Eva Erne, Nicole Anderle, Christian Schmees, Arnulf Stenzl
{"title":"[患者来源的微肿瘤:治疗反应预测的潜力-一个案例研究]。","authors":"Eva Erne, Nicole Anderle, Christian Schmees, Arnulf Stenzl","doi":"10.1007/s00120-022-01851-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>In view of continued development of new oncological approaches, there is a high demand for personalized tumor therapy. However, fast and effective functional platforms for the prediction of individual patient response to drug therapy are largely unavailable. Various promising approaches have already been described for three-dimensional cell culture models, which represent cellular complexity and almost identical structures of the original tumor tissue.</p><p><strong>Objectives: </strong>Based on a case report, we show the capability and results of a novel test system using patient-derived microtumors (PDMs) and autologous tumor-infiltrating lymphocytes (TILs) for the prediction of response to cancer therapy.</p><p><strong>Methods: </strong>We established PDMs and TILs from primary tumor tissue of a renal cell carcinoma metastasis. Using immunohistochemistry and multiplex florescence-activated cell sorting (FACS ) analyses, the PDMs and TILs were characterized regarding to histology and immunophenotype. Tumor-specific cytotoxicity of standard of care and investigational compounds were assessed. The results were compared to the patient's individual in vivo response to therapy.</p><p><strong>Conclusion: </strong>The cytotoxicity assay of PDMs and TILs showed a significant therapeutic response (p = 0.0004) to therapy with a programmed cell death protein 1 (PD-1) inhibitor and lenvatinib compared to the control. The in vitro results correlated positively with the in vivo data. In the future, patient-derived models could predict response to cancer therapy and may help to optimize treatment decision-making.</p>","PeriodicalId":319655,"journal":{"name":"Urologie (Heidelberg, Germany)","volume":" ","pages":"739-744"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Patient-derived microtumors : Potential for therapeutic response prediction-a case study].\",\"authors\":\"Eva Erne, Nicole Anderle, Christian Schmees, Arnulf Stenzl\",\"doi\":\"10.1007/s00120-022-01851-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>In view of continued development of new oncological approaches, there is a high demand for personalized tumor therapy. However, fast and effective functional platforms for the prediction of individual patient response to drug therapy are largely unavailable. Various promising approaches have already been described for three-dimensional cell culture models, which represent cellular complexity and almost identical structures of the original tumor tissue.</p><p><strong>Objectives: </strong>Based on a case report, we show the capability and results of a novel test system using patient-derived microtumors (PDMs) and autologous tumor-infiltrating lymphocytes (TILs) for the prediction of response to cancer therapy.</p><p><strong>Methods: </strong>We established PDMs and TILs from primary tumor tissue of a renal cell carcinoma metastasis. Using immunohistochemistry and multiplex florescence-activated cell sorting (FACS ) analyses, the PDMs and TILs were characterized regarding to histology and immunophenotype. Tumor-specific cytotoxicity of standard of care and investigational compounds were assessed. The results were compared to the patient's individual in vivo response to therapy.</p><p><strong>Conclusion: </strong>The cytotoxicity assay of PDMs and TILs showed a significant therapeutic response (p = 0.0004) to therapy with a programmed cell death protein 1 (PD-1) inhibitor and lenvatinib compared to the control. The in vitro results correlated positively with the in vivo data. In the future, patient-derived models could predict response to cancer therapy and may help to optimize treatment decision-making.</p>\",\"PeriodicalId\":319655,\"journal\":{\"name\":\"Urologie (Heidelberg, Germany)\",\"volume\":\" \",\"pages\":\"739-744\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Urologie (Heidelberg, Germany)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s00120-022-01851-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/6/8 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Urologie (Heidelberg, Germany)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s00120-022-01851-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/6/8 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
[Patient-derived microtumors : Potential for therapeutic response prediction-a case study].
Background: In view of continued development of new oncological approaches, there is a high demand for personalized tumor therapy. However, fast and effective functional platforms for the prediction of individual patient response to drug therapy are largely unavailable. Various promising approaches have already been described for three-dimensional cell culture models, which represent cellular complexity and almost identical structures of the original tumor tissue.
Objectives: Based on a case report, we show the capability and results of a novel test system using patient-derived microtumors (PDMs) and autologous tumor-infiltrating lymphocytes (TILs) for the prediction of response to cancer therapy.
Methods: We established PDMs and TILs from primary tumor tissue of a renal cell carcinoma metastasis. Using immunohistochemistry and multiplex florescence-activated cell sorting (FACS ) analyses, the PDMs and TILs were characterized regarding to histology and immunophenotype. Tumor-specific cytotoxicity of standard of care and investigational compounds were assessed. The results were compared to the patient's individual in vivo response to therapy.
Conclusion: The cytotoxicity assay of PDMs and TILs showed a significant therapeutic response (p = 0.0004) to therapy with a programmed cell death protein 1 (PD-1) inhibitor and lenvatinib compared to the control. The in vitro results correlated positively with the in vivo data. In the future, patient-derived models could predict response to cancer therapy and may help to optimize treatment decision-making.