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4.2 Terapias avanzadas en el cáncer: papel de la inmunoterapia adoptiva en neoplasias hematológicas y sólidas
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Cursos
2025
Módulo 4
4.2 Terapias avanzadas
MÓDULO 4
Xu Z, et al. Applying artificial intelligence for cancer immunotherapy. Acta Pharm Sin B. 2021 Nov;11(11):3393-3405. doi: 10.1016/j.apsb.2021.02.007.
Salta al contenido principal
Xu Z, et al. Applying artificial intelligence for cancer immunotherapy. Acta Pharm Sin B. 2021 Nov;11(11):3393-3405. doi: 10.1016/j.apsb.2021.02.007.
Haga clic en el enlace
https://pubmed.ncbi.nlm.nih.gov/34900525/
para abrir el recurso.
◄ Xie J, Luo X,et al. Advances in artificial intelligence to predict cancer immunotherapy efficacy. Front Immunol. 2023 Jan 4;13:1076883. doi: 10.3389/fimmu.2022.1076883.
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Avisos
Cuestionario de expectativas
Avisos
Non–Small Cell Lung Cancer Metastatic Without Oncogenic Alterations
Perioperative Pembrolizumab for Early-Stage Non–Small-Cell Lung Cancer
Non-oncogene-addicted metastatic non-small-cell lung cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up
Multidisciplinary approach for locally advanced non‐small cell lung cancer (NSCLC): 2023 expert consensus of the Spanish Lung Cancer Group GECP
New Treatment Options for Patients With Oncogene-Addicted Non–Small Cell Lung Cancer Focusing on EGFR-Mutant Tumors
Retos en la inmunoterapia del hepatocarcinoma
Immunotherapies for hepatocellular carcinoma and intrahepatic cholangiocarcinoma: Current and developing strategies.
Artificial intelligence-based pathology as a biomarker of sensitivity to atezolizumab–bevacizumab in patients with hepatocellular carcinoma: a multicentre retrospective study.
Biomarkers for immunotherapy of hepatocellular carcinoma.
Atezolizumab plus bevacizumab versus active surveillance in patients with resected or ablated high-risk hepatocellular carcinoma (IMbrave050): a randomised, open-label, multicentre, phase 3 trial.
BCLC strategy for prognosis prediction and treatment recommendation: The 2022 update.
Jacob SL, Huppert LA, Rugo HS. Role of Immunotherapy in Breast Cancer. JCO Oncol Pract. 2023 Apr;19(4):167-179. doi: 10.1200/OP.22.00483.
Santa-Maria, C. A. Optimizing and Refining Immunotherapy in Breast Cancer. JCO Oncol. Pr. 19, 190–191 (2023).
Debien, V., Caluwé, A. D., Wang, X., Piccart-Gebhart, M., Tuohy, V. K., Romano, E. & Buisseret, L. Immunotherapy in breast cancer: an overview of current strategies and perspectives. npj Breast Cancer 9, 7 (2023).
Rius Ruiz I, et al. p95HER2-T cell bispecific antibody for breast cancer treatment. Sci Transl Med. 2018 Oct 3;10(461):eaat1445. doi: 10.1126/scitranslmed.aat1445.
Slabik C, et al. CAR-T Cells Targeting Epstein-Barr Virus gp350 Validated in a Humanized Mouse Model of EBV Infection and Lymphoproliferative Disease. Mol Ther Oncolytics. 2020 Aug 8;18:504-524. doi: 10.1016/j.omto.2020.08.005.
Vanguri RS, el al. Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer. Nat Cancer. 2022 Oct;3(10):1151-1164. doi: 10.1038/s43018-022-00416-8
Ghaffari Laleh N, et al. Facts and Hopes on the Use of Artificial Intelligence for Predictive Immunotherapy Biomarkers in Cancer. Clin Cancer Res. 2023 Jan 17;29(2):316-323. doi: 10.1158/1078-0432.CCR-22-0390.
Xie J, Luo X,et al. Advances in artificial intelligence to predict cancer immunotherapy efficacy. Front Immunol. 2023 Jan 4;13:1076883. doi: 10.3389/fimmu.2022.1076883.
Examen Final
Encuesta de satisfacción del curso
Encuesta de evaluación a los docentes
Ponencia. [Video 35:43 minutos]
Debate. [Video 30:54 minutos]
Examen Final ►
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