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- Serra-Musach, Jordi, et al.
(författare)
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Cancer network activity associated with therapeutic response and synergism
- 2016
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Ingår i: Genome Medicine. - : BIOMED CENTRAL LTD. - 1756-994X .- 1756-994X. ; 8:88
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Tidskriftsartikel (refereegranskat)abstract
- Background: Cancer patients often show no or only modest benefit from a given therapy. This major problem in oncology is generally attributed to the lack of specific predictive biomarkers, yet a global measure of cancer cell activity may support a comprehensive mechanistic understanding of therapy efficacy. We reasoned that network analysis of omic data could help to achieve this goal. Methods: A measure of "cancer network activity" (CNA) was implemented based on a previously defined network feature of communicability. The network nodes and edges corresponded to human proteins and experimentally identified interactions, respectively. The edges were weighted proportionally to the expression of the genes encoding for the corresponding proteins and relative to the number of direct interactors. The gene expression data corresponded to the basal conditions of 595 human cancer cell lines. Therapeutic responses corresponded to the impairment of cell viability measured by the half maximal inhibitory concentration (IC50) of 130 drugs approved or under clinical development. Gene ontology, signaling pathway, and transcription factor-binding annotations were taken from public repositories. Predicted synergies were assessed by determining the viability of four breast cancer cell lines and by applying two different analytical methods. Results: The effects of drug classes were associated with CNAs formed by different cell lines. CNAs also differentiate target families and effector pathways. Proteins that occupy a central position in the network largely contribute to CNA. Known key cancer-associated biological processes, signaling pathways, and master regulators also contribute to CNA. Moreover, the major cancer drivers frequently mediate CNA and therapeutic differences. Cell-based assays centered on these differences and using uncorrelated drug effects reveals novel synergistic combinations for the treatment of breast cancer dependent on PI3K-mTOR signaling. Conclusions: Cancer therapeutic responses can be predicted on the basis of a systems-level analysis of molecular interactions and gene expression. Fundamental cancer processes, pathways, and drivers contribute to this feature, which can also be exploited to predict precise synergistic drug combinations.
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| 2. |
- Vizoso, Miguel, et al.
(författare)
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Epigenetic activation of a cryptic TBC1D16 transcript enhances melanoma progression by targeting EGFR
- 2015
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 21:7, s. 741-
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Tidskriftsartikel (refereegranskat)abstract
- Metastasis is responsible for most cancer-related deaths, and, among common tumor types, melanoma is one with great potential to metastasize. Here we study the contribution of epigenetic changes to the dissemination process by analyzing the changes that occur at the DNA methylation level between primary cancer cells and metastases. We found a hypomethylation event that reactivates a cryptic transcript of the Rab GTPase activating protein TBC1D16 (TBC1D16-47 kDa; referred to hereafter as TBC1D16-47KD) to be a characteristic feature of the metastatic cascade. This short isoform of TBC1D16 exacerbates melanoma growth and metastasis both in vitro and in vivo. By combining immunoprecipitation and mass spectrometry, we identified RAB5C as a new TBC1D16 target and showed that it regulates EGFR in melanoma cells. We also found that epigenetic reactivation of TBC1D16-47KD is associated with poor clinical outcome in melanoma, while conferring greater sensitivity to BRAF and MEK inhibitors.
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