cff-version: 1.2.0 abstract: "<p>Code underlying the publications described in the thesis. The dataset includes the Python 3, R and bash scripts for bioinformatic analyses included in the following research papers:</p><p><br></p><p>1) <span style="color: rgb(34, 34, 34);">Nederlof, I., Isaeva, O.I., de Graaf, M. </span><em style="color: rgb(34, 34, 34);">et al.</em><span style="color: rgb(34, 34, 34);"> Neoadjuvant nivolumab or nivolumab plus ipilimumab in early-stage triple-negative breast cancer: a phase 2 adaptive trial. </span><em style="color: rgb(34, 34, 34);">Nat Med</em><span style="color: rgb(34, 34, 34);"> </span><strong style="color: rgb(34, 34, 34);">30</strong><span style="color: rgb(34, 34, 34);">, 3223–3235 (2024). https://doi.org/10.1038/s41591-024-03249-3</span></p><p><span style="color: rgb(34, 34, 34);">2) Voorwerk, L., Isaeva, O.I., Horlings, H.M. </span><em style="color: rgb(34, 34, 34);">et al.</em><span style="color: rgb(34, 34, 34);"> PD-L1 blockade in combination with carboplatin as immune induction in metastatic lobular breast cancer: the GELATO trial. </span><em style="color: rgb(34, 34, 34);">Nat Cancer</em><span style="color: rgb(34, 34, 34);"> </span><strong style="color: rgb(34, 34, 34);">4</strong><span style="color: rgb(34, 34, 34);">, 535–549 (2023). https://doi.org/10.1038/s43018-023-00542-x</span></p><p><span style="color: rgb(34, 34, 34);">3) Gangaev, A., Ketelaars, S.L.C., Isaeva, O.I. </span><em style="color: rgb(34, 34, 34);">et al.</em><span style="color: rgb(34, 34, 34);"> Identification and characterization of a SARS-CoV-2 specific CD8+ T cell response with immunodominant features. </span><em style="color: rgb(34, 34, 34);">Nat Commun</em><span style="color: rgb(34, 34, 34);"> </span><strong style="color: rgb(34, 34, 34);">12</strong><span style="color: rgb(34, 34, 34);">, 2593 (2021). https://doi.org/10.1038/s41467-021-22811-y</span></p>" authors: - family-names: Isaeva given-names: Olga orcid: "https://orcid.org/0000-0001-7377-0944" title: "Data underlying the PhD thesis: Computational approaches to dissect immunotherapy response in breast cancer" keywords: version: 1 identifiers: - type: doi value: 10.4121/1881e4a5-55ff-4b51-984b-3d9a2dda1821.v1 license: Restrictive Licence date-released: 2025-02-17