Genomic and experimental evidence that ALKATI does not predict single agent sensitivity to ALK inhibitors

Summary: Genomic data can facilitate personalized treatment decisions by enabling therapeutic hypotheses in individual patients. Mutual exclusivity has been an empirically useful signal for identifying activating mutations that respond to single agent targeted therapies. However, a low mutation freq...

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Autores principales:	Haider Inam, Ivan Sokirniy, Yiyun Rao, Anushka Shah, Farnaz Naeemikia, Edward O'Brien, Cheng Dong, David M. McCandlish, Justin R. Pritchard
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Biological sciences Systems biology Cancer systems biology Science Q
Acceso en línea:	https://doaj.org/article/f98a7049c703493fbae9b06d38862432
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spelling	oai:doaj.org-article:f98a7049c703493fbae9b06d388624322021-11-20T05:10:13ZGenomic and experimental evidence that ALKATI does not predict single agent sensitivity to ALK inhibitors2589-004210.1016/j.isci.2021.103343https://doaj.org/article/f98a7049c703493fbae9b06d388624322021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2589004221013122https://doaj.org/toc/2589-0042Summary: Genomic data can facilitate personalized treatment decisions by enabling therapeutic hypotheses in individual patients. Mutual exclusivity has been an empirically useful signal for identifying activating mutations that respond to single agent targeted therapies. However, a low mutation frequency can underpower this signal for rare variants. We develop a resampling based method for the direct pairwise comparison of conditional selection between sets of gene pairs. We apply this method to a transcript variant of anaplastic lymphoma kinase (ALK) in melanoma, termed ALKATI that was suggested to predict sensitivity to ALK inhibitors and we find that it is not mutually exclusive with key melanoma oncogenes. Furthermore, we find that ALKATI is not likely to be sufficient for cellular transformation or growth, and it does not predict single agent therapeutic dependency. Our work strongly disfavors the role of ALKATI as a targetable oncogenic driver that might be sensitive to single agent ALK treatment.Haider InamIvan SokirniyYiyun RaoAnushka ShahFarnaz NaeemikiaEdward O'BrienCheng DongDavid M. McCandlishJustin R. PritchardElsevierarticleBiological sciencesSystems biologyCancer systems biologyScienceQENiScience, Vol 24, Iss 11, Pp 103343- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biological sciences Systems biology Cancer systems biology Science Q
spellingShingle	Biological sciences Systems biology Cancer systems biology Science Q Haider Inam Ivan Sokirniy Yiyun Rao Anushka Shah Farnaz Naeemikia Edward O'Brien Cheng Dong David M. McCandlish Justin R. Pritchard Genomic and experimental evidence that ALKATI does not predict single agent sensitivity to ALK inhibitors
description	Summary: Genomic data can facilitate personalized treatment decisions by enabling therapeutic hypotheses in individual patients. Mutual exclusivity has been an empirically useful signal for identifying activating mutations that respond to single agent targeted therapies. However, a low mutation frequency can underpower this signal for rare variants. We develop a resampling based method for the direct pairwise comparison of conditional selection between sets of gene pairs. We apply this method to a transcript variant of anaplastic lymphoma kinase (ALK) in melanoma, termed ALKATI that was suggested to predict sensitivity to ALK inhibitors and we find that it is not mutually exclusive with key melanoma oncogenes. Furthermore, we find that ALKATI is not likely to be sufficient for cellular transformation or growth, and it does not predict single agent therapeutic dependency. Our work strongly disfavors the role of ALKATI as a targetable oncogenic driver that might be sensitive to single agent ALK treatment.
format	article
author	Haider Inam Ivan Sokirniy Yiyun Rao Anushka Shah Farnaz Naeemikia Edward O'Brien Cheng Dong David M. McCandlish Justin R. Pritchard
author_facet	Haider Inam Ivan Sokirniy Yiyun Rao Anushka Shah Farnaz Naeemikia Edward O'Brien Cheng Dong David M. McCandlish Justin R. Pritchard
author_sort	Haider Inam
title	Genomic and experimental evidence that ALKATI does not predict single agent sensitivity to ALK inhibitors
title_short	Genomic and experimental evidence that ALKATI does not predict single agent sensitivity to ALK inhibitors
title_full	Genomic and experimental evidence that ALKATI does not predict single agent sensitivity to ALK inhibitors
title_fullStr	Genomic and experimental evidence that ALKATI does not predict single agent sensitivity to ALK inhibitors
title_full_unstemmed	Genomic and experimental evidence that ALKATI does not predict single agent sensitivity to ALK inhibitors
title_sort	genomic and experimental evidence that alkati does not predict single agent sensitivity to alk inhibitors
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/f98a7049c703493fbae9b06d38862432
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Genomic and experimental evidence that ALKATI does not predict single agent sensitivity to ALK inhibitors

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