Megan Wind‐Rotolo

14.3k total citations · 1 hit paper
87 papers, 3.1k citations indexed

About

Megan Wind‐Rotolo is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Immunology. According to data from OpenAlex, Megan Wind‐Rotolo has authored 87 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Oncology, 19 papers in Pulmonary and Respiratory Medicine and 19 papers in Immunology. Recurrent topics in Megan Wind‐Rotolo's work include Cancer Immunotherapy and Biomarkers (33 papers), Hepatitis C virus research (16 papers) and Cancer Genomics and Diagnostics (14 papers). Megan Wind‐Rotolo is often cited by papers focused on Cancer Immunotherapy and Biomarkers (33 papers), Hepatitis C virus research (16 papers) and Cancer Genomics and Diagnostics (14 papers). Megan Wind‐Rotolo collaborates with scholars based in United States, Germany and Italy. Megan Wind‐Rotolo's co-authors include Robert F. Siliciano, Dennis M. Grasela, Fiona McPhee, David Gardiner, Janet D. Siliciano, Eric Lawitz, Timothy Eley, C Pasquinelli, Anna S. Lok and Gregory T. Everson and has published in prestigious journals such as New England Journal of Medicine, Journal of Biological Chemistry and Journal of Clinical Oncology.

In The Last Decade

Megan Wind‐Rotolo

81 papers receiving 3.1k citations

Hit Papers

Preliminary Study of Two Antiviral Agents for Hepatitis C... 2012 2026 2016 2021 2012 100 200 300 400

Peers

Megan Wind‐Rotolo
Norah J. Shire United States
Megan Wind‐Rotolo
Citations per year, relative to Megan Wind‐Rotolo Megan Wind‐Rotolo (= 1×) peers Norah J. Shire

Countries citing papers authored by Megan Wind‐Rotolo

Since Specialization
Citations

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

Fields of papers citing papers by Megan Wind‐Rotolo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Megan Wind‐Rotolo. 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 Megan Wind‐Rotolo. The network helps show where Megan Wind‐Rotolo may publish in the future.

Co-authorship network of co-authors of Megan Wind‐Rotolo

This figure shows the co-authorship network connecting the top 25 collaborators of Megan Wind‐Rotolo. A scholar is included among the top collaborators of Megan Wind‐Rotolo 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 Megan Wind‐Rotolo. Megan Wind‐Rotolo 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.
Siciliano, Angela, Angelo D’Alessandro, Alessandro Mattè, et al.. (2025). Mitapivat metabolically reprograms human β-thalassemic erythroblasts, increasing their responsiveness to oxidation. Blood Advances. 9(11). 2818–2830. 1 indexed citations
2.
Oirschot, Brigitte A. van, Judith Jans, Megan Wind‐Rotolo, et al.. (2025). Ex vivo activation of pyruvate kinase improves red blood cell metabolism and hydration in hereditary spherocytosis. 1(1). 100005–100005.
3.
Conrey, Anna, Ingrid Frey, Julia Xu, et al.. (2025). Long-term mitapivat treatment is safe and efficacious in patients with sickle cell disease. PubMed. 1(2). 100014–100014.
5.
Galsky, Matthew D., Dean F. Bajorin, J. Alfred Witjes, et al.. (2023). Disease-free Survival Analysis for Patients with High-risk Muscle-invasive Urothelial Carcinoma from the Randomized CheckMate 274 Trial by PD-L1 Combined Positive Score and Tumor Cell Score. European Urology. 83(5). 432–440. 14 indexed citations
6.
Fattizzo, Bruno, Cristina Vercellati, Anna Paola Marcello, et al.. (2023). Biochemical and Metabolomic Analysis of Glycolytic Activity in Red Blood Cells from Low-Risk Myelodysplastic Syndromes (LR-MDS) Patients and in-Vitro Effect of the Pyruvate Kinase Activator AG-946. Blood. 142(Supplement 1). 6456–6456. 2 indexed citations
7.
Johannet, Paul, Wenke Liu, David Fenyö, et al.. (2022). Baseline Serum Autoantibody Signatures Predict Recurrence and Toxicity in Melanoma Patients Receiving Adjuvant Immune Checkpoint Blockade. Clinical Cancer Research. 28(18). 4121–4130. 30 indexed citations
8.
Mahoney, Kathleen M., Petra Ross‐Macdonald, Long Yuan, et al.. (2022). Soluble PD-L1 as an early marker of progressive disease on nivolumab. Journal for ImmunoTherapy of Cancer. 10(2). e003527–e003527. 55 indexed citations
9.
Ross‐Macdonald, Petra, Alice M. Walsh, Scott D. Chasalow, et al.. (2021). Molecular correlates of response to nivolumab at baseline and on treatment in patients with RCC. Journal for ImmunoTherapy of Cancer. 9(3). e001506–e001506. 28 indexed citations
10.
Hodi, F. Stephen, Jedd D. Wolchok, Dirk Schadendorf, et al.. (2021). TMB and Inflammatory Gene Expression Associated with Clinical Outcomes following Immunotherapy in Advanced Melanoma. Cancer Immunology Research. 9(10). 1202–1213. 76 indexed citations
11.
Naranbhai, Vivek, Mathias Viard, Michael Dean, et al.. (2021). HLA-A*03 and response to immune checkpoint blockade in cancer: an epidemiological biomarker study. The Lancet Oncology. 23(1). 172–184. 64 indexed citations
12.
Srinivasan, Sujaya, Natallia Kalinava, Rafael Aldana, et al.. (2020). Misannotated Multi-Nucleotide Variants in Public Cancer Genomics Datasets Lead to Inaccurate Mutation Calls with Significant Implications. Cancer Research. 81(2). 282–288. 7 indexed citations
13.
Ficial, Miriam, Opeyemi A. Jegede, Yue Hou, et al.. (2020). Expression of T-Cell Exhaustion Molecules and Human Endogenous Retroviruses as Predictive Biomarkers for Response to Nivolumab in Metastatic Clear Cell Renal Cell Carcinoma. Clinical Cancer Research. 27(5). 1371–1380. 51 indexed citations
14.
Stein, Julie E., Abhishek Soni, Ludmila Danilova, et al.. (2019). Major pathologic response on biopsy (MPRbx) in patients with advanced melanoma treated with anti-PD-1: evidence for an early, on-therapy biomarker of response. Annals of Oncology. 30(4). 589–596. 35 indexed citations
16.
Wind‐Rotolo, Megan, Dong Xu, Matthew Hruska, et al.. (2016). Mechanisms of Hyperbilirubinemia During Peginterferon Lambda-1a Therapy for Chronic Hepatitis C Infection: A Retrospective Investigation. Journal of Interferon & Cytokine Research. 36(11). 644–651. 1 indexed citations
17.
Lok, Anna S., David Gardiner, Christophe Hézode, et al.. (2013). Randomized trial of daclatasvir and asunaprevir with or without PegIFN/RBV for hepatitis C virus genotype 1 null responders. Journal of Hepatology. 60(3). 490–499. 111 indexed citations
19.
Wind‐Rotolo, Megan, Christine M. Durand, Lisa M. Cranmer, et al.. (2009). Identification of Nevirapine‐Resistant HIV‐1 in the Latent Reservoir after Single‐Dose Nevirapine to Prevent Mother‐to‐Child Transmission of HIV‐1. The Journal of Infectious Diseases. 199(9). 1301–1309. 35 indexed citations
20.
Han, Wenlong, Megan Wind‐Rotolo, Richard Kirkman, & Casey D. Morrow. (2004). Inhibition of human immunodeficiency virus type 1 replication by siRNA targeted to the highly conserved primer binding site. Virology. 330(1). 221–232. 29 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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