Nicolas Mach

8.1k total citations · 1 hit paper
96 papers, 3.1k citations indexed

About

Nicolas Mach is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Immunology. According to data from OpenAlex, Nicolas Mach has authored 96 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Oncology, 30 papers in Pulmonary and Respiratory Medicine and 26 papers in Immunology. Recurrent topics in Nicolas Mach's work include Cancer Immunotherapy and Biomarkers (27 papers), Immunotherapy and Immune Responses (22 papers) and CAR-T cell therapy research (19 papers). Nicolas Mach is often cited by papers focused on Cancer Immunotherapy and Biomarkers (27 papers), Immunotherapy and Immune Responses (22 papers) and CAR-T cell therapy research (19 papers). Nicolas Mach collaborates with scholars based in Switzerland, United States and Italy. Nicolas Mach's co-authors include Glenn Dranoff, Silke Gillessen, Martín C. Mihm, S. Brian Wilson, C. Sheehan, Richard C. Mulligan, Chris S. Lantz, Stephen J. Galli, Yukifumi Nawa and Chang Ho Song and has published in prestigious journals such as Nature, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

In The Last Decade

Nicolas Mach

93 papers receiving 3.1k citations

Hit Papers

Phase I/Ib Clinical Trial of Sabatolimab, an Anti–TIM-3 A... 2021 2026 2022 2024 2021 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicolas Mach Switzerland 25 1.6k 1.2k 553 434 330 96 3.1k
Bruce Allen Bach United States 25 1.1k 0.7× 659 0.6× 499 0.9× 600 1.4× 184 0.6× 57 2.7k
Voravit Ratanatharathorn United States 29 1.1k 0.7× 857 0.7× 350 0.6× 234 0.5× 265 0.8× 140 3.6k
Mélissa Dullaers Belgium 29 2.5k 1.6× 524 0.5× 816 1.5× 188 0.4× 241 0.7× 45 3.6k
Shaun R. McCann Ireland 28 537 0.3× 898 0.8× 322 0.6× 311 0.7× 263 0.8× 107 2.9k
Vincent R. Bonagura United States 33 1.6k 1.0× 447 0.4× 637 1.2× 372 0.9× 221 0.7× 133 3.3k
Shuichi Taniguchi Japan 40 1.7k 1.1× 1.8k 1.6× 1.0k 1.8× 388 0.9× 406 1.2× 275 6.1k
Lukas Flatz Switzerland 29 1.6k 1.0× 1.8k 1.6× 721 1.3× 542 1.2× 210 0.6× 102 4.0k
E Naparstek Israel 24 1.9k 1.2× 1.5k 1.3× 395 0.7× 196 0.5× 207 0.6× 65 5.3k
Aks Chiang Hong Kong 35 833 0.5× 1.7k 1.5× 457 0.8× 151 0.3× 231 0.7× 121 3.0k
George E. Sale United States 37 2.1k 1.3× 1.7k 1.5× 680 1.2× 857 2.0× 624 1.9× 97 7.4k

Countries citing papers authored by Nicolas Mach

Since Specialization
Citations

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

Fields of papers citing papers by Nicolas Mach

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicolas Mach

This figure shows the co-authorship network connecting the top 25 collaborators of Nicolas Mach. A scholar is included among the top collaborators of Nicolas Mach 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 Nicolas Mach. Nicolas Mach 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.
McKee, Thomas, Nicolas Mach, Kaveh Samii, et al.. (2024). Effectiveness of fractionated rituximab in preventing tumor lysis syndrome in aggressive B‐cell lymphoma: Insights from real‐life clinical practice. Cancer Reports. 7(10). e1983–e1983. 1 indexed citations
2.
Lin, Chia‐Chi, Giuseppe Curigliano, Armando Santoro, et al.. (2024). Sabatolimab in combination with spartalizumab in patients with non-small cell lung cancer or melanoma who received prior treatment with anti-PD-1/PD-L1 therapy: a phase 2 multicentre study. BMJ Open. 14(8). e079132–e079132. 8 indexed citations
3.
Fernández, Eugenio, Denis Migliorini, Emily Charrier, et al.. (2024). A First-in-Human Phase I Clinical Study with MVX-ONCO-1, a Personalized Active Immunotherapy, in Patients with Advanced Solid Tumors. Cancer Research Communications. 4(8). 2089–2100.
4.
Zilli, Thomas, Ciro Franzese, Matthias Gückenberger, et al.. (2024). ONE SHOT - single shot radiotherapy for localized prostate cancer: 18-month results of a single arm, multicenter phase I/II trial. Radiotherapy and Oncology. 194. 110181–110181. 4 indexed citations
7.
Mach, Nicolas, Carmen Belli, Eduardo Fernández, et al.. (2023). 1037P Phase I dose-escalation trial with tumor-targeted interleukin-12 (IL12-L19L19) in patients with solid tumors. Annals of Oncology. 34. S629–S630. 2 indexed citations
8.
Joerger, Markus, Yannis Metaxas, Khalil Zaman, et al.. (2022). Outcome and Prognostic Factors of COVID-19 Infection in Swiss Cancer Patients: Final Results of SAKK 80/20 (CaSA). Cancers. 14(9). 2191–2191. 3 indexed citations
9.
Reis, Daniela, et al.. (2022). Complementary and Integrative Medicine in Pediatric Oncology – Development and Evaluation of a Blended Learning Program. Klinische Pädiatrie. 234(3). 163–168. 2 indexed citations
10.
Curigliano, Giuseppe, Hans Gelderblom, Nicolas Mach, et al.. (2021). Phase I/Ib Clinical Trial of Sabatolimab, an Anti–TIM-3 Antibody, Alone and in Combination with Spartalizumab, an Anti–PD-1 Antibody, in Advanced Solid Tumors. Clinical Cancer Research. 27(13). 3620–3629. 257 indexed citations breakdown →
11.
Charrier, Emily, et al.. (2021). A Functional GM-CSF Receptor on Dendritic Cells Is Required for Efficient Protective Anti-Tumor Immunity. SHILAP Revista de lepidopterología. 1(3). 240–252. 1 indexed citations
13.
Charrier, Emily, et al.. (2021). A Quantitative ELISA Protocol for Detection of Specific Human IgG against the SARS-CoV-2 Spike Protein. Vaccines. 9(7). 770–770. 11 indexed citations
14.
Harrington, Kevin J., Anthony Kong, Nicolas Mach, et al.. (2020). Talimogene Laherparepvec and Pembrolizumab in Recurrent or Metastatic Squamous Cell Carcinoma of the Head and Neck (MASTERKEY-232): A Multicenter, Phase 1b Study. Clinical Cancer Research. 26(19). 5153–5161. 83 indexed citations
15.
16.
Curioni‐Fontecedro, Alessandra, Jean Yannis Perentes, Hans Gelpke, et al.. (2019). Preoperative chemotherapy and radiotherapy concomitant to cetuximab in resectable stage IIIB NSCLC: a multicentre phase 2 trial (SAKK 16/08). British Journal of Cancer. 120(10). 968–974. 5 indexed citations
17.
Siano, Marco, Vittoria Espeli, Nicolas Mach, et al.. (2018). Gene signatures and expression of miRNAs associated with efficacy of panitumumab in a head and neck cancer phase II trial. Oral Oncology. 82. 144–151. 10 indexed citations
18.
Groß, Stefanie, Volker Lennerz, Elisa Gallerani, et al.. (2015). Short Peptide Vaccine Induces CD4+ T Helper Cells in Patients with Different Solid Cancers. Cancer Immunology Research. 4(1). 18–25. 18 indexed citations
19.
Aïssa, Assma Ben, et al.. (2011). [b]Anticancéreux[/b] sous haute tension. Revue Médicale Suisse. 7(308). 1761–1766.
20.
Schwenter, Frank, et al.. (2008). Development Of A Cell Encapsulation Approach For Human Anti-Tumor Immunotherapy. The International Journal of Artificial Organs. 31(7). 601–601. 1 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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