Academic Journal

Patient-Derived Tumoroid for the Prediction of Radiotherapy and Chemotherapy Responses in Non-Small-Cell Lung Cancer

التفاصيل البيبلوغرافية
العنوان: Patient-Derived Tumoroid for the Prediction of Radiotherapy and Chemotherapy Responses in Non-Small-Cell Lung Cancer
المؤلفون: Anasse Nounsi, Joseph Seitlinger, Charlotte Ponté, Julien Demiselle, Ysia Idoux-Gillet, Erwan Pencreach, Michèle Beau-Faller, Véronique Lindner, Jean-Marc Balloul, Eric Quemeneur, Hélène Burckel, Georges Noël, Anne Olland, Florence Fioretti, Pierre-Emmanuel Falcoz, Nadia Benkirane-Jessel, Guoqiang Hua
المصدر: Biomedicines; Volume 11; Issue 7; Pages: 1824
بيانات النشر: Multidisciplinary Digital Publishing Institute
سنة النشر: 2023
المجموعة: MDPI Open Access Publishing
مصطلحات موضوعية: patient-derived tumoroid, radiation therapy, chemotherapy, personalized medicine, non-small-cell lung cancer
الوصف: Radiation therapy and platinum-based chemotherapy are common treatments for lung cancer patients. Several factors are considered for the low overall survival rate of lung cancer, such as the patient’s physical state and the complex heterogeneity of the tumor, which leads to resistance to the treatment. Consequently, precision medicines are needed for the patients to improve their survival and their quality of life. Until now, no patient-derived tumoroid model has been reported to predict the efficiency of radiation therapy in non-small-cell lung cancer. Using our patient-derived tumoroid model, we report that this model could be used to evaluate the efficiency of radiation therapy and cisplatin-based chemotherapy in non-small-cell lung cancer. In addition, these results can be correlated to clinical outcomes of patients, indicating that this patient-derived tumoroid model can predict the response to radiotherapy and chemotherapy in non-small-cell lung cancer.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
Relation: Cancer Biology and Therapeutics; https://dx.doi.org/10.3390/biomedicines11071824
DOI: 10.3390/biomedicines11071824
الاتاحة: https://doi.org/10.3390/biomedicines11071824
Rights: https://creativecommons.org/licenses/by/4.0/
رقم الانضمام: edsbas.B6239C2B
قاعدة البيانات: BASE
الوصف
DOI:10.3390/biomedicines11071824