A functional genomic approach to actionable gene fusions for precision oncology

Jun Li; Hengyu Lu; Patrick Kwok Shing Ng; Angeliki Pantazi; Carman Ka Man Ip; Kang Jin Jeong; Bianca Amador; Richard Tran; Yiu Huen Tsang; Lixing Yang; Xingzhi Song; Turgut Dogruluk; Xiaojia Ren; Angela Hadjipanayis; Christopher A. Bristow; Semin Lee; Melanie Kucherlapati; Michael Parfenov; Jiabin Tang; Sahil Seth; Harshad S. Mahadeshwar; Kamalika Mojumdar; Dong Zeng; Jianhua Zhang; Alexei Protopopov; Jonathan G. Seidman; Chad J. Creighton; Yiling Lu; Nidhi Sahni; Kenna R. Shaw; Funda Meric-Bernstam; Andrew Futreal; Lynda Chin; Kenneth L. Scott; Raju Kucherlapati; Gordon B Mills; Han Liang

doi:10.1126/sciadv.abm2382

A functional genomic approach to actionable gene fusions for precision oncology

Jun Li, Hengyu Lu, Patrick Kwok Shing Ng, Angeliki Pantazi, Carman Ka Man Ip, Kang Jin Jeong, Bianca Amador, Richard Tran, Yiu Huen Tsang, Lixing Yang, Xingzhi Song, Turgut Dogruluk, Xiaojia Ren, Angela Hadjipanayis, Christopher A. Bristow, Semin Lee, Melanie Kucherlapati, Michael Parfenov, Jiabin Tang, Sahil SethHarshad S. Mahadeshwar, Kamalika Mojumdar, Dong Zeng, Jianhua Zhang, Alexei Protopopov, Jonathan G. Seidman, Chad J. Creighton, Yiling Lu, Nidhi Sahni, Kenna R. Shaw, Funda Meric-Bernstam, Andrew Futreal, Lynda Chin, Kenneth L. Scott, Raju Kucherlapati, Gordon B Mills, Han Liang

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Abstract

Fusion genes represent a class of attractive therapeutic targets. Thousands of fusion genes have been identified in patients with cancer, but the functional consequences and therapeutic implications of most of these remain largely unknown. Here, we develop a functional genomic approach that consists of efficient fusion reconstruction and sensitive cell viability and drug response assays. Applying this approach, we characterize ∼100 fusion genes detected in patient samples of The Cancer Genome Atlas, revealing a notable fraction of low-frequency fusions with activating effects on tumor growth. Focusing on those in the RTK-RAS pathway, we identify a number of activating fusions that can markedly affect sensitivity to relevant drugs. Last, we propose an integrated, level-of-evidence classification system to prioritize gene fusions systematically. Our study reiterates the urgent clinical need to incorporate similar functional genomic approaches to characterize gene fusions, thereby maximizing the utility of gene fusions for precision oncology.

Original language	English (US)
Article number	abm2382
Journal	Science Advances
Volume	8
Issue number	6
DOIs	https://doi.org/10.1126/sciadv.abm2382
State	Published - Feb 2022

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Advanced Technology Genomics Core
Cytogenetics and Cell Authentication Core
Functional Proteomics Reverse Phase Protein Array Core
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Li, J., Lu, H., Ng, P. K. S., Pantazi, A., Ip, C. K. M., Jeong, K. J., Amador, B., Tran, R., Tsang, Y. H., Yang, L., Song, X., Dogruluk, T., Ren, X., Hadjipanayis, A., Bristow, C. A., Lee, S., Kucherlapati, M., Parfenov, M., Tang, J., ... Liang, H. (2022). A functional genomic approach to actionable gene fusions for precision oncology. Science Advances, 8(6), Article abm2382. https://doi.org/10.1126/sciadv.abm2382

Li, J , Lu, H, Ng, PKS, Pantazi, A, Ip, CKM, Jeong, KJ, Amador, B, Tran, R, Tsang, YH, Yang, L, Song, X, Dogruluk, T, Ren, X, Hadjipanayis, A, Bristow, CA, Lee, S, Kucherlapati, M, Parfenov, M, Tang, J, Seth, S, Mahadeshwar, HS, Mojumdar, K, Zeng, D, Zhang, J, Protopopov, A, Seidman, JG, Creighton, CJ, Lu, Y , Sahni, N, Shaw, KR, Meric-Bernstam, F , Futreal, A, Chin, L, Scott, KL, Kucherlapati, R, Mills, GB & Liang, H 2022, 'A functional genomic approach to actionable gene fusions for precision oncology', Science Advances, vol. 8, no. 6, abm2382. https://doi.org/10.1126/sciadv.abm2382

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title = "A functional genomic approach to actionable gene fusions for precision oncology",

abstract = "Fusion genes represent a class of attractive therapeutic targets. Thousands of fusion genes have been identified in patients with cancer, but the functional consequences and therapeutic implications of most of these remain largely unknown. Here, we develop a functional genomic approach that consists of efficient fusion reconstruction and sensitive cell viability and drug response assays. Applying this approach, we characterize ∼100 fusion genes detected in patient samples of The Cancer Genome Atlas, revealing a notable fraction of low-frequency fusions with activating effects on tumor growth. Focusing on those in the RTK-RAS pathway, we identify a number of activating fusions that can markedly affect sensitivity to relevant drugs. Last, we propose an integrated, level-of-evidence classification system to prioritize gene fusions systematically. Our study reiterates the urgent clinical need to incorporate similar functional genomic approaches to characterize gene fusions, thereby maximizing the utility of gene fusions for precision oncology.",

author = "Jun Li and Hengyu Lu and Ng, {Patrick Kwok Shing} and Angeliki Pantazi and Ip, {Carman Ka Man} and Jeong, {Kang Jin} and Bianca Amador and Richard Tran and Tsang, {Yiu Huen} and Lixing Yang and Xingzhi Song and Turgut Dogruluk and Xiaojia Ren and Angela Hadjipanayis and Bristow, {Christopher A.} and Semin Lee and Melanie Kucherlapati and Michael Parfenov and Jiabin Tang and Sahil Seth and Mahadeshwar, {Harshad S.} and Kamalika Mojumdar and Dong Zeng and Jianhua Zhang and Alexei Protopopov and Seidman, {Jonathan G.} and Creighton, {Chad J.} and Yiling Lu and Nidhi Sahni and Shaw, {Kenna R.} and Funda Meric-Bernstam and Andrew Futreal and Lynda Chin and Scott, {Kenneth L.} and Raju Kucherlapati and Mills, {Gordon B} and Han Liang",

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doi = "10.1126/sciadv.abm2382",

language = "English (US)",

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AU - Lu, Hengyu

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AU - Ip, Carman Ka Man

AU - Jeong, Kang Jin

AU - Amador, Bianca

AU - Tran, Richard

AU - Tsang, Yiu Huen

AU - Yang, Lixing

AU - Song, Xingzhi

AU - Dogruluk, Turgut

AU - Ren, Xiaojia

AU - Hadjipanayis, Angela

AU - Bristow, Christopher A.

AU - Lee, Semin

AU - Kucherlapati, Melanie

AU - Parfenov, Michael

AU - Tang, Jiabin

AU - Seth, Sahil

AU - Mahadeshwar, Harshad S.

AU - Mojumdar, Kamalika

AU - Zeng, Dong

AU - Zhang, Jianhua

AU - Protopopov, Alexei

AU - Seidman, Jonathan G.

AU - Creighton, Chad J.

AU - Lu, Yiling

AU - Sahni, Nidhi

AU - Shaw, Kenna R.

AU - Meric-Bernstam, Funda

AU - Futreal, Andrew

AU - Chin, Lynda

AU - Scott, Kenneth L.

AU - Kucherlapati, Raju

AU - Mills, Gordon B

AU - Liang, Han

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N2 - Fusion genes represent a class of attractive therapeutic targets. Thousands of fusion genes have been identified in patients with cancer, but the functional consequences and therapeutic implications of most of these remain largely unknown. Here, we develop a functional genomic approach that consists of efficient fusion reconstruction and sensitive cell viability and drug response assays. Applying this approach, we characterize ∼100 fusion genes detected in patient samples of The Cancer Genome Atlas, revealing a notable fraction of low-frequency fusions with activating effects on tumor growth. Focusing on those in the RTK-RAS pathway, we identify a number of activating fusions that can markedly affect sensitivity to relevant drugs. Last, we propose an integrated, level-of-evidence classification system to prioritize gene fusions systematically. Our study reiterates the urgent clinical need to incorporate similar functional genomic approaches to characterize gene fusions, thereby maximizing the utility of gene fusions for precision oncology.

AB - Fusion genes represent a class of attractive therapeutic targets. Thousands of fusion genes have been identified in patients with cancer, but the functional consequences and therapeutic implications of most of these remain largely unknown. Here, we develop a functional genomic approach that consists of efficient fusion reconstruction and sensitive cell viability and drug response assays. Applying this approach, we characterize ∼100 fusion genes detected in patient samples of The Cancer Genome Atlas, revealing a notable fraction of low-frequency fusions with activating effects on tumor growth. Focusing on those in the RTK-RAS pathway, we identify a number of activating fusions that can markedly affect sensitivity to relevant drugs. Last, we propose an integrated, level-of-evidence classification system to prioritize gene fusions systematically. Our study reiterates the urgent clinical need to incorporate similar functional genomic approaches to characterize gene fusions, thereby maximizing the utility of gene fusions for precision oncology.

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A functional genomic approach to actionable gene fusions for precision oncology

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