TY - JOUR
T1 - Genomic and experimental evidence that ALKATI does not predict single agent sensitivity to ALK inhibitors
AU - Inam, Haider
AU - Sokirniy, Ivan
AU - Rao, Yiyun
AU - Shah, Anushka
AU - Naeemikia, Farnaz
AU - O'Brien, Edward
AU - Dong, Cheng
AU - McCandlish, David M.
AU - Pritchard, Justin R.
N1 - Funding Information:
This publication was supported, in part, by NIH Grants 5R21EB026617 , T32GM108563 , 1U01CA265709 , R35GM133613 , and R35GM124818 , and by an Alfred P. Sloan Research Fellowship and additional support from the Simons Center for Quantitative Biology . We would like to thank Scott Leighow for his contribution with idea generation, critical analysis, and proofreading of this manuscript. We would also like to thank Kelly Hartsough, Lauren Randolph, Kyle Mcllroy, and Joshua Reynolds for their help revising previous versions of this manuscript.
Publisher Copyright:
© 2021
PY - 2021/11/19
Y1 - 2021/11/19
N2 - 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.
AB - 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.
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U2 - 10.1016/j.isci.2021.103343
DO - 10.1016/j.isci.2021.103343
M3 - Article
C2 - 34825133
AN - SCOPUS:85118889248
SN - 2589-0042
VL - 24
JO - iScience
JF - iScience
IS - 11
M1 - 103343
ER -