Cargando…
Time 2EVOLVE: predicting efficacy of engineered T-cells – how far is the bench from the bedside?
Immunotherapy with gene engineered CAR and TCR transgenic T-cells is a transformative treatment in cancer medicine. There is a rich pipeline with target antigens and sophisticated technologies that will enable establishing this novel treatment not only in rare hematological malignancies, but also in...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9115015/ https://www.ncbi.nlm.nih.gov/pubmed/35577501 http://dx.doi.org/10.1136/jitc-2021-003487 |
_version_ | 1784709891862036480 |
---|---|
author | Guedan, Sonia Luu, Maik Ammar, Delphine Barbao, Paula Bonini, Chiara Bousso, Philippe Buchholz, Christian J Casucci, Monica De Angelis, Biagio Donnadieu, Emmanuel Espie, David Greco, Beatrice Groen, Richard Huppa, Johannes B Kantari-Mimoun, Chahrazade Laugel, Bruno Mantock, Mary Markman, Janet L Morris, Emma Quintarelli, Concetta Rade, Michael Reiche, Kristin Rodriguez-Garcia, Alba Rodriguez-Madoz, Juan Roberto Ruggiero, Eliana Themeli, Maria Hudecek, Michael Marchiq, Ibtissam |
author_facet | Guedan, Sonia Luu, Maik Ammar, Delphine Barbao, Paula Bonini, Chiara Bousso, Philippe Buchholz, Christian J Casucci, Monica De Angelis, Biagio Donnadieu, Emmanuel Espie, David Greco, Beatrice Groen, Richard Huppa, Johannes B Kantari-Mimoun, Chahrazade Laugel, Bruno Mantock, Mary Markman, Janet L Morris, Emma Quintarelli, Concetta Rade, Michael Reiche, Kristin Rodriguez-Garcia, Alba Rodriguez-Madoz, Juan Roberto Ruggiero, Eliana Themeli, Maria Hudecek, Michael Marchiq, Ibtissam |
author_sort | Guedan, Sonia |
collection | PubMed |
description | Immunotherapy with gene engineered CAR and TCR transgenic T-cells is a transformative treatment in cancer medicine. There is a rich pipeline with target antigens and sophisticated technologies that will enable establishing this novel treatment not only in rare hematological malignancies, but also in common solid tumors. The T2EVOLVE consortium is a public private partnership directed at accelerating the preclinical development of and increasing access to engineered T-cell immunotherapies for cancer patients. A key ambition in T2EVOLVE is to assess the currently available preclinical models for evaluating safety and efficacy of engineered T cell therapy and developing new models and test parameters with higher predictive value for clinical safety and efficacy in order to improve and accelerate the selection of lead T-cell products for clinical translation. Here, we review existing and emerging preclinical models that permit assessing CAR and TCR signaling and antigen binding, the access and function of engineered T-cells to primary and metastatic tumor ligands, as well as the impact of endogenous factors such as the host immune system and microbiome. Collectively, this review article presents a perspective on an accelerated translational development path that is based on innovative standardized preclinical test systems for CAR and TCR transgenic T-cell products. |
format | Online Article Text |
id | pubmed-9115015 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-91150152022-06-04 Time 2EVOLVE: predicting efficacy of engineered T-cells – how far is the bench from the bedside? Guedan, Sonia Luu, Maik Ammar, Delphine Barbao, Paula Bonini, Chiara Bousso, Philippe Buchholz, Christian J Casucci, Monica De Angelis, Biagio Donnadieu, Emmanuel Espie, David Greco, Beatrice Groen, Richard Huppa, Johannes B Kantari-Mimoun, Chahrazade Laugel, Bruno Mantock, Mary Markman, Janet L Morris, Emma Quintarelli, Concetta Rade, Michael Reiche, Kristin Rodriguez-Garcia, Alba Rodriguez-Madoz, Juan Roberto Ruggiero, Eliana Themeli, Maria Hudecek, Michael Marchiq, Ibtissam J Immunother Cancer Review Immunotherapy with gene engineered CAR and TCR transgenic T-cells is a transformative treatment in cancer medicine. There is a rich pipeline with target antigens and sophisticated technologies that will enable establishing this novel treatment not only in rare hematological malignancies, but also in common solid tumors. The T2EVOLVE consortium is a public private partnership directed at accelerating the preclinical development of and increasing access to engineered T-cell immunotherapies for cancer patients. A key ambition in T2EVOLVE is to assess the currently available preclinical models for evaluating safety and efficacy of engineered T cell therapy and developing new models and test parameters with higher predictive value for clinical safety and efficacy in order to improve and accelerate the selection of lead T-cell products for clinical translation. Here, we review existing and emerging preclinical models that permit assessing CAR and TCR signaling and antigen binding, the access and function of engineered T-cells to primary and metastatic tumor ligands, as well as the impact of endogenous factors such as the host immune system and microbiome. Collectively, this review article presents a perspective on an accelerated translational development path that is based on innovative standardized preclinical test systems for CAR and TCR transgenic T-cell products. BMJ Publishing Group 2022-05-16 /pmc/articles/PMC9115015/ /pubmed/35577501 http://dx.doi.org/10.1136/jitc-2021-003487 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Review Guedan, Sonia Luu, Maik Ammar, Delphine Barbao, Paula Bonini, Chiara Bousso, Philippe Buchholz, Christian J Casucci, Monica De Angelis, Biagio Donnadieu, Emmanuel Espie, David Greco, Beatrice Groen, Richard Huppa, Johannes B Kantari-Mimoun, Chahrazade Laugel, Bruno Mantock, Mary Markman, Janet L Morris, Emma Quintarelli, Concetta Rade, Michael Reiche, Kristin Rodriguez-Garcia, Alba Rodriguez-Madoz, Juan Roberto Ruggiero, Eliana Themeli, Maria Hudecek, Michael Marchiq, Ibtissam Time 2EVOLVE: predicting efficacy of engineered T-cells – how far is the bench from the bedside? |
title | Time 2EVOLVE: predicting efficacy of engineered T-cells – how far is the bench from the bedside? |
title_full | Time 2EVOLVE: predicting efficacy of engineered T-cells – how far is the bench from the bedside? |
title_fullStr | Time 2EVOLVE: predicting efficacy of engineered T-cells – how far is the bench from the bedside? |
title_full_unstemmed | Time 2EVOLVE: predicting efficacy of engineered T-cells – how far is the bench from the bedside? |
title_short | Time 2EVOLVE: predicting efficacy of engineered T-cells – how far is the bench from the bedside? |
title_sort | time 2evolve: predicting efficacy of engineered t-cells – how far is the bench from the bedside? |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9115015/ https://www.ncbi.nlm.nih.gov/pubmed/35577501 http://dx.doi.org/10.1136/jitc-2021-003487 |
work_keys_str_mv | AT guedansonia time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT luumaik time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT ammardelphine time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT barbaopaula time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT boninichiara time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT boussophilippe time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT buchholzchristianj time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT casuccimonica time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT deangelisbiagio time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT donnadieuemmanuel time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT espiedavid time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT grecobeatrice time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT groenrichard time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT huppajohannesb time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT kantarimimounchahrazade time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT laugelbruno time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT mantockmary time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT markmanjanetl time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT morrisemma time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT quintarelliconcetta time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT rademichael time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT reichekristin time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT rodriguezgarciaalba time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT rodriguezmadozjuanroberto time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT ruggieroeliana time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT themelimaria time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT hudecekmichael time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside AT marchiqibtissam time2evolvepredictingefficacyofengineeredtcellshowfaristhebenchfromthebedside |