Peter M.K. Westcott

2.6k total citations · 1 hit paper
18 papers, 1.0k citations indexed

About

Peter M.K. Westcott is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Peter M.K. Westcott has authored 18 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Oncology, 10 papers in Molecular Biology and 6 papers in Immunology. Recurrent topics in Peter M.K. Westcott's work include Cancer Immunotherapy and Biomarkers (5 papers), Immunotherapy and Immune Responses (4 papers) and Cancer Genomics and Diagnostics (4 papers). Peter M.K. Westcott is often cited by papers focused on Cancer Immunotherapy and Biomarkers (5 papers), Immunotherapy and Immune Responses (4 papers) and Cancer Genomics and Diagnostics (4 papers). Peter M.K. Westcott collaborates with scholars based in United States, United Kingdom and Sweden. Peter M.K. Westcott's co-authors include Minh D. To, Tyler Jacks, Allan Balmain, Reyno Delrosario, Thomas Keane, David A. Quigley, Kuang‐Yu Jen, Alistair G. Rust, Erik Fredlund and Kyle Halliwill and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Peter M.K. Westcott

18 papers receiving 1.0k citations

Hit Papers

SOX17 enables immune evasion of early colorectal adenomas... 2024 2026 2025 2024 10 20 30 40

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter M.K. Westcott United States 13 631 432 319 218 166 18 1.0k
Julia V. Burnier Canada 21 592 0.9× 408 0.9× 318 1.0× 174 0.8× 123 0.7× 73 1.2k
Caining Jin United States 22 922 1.5× 512 1.2× 287 0.9× 286 1.3× 157 0.9× 28 1.3k
Martine H. van Miltenburg Netherlands 9 677 1.1× 573 1.3× 266 0.8× 275 1.3× 121 0.7× 9 1.2k
Katja Harbst Sweden 15 512 0.8× 711 1.6× 220 0.7× 381 1.7× 139 0.8× 24 1.0k
Stacey M. Bagby United States 21 568 0.9× 516 1.2× 242 0.8× 194 0.9× 158 1.0× 62 1.1k
Frank J. Lowery United States 14 565 0.9× 580 1.3× 140 0.4× 408 1.9× 197 1.2× 26 1.1k
Robert Cornelison United States 18 770 1.2× 297 0.7× 230 0.7× 114 0.5× 115 0.7× 29 1.1k
Yoshihiko Hagiwara Japan 12 749 1.2× 648 1.5× 138 0.4× 287 1.3× 206 1.2× 15 1.2k
Michela Croce Italy 21 436 0.7× 490 1.1× 184 0.6× 510 2.3× 124 0.7× 47 1.2k
Elizabeth L. Christie Australia 13 498 0.8× 403 0.9× 267 0.8× 120 0.6× 87 0.5× 24 883

Countries citing papers authored by Peter M.K. Westcott

Since Specialization
Citations

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

Fields of papers citing papers by Peter M.K. Westcott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter M.K. Westcott. 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 Peter M.K. Westcott. The network helps show where Peter M.K. Westcott may publish in the future.

Co-authorship network of co-authors of Peter M.K. Westcott

This figure shows the co-authorship network connecting the top 25 collaborators of Peter M.K. Westcott. A scholar is included among the top collaborators of Peter M.K. Westcott 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 Peter M.K. Westcott. Peter M.K. Westcott 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.
Goto, Norihiro, Peter M.K. Westcott, Saori Goto, et al.. (2024). SOX17 enables immune evasion of early colorectal adenomas and cancers. Nature. 627(8004). 636–645. 47 indexed citations breakdown →
2.
Koehler, Angela N., et al.. (2024). New opportunities to overcome T cell dysfunction: the role of transcription factors and how to target them. Trends in Biochemical Sciences. 49(11). 1014–1029. 1 indexed citations
3.
Romero, Rodrigo, Emma V. Watson, Anthony C. Liang, et al.. (2022). A GATA4-regulated secretory program suppresses tumors through recruitment of cytotoxic CD8 T cells. Nature Communications. 13(1). 256–256. 9 indexed citations
4.
Naranjo, Santiago, Lindsay M. LaFave, Rodrigo Romero, et al.. (2022). Modeling diverse genetic subtypes of lung adenocarcinoma with a next-generation alveolar type 2 organoid platform. Genes & Development. 36(15-16). 936–949. 23 indexed citations
5.
Jaeger, Alex M., Lauren Stopfer, Ryuhjin Ahn, et al.. (2022). Deciphering the immunopeptidome in vivo reveals new tumour antigens. Nature. 607(7917). 149–155. 66 indexed citations
6.
Westcott, Peter M.K., Jason M. Schenkel, Zackery A. Ely, et al.. (2021). Low neoantigen expression and poor T-cell priming underlie early immune escape in colorectal cancer. Nature Cancer. 2(10). 1071–1085. 105 indexed citations
7.
Chen, Wei-Ching, Minh D. To, Peter M.K. Westcott, et al.. (2021). Targeting KRAS4A splicing through the RBM39/DCAF15 pathway inhibits cancer stem cells. Nature Communications. 12(1). 4288–4288. 34 indexed citations
8.
Burger, Megan L., Giorgio Gaglia, Cecily C. Ritch, et al.. (2021). Antigen Dominance Hierarchies Shape TCF1+ Progenitor CD8 T Cell Phenotypes in Tumors. SSRN Electronic Journal. 3 indexed citations
9.
LaFave, Lindsay M., Vinay K. Kartha, Sai Ma, et al.. (2020). Epigenomic State Transitions Characterize Tumor Progression in Mouse Lung Adenocarcinoma. Cancer Cell. 38(2). 212–228.e13. 133 indexed citations
10.
Romero, Rodrigo, Francisco J. Sánchez‐Rivera, Peter M.K. Westcott, et al.. (2020). Keap1 mutation renders lung adenocarcinomas dependent on Slc33a1. Nature Cancer. 1(6). 589–602. 42 indexed citations
11.
Freed-Pastor, William A., Zackery A. Ely, Arjun Bhutkar, et al.. (2020). The CD155/TIGIT Axis Promotes and Maintains Immune Evasion in Neoantigen-Expressing Pancreatic Cancer. SSRN Electronic Journal. 8 indexed citations
12.
Kirkpatrick, Jesse D., Andrew Warren, Ava P. Soleimany, et al.. (2020). Urinary detection of lung cancer in mice via noninvasive pulmonary protease profiling. Science Translational Medicine. 12(537). 59 indexed citations
13.
Li, Leanne, Sheng Rong Ng, Caterina I. Colón, et al.. (2019). Identification of DHODH as a therapeutic target in small cell lung cancer. Science Translational Medicine. 11(517). 103 indexed citations
14.
Smith, Olivia, Peter M.K. Westcott, David Canner, et al.. (2018). Abstract LB-284: Engineering a hypermutant mouse model of NSCLC to modulate immune response. Cancer Research. 78(13_Supplement). LB–284. 1 indexed citations
15.
Westcott, Peter M.K., Kyle Halliwill, Minh D. To, et al.. (2014). The mutational landscapes of genetic and chemical models of Kras-driven lung cancer. Nature. 517(7535). 489–492. 239 indexed citations
16.
Westcott, Peter M.K. & Minh D. To. (2012). The genetics and biology of KRAS in lung cancer. Chinese Journal of Cancer. 32(2). 63–70. 75 indexed citations
17.
To, Minh D., Reyno Del Rosario, Peter M.K. Westcott, Karl L. Banta, & Allan Balmain. (2012). Interactions between wild-type and mutant Ras genes in lung and skin carcinogenesis. Oncogene. 32(34). 4028–4033. 68 indexed citations
18.
Yazinski, Stephanie A., Peter M.K. Westcott, Kelly Ong, et al.. (2009). Dual inactivation of Hus1 and p53 in the mouse mammary gland results in accumulation of damaged cells and impaired tissue regeneration. Proceedings of the National Academy of Sciences. 106(50). 21282–21287. 14 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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