MAP kinase and autophagy pathways cooperate to maintain RAS mutant cancer cell survival

Lee, C. S., Lee, L. C., Yuan, T. L., Chakka, S., Fellmann, C., Lowe, S. W., Caplen, N. J., McCormick, F., Luo, J. (February 2019) MAP kinase and autophagy pathways cooperate to maintain RAS mutant cancer cell survival. Proc Natl Acad Sci U S A, 116 (10). pp. 4508-4517. ISSN 0027-8424

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Abstract

Oncogenic mutations in the small GTPase KRAS are frequently found in human cancers, and, currently, there are no effective targeted therapies for these tumors. Using a combinatorial siRNA approach, we analyzed a panel of KRAS mutant colorectal and pancreatic cancer cell lines for their dependency on 28 gene nodes that represent canonical RAS effector pathways and selected stress response pathways. We found that RAF node knockdown best differentiated KRAS mutant and KRAS WT cancer cells, suggesting RAF kinases are key oncoeffectors for KRAS addiction. By analyzing all 376 pairwise combination of these gene nodes, we found that cotargeting the RAF, RAC, and autophagy pathways can improve the capture of KRAS dependency better than targeting RAF alone. In particular, codepletion of the oncoeffector kinases BRAF and CRAF, together with the autophagy E1 ligase ATG7, gives the best therapeutic window between KRAS mutant cells and normal, untransformed cells. Distinct patterns of RAS effector dependency were observed across KRAS mutant cell lines, indicative of heterogeneous utilization of effector and stress response pathways in supporting KRAS addiction. Our findings revealed previously unappreciated complexity in the signaling network downstream of the KRAS oncogene and suggest rational target combinations for more effective therapeutic intervention.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification
diseases & disorders
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics
diseases & disorders > neoplasms
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > RNA silencing
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification > protein types > enzymes
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification > protein types > G protein
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > genes: types
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification > protein types > enzymes > Mitogen-activated protein kinase
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > genes: types > oncogene
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification > protein types > G protein > Ras
CSHL Authors:
Communities: CSHL labs > Lowe lab
Depositing User: Matthew Dunn
Date: 1 February 2019
Date Deposited: 05 Feb 2019 21:00
Last Modified: 02 Feb 2024 16:37
PMCID: PMC6410784
Related URLs:
URI: https://repository.cshl.edu/id/eprint/37684

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