Solène Perez

1.4k total citations · 1 hit paper
7 papers, 966 citations indexed

About

Solène Perez is a scholar working on Oncology, Immunology and Genetics. According to data from OpenAlex, Solène Perez has authored 7 papers receiving a total of 966 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Oncology, 5 papers in Immunology and 2 papers in Genetics. Recurrent topics in Solène Perez's work include Cancer Immunotherapy and Biomarkers (6 papers), Immunotherapy and Immune Responses (4 papers) and CAR-T cell therapy research (3 papers). Solène Perez is often cited by papers focused on Cancer Immunotherapy and Biomarkers (6 papers), Immunotherapy and Immune Responses (4 papers) and CAR-T cell therapy research (3 papers). Solène Perez collaborates with scholars based in France, United States and Switzerland. Solène Perez's co-authors include Nicolas Pasqual, Christophe Caux, Jean‐Yves Blay, Christine Ménétrier‐Caux, Thomas Bachelot, Isabelle Ray‐Coquard, Michael Gobert, Sophie Goddard‐Léon, Nathalie Bendriss‐Vermare and Isabelle Durand and has published in prestigious journals such as Cancer Research, Cancer Immunology Research and Journal for ImmunoTherapy of Cancer.

In The Last Decade

Solène Perez

7 papers receiving 959 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.

Regulatory T Cells Recruited through CCL22/CCR4 Are Selectively Activated in Lymphoid Infiltrates Surrounding Primary Breast Tumors and Lead to an Adverse Clinical Outcome

2009 562 citations Michael Gobert, Isabelle Treilleux et al. Cancer Research profile →

Peers

Solène Perez

ONCOL

IMMUN

MB

PRM

CR

Cathy Biota France

Anushruti Sarvaria United Kingdom

Chrysoula I. Liakou United States

Jonathan J. Hodgins Canada

Shamayel Mohammed Saudi Arabia

Linghua Zheng United States

Keyon Taravati United States

Annegé Vledder Netherlands

Amelia Roman Aguilera Australia

Priscila Muñoz Sandoval United States

Cathy Biota France

Solène Perez

628 ×0.9

ONCOL

776 ×1.1

IMMUN

115 ×1.1

MB

63 ×0.6

PRM

56 ×0.6

CR

Citations per year, relative to Solène Perez Solène Perez (= 1×) peers Cathy Biota

Countries citing papers authored by Solène Perez

Since Specialization

Citations

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

Fields of papers citing papers by Solène Perez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Solène Perez

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

All Works

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7 of 7 papers shown

1.

Charles, J., Stéphane Mouret, M.‐T. Leccia, et al.. (2020). T‐cell receptor diversity as a prognostic biomarker in melanoma patients. Pigment Cell & Melanoma Research. 33(4). 612–624. 28 indexed citations

2.

Hogan, Sabrina A., Anaïs Courtier, Phil F. Cheng, et al.. (2018). Peripheral Blood TCR Repertoire Profiling May Facilitate Patient Stratification for Immunotherapy against Melanoma. Cancer Immunology Research. 7(1). 77–85. 100 indexed citations

3.

Postow, Michael A., Manuarii Manuel, Phillip Wong, et al.. (2015). Peripheral T cell receptor diversity is associated with clinical outcomes following ipilimumab treatment in metastatic melanoma. Journal for ImmunoTherapy of Cancer. 3(1). 23–23. 172 indexed citations

4.

Courtier, Anaïs, et al.. (2013). ImmunTraCkeR® as a reliable TCR repertoire profiling tool to understand immune response and to explore immunotherapy biomarkers. Journal for ImmunoTherapy of Cancer. 1(S1). 2 indexed citations

5.

Manuel, Manuarii, Olivier Trédan, Thomas Bachelot, et al.. (2012). Lymphopenia combined with low TCR diversity (divpenia) predicts poor overall survival in metastatic breast cancer patients. OncoImmunology. 1(4). 432–440. 101 indexed citations

6.

Manuel, Manuarii, Olivier Trédan, Thomas Bachelot, et al.. (2011). Abstract LB-165: Low TCR diversity (divpenia) is a new prognosis factor of overall survival in metastatic breast cancer. Cancer Research. 71(8_Supplement). LB–165. 1 indexed citations

7.

Gobert, Michael, Isabelle Treilleux, Nathalie Bendriss‐Vermare, et al.. (2009). Regulatory T Cells Recruited through CCL22/CCR4 Are Selectively Activated in Lymphoid Infiltrates Surrounding Primary Breast Tumors and Lead to an Adverse Clinical Outcome. Cancer Research. 69(5). 2000–2009. 562 indexed citations breakdown →

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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