Leandro Cerchietti

10.8k total citations
132 papers, 5.4k citations indexed

About

Leandro Cerchietti is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Oncology. According to data from OpenAlex, Leandro Cerchietti has authored 132 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Molecular Biology, 44 papers in Pathology and Forensic Medicine and 36 papers in Oncology. Recurrent topics in Leandro Cerchietti's work include Lymphoma Diagnosis and Treatment (43 papers), CAR-T cell therapy research (20 papers) and Epigenetics and DNA Methylation (17 papers). Leandro Cerchietti is often cited by papers focused on Lymphoma Diagnosis and Treatment (43 papers), CAR-T cell therapy research (20 papers) and Epigenetics and DNA Methylation (17 papers). Leandro Cerchietti collaborates with scholars based in United States, Canada and Argentina. Leandro Cerchietti's co-authors include Ari Melnick, Alfredo Navigante, Shao Ning Yang, José M. Polo, M. Castro, Rita Shaknovich, Olivier Elemento, Gilbert G. Privé, Katerina Hatzi and María E. Cabalar and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.

In The Last Decade

Leandro Cerchietti

126 papers receiving 5.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Leandro Cerchietti United States 42 2.9k 1.6k 1.0k 992 725 132 5.4k
Michael Fiegl Austria 37 2.3k 0.8× 1.9k 1.2× 476 0.5× 841 0.8× 1.1k 1.5× 165 5.9k
Takemi Otsuki Japan 41 2.1k 0.7× 1.4k 0.8× 571 0.5× 1.0k 1.0× 555 0.8× 190 5.2k
Jean‐Baptiste Demoulin Belgium 41 2.2k 0.7× 1.1k 0.7× 419 0.4× 778 0.8× 593 0.8× 93 4.6k
Andrea Rinaldi Italy 39 1.8k 0.6× 807 0.5× 661 0.6× 1.5k 1.5× 363 0.5× 190 5.1k
Elizabeth Fox United States 42 1.9k 0.7× 2.0k 1.2× 682 0.7× 326 0.3× 651 0.9× 220 5.8k
Tetsuji Takayama Japan 37 2.3k 0.8× 1.7k 1.0× 880 0.8× 328 0.3× 774 1.1× 268 6.2k
Yoshihisa Nojima Japan 40 2.2k 0.7× 844 0.5× 424 0.4× 1.6k 1.6× 362 0.5× 231 6.1k
Shiyong Li United States 35 1.3k 0.4× 1.1k 0.7× 595 0.6× 551 0.6× 534 0.7× 124 3.4k
Arthur Zimmermann Switzerland 53 2.6k 0.9× 2.4k 1.5× 512 0.5× 578 0.6× 737 1.0× 181 7.6k
Ying Yang China 41 2.2k 0.7× 1.7k 1.0× 432 0.4× 502 0.5× 1.3k 1.7× 136 5.1k

Countries citing papers authored by Leandro Cerchietti

Since Specialization
Citations

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

Fields of papers citing papers by Leandro Cerchietti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leandro Cerchietti

This figure shows the co-authorship network connecting the top 25 collaborators of Leandro Cerchietti. A scholar is included among the top collaborators of Leandro Cerchietti 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 Leandro Cerchietti. Leandro Cerchietti 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.
Rivera‐Correa, Juan, Sanjay Gupta, Edd Ricker, et al.. (2025). ROCK1 promotes B cell differentiation and proteostasis under stress through the heme-regulated proteins, BACH2 and HRI. JCI Insight. 10(5).
2.
Correa, Alejandro, María V. Revuelta, Helena Sterle, et al.. (2025). Thyroid hormones contribute to JAK/STAT pathway abnormal activation, promoting T-cell lymphoma dissemination. Blood Advances. 9(15). 4067–4080.
3.
4.
Cerchietti, Leandro. (2024). Genetic mechanisms underlying tumor microenvironment composition and function in diffuse large B-cell lymphoma. Blood. 143(12). 1101–1111. 17 indexed citations
5.
Ghram, Mehdi, Biljana Culjkovic‐Kraljacic, Jean-Clément Mars, et al.. (2023). The eukaryotic translation initiation factor eIF4E reprograms alternative splicing. The EMBO Journal. 42(7). e110496–e110496. 15 indexed citations
6.
Xia, Min, Liron David, Matt Teater, et al.. (2022). BCL10 Mutations Define Distinct Dependencies Guiding Precision Therapy for DLBCL. Cancer Discovery. 12(8). OF1–OF20. 12 indexed citations
7.
Calvo-Vidal, M. Nieves, Nahuel Zamponi, Jan Krumsiek, et al.. (2021). Oncogenic HSP90 Facilitates Metabolic Alterations in Aggressive B-cell Lymphomas. Cancer Research. 81(20). 5202–5216. 19 indexed citations
8.
Li, Meng, Matthew Teater, Jun Young Hong, et al.. (2021). Translational Activation of ATF4 through Mitochondrial Anaplerotic Metabolic Pathways Is Required for DLBCL Growth and Survival. Blood Cancer Discovery. 3(1). 50–65. 18 indexed citations
9.
Martin, Peter, Nancy L. Bartlett, Julio C. Chávez, et al.. (2021). Phase 1 study of oral azacitidine (CC-486) plus R-CHOP in previously untreated intermediate- to high-risk DLBCL. Blood. 139(8). 1147–1159. 21 indexed citations
10.
Fernando, Tharu M., Rossella Marullo, Jude M. Phillip, et al.. (2019). BCL6 Evolved to Enable Stress Tolerance in Vertebrates and Is Broadly Required by Cancer Cells to Adapt to Stress. Cancer Discovery. 9(5). 662–679. 31 indexed citations
11.
12.
Deb, Dhruba, Satwik Rajaram, Jill E. Larsen, et al.. (2017). Combination Therapy Targeting BCL6 and Phospho-STAT3 Defeats Intratumor Heterogeneity in a Subset of Non–Small Cell Lung Cancers. Cancer Research. 77(11). 3070–3081. 33 indexed citations
13.
Pera, Benet, Tiffany Tang, Rossella Marullo, et al.. (2016). Combinatorial epigenetic therapy in diffuse large B cell lymphoma pre-clinical models and patients. Clinical Epigenetics. 8(1). 79–79. 40 indexed citations
14.
Du, Wei, Rebecca Goldstein, Yanwen Jiang, et al.. (2014). A Virtual B Cell Lymphoma Model to Predict Effective Combination Therapy. Blood. 124(21). 928–928. 1 indexed citations
15.
Nayar, Utthara, Pin Lü, Rebecca Goldstein, et al.. (2013). Targeting the Hsp90-associated viral oncoproteome in gammaherpesvirus-associated malignancies. Blood. 122(16). 2837–2847. 54 indexed citations
16.
Cerchietti, Leandro, José M. Polo, Gustavo Felippe da Silva, et al.. (2008). Sequential Transcription Factor Targeting for Diffuse Large B-Cell Lymphomas. Cancer Research. 68(9). 3361–3369. 25 indexed citations
17.
18.
Cerchietti, Leandro, et al.. (2004). Effects of celecoxib, medroxyprogesterone, and dietary intervention on systemic syndromes in patients with advanced lung adenocarcinoma: a pilot study. Journal of Pain and Symptom Management. 27(1). 85–95. 46 indexed citations
19.
Cerchietti, Leandro, María E. Cabalar, & Alfredo Navigante. (2003). Morfina más midazolan versus oxigenoterapia en el control de la disnea severa durante la última semana de vida en pacientes hipoxémicos con cáncer avanzado. Medicina Paliativa. 10(1). 14–19. 5 indexed citations
20.
Cerchietti, Leandro, et al.. (2003). Potential utility of the peripheral analgesic properties of morphine in stomatitis-related pain: a pilot study. Pain. 105(1). 265–273. 75 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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