Ensar Halilovic

4.5k total citations · 1 hit paper
33 papers, 2.3k citations indexed

About

Ensar Halilovic is a scholar working on Oncology, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Ensar Halilovic has authored 33 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Oncology, 18 papers in Molecular Biology and 8 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Ensar Halilovic's work include Cancer-related Molecular Pathways (12 papers), Melanoma and MAPK Pathways (8 papers) and Advanced Breast Cancer Therapies (6 papers). Ensar Halilovic is often cited by papers focused on Cancer-related Molecular Pathways (12 papers), Melanoma and MAPK Pathways (8 papers) and Advanced Breast Cancer Therapies (6 papers). Ensar Halilovic collaborates with scholars based in United States, Switzerland and France. Ensar Halilovic's co-authors include David B. Solit, Neal Rosen, Qing‐Bai She, Christine A. Pratilas, Poulikos I. Poulikakos, Eric W. Joseph, Madhavi Tadi, Stephen Doxsey, Takehiko Sasazuki and Senji Shirasawa and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.

In The Last Decade

Ensar Halilovic

32 papers receiving 2.3k citations

Hit Papers

align trajectories

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.

Relief of Profound Feedback Inhibition of Mitogenic Signaling by RAF Inhibitors Attenuates Their Activity in BRAFV600E Melanomas

2012 410 citations Christine A. Pratilas, Eric W. Joseph et al. Cancer Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ensar Halilovic United States	19	1.8k	977	375	373	336	33	2.3k
Matthias Drosten Spain	22	1.4k 0.8×	777 0.8×	261 0.7×	254 0.7×	301 0.9×	43	2.0k
Paul Wan United Kingdom	9	1.9k 1.1×	991 1.0×	226 0.6×	208 0.6×	425 1.3×	9	2.5k
Ayana Sawai United States	9	2.7k 1.5×	1.1k 1.1×	539 1.4×	183 0.5×	354 1.1×	10	3.3k
Katherine G. Moss United States	15	1.2k 0.7×	666 0.7×	214 0.6×	423 1.1×	189 0.6×	17	1.9k
Chris M. Jones United Kingdom	3	1.7k 0.9×	962 1.0×	228 0.6×	167 0.4×	421 1.3×	4	2.2k
Zhan Yao United States	24	2.1k 1.2×	1.2k 1.2×	521 1.4×	164 0.4×	549 1.6×	39	2.9k
Sidong Huang Canada	22	1.9k 1.1×	1.2k 1.2×	404 1.1×	201 0.5×	518 1.5×	44	2.9k
Maria Karasarides United States	12	1.8k 1.0×	833 0.9×	152 0.4×	307 0.8×	262 0.8×	20	2.3k
Narsis Attar United States	11	2.1k 1.2×	1.3k 1.4×	197 0.5×	194 0.5×	298 0.9×	13	2.6k
Vanessa Rodrik-Outmezguine United States	16	2.1k 1.2×	943 1.0×	561 1.5×	164 0.4×	367 1.1×	32	2.8k

Countries citing papers authored by Ensar Halilovic

Since Specialization

Citations

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

Fields of papers citing papers by Ensar Halilovic

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ensar Halilovic

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

All Works

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20 of 20 papers shown

Saad, Joseph, Roland Newman, Éric Durand, et al.. (2025). Predictors of response and rational combinations for the novel MCL ‐1 inhibitor MIK665 in acute myeloid leukemia. Molecular Oncology. 20(2). 389–408. 1 indexed citations

Wang, Hui Qin, Iain J. Mulford, Fiona A. Sharp, et al.. (2021). Inhibition of MDM2 Promotes Antitumor Responses in p53 Wild-Type Cancer Cells through Their Interaction with the Immune and Stromal Microenvironment. Cancer Research. 81(11). 3079–3091. 43 indexed citations

Razak, Albiruni R. Abdul, Sebastian Bauer, Cristina Suárez, et al.. (2021). Co-Targeting of MDM2 and CDK4/6 with Siremadlin and Ribociclib for the Treatment of Patients with Well-Differentiated or Dedifferentiated Liposarcoma: Results from a Proof-of-Concept, Phase Ib Study. Clinical Cancer Research. 28(6). 1087–1097. 43 indexed citations

Bauer, Sebastian, George D. Demetri, Ensar Halilovic, et al.. (2021). Pharmacokinetic–pharmacodynamic guided optimisation of dose and schedule of CGM097, an HDM2 inhibitor, in preclinical and clinical studies. British Journal of Cancer. 125(5). 687–698. 25 indexed citations

Wei, Andrew H., Massimo Breccia, Melissa Ooi, et al.. (2021). Preliminary Results from a Phase Ib Study Exploring MDM2 Inhibitor Siremadlin (HDM201) in Combination with B-Cell Lymphoma-2 (BCL-2) Inhibitor Venetoclax in Patients with Acute Myeloid Leukemia (AML) or High-Risk Myelodysplastic Syndrome (HR-MDS). Blood. 138(Supplement 1). 1283–1283. 6 indexed citations

Decaudin, Didier, Fariba Némati, Mohamed Zerara, et al.. (2020). Preclinical evaluation of drug combinations identifies co-inhibition of Bcl-2/XL/W and MDM2 as a potential therapy in uveal melanoma. European Journal of Cancer. 126. 93–103. 20 indexed citations

Portman, Neil, Heloisa Milioli, Sarah Alexandrou, et al.. (2020). MDM2 inhibition in combination with endocrine therapy and CDK4/6 inhibition for the treatment of ER-positive breast cancer. Breast Cancer Research. 22(1). 87–87. 49 indexed citations

Vilgelm, Anna E., Nabil Saleh, Rebecca L. Shattuck-Brandt, et al.. (2019). MDM2 antagonists overcome intrinsic resistance to CDK4/6 inhibition by inducing p21. Science Translational Medicine. 11(505). 88 indexed citations

Hernández-García, Susana, Luís A. Corchete, Laura San‐Segundo, et al.. (2019). Preclinical evaluation of the simultaneous inhibition of MCL-1 and BCL-2 with the combination of S63845 and venetoclax in multiple myeloma. Haematologica. 105(3). e116–e120. 42 indexed citations

10.

Horn, Thomas, Stéphane Ferretti, Nicolas Ebel, et al.. (2016). High-Order Drug Combinations Are Required to Effectively Kill Colorectal Cancer Cells. Cancer Research. 76(23). 6950–6963. 24 indexed citations

11.

Bauer, Sebastian, George D. Demetri, Sébastien Jeay, et al.. (2016). A phase I, open-label, multi-center, dose escalation study of oral NVP-CGM097, a p53/HDM2-protein-protein interaction inhibitor, in adult patients with selected advanced solid tumors. Annals of Oncology. 27. vi116–vi116. 13 indexed citations

12.

Nölting, Svenja, Sabine Herterich, Stefanie Hahner, et al.. (2016). The HDM2 (MDM2) Inhibitor NVP-CGM097 Inhibits Tumor Cell Proliferation and Shows Additive Effects with 5-Fluorouracil on the p53-p21-Rb-E2F1 Cascade in the p53<sup>wild type</sup> Neuroendocrine Tumor Cell Line GOT1. Neuroendocrinology. 106(1). 1–19. 25 indexed citations

13.

Dahmani, Ahmed, Nathalie Cassoux, Sophie Piperno‐Neumann, et al.. (2016). Dual inhibition of protein kinase C and p53-MDM2 or PKC and mTORC1 are novel efficient therapeutic approaches for uveal melanoma. Oncotarget. 7(23). 33542–33556. 50 indexed citations

14.

Townsend, Elizabeth C., Tiffany DeSouza, Mark A. Murakami, et al.. (2015). The MDM2 Inhibitor NVP-CGM097 Is Highly Active in a Randomized Preclinical Trial of B-Cell Acute Lymphoblastic Leukemia Patient Derived Xenografts. Blood. 126(23). 797–797. 8 indexed citations

15.

Wang, Hui Qin, Matthew Zubrowski, Erling O. Emerson, et al.. (2014). Abstract 5466: The Mdm2 inhibitor, NVP-CGM097, in combination with the BRAF inhibitor NVP-LGX818 elicits synergistic antitumor effects in melanoma. Cancer Research. 74(19_Supplement). 5466–5466. 3 indexed citations

16.

Halilovic, Ensar, Qing‐Bai She, Qing Ye, et al.. (2010). PIK3CA Mutation Uncouples Tumor Growth and Cyclin D1 Regulation from MEK/ERK and Mutant KRAS Signaling. Cancer Research. 70(17). 6804–6814. 133 indexed citations

17.

She, Qing‐Bai, Ensar Halilovic, Qing Ye, et al.. (2010). 4E-BP1 Is a Key Effector of the Oncogenic Activation of the AKT and ERK Signaling Pathways that Integrates Their Function in Tumors. Cancer Cell. 18(1). 39–51. 326 indexed citations

18.

Joseph, Eric W., Christine A. Pratilas, Poulikos I. Poulikakos, et al.. (2010). The RAF inhibitor PLX4032 inhibits ERK signaling and tumor cell proliferation in a V600E BRAF-selective manner. Proceedings of the National Academy of Sciences. 107(33). 14903–14908. 349 indexed citations

19.

Pratilas, Christine A., Aphrothiti J. Hanrahan, Ensar Halilovic, et al.. (2008). Genetic Predictors of MEK Dependence in Non–Small Cell Lung Cancer. Cancer Research. 68(22). 9375–9383. 195 indexed citations

20.

Halilovic, Ensar & David B. Solit. (2008). Therapeutic strategies for inhibiting oncogenic BRAF signaling. Current Opinion in Pharmacology. 8(4). 419–426. 64 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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