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Large-Scale In Vitro and In Vivo CRISPR-Cas9 Knockout Screens Identify a 16-Gene Fitness Score for Improved Risk Assessment in Acute Myeloid Leukemia
PURPOSE: The molecular complexity of acute myeloid leukemia (AML) presents a considerable challenge to implementation of clinical genetic testing for accurate risk stratification. Identification of better biomarkers therefore remains a high priority to enable improving established stratification and...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for Cancer Research
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9475249/ https://www.ncbi.nlm.nih.gov/pubmed/35877119 http://dx.doi.org/10.1158/1078-0432.CCR-22-1618 |
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author | Jin, Peng Jin, Qiqi Wang, Xiaoling Zhao, Ming Dong, Fangyi Jiang, Ge Li, Zeyi Shen, Jie Zhang, Wei Wu, Shishuang Li, Ran Zhang, Yunxiang Li, Xiaoyang Li, Junmin |
author_facet | Jin, Peng Jin, Qiqi Wang, Xiaoling Zhao, Ming Dong, Fangyi Jiang, Ge Li, Zeyi Shen, Jie Zhang, Wei Wu, Shishuang Li, Ran Zhang, Yunxiang Li, Xiaoyang Li, Junmin |
author_sort | Jin, Peng |
collection | PubMed |
description | PURPOSE: The molecular complexity of acute myeloid leukemia (AML) presents a considerable challenge to implementation of clinical genetic testing for accurate risk stratification. Identification of better biomarkers therefore remains a high priority to enable improving established stratification and guiding risk-adapted therapy decisions. EXPERIMENTAL DESIGN: We systematically integrated and analyzed the genome-wide CRISPR-Cas9 data from more than 1,000 in vitro and in vivo knockout screens to identify the AML-specific fitness genes. A prognostic fitness score was developed using the sparse regression analysis in a training cohort of 618 cases and validated in five publicly available independent cohorts (n = 1,570) and our RJAML cohort (n = 157) with matched RNA sequencing and targeted gene sequencing performed. RESULTS: A total of 280 genes were identified as AML fitness genes and a 16-gene AML fitness (AFG16) score was further generated and displayed highly prognostic power in more than 2,300 patients with AML. The AFG16 score was able to distill downstream consequences of several genetic abnormalities and can substantially improve the European LeukemiaNet classification. The multi-omics data from the RJAML cohort further demonstrated its clinical applicability. Patients with high AFG16 scores had significantly poor response to induction chemotherapy. Ex vivo drug screening indicated that patients with high AFG16 scores were more sensitive to the cell-cycle inhibitors flavopiridol and SNS-032, and exhibited strongly activated cell-cycle signaling. CONCLUSIONS: Our findings demonstrated the utility of the AFG16 score as a powerful tool for better risk stratification and selecting patients most likely to benefit from chemotherapy and alternative experimental therapies. |
format | Online Article Text |
id | pubmed-9475249 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Association for Cancer Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-94752492023-01-05 Large-Scale In Vitro and In Vivo CRISPR-Cas9 Knockout Screens Identify a 16-Gene Fitness Score for Improved Risk Assessment in Acute Myeloid Leukemia Jin, Peng Jin, Qiqi Wang, Xiaoling Zhao, Ming Dong, Fangyi Jiang, Ge Li, Zeyi Shen, Jie Zhang, Wei Wu, Shishuang Li, Ran Zhang, Yunxiang Li, Xiaoyang Li, Junmin Clin Cancer Res Precision Medicine and Imaging PURPOSE: The molecular complexity of acute myeloid leukemia (AML) presents a considerable challenge to implementation of clinical genetic testing for accurate risk stratification. Identification of better biomarkers therefore remains a high priority to enable improving established stratification and guiding risk-adapted therapy decisions. EXPERIMENTAL DESIGN: We systematically integrated and analyzed the genome-wide CRISPR-Cas9 data from more than 1,000 in vitro and in vivo knockout screens to identify the AML-specific fitness genes. A prognostic fitness score was developed using the sparse regression analysis in a training cohort of 618 cases and validated in five publicly available independent cohorts (n = 1,570) and our RJAML cohort (n = 157) with matched RNA sequencing and targeted gene sequencing performed. RESULTS: A total of 280 genes were identified as AML fitness genes and a 16-gene AML fitness (AFG16) score was further generated and displayed highly prognostic power in more than 2,300 patients with AML. The AFG16 score was able to distill downstream consequences of several genetic abnormalities and can substantially improve the European LeukemiaNet classification. The multi-omics data from the RJAML cohort further demonstrated its clinical applicability. Patients with high AFG16 scores had significantly poor response to induction chemotherapy. Ex vivo drug screening indicated that patients with high AFG16 scores were more sensitive to the cell-cycle inhibitors flavopiridol and SNS-032, and exhibited strongly activated cell-cycle signaling. CONCLUSIONS: Our findings demonstrated the utility of the AFG16 score as a powerful tool for better risk stratification and selecting patients most likely to benefit from chemotherapy and alternative experimental therapies. American Association for Cancer Research 2022-09-15 2022-07-25 /pmc/articles/PMC9475249/ /pubmed/35877119 http://dx.doi.org/10.1158/1078-0432.CCR-22-1618 Text en ©2022 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license. |
spellingShingle | Precision Medicine and Imaging Jin, Peng Jin, Qiqi Wang, Xiaoling Zhao, Ming Dong, Fangyi Jiang, Ge Li, Zeyi Shen, Jie Zhang, Wei Wu, Shishuang Li, Ran Zhang, Yunxiang Li, Xiaoyang Li, Junmin Large-Scale In Vitro and In Vivo CRISPR-Cas9 Knockout Screens Identify a 16-Gene Fitness Score for Improved Risk Assessment in Acute Myeloid Leukemia |
title | Large-Scale In Vitro and In Vivo CRISPR-Cas9 Knockout Screens Identify a 16-Gene Fitness Score for Improved Risk Assessment in Acute Myeloid Leukemia |
title_full | Large-Scale In Vitro and In Vivo CRISPR-Cas9 Knockout Screens Identify a 16-Gene Fitness Score for Improved Risk Assessment in Acute Myeloid Leukemia |
title_fullStr | Large-Scale In Vitro and In Vivo CRISPR-Cas9 Knockout Screens Identify a 16-Gene Fitness Score for Improved Risk Assessment in Acute Myeloid Leukemia |
title_full_unstemmed | Large-Scale In Vitro and In Vivo CRISPR-Cas9 Knockout Screens Identify a 16-Gene Fitness Score for Improved Risk Assessment in Acute Myeloid Leukemia |
title_short | Large-Scale In Vitro and In Vivo CRISPR-Cas9 Knockout Screens Identify a 16-Gene Fitness Score for Improved Risk Assessment in Acute Myeloid Leukemia |
title_sort | large-scale in vitro and in vivo crispr-cas9 knockout screens identify a 16-gene fitness score for improved risk assessment in acute myeloid leukemia |
topic | Precision Medicine and Imaging |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9475249/ https://www.ncbi.nlm.nih.gov/pubmed/35877119 http://dx.doi.org/10.1158/1078-0432.CCR-22-1618 |
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