Uveal melanoma: Recent advances in immunotherapy

Sorrentino, Francesco Saverio; De Rosa, Francesco; Di Terlizzi, Patrick; Toneatto, Giacomo; Gabai, Andrea; Finocchio, Lucia; Salati, Carlo; Spadea, Leopoldo; Zeppieri, Marco

doi:10.5306/wjco.v15.i1.23

Cited by 3 publications

(1 citation statement)

References 63 publications

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“…Many efforts have been made in the treatment of cancer metastasis via chemotherapy and radiotherapy with limited effect. For example, clinical trials aimed at treating metastatic uveal melanoma using a range of targeted strategies failed [39]. There is an urgent need for novel treatment modalities of metastases to overcome drug resistance.…”

Section: Participation Of Modified Evs In Metastasis Preventionmentioning

confidence: 99%

Participation of suicide gene extracellular vesicles in metastasis prevention

Vanova,

Andrezal,

Jakubechova

et al. 2024

neo

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The incidence of distant metastases is associated with most cancer-related mortalities. Extracellular vesicles (EVs), secreted from tumors and cancer-associated fibroblasts, are involved in the metastatic process mediating their organotropism through their involvement in the pre-metastatic niche formation. We have been developing suicide gene therapy mediated by EVs secreted from mesenchymal stem/ stromal cells, tumor cells, and cancer-associated fibroblasts. Suicide gene EVs conjugated with prodrug are tumor tropic, penetrate tumor cells, and kill them by intracellular conversion of nontoxic prodrug to an efficient anti-cancer drug. Here, we discuss findings regarding the possibility of using suicide gene EVs as a novel therapeutic approach for metastases, via pre-metastatic niche modification. The suicide gene EVs provide a future perspective for metastasis prevention.

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Section: Participation Of Modified Evs In Metastasis Preventionmentioning

confidence: 99%

Participation of suicide gene extracellular vesicles in metastasis prevention

Vanova,

Andrezal,

Jakubechova

et al. 2024

neo

View full text Add to dashboard Cite

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Extended survival in a case of metastatic choroidal melanoma with immunotherapy

Mirzayev,

Gündüz,

Mirzayeva

et al. 2024

Anti-Cancer Drugs

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Uveal melanoma is the most common intraocular malignancy in adults. Despite advances in local treatments, approximately 50% of all cases eventually die from metastatic disease. In cases with metastasis, 2- and 5-year survival rates are approximately 10% and <1%, respectively. Advances in molecular biology have led to the identification of a number of promising drugs including immune checkpoint inhibitors (ICIs). Ipilimumab and nivolumab are ICIs targeting the cytotoxic T-lymphocyte-associated antigen-4 and the programmed-cell death protein-1, respectively. Herein, we present a case of choroidal melanoma having liver metastasis treated with nivolumab and ipilimumab and transarterial radioembolization, achieving a 3-year survival.

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Using Deep Learning to Distinguish Highly Malignant Uveal Melanoma from Benign Choroidal Nevi

Hoffmann,

Runkel,

Künzel

et al. 2024

JCM

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Background: This study aimed to evaluate the potential of human–machine interaction (HMI) in a deep learning software for discerning the malignancy of choroidal melanocytic lesions based on fundus photographs. Methods: The study enrolled individuals diagnosed with a choroidal melanocytic lesion at a tertiary clinic between 2011 and 2023, resulting in a cohort of 762 eligible cases. A deep learning-based assistant integrated into the software underwent training using a dataset comprising 762 color fundus photographs (CFPs) of choroidal lesions captured by various fundus cameras. The dataset was categorized into benign nevi, untreated choroidal melanomas, and irradiated choroidal melanomas. The reference standard for evaluation was established by retinal specialists using multimodal imaging. Trinary and binary models were trained, and their classification performance was evaluated on a test set consisting of 100 independent images. The discriminative performance of deep learning models was evaluated based on accuracy, recall, and specificity. Results: The final accuracy rates on the independent test set for multi-class and binary (benign vs. malignant) classification were 84.8% and 90.9%, respectively. Recall and specificity ranged from 0.85 to 0.90 and 0.91 to 0.92, respectively. The mean area under the curve (AUC) values were 0.96 and 0.99, respectively. Optimal discriminative performance was observed in binary classification with the incorporation of a single imaging modality, achieving an accuracy of 95.8%. Conclusions: The deep learning models demonstrated commendable performance in distinguishing the malignancy of choroidal lesions. The software exhibits promise for resource-efficient and cost-effective pre-stratification.

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Uveal melanoma: Recent advances in immunotherapy

Cited by 3 publications

References 63 publications

Participation of suicide gene extracellular vesicles in metastasis prevention

Participation of suicide gene extracellular vesicles in metastasis prevention

Extended survival in a case of metastatic choroidal melanoma with immunotherapy

Using Deep Learning to Distinguish Highly Malignant Uveal Melanoma from Benign Choroidal Nevi

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