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Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes

Assessing the phenotypic diversity underlying tumour progression requires the identification of variations in the respective molecular interaction networks. Here we report proof-of-concept for a platform called poly-ligand profiling (PLP) that surveys these system states and distinguishes breast can...

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Autores principales: Domenyuk, Valeriy, Gatalica, Zoran, Santhanam, Radhika, Wei, Xixi, Stark, Adam, Kennedy, Patrick, Toussaint, Brandon, Levenberg, Symon, Wang, Jie, Xiao, Nianqing, Greil, Richard, Rinnerthaler, Gabriel, Gampenrieder, Simon P., Heimberger, Amy B., Berry, Donald A., Barker, Anna, Quackenbush, John, Marshall, John L., Poste, George, Vacirca, Jeffrey L., Vidal, Gregory A., Schwartzberg, Lee S., Halbert, David D., Voss, Andreas, Magee, Daniel, Miglarese, Mark R., Famulok, Michael, Mayer, Günter, Spetzler, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5865185/
https://www.ncbi.nlm.nih.gov/pubmed/29572535
http://dx.doi.org/10.1038/s41467-018-03631-z
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author Domenyuk, Valeriy
Gatalica, Zoran
Santhanam, Radhika
Wei, Xixi
Stark, Adam
Kennedy, Patrick
Toussaint, Brandon
Levenberg, Symon
Wang, Jie
Xiao, Nianqing
Greil, Richard
Rinnerthaler, Gabriel
Gampenrieder, Simon P.
Heimberger, Amy B.
Berry, Donald A.
Barker, Anna
Quackenbush, John
Marshall, John L.
Poste, George
Vacirca, Jeffrey L.
Vidal, Gregory A.
Schwartzberg, Lee S.
Halbert, David D.
Voss, Andreas
Magee, Daniel
Miglarese, Mark R.
Famulok, Michael
Mayer, Günter
Spetzler, David
author_facet Domenyuk, Valeriy
Gatalica, Zoran
Santhanam, Radhika
Wei, Xixi
Stark, Adam
Kennedy, Patrick
Toussaint, Brandon
Levenberg, Symon
Wang, Jie
Xiao, Nianqing
Greil, Richard
Rinnerthaler, Gabriel
Gampenrieder, Simon P.
Heimberger, Amy B.
Berry, Donald A.
Barker, Anna
Quackenbush, John
Marshall, John L.
Poste, George
Vacirca, Jeffrey L.
Vidal, Gregory A.
Schwartzberg, Lee S.
Halbert, David D.
Voss, Andreas
Magee, Daniel
Miglarese, Mark R.
Famulok, Michael
Mayer, Günter
Spetzler, David
author_sort Domenyuk, Valeriy
collection PubMed
description Assessing the phenotypic diversity underlying tumour progression requires the identification of variations in the respective molecular interaction networks. Here we report proof-of-concept for a platform called poly-ligand profiling (PLP) that surveys these system states and distinguishes breast cancer patients who did or did not derive benefit from trastuzumab. We perform tissue-SELEX on breast cancer specimens to enrich single-stranded DNA (ssDNA) libraries that preferentially interact with molecular components associated with the two clinical phenotypes. Testing of independent sample sets verifies the ability of PLP to classify trastuzumab-treated patients according to their clinical outcomes with ROC-AUC of 0.78. Standard HER2 testing of the same patients gives a ROC-AUC of 0.47. Kaplan–Meier analysis reveals a median increase in benefit from trastuzumab-containing treatments of 300 days for PLP-positive compared to PLP-negative patients. If prospectively validated, PLP may increase success rates in precision oncology and clinical trials, thus improving both patient care and drug development.
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spelling pubmed-58651852018-03-28 Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes Domenyuk, Valeriy Gatalica, Zoran Santhanam, Radhika Wei, Xixi Stark, Adam Kennedy, Patrick Toussaint, Brandon Levenberg, Symon Wang, Jie Xiao, Nianqing Greil, Richard Rinnerthaler, Gabriel Gampenrieder, Simon P. Heimberger, Amy B. Berry, Donald A. Barker, Anna Quackenbush, John Marshall, John L. Poste, George Vacirca, Jeffrey L. Vidal, Gregory A. Schwartzberg, Lee S. Halbert, David D. Voss, Andreas Magee, Daniel Miglarese, Mark R. Famulok, Michael Mayer, Günter Spetzler, David Nat Commun Article Assessing the phenotypic diversity underlying tumour progression requires the identification of variations in the respective molecular interaction networks. Here we report proof-of-concept for a platform called poly-ligand profiling (PLP) that surveys these system states and distinguishes breast cancer patients who did or did not derive benefit from trastuzumab. We perform tissue-SELEX on breast cancer specimens to enrich single-stranded DNA (ssDNA) libraries that preferentially interact with molecular components associated with the two clinical phenotypes. Testing of independent sample sets verifies the ability of PLP to classify trastuzumab-treated patients according to their clinical outcomes with ROC-AUC of 0.78. Standard HER2 testing of the same patients gives a ROC-AUC of 0.47. Kaplan–Meier analysis reveals a median increase in benefit from trastuzumab-containing treatments of 300 days for PLP-positive compared to PLP-negative patients. If prospectively validated, PLP may increase success rates in precision oncology and clinical trials, thus improving both patient care and drug development. Nature Publishing Group UK 2018-03-23 /pmc/articles/PMC5865185/ /pubmed/29572535 http://dx.doi.org/10.1038/s41467-018-03631-z Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Domenyuk, Valeriy
Gatalica, Zoran
Santhanam, Radhika
Wei, Xixi
Stark, Adam
Kennedy, Patrick
Toussaint, Brandon
Levenberg, Symon
Wang, Jie
Xiao, Nianqing
Greil, Richard
Rinnerthaler, Gabriel
Gampenrieder, Simon P.
Heimberger, Amy B.
Berry, Donald A.
Barker, Anna
Quackenbush, John
Marshall, John L.
Poste, George
Vacirca, Jeffrey L.
Vidal, Gregory A.
Schwartzberg, Lee S.
Halbert, David D.
Voss, Andreas
Magee, Daniel
Miglarese, Mark R.
Famulok, Michael
Mayer, Günter
Spetzler, David
Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes
title Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes
title_full Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes
title_fullStr Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes
title_full_unstemmed Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes
title_short Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes
title_sort poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5865185/
https://www.ncbi.nlm.nih.gov/pubmed/29572535
http://dx.doi.org/10.1038/s41467-018-03631-z
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