Daniel L. Adams

1.5k total citations
61 papers, 1.1k citations indexed

About

Daniel L. Adams is a scholar working on Oncology, Molecular Biology and Cancer Research. According to data from OpenAlex, Daniel L. Adams has authored 61 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Oncology, 18 papers in Molecular Biology and 18 papers in Cancer Research. Recurrent topics in Daniel L. Adams's work include Cancer Cells and Metastasis (41 papers), Cancer Genomics and Diagnostics (15 papers) and Cancer Immunotherapy and Biomarkers (15 papers). Daniel L. Adams is often cited by papers focused on Cancer Cells and Metastasis (41 papers), Cancer Genomics and Diagnostics (15 papers) and Cancer Immunotherapy and Biomarkers (15 papers). Daniel L. Adams collaborates with scholars based in United States, Japan and Switzerland. Daniel L. Adams's co-authors include Saranya Chumsri, Cha-Mei Tang, Stuart S. Martin, Cha‐Mei Tang, R. Katherine Alpaugh, Massimo Cristofanilli, Monica S. Charpentier, Peixuan Zhu, Steingrimur Stefansson and Susan Tsai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Daniel L. Adams

57 papers receiving 1.0k citations

Peers

Daniel L. Adams
Christina Hartl United States
Simone Gaedicke Germany
Lanlan Hui China
F Meier-Stiegen Germany
Yuan‐Tong Liu China
Shelly Maman Israel
Myrofora Panagi Cyprus
Sheila Spada United States
Bruno L. Cadilha Germany
Carrie Maynard Netherlands
Christina Hartl United States
Daniel L. Adams
Citations per year, relative to Daniel L. Adams Daniel L. Adams (= 1×) peers Christina Hartl

Countries citing papers authored by Daniel L. Adams

Since Specialization
Citations

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

Fields of papers citing papers by Daniel L. Adams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel L. Adams

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel L. Adams. A scholar is included among the top collaborators of Daniel L. Adams 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 Daniel L. Adams. Daniel L. Adams 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.
Chumsri, Saranya, Joseph J. Larson, Kathleen Tenner, et al.. (2025). Pembrolizumab in Combination with Binimetinib in Patients with Unresectable Locally Advanced or Metastatic Triple-Negative Breast Cancer. Clinical Cancer Research. 31(10). 1885–1893. 1 indexed citations
2.
Adams, Daniel L., Massimo Cristofanilli, Steven H. Lin, et al.. (2025). Phenotyping and clinical utility of phagocytic polyploid giant cancer macrophages in blood. Cancer Letters. 631. 218007–218007. 2 indexed citations
3.
Iwase, Toshiaki, Wenli Dong, Daniel L. Adams, et al.. (2024). Circulating cancer-associated macrophage-like cells and macrophage-related cytokines in obese patients with advanced breast cancer who undergo neoadjuvant chemotherapy. Journal of Cancer. 15(18). 5855–5862. 1 indexed citations
4.
Adams, Daniel L., et al.. (2023). Cancer associated macrophage-like cells in metastatic renal cell carcinoma predicts for poor prognosis and tracks treatment response in real time. Scientific Reports. 13(1). 10544–10544. 4 indexed citations
5.
6.
Tsai, Susan, et al.. (2022). CXCR4 expression in tumor associated cells in blood is prognostic for progression and survival in pancreatic cancer. PLoS ONE. 17(3). e0264763–e0264763. 13 indexed citations
7.
8.
Aldakkak, Mohammed, et al.. (2021). Circulating stromal cells in resectable pancreatic cancer correlates to pathological stage and predicts for poor clinical outcomes. npj Precision Oncology. 5(1). 25–25. 17 indexed citations
9.
Adams, Daniel L., Jianzhong He, Ting Xu, et al.. (2020). Cancer associated macrophage-like cells and prognosis of esophageal cancer after chemoradiation therapy. Journal of Translational Medicine. 18(1). 413–413. 26 indexed citations
10.
Augustyn, Alexander, Daniel L. Adams, Jianzhong He, et al.. (2020). Giant Circulating Cancer-Associated Macrophage-Like Cells Are Associated With Disease Recurrence and Survival in Non–Small-Cell Lung Cancer Treated With Chemoradiation and Atezolizumab. Clinical Lung Cancer. 22(3). e451–e465. 29 indexed citations
11.
Lin, Shiyu, Alexander Augustyn, Jianzhong He, et al.. (2019). MA08.01 Analysis of PD-L1 Expression on Circulating Stromal and Tumor Cells in Lung Cancer Patients Treated with Chemoradiation Therapy and Atezolizumab. Journal of Thoracic Oncology. 14(10). S277–S277. 1 indexed citations
12.
Adams, Daniel L., Diane K. Adams, Jianzhong He, et al.. (2017). Sequential Tracking of PD-L1 Expression and RAD50 Induction in Circulating Tumor and Stromal Cells of Lung Cancer Patients Undergoing Radiotherapy. Clinical Cancer Research. 23(19). 5948–5958. 80 indexed citations
13.
Tang, Cha‐Mei, Peixuan Zhu, Shuhong Li, et al.. (2017). Filtration and Analysis of Circulating Cancer Associated Cells from the Blood of Cancer Patients. Methods in molecular biology. 1572. 511–524. 7 indexed citations
14.
Zhu, Peixuan, Daniel L. Adams, Shuhong Li, et al.. (2017). Enrichment and Molecular Analysis of Breast Cancer Disseminated Tumor Cells from Bone Marrow Using Microfiltration. PLoS ONE. 12(1). e0170761–e0170761. 10 indexed citations
15.
Adams, Daniel L., Diane K. Adams, R. Katherine Alpaugh, et al.. (2016). Circulating Cancer-Associated Macrophage-Like Cells Differentiate Malignant Breast Cancer and Benign Breast Conditions. Cancer Epidemiology Biomarkers & Prevention. 25(7). 1037–1042. 63 indexed citations
16.
Макарова, О. В., Daniel L. Adams, Ralu Divan, et al.. (2016). Polymer microfilters with nanostructured surfaces for the culture of circulating cancer cells. Materials Science and Engineering C. 66. 193–198. 5 indexed citations
17.
Adams, Daniel L., Diane K. Adams, Steingrimur Stefansson, et al.. (2016). Mitosis in circulating tumor cells stratifies highly aggressive breast carcinomas. Breast Cancer Research. 18(1). 44–44. 32 indexed citations
18.
Rezai, Shadi, et al.. (2015). Untreated Active Tuberculosis in Pregnancy with Intraocular Dissemination: A Case Report and Review of the Literature. SHILAP Revista de lepidopterología. 2015. 1–6. 3 indexed citations
19.
Adams, Daniel L., Peixuan Zhu, О. В. Макарова, et al.. (2012). Abstract 2395: HER-2 FISH analysis and H & E staining of circulating tumor cells pre-isolated using high porosity precision microfilters. Cancer Research. 72(8_Supplement). 2395–2395. 5 indexed citations
20.
Zhu, Peixuan, Daniel R. Shelton, Shuhong Li, et al.. (2011). Detection of E. coli O157:H7 by immunomagnetic separation coupled with fluorescence immunoassay. Biosensors and Bioelectronics. 30(1). 337–341. 68 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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