Randomized, open-label phase III study to evaluate the adjuvant vaccination with tumor RNAloaded autologous dendritic cells versus observation of patients with resected monosomy 3 uveal melanoma

Schuler‐Thurner, Beatrice; Doerrie, Jan; Schaft, Niels; Groß, Stefanie; Uslu, Uğur

doi:10.4172/2155-9570.c1.054

Cited by 2 publications

(1 citation statement)

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“…In-house UM sample preparation and RNA sequencing In accordance with current regulatory and ethics standards within the context of clinical trial NCT01983748, 11 patients with UM gave informed consent before tumors were surgically removed. Tumor samples were preserved in RNAlater (ThermoFisher Scientific, Waltham, Massachusetts, USA) and RNA was extracted with RNeasy Mini kits (Qiagen, Hilden, Germany) according to the manufacturer's protocol.…”

Section: Efficacy Score (Es)-based Candidate Peptide Rankingmentioning

confidence: 99%

Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy

Lischer,

Eberhardt,

Flamann

et al. 2024

J Immunother Cancer

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BackgroundTumor-associated antigens and their derived peptides constitute an opportunity to design off-the-shelf mainline or adjuvant anti-cancer immunotherapies for a broad array of patients. A performant and rational antigen selection pipeline would lay the foundation for immunotherapy trials with the potential to enhance treatment, tremendously benefiting patients suffering from rare, understudied cancers.MethodsWe present an experimentally validated, data-driven computational pipeline that selects and ranks antigens in a multipronged approach. In addition to minimizing the risk of immune-related adverse events by selecting antigens based on their expression profile in tumor biopsies and healthy tissues, we incorporated a network analysis-derived antigen indispensability index based on computational modeling results, and candidate immunogenicity predictions from a machine learning ensemble model relying on peptide physicochemical characteristics.ResultsIn a model study of uveal melanoma, Human Leukocyte Antigen (HLA) docking simulations and experimental quantification of the peptide–major histocompatibility complex binding affinities confirmed that our approach discriminates between high-binding and low-binding affinity peptides with a performance similar to that of established methodologies. Blinded validation experiments with autologous T-cells yielded peptide stimulation-induced interferon-γ secretion and cytotoxic activity despite high interdonor variability. Dissecting the score contribution of the tested antigens revealed that peptides with the potential to induce cytotoxicity but unsuitable due to potential tissue damage or instability of expression were properly discarded by the computational pipeline.ConclusionsIn this study, we demonstrate the feasibility of the de novo computational selection of antigens with the capacity to induce an anti-tumor immune response and a predicted low risk of tissue damage. On translation to the clinic, our pipeline supports fast turn-around validation, for example, for adoptive T-cell transfer preparations, in both generalized and personalized antigen-directed immunotherapy settings.

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Section: Efficacy Score (Es)-based Candidate Peptide Rankingmentioning

confidence: 99%

Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy

Lischer,

Eberhardt,

Flamann

et al. 2024

J Immunother Cancer

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Nanotechnology-Based Approaches to Promote Lymph Node Targeted Delivery of Cancer Vaccines

Zang

Zhao

et al. 2022

ACS Biomater. Sci. Eng.

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Vaccines are a promising immunotherapy that awakens the human immune system to inhibit and eliminate cancer with fewer side effects compared with traditional radiotherapy and chemotherapy. Although cancer vaccines have shown some efficacy, there are still troublesome bottlenecks to expand their benefits in the clinic, including weak immune effects and limited therapeutic outcomes. In the past few years, in addition to neoantigen screening, a main branch of the efforts has been devoted to promoting the lymph nodes (LNs) targeting of cancer vaccines and the cross-presentation of antigens by dendritic cells (DCs), two cardinal stages in effective initiation of the immune response. Especially, nanomaterials have shown hopeful biomedical applications in the improvement of vaccine effectiveness. This Review briefly outlines the possible mechanisms by which nanoparticle properties affect LN targeting and antigen cross-presentation and then gives an overview of state-of-the-art advances in improving these biological outcomes with nanotechnology.

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Randomized, open-label phase III study to evaluate the adjuvant vaccination with tumor RNAloaded autologous dendritic cells versus observation of patients with resected monosomy 3 uveal melanoma

Cited by 2 publications

References 0 publications

Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy

Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy

Nanotechnology-Based Approaches to Promote Lymph Node Targeted Delivery of Cancer Vaccines

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