Michael P. DiGiovanna

7.3k total citations · 1 hit paper
74 papers, 2.8k citations indexed

About

Michael P. DiGiovanna is a scholar working on Oncology, Cancer Research and Molecular Biology. According to data from OpenAlex, Michael P. DiGiovanna has authored 74 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Oncology, 27 papers in Cancer Research and 24 papers in Molecular Biology. Recurrent topics in Michael P. DiGiovanna's work include HER2/EGFR in Cancer Research (32 papers), Breast Cancer Treatment Studies (23 papers) and Cancer Treatment and Pharmacology (18 papers). Michael P. DiGiovanna is often cited by papers focused on HER2/EGFR in Cancer Research (32 papers), Breast Cancer Treatment Studies (23 papers) and Cancer Treatment and Pharmacology (18 papers). Michael P. DiGiovanna collaborates with scholars based in United States, Canada and Poland. Michael P. DiGiovanna's co-authors include David F. Stern, Donald R. Lannin, Lajos Pusztai, Darryl Carter, Brigid K. Killelea, Maysa Abu‐Khalaf, Bruce G. Haffty, Tara Sanft, Anees B. Chagpar and Ann D. Thor and has published in prestigious journals such as Journal of Clinical Oncology, JNCI Journal of the National Cancer Institute and Cancer.

In The Last Decade

Michael P. DiGiovanna

73 papers receiving 2.8k citations

Hit Papers

Impact of Financial Burden of Cancer on Survivors' Qualit... 2014 2026 2018 2022 2014 100 200 300

Peers

Michael P. DiGiovanna
Paul Smith United Kingdom
Peter Barrett‐Lee United Kingdom
Günther Gruber Switzerland
Christopher Poole United Kingdom
Bhavana Pothuri United States
Paul Smith United Kingdom
Michael P. DiGiovanna
Citations per year, relative to Michael P. DiGiovanna Michael P. DiGiovanna (= 1×) peers Paul Smith

Countries citing papers authored by Michael P. DiGiovanna

Since Specialization
Citations

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

Fields of papers citing papers by Michael P. DiGiovanna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael P. DiGiovanna. 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 Michael P. DiGiovanna. The network helps show where Michael P. DiGiovanna may publish in the future.

Co-authorship network of co-authors of Michael P. DiGiovanna

This figure shows the co-authorship network connecting the top 25 collaborators of Michael P. DiGiovanna. A scholar is included among the top collaborators of Michael P. DiGiovanna 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 Michael P. DiGiovanna. Michael P. DiGiovanna 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.
Kunst, Natalia, Shi‐Yi Wang, Sarah S. Mougalian, et al.. (2020). Cost-Effectiveness of Neoadjuvant-Adjuvant Treatment Strategies for Women WithERBB2(HER2)–Positive Breast Cancer. JAMA Network Open. 3(11). e2027074–e2027074. 14 indexed citations
2.
Pusztai, Lajos, et al.. (2019). Changing frameworks in treatment sequencing of triple-negative and HER2-positive, early-stage breast cancers. The Lancet Oncology. 20(7). e390–e396. 57 indexed citations
3.
Gale, Molly, Yao Li, Jian Cao, et al.. (2019). Acquired Resistance to HER2-Targeted Therapies Creates Vulnerability to ATP Synthase Inhibition. Cancer Research. 80(3). 524–535. 36 indexed citations
5.
Chagpar, Anees B., Nina Horowitz, Tara Sanft, et al.. (2017). Does lymph node status influence adjuvant therapy decision-making in women 70 years of age or older with clinically node negative hormone receptor positive breast cancer?. The American Journal of Surgery. 214(6). 1082–1088. 30 indexed citations
6.
Chakraborty, Ashok K., Cynthia Zerillo, & Michael P. DiGiovanna. (2015). In vitro and in vivo studies of the combination of IGF1R inhibitor figitumumab (CP-751,871) with HER2 inhibitors trastuzumab and neratinib. Breast Cancer Research and Treatment. 152(3). 533–544. 17 indexed citations
7.
Abu‐Khalaf, Maysa, Sarah S. Mougalian, Tara Sanft, et al.. (2015). A phase II trial of neoadjuvant aromatase inhibitor therapy and the mTOR inhibitor everolimus in postmenopausal women with hormone receptor positive/HER2 negative breast cancer and a low/intermediate risk Oncotype Dx Recurrence Score (≤ 25).. Journal of Clinical Oncology. 1 indexed citations
9.
Schulman‐Green, Dena, Elizabeth H. Bradley, M. Tish Knobf, et al.. (2011). Self-Management and Transitions in Women With Advanced Breast Cancer. Journal of Pain and Symptom Management. 42(4). 517–525. 67 indexed citations
10.
DiGiovanna, Michael P., et al.. (2009). Co-targeting the insulin-like growth factor I receptor enhances growth-inhibitory and pro-apoptotic effects of anti-estrogens in human breast cancer cell lines. Breast Cancer Research and Treatment. 120(2). 327–335. 43 indexed citations
11.
Grube, Baiba J., Maysa Abu‐Khalaf, Gina G. Chung, et al.. (2009). Preoperative Chemotherapy Decreases the Need for Re-Excision of Breast Cancers Between 2 and 4 cm Diameter. Annals of Surgical Oncology. 16(3). 697–702. 28 indexed citations
12.
Chakraborty, Ashok K., Liang Ke, & Michael P. DiGiovanna. (2008). Co-Targeting Insulin-Like Growth Factor I Receptor and HER2: Dramatic Effects of HER2 Inhibitors on Nonoverexpressing Breast Cancer. Cancer Research. 68(5). 1538–1545. 49 indexed citations
13.
DiGiovanna, Michael P., David F. Stern, Susan M. Edgerton, et al.. (2008). Influence of Activation State of ErbB-2 (HER-2) on Response to Adjuvant Cyclophosphamide, Doxorubicin, and Fluorouracil for Stage II, Node-Positive Breast Cancer: Study 8541 From the Cancer and Leukemia Group B. Journal of Clinical Oncology. 26(14). 2364–2372. 7 indexed citations
14.
DiGiovanna, Michael P. & Ashok K. Chakraborty. (2006). Combinations of HER2, estrogen receptor (ER) and IGF-I receptor (IGF1R) inhibitors induce apoptosis in breast cancer cells: Dramatic effects of HER2 inhibitors on non-overexpressing cells. Cancer Research. 66. 290–290. 6 indexed citations
15.
DiGiovanna, Michael P., et al.. (2005). Relationship of Epidermal Growth Factor Receptor Expression to ErbB-2 Signaling Activity and Prognosis in Breast Cancer Patients. Journal of Clinical Oncology. 23(6). 1152–1160. 193 indexed citations
16.
Abu‐Khalaf, Maysa, Keita Ebisu, Gina G. Chung, et al.. (2005). Five-Year Update of an Expanded Phase II Study of Dose-Dense and -Intense Doxorubicin, Paclitaxel and Cyclophosphamide (ATC) in High-Risk Breast Cancer. Oncology. 69(5). 372–383. 8 indexed citations
17.
DiGiovanna, Michael P., et al.. (2004). Synergistic interaction between all-trans retinoic acid, Herceptin, and tamoxifen in BT-474 human breast cancer cells.. Cancer Research. 64. 508–508. 1 indexed citations
18.
Khan, Atif J., Michael P. DiGiovanna, Douglas A. Ross, et al.. (2001). Adenoid cystic carcinoma: A retrospective clinical review. International Journal of Cancer. 96(3). 149–158. 209 indexed citations
19.
DiGiovanna, Michael P.. (1997). Phosphorylation Sensitivity of the Commonly Used Anti-p185B2Monoclonal Antibody Clone 3B5 Suggests Selective Usage of Autophosphorylation Sites. Analytical Biochemistry. 247(1). 167–170. 7 indexed citations
20.
Keyes, S R, R. S. Loomis, Michael P. DiGiovanna, et al.. (1991). Cytotoxicity and DNA Crosslinks Produced by Mitomycin Analogs in Aerobic and Hypoxic EMT6 Cells. PubMed. 3(10). 351–356. 47 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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