Marco Mineo

1.5k total citations
18 papers, 1.1k citations indexed

About

Marco Mineo is a scholar working on Molecular Biology, Cancer Research and Immunology. According to data from OpenAlex, Marco Mineo has authored 18 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 11 papers in Cancer Research and 5 papers in Immunology. Recurrent topics in Marco Mineo's work include Cancer-related molecular mechanisms research (8 papers), Extracellular vesicles in disease (7 papers) and MicroRNA in disease regulation (5 papers). Marco Mineo is often cited by papers focused on Cancer-related molecular mechanisms research (8 papers), Extracellular vesicles in disease (7 papers) and MicroRNA in disease regulation (5 papers). Marco Mineo collaborates with scholars based in United States, Italy and Germany. Marco Mineo's co-authors include Jakub Godlewski, Arun K. Rooj, Agnieszka Bronisz, Ichiro Nakano, E. Antonio Chiocca, Elise C. Kohn, Riccardo Alessandro, Simona Taverna, Giacomo De Leo and A. Flugý and has published in prestigious journals such as Cancer Research, Clinical Cancer Research and Cell Reports.

In The Last Decade

Marco Mineo

18 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marco Mineo United States 11 897 675 138 137 102 18 1.1k
Brittany C. Parker Kerrigan United States 14 675 0.8× 430 0.6× 210 1.5× 220 1.6× 273 2.7× 26 1.0k
Gaetano Gargiulo Netherlands 17 1.6k 1.7× 362 0.5× 407 2.9× 185 1.4× 129 1.3× 27 1.9k
Danielle Hulsman Netherlands 16 1.2k 1.4× 298 0.4× 360 2.6× 125 0.9× 219 2.1× 26 1.5k
Noemí Garcia‐Romero Spain 14 599 0.7× 403 0.6× 120 0.9× 87 0.6× 177 1.7× 24 837
Benedetto Daniele Giaimo Germany 16 889 1.0× 178 0.3× 108 0.8× 102 0.7× 35 0.3× 27 1.1k
Junjun Ding China 17 1.8k 2.0× 311 0.5× 117 0.8× 142 1.0× 68 0.7× 38 2.0k
Yizeng Yang United States 18 839 0.9× 186 0.3× 105 0.8× 82 0.6× 149 1.5× 26 1.1k
Mamie Yu United States 10 1.3k 1.5× 1.1k 1.6× 193 1.4× 57 0.4× 252 2.5× 12 1.7k
Daniel Rosebrock United States 8 483 0.5× 363 0.5× 137 1.0× 74 0.5× 81 0.8× 12 745
Yangmi Lim South Korea 17 786 0.9× 255 0.4× 277 2.0× 99 0.7× 35 0.3× 27 1.4k

Countries citing papers authored by Marco Mineo

Since Specialization
Citations

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

Fields of papers citing papers by Marco Mineo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Mineo

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

All Works

18 of 18 papers shown
1.
Mrid, Reda Ben, et al.. (2025). The emerging roles of aberrant alternative splicing in glioma. Cell Death Discovery. 11(1). 50–50. 5 indexed citations
2.
Saini, Shikha, et al.. (2025). Improving IL12 immunotherapy in glioblastoma by targeting the long noncoding RNA INCR1. Journal of Neuro-Oncology. 173(1). 205–216. 1 indexed citations
3.
Toker, Joseph, J. Bryan Iorgulescu, Alexander Ling, et al.. (2023). Clinical Importance of the lncRNA NEAT1 in Cancer Patients Treated with Immune Checkpoint Inhibitors. Clinical Cancer Research. 29(12). 2226–2238. 27 indexed citations
4.
Passaro, Carmela, Quazim A. Alayo, Isabel DeLaura, et al.. (2018). Arming an Oncolytic Herpes Simplex Virus Type 1 with a Single-chain Fragment Variable Antibody against PD-1 for Experimental Glioblastoma Therapy. Clinical Cancer Research. 25(1). 290–299. 103 indexed citations
5.
Godlewski, Jakub, Rubén Ferrer-Luna, Arun K. Rooj, et al.. (2017). MicroRNA Signatures and Molecular Subtypes of Glioblastoma: The Role of Extracellular Transfer. Stem Cell Reports. 8(6). 1497–1505. 55 indexed citations
6.
Rooj, Arun K., Franz Ricklefs, Marco Mineo, et al.. (2017). MicroRNA-Mediated Dynamic Bidirectional Shift between the Subclasses of Glioblastoma Stem-like Cells. Cell Reports. 19(10). 2026–2032. 31 indexed citations
7.
Ricklefs, Franz, Marco Mineo, Arun K. Rooj, et al.. (2016). Extracellular Vesicles from High-Grade Glioma Exchange Diverse Pro-oncogenic Signals That Maintain Intratumoral Heterogeneity. Cancer Research. 76(10). 2876–2881. 81 indexed citations
8.
Rooj, Arun K., Marco Mineo, & Jakub Godlewski. (2016). MicroRNA and extracellular vesicles in glioblastoma: small but powerful. Brain Tumor Pathology. 33(2). 77–88. 49 indexed citations
9.
Mineo, Marco, Franz Ricklefs, Arun K. Rooj, et al.. (2016). The Long Non-coding RNA HIF1A-AS2 Facilitates the Maintenance of Mesenchymal Glioblastoma Stem-like Cells in Hypoxic Niches. Cell Reports. 15(11). 2500–2509. 156 indexed citations
10.
Mineo, Marco, Franz Ricklefs, Arun K. Rooj, et al.. (2016). Abstract 1000: The long non-coding RNA HIF1A-AS2 regulates mesenchymal glioma stem cell tumorigenicity. Cancer Research. 76(14_Supplement). 1000–1000. 1 indexed citations
11.
Mineo, Marco, Franz Ricklefs, Shawn M. Lyons, et al.. (2016). Abstract PR04: The role of long noncoding RNA HIF1A-AS2 in hypoxic environment of glioblastoma. Cancer Research. 76(6_Supplement). PR04–PR04. 1 indexed citations
12.
Bronisz, Agnieszka, Yan Wang, Michal O. Nowicki, et al.. (2013). Extracellular Vesicles Modulate the Glioblastoma Microenvironment via a Tumor Suppression Signaling Network Directed by miR-1. Cancer Research. 74(3). 738–750. 197 indexed citations
13.
14.
Mineo, Marco, Simona Taverna, A. Flugý, et al.. (2012). Abstract 4372: Chronic myeloid leukemia (CML) exosomes promote angiogenesis in a Src-dependent fashion in vitro and in vivo. Cancer Research. 72(8_Supplement). 4372–4372. 3 indexed citations
15.
Mineo, Marco, Susan H. Garfield, Simona Taverna, et al.. (2011). Exosomes released by K562 chronic myeloid leukemia cells promote angiogenesis in a src-dependent fashion. Angiogenesis. 15(1). 33–45. 227 indexed citations
16.
Mineo, Marco, Susan H. Garfield, Riccardo Alessandro, & Elise C. Kohn. (2011). Abstract 5135: Exosomes released by K562 chronic myeloid leukemia cells promote endothelial cell tubular differentiation through uptake and cell-to-cell transfer. Cancer Research. 71(8_Supplement). 5135–5135. 1 indexed citations
17.
Proia, Patrizia, et al.. (2008). Astrocytes shed extracellular vesicles that contain fibroblast growth factor-2 and vascular endothelial growth factor. International Journal of Molecular Medicine. 21(1). 63–7. 118 indexed citations
18.
Schiera, Gabriella, Patrizia Proia, Chiara Alberti, et al.. (2007). Neurons produce FGF2 and VEGF and secrete them at least in part by shedding extracellular vesicles. Journal of Cellular and Molecular Medicine. 11(6). 1384–1394. 84 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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