Diana L. Simons

1.2k total citations
19 papers, 791 citations indexed

About

Diana L. Simons is a scholar working on Oncology, Immunology and Molecular Biology. According to data from OpenAlex, Diana L. Simons has authored 19 papers receiving a total of 791 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Oncology, 14 papers in Immunology and 3 papers in Molecular Biology. Recurrent topics in Diana L. Simons's work include Cancer Immunotherapy and Biomarkers (13 papers), Immunotherapy and Immune Responses (9 papers) and Immune Cell Function and Interaction (7 papers). Diana L. Simons is often cited by papers focused on Cancer Immunotherapy and Biomarkers (13 papers), Immunotherapy and Immune Responses (9 papers) and Immune Cell Function and Interaction (7 papers). Diana L. Simons collaborates with scholars based in United States and China. Diana L. Simons's co-authors include Peter P. Lee, John H. Yim, Frederick M. Dirbas, Christian Avalos, James Waisman, Travis Y. Tu, Ning Yan, Denise Johnson, Susan Holmes and Xuyang Lu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature Immunology.

In The Last Decade

Diana L. Simons

19 papers receiving 788 citations

Peers

Diana L. Simons

ONCOL

IMMUN

GENET

Remy Thomas Qatar

Jens Pahl Germany

Karthik Dhatchinamoorthy United States

Anna‐Maria Georgoudaki Sweden

Hsiao‐Wei Tsao United States

Kito Nzingha United States

Scott D. Brown Canada

Robert A. Kurt United States

Perpetua U. Emeagi Belgium

Judy Browning Australia

Remy Thomas Qatar

Diana L. Simons

376 ×0.8

ONCOL

364 ×0.8

IMMUN

265 ×1.1

71 ×0.6

43 ×0.6

GENET

Citations per year, relative to Diana L. Simons Diana L. Simons (= 1×) peers Remy Thomas

Countries citing papers authored by Diana L. Simons

Since Specialization

Citations

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

Fields of papers citing papers by Diana L. Simons

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Diana L. Simons. 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 Diana L. Simons. The network helps show where Diana L. Simons may publish in the future.

Co-authorship network of co-authors of Diana L. Simons

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

All Works

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19 of 19 papers shown

Wang, Lei, Weihua Guo, Jiangnan Yu, et al.. (2024). PD-L1-expressing tumor-associated macrophages are immunostimulatory and associate with good clinical outcome in human breast cancer. Cell Reports Medicine. 5(2). 101420–101420. 46 indexed citations

Egelston, Colt A., Weihua Guo, Diana L. Simons, et al.. (2024). Organ-Specific Immune Setpoints Underlie Divergent Immune Profiles across Metastatic Sites in Breast Cancer. Cancer Immunology Research. 12(11). 1559–1573. 2 indexed citations

Guo, Weihua, Jiayi Tan, Lei Wang, et al.. (2024). Tumor draining lymph nodes connected to cold triple-negative breast cancers are characterized by Th2-associated microenvironment. Nature Communications. 15(1). 8592–8592. 5 indexed citations

Guo, Weihua, Colt A. Egelston, Diana L. Simons, et al.. (2024). Tumor heterogeneity and clinically invisible micrometastases in metastatic breast cancer—a call for enhanced surveillance strategies. npj Precision Oncology. 8(1). 81–81. 4 indexed citations

Branciamore, Sergio, Grigoriy Gogoshin, Diana L. Simons, et al.. (2023). Bow-tie architectures in biological and artificial neural networks: Implications for network evolution and assay design. iScience. 26(2). 106041–106041. 3 indexed citations

Egelston, Colt A., Weihua Guo, Jiayi Tan, et al.. (2022). Tumor-infiltrating exhausted CD8+ T cells dictate reduced survival in premenopausal estrogen receptor–positive breast cancer. JCI Insight. 7(3). 25 indexed citations

Wang, Lei, Diana L. Simons, Xuyang Lu, et al.. (2020). Breast cancer induces systemic immune changes on cytokine signaling in peripheral blood monocytes and lymphocytes. EBioMedicine. 52. 102631–102631. 60 indexed citations

Wang, Lei, Diana L. Simons, Xuyang Lu, et al.. (2019). Connecting blood and intratumoral Treg cell activity in predicting future relapse in breast cancer. Nature Immunology. 20(9). 1220–1230. 125 indexed citations

Egelston, Colt A., et al.. (2019). Identification of exhausted CD8+ T cells in low tumor mutation burden breast cancer patients. The Journal of Immunology. 202(1_Supplement). 138.21–138.21. 1 indexed citations

10.

Egelston, Colt A., Christian Avalos, Travis Y. Tu, et al.. (2018). Human breast tumor-infiltrating CD8+ T cells retain polyfunctionality despite PD-1 expression. Nature Communications. 9(1). 4297–4297. 97 indexed citations

11.

Egelston, Colt A., Christian Avalos, Yinghui Huang, et al.. (2018). Complex phenotyping of PD-1+ CD39+ exhausted CD8+ T cells in human carcinomas. The Journal of Immunology. 200(Supplement_1). 57.23–57.23. 2 indexed citations

12.

Egelston, Colt A., Gayathri Srinivasan, Christian Avalos, et al.. (2017). CD8+ tissue resident memory T cells are associated with good prognosis in breast cancer patients. The Journal of Immunology. 198(Supplement_1). 196.11–196.11. 4 indexed citations

13.

Wang, Lei, Andrea K. Miyahira, Diana L. Simons, et al.. (2016). IL6 Signaling in Peripheral Blood T Cells Predicts Clinical Outcome in Breast Cancer. Cancer Research. 77(5). 1119–1126. 37 indexed citations

14.

Munson, Daniel J., Colt A. Egelston, Kami Chiotti, et al.. (2016). Identification of shared TCR sequences from T cells in human breast cancer using emulsion RT-PCR. Proceedings of the National Academy of Sciences. 113(29). 8272–8277. 43 indexed citations

15.

Chang, Andrew Y., Nupur Bhattacharya, Jian Mu, et al.. (2013). Spatial organization of dendritic cells within tumor draining lymph nodes impacts clinical outcome in breast cancer patients. Journal of Translational Medicine. 11(1). 242–242. 40 indexed citations

16.

Yu, Hongxiang, Diana L. Simons, Erich Schwartz, et al.. (2012). PRC2/EED-EZH2 Complex Is Up-Regulated in Breast Cancer Lymph Node Metastasis Compared to Primary Tumor and Correlates with Tumor Proliferation In Situ. PLoS ONE. 7(12). e51239–e51239. 50 indexed citations

17.

Zuckerman, Neta S., Hongxiang Yu, Diana L. Simons, et al.. (2012). Altered local and systemic immune profiles underlie lymph node metastasis in breast cancer patients. International Journal of Cancer. 132(11). 2537–2547. 32 indexed citations

18.

Simons, Diana L., et al.. (2011). Interferon signaling patterns in peripheral blood lymphocytes may predict clinical outcome after high-dose interferon therapy in melanoma patients. Journal of Translational Medicine. 9(1). 52–52. 24 indexed citations

19.

Critchley-Thorne, Rebecca J., Diana L. Simons, Ning Yan, et al.. (2009). Impaired interferon signaling is a common immune defect in human cancer. Proceedings of the National Academy of Sciences. 106(22). 9010–9015. 191 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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