correlation with gene expression in patients with advanced gastric cancer treated with pembrolizumab (MK-3475): KEYNOTE-012. Annals of Oncology. 26. iv118–iv118. 5 indexed citations
13.
Rouzier, Roman, Charles M. Perou, W. Fraser Symmans, et al.. (2005). Breast Cancer Molecular Subtypes Respond Differently to Preoperative Chemotherapy. Clinical Cancer Research. 11(16). 5678–5685. 1414 indexed citations breakdown →
14.
Stec, James, Jing Wang, Kevin R. Coombes, et al.. (2005). Comparison of the Predictive Accuracy of DNA Array-Based Multigene Classifiers across cDNA Arrays and Affymetrix GeneChips. Journal of Molecular Diagnostics. 7(3). 357–367. 41 indexed citations
15.
Symmans, W. Fraser, S. Keith Anderson, Mark Ayers, et al.. (2005). A single-gene biomarker identifies breast cancers associated with immature cell type and short duration of prior breastfeeding. Endocrine Related Cancer. 12(4). 1059–1069. 34 indexed citations
16.
Pusztai, Lajos, Kevin R. Coombes, Sebastian Hoersch, et al.. (2004). Cross platform comparison of multigene predictors of response to neoadjuvant paclitaxel/FAC chemotherapy in breast cancer generated by cDNA arrays and Affymetrix GeneChips. Journal of Clinical Oncology. 22(14_suppl). 503–503. 2 indexed citations
17.
Symmans, W. Fraser, Mark Ayers, Edwin Clark, et al.. (2003). Total RNA yield and microarray gene expression profiles from fine‐needle aspiration biopsy and core‐needle biopsy samples of breast carcinoma. Cancer. 97(12). 2960–2971. 140 indexed citations
18.
Ross, Jeffrey S., Jonathan A. Fletcher, Kenneth J. Bloom, et al.. (2003). HER-2/neu Testing in Breast Cancer. PubMed. 120(suppl_1). S53–S71. 46 indexed citations
19.
Pusztai, Lajos, Mark Ayers, James Stec, et al.. (2003). Gene expression profiles obtained from fine-needle aspirations of breast cancer reliably identify routine prognostic markers and reveal large-scale molecular differences between estrogen-negative and estrogen-positive tumors.. PubMed. 9(7). 2406–15. 168 indexed citations
20.
Ross, Jeffrey S., Gerald P. Linette, James Stec, et al.. (2003). Breast cancer biomarkers and molecular medicine. Expert Review of Molecular Diagnostics. 3(5). 573–585. 80 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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