Sunil Badve

42.0k total citations · 6 hit papers
309 papers, 14.3k citations indexed

About

Sunil Badve is a scholar working on Oncology, Cancer Research and Molecular Biology. According to data from OpenAlex, Sunil Badve has authored 309 papers receiving a total of 14.3k indexed citations (citations by other indexed papers that have themselves been cited), including 153 papers in Oncology, 110 papers in Cancer Research and 105 papers in Molecular Biology. Recurrent topics in Sunil Badve's work include Breast Cancer Treatment Studies (74 papers), Cancer Cells and Metastasis (39 papers) and HER2/EGFR in Cancer Research (37 papers). Sunil Badve is often cited by papers focused on Breast Cancer Treatment Studies (74 papers), Cancer Cells and Metastasis (39 papers) and HER2/EGFR in Cancer Research (37 papers). Sunil Badve collaborates with scholars based in United States, United Kingdom and Canada. Sunil Badve's co-authors include Harikrishna Nakshatri, Poornima Bhat‐Nakshatri, George W. Sledge, Yesim Gökmen‐Polar, Edith A. Perez, Frederick L. Baehner, Akira Morimiya, Nancy E. Davidson, Romil Saxena and Susan E. Clare and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Sunil Badve

301 papers receiving 14.0k citations

Hit Papers

Prognostic Value of Tumor-Infiltrating ... 2000 2026 2008 2017 2014 2006 2000 2010 2006 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Prognostic Value of Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancers From Two Phase III Randomized Adjuvant Breast Cancer Trials: ECOG 2197 and ECOG 1199
    2014 953 citations Sylvia Adams, Robert J. Gray et al. Journal of Clinical Oncology profile →
  2. CD44+/CD24-breast cancer cells exhibit enhanced invasive properties: an early step necessary for metastasis
    2006 798 citations Poornima Bhat‐Nakshatri, Sunil Badve et al. profile →
  3. Derivation of hepatocytes from bone marrow cells in mice after radiation-induced myeloablation
    2000 750 citations Sunil Badve et al. profile →
  4. Breast cancer prognostic classification in the molecular era: the role of histological grade
    2010 648 citations Jorge S. Reis‐Filho, Frederick L. Baehner et al. profile →
  5. NF-κB represses E-cadherin expression and enhances epithelial to mesenchymal transition of mammary epithelial cells: potential involvement of ZEB-1 and ZEB-2
    2006 507 citations Poornima Bhat‐Nakshatri, Sunil Badve et al. profile →
  6. Basal-like and triple-negative breast cancers: a critical review with an emphasis on the implications for pathologists and oncologists
    2010 506 citations Sunil Badve, Frederick L. Baehner et al. Modern Pathology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sunil Badve United States 59 6.4k 5.5k 4.6k 2.0k 1.5k 309 14.3k
Celina G. Kleer United States 65 7.9k 1.2× 9.2k 1.7× 5.8k 1.3× 1.9k 0.9× 2.0k 1.3× 174 17.2k
Denis Larsimont Belgium 50 7.3k 1.1× 4.8k 0.9× 5.3k 1.1× 2.0k 1.0× 1.3k 0.9× 276 12.8k
Edi Brogi United States 55 5.6k 0.9× 6.0k 1.1× 5.4k 1.2× 2.1k 1.1× 2.7k 1.7× 237 15.8k
Anne Vincent‐Salomon France 70 8.8k 1.4× 5.5k 1.0× 6.7k 1.5× 2.2k 1.1× 3.0k 2.0× 381 16.1k
Derek C. Radisky United States 61 5.9k 0.9× 7.1k 1.3× 3.8k 0.8× 1.7k 0.8× 1.1k 0.7× 196 14.3k
Maria Grazia Daidone Italy 59 6.2k 1.0× 8.0k 1.4× 5.6k 1.2× 1.5k 0.8× 1.3k 0.8× 279 14.6k
Joseph Geradts United States 55 6.5k 1.0× 5.1k 0.9× 5.1k 1.1× 2.1k 1.1× 1.5k 0.9× 195 12.8k
Andrew Berchuck United States 73 5.8k 0.9× 8.1k 1.5× 3.8k 0.8× 1.7k 0.9× 2.6k 1.7× 358 19.9k
Stefan Sleijfer Netherlands 61 7.1k 1.1× 4.2k 0.8× 3.5k 0.8× 4.7k 2.4× 1.3k 0.8× 379 13.6k
Michael J. Duffy Ireland 77 8.0k 1.3× 9.0k 1.6× 7.0k 1.5× 2.8k 1.4× 1.5k 1.0× 264 19.1k

Countries citing papers authored by Sunil Badve

Since Specialization
Citations

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

Fields of papers citing papers by Sunil Badve

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunil Badve. 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 Sunil Badve. The network helps show where Sunil Badve may publish in the future.

Co-authorship network of co-authors of Sunil Badve

This figure shows the co-authorship network connecting the top 25 collaborators of Sunil Badve. A scholar is included among the top collaborators of Sunil Badve 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 Sunil Badve. Sunil Badve 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.
Schildhaus, Hans‐Ulrich, Sunil Badve, Corrado D’Arrigo, et al.. (2025). A Global Ring Study: Concordance Between Ventana PATHWAY Anti-HER2/neu (4B5) Companion Diagnostic Assay and Comparators in Detecting HER2-Low Breast Cancer. Modern Pathology. 38(11). 100867–100867. 2 indexed citations
2.
Corredor, Germán, et al.. (2025). Artificial intelligence in digital pathology — time for a reality check. Nature Reviews Clinical Oncology. 22(4). 283–291. 8 indexed citations
3.
Kulkarni, Madhura, Devaki A. Kelkar, Anand Deshpande, et al.. (2023). Proceedings of the 3rd Indian Cancer Genome Atlas Conference 2022: Biobanking to Omics: Collecting the Global Experience. JCO Global Oncology. 9(9). e2200176–e2200176. 1 indexed citations
4.
Radovich, Milan, Jeffrey P. Solzak, Bradley A. Hancock, et al.. (2022). Initial Phase I Safety Study of Gedatolisib plus Cofetuzumab Pelidotin for Patients with Metastatic Triple-Negative Breast Cancer. Clinical Cancer Research. 28(15). 3235–3241. 21 indexed citations
5.
Postlewait, Lauren M., Chao Zhang, Jane Meisel, et al.. (2022). Utility of Oncotype DX score in clinical management for T1 estrogen receptor positive, HER2 negative, and lymph node negative breast cancer. Breast Cancer Research and Treatment. 192(3). 509–516. 2 indexed citations
6.
Afghahi, Anosheh, Natasha Purington, Summer S. Han, et al.. (2018). Higher Absolute Lymphocyte Counts Predict Lower Mortality from Early-Stage Triple-Negative Breast Cancer. Clinical Cancer Research. 24(12). 2851–2858. 67 indexed citations
7.
Badve, Sunil, Jun Li, Mayra J. Sandoval-Cooper, et al.. (2016). Aggressive breast cancer in western Kenya has early onset, high proliferation, and immune cell infiltration. BMC Cancer. 16(1). 204–204. 35 indexed citations
8.
Gökmen‐Polar, Yesim & Sunil Badve. (2016). Upregulation of HSF1 in estrogen receptor positive breast cancer. Publisher. 2 indexed citations
9.
Gökmen‐Polar, Yesim, et al.. (2015). Prognostic Impact of HOTAIR Expression is Restricted to ER-Negative Breast Cancers. Scientific Reports. 5(1). 8765–8765. 59 indexed citations
10.
Craven, Kelly E., Chirayu Goswami, Sunil Badve, et al.. (2015). Organ-specific adaptive signaling pathway activation in metastatic breast cancer cells. PubMed Central. 1 indexed citations
11.
Adams, Sylvia, Robert J. Gray, Sandra Demaria, et al.. (2014). Prognostic Value of Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancers From Two Phase III Randomized Adjuvant Breast Cancer Trials: ECOG 2197 and ECOG 1199. Journal of Clinical Oncology. 32(27). 2959–2966. 953 indexed citations breakdown →
12.
Chen, Daohong, Poornima Bhat‐Nakshatri, Chirayu Goswami, Sunil Badve, & Harikrishna Nakshatri. (2013). ANTXR1, a Stem Cell-Enriched Functional Biomarker, Connects Collagen Signaling to Cancer Stem-like Cells and Metastasis in Breast Cancer. Cancer Research. 73(18). 5821–5833. 92 indexed citations
13.
14.
Miller, Margaret A., et al.. (2010). Prevalence and Classification of Spontaneous Mammary Intraepithelial Lesions in Dogs Without Clinical Mammary Disease. Veterinary Pathology. 47(2). 275–284. 21 indexed citations
15.
16.
Resetkova, Erika, Jorge S. Reis‐Filho, Rohit Jain, et al.. (2009). Prognostic impact of ALDH1 in breast cancer: a story of stem cells and tumor microenvironment. Breast Cancer Research and Treatment. 123(1). 97–108. 159 indexed citations
17.
Sparano, Joseph A., Lori J. Goldstein, Barrett H. Childs, et al.. (2009). Relationship between Topoisomerase 2A RNA Expression and Recurrence after Adjuvant Chemotherapy for Breast Cancer. Clinical Cancer Research. 15(24). 7693–7700. 21 indexed citations
18.
19.
Antuofermo, Elisabetta, Margaret A. Miller, S. Pirino, et al.. (2007). Spontaneous Mammary Intraepithelial Lesions in Dogs—A Model of Breast Cancer. Cancer Epidemiology Biomarkers & Prevention. 16(11). 2247–2256. 55 indexed citations
20.
Hochreiter, Amelia E., Erin M. Goldblatt, Sergei Gryaznov, et al.. (2006). Telomerase Template Antagonist GRN163L Disrupts Telomere Maintenance, Tumor Growth, and Metastasis of Breast Cancer. Clinical Cancer Research. 12(10). 3184–3192. 114 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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