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Hsp70-Bag3 interactions regulate cancer-related signaling networks.

ABSTRACT: Bag3, a nucleotide exchange factor of the heat shock protein Hsp70, has been implicated in cell signaling. Here, we report that Bag3 interacts with the SH3 domain of Src, thereby mediating the effects of Hsp70 on Src signaling. Using several complementary approaches, we established that the Hsp70-Bag3 module is a broad-acting regulator of cancer cell signaling by modulating the activity of the transcription factors NF-?B, FoxM1, Hif1?, the translation regulator HuR, and the cell-cycle regulators p21 and survivin. We also identified a small-molecule inhibitor, YM-1, that disrupts the Hsp70-Bag3 interaction. YM-1 mirrored the effects of Hsp70 depletion on these signaling pathways, and in vivo administration of this drug was sufficient to suppress tumor growth in mice. Overall, our results defined Bag3 as a critical factor in Hsp70-modulated signaling and offered a preclinical proof-of-concept that the Hsp70-Bag3 complex may offer an appealing anticancer target.

SUBMITTER: Colvin TA

PROVIDER: S-EPMC4174322 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Hsp70-Bag3 interactions regulate cancer-related signaling networks.

Colvin Teresa A TA Gabai Vladimir L VL Gong Jianlin J Calderwood Stuart K SK Li Hu H Gummuluru Suryaram S Matchuk Olga N ON Smirnova Svetlana G SG Orlova Nina V NV Zamulaeva Irina A IA Garcia-Marcos Mikel M Li Xiaokai X Young Z T ZT Rauch Jennifer N JN Gestwicki Jason E JE Takayama Shinichi S Sherman Michael Y MY

Cancer research 20140703 17

Bag3, a nucleotide exchange factor of the heat shock protein Hsp70, has been implicated in cell signaling. Here, we report that Bag3 interacts with the SH3 domain of Src, thereby mediating the effects of Hsp70 on Src signaling. Using several complementary approaches, we established that the Hsp70-Bag3 module is a broad-acting regulator of cancer cell signaling by modulating the activity of the transcription factors NF-κB, FoxM1, Hif1α, the translation regulator HuR, and the cell-cycle regulators ...[more]

PMID: 24994713

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Project description:Cancer has been increasingly recognized as a systems biology disease since many investigators have demonstrated that this malignant phenotype emerges from abnormal protein-protein, regulatory and metabolic interactions induced by simultaneous structural and regulatory changes in multiple genes and pathways. Therefore, the identification of oncogenic interactions and cancer-related signaling networks is crucial for better understanding cancer. As experimental techniques for determining such interactions and signaling networks are labor-intensive and time-consuming, the development of a computational approach capable to accomplish this task would be of great value. For this purpose, we present here a novel computational approach based on network topology and machine learning capable to predict oncogenic interactions and extract relevant cancer-related signaling subnetworks from an integrated network of human genes interactions (INHGI). This approach, called graph2sig, is twofold: first, it assigns oncogenic scores to all interactions in the INHGI and then these oncogenic scores are used as edge weights to extract oncogenic signaling subnetworks from INHGI. Regarding the prediction of oncogenic interactions, we showed that graph2sig is able to recover 89% of known oncogenic interactions with a precision of 77%. Moreover, the interactions that received high oncogenic scores are enriched in genes for which mutations have been causally implicated in cancer. We also demonstrated that graph2sig is potentially useful in extracting oncogenic signaling subnetworks: more than 80% of constructed subnetworks contain more than 50% of original interactions in their corresponding oncogenic linear pathways present in the KEGG PATHWAY database. In addition, the potential oncogenic signaling subnetworks discovered by graph2sig are supported by experimental evidence. Taken together, these results suggest that graph2sig can be a useful tool for investigators involved in cancer research interested in detecting signaling networks most prone to contribute with the emergence of malignant phenotype.

Dataset Information

Hsp70-Bag3 interactions regulate cancer-related signaling networks.

Publications

Hsp70-Bag3 interactions regulate cancer-related signaling networks.

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