Combined BET bromodomain and CDK2 inhibition in MYC-driven medulloblastoma

Bolin, Sara; Borgenvik, Anna; Persson, C.; Sundström, Anders; Qi, Jun; Bradner, James E.; Weiss, William A.; Cho, Yoon Jae; Weishaupt, Holger; Swartling, Fredrik J.

doi:10.1038/s41388-018-0135-1

Cited by 73 publications

(58 citation statements)

References 49 publications

(65 reference statements)

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“…Again, CCNB1 expression was significantly reduced, from 7.48 to 7.04 average log(CPM). Support for the inferred activation of MYC by CCNB1 was found by the fact that the CCNB1 expression changed from normal newborn mouse brain to adult mouse brain (from FPKM 20.3 to 0.2) which agrees with the change of MYC (from FPKM 9.2 to 0.8) [28] .…”

Section: Validation Of the Best Grnsupporting

confidence: 58%

“…The novel regulatory relationships BRD4→CCNB1 and CCNB1→MYC (Fig. 3) were examined in an independent study [28] in which JQ1 was used to inhibit BRD4 in the GTML2 cell line, a mouse brain tumor cell line that overexpresses human MYCN. The inferred activation of CCNB1 by BRD4 was supported by a significant reduction of CCNB1 expression when BRD4 was inhibited, from 7.12 to 7.04 average log(CPM) after 6h (Fig.…”

Section: Validation Of the Best Grnmentioning

confidence: 99%

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Perturbation-based gene regulatory network inference to unravel oncogenic mechanisms

Morgan

Studham

Tjärnberg

et al. 2019

Preprint

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The gene regulatory network (GRN) of human cells encodes mechanisms to ensure proper functioning. However, if this GRN is dysregulated, the cell may enter into a disease state such as cancer. Understanding the GRN as a system can therefore help identify novel mechanisms underlying disease, which can lead to new therapies. Reliable inference of GRNs is however still a major challenge in systems biology.To deduce regulatory interactions relevant to cancer, we applied a recent computational inference framework to data from perturbation experiments in squamous carcinoma cell line A431. GRNs were inferred using several methods, and the false discovery rate was controlled by the NestBoot framework. We developed a novel approach to assess the predictiveness of inferred GRNs against validation data, despite the lack of a gold standard. The best GRN was significantly more predictive than the null model, both in crossvalidated benchmarks and for an independent dataset of the same genes under a different perturbation design. It agrees with many known links, in addition to predicting a large number of novel interactions from which a subset was experimentally validated. The inferred GRN captures regulatory interactions central to cancer-relevant processes and thus provides mechanistic insights that are useful for future cancer research. Author SummaryCancer is the second most common cause of death globally, and although cancer treatments have improved in recent years, we need to understand how regulatory mechanisms are altered in cancer to combat the disease efficiently. By applying gene perturbations and inference of gene regulatory networks to 40 genes known or suspected to have a role in cancer due to interactions with the oncogene MYC, we deduce their underlying regulatory interactions. Using a recent computational framework for inference together with a novel method for cross validation, we infer a reliable regulatory model of this system in a completely data driven manner, not reliant on literature or priors. The novel interactions add to the understanding of the progressive oncogenic regulatory process and may provide new targets for therapy.

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Section: Validation Of the Best Grnsupporting

confidence: 58%

Section: Validation Of the Best Grnmentioning

confidence: 99%

Perturbation-based gene regulatory network inference to unravel oncogenic mechanisms

Morgan

Studham

Tjärnberg

et al. 2019

Preprint

Self Cite

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“…So we speculated that c-Myc plays a role in GCMSC-CM-mediated PD-L1 up-regulation in GC cells. We used JQ1, a novel small molecule that inhibits actions of BRDs and mainly down-regulates the expression of c-Myc to resist cells proliferation 34 . Therefore, we inhibited c-Myc expression by JQ1 and found that GCMSC-CM could up-regulate c-Myc and PD-L1.…”

Section: Discussionmentioning

confidence: 99%

Gastric cancer mesenchymal stem cells derived IL-8 induces PD-L1 expression in gastric cancer cells via STAT3/mTOR-c-Myc signal axis

et al. 2018

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The expression of PD-L1 in tumor cells is one of the main causes of tumor immune escape. However, the exact mechanism for regulating PD-L1 expression in gastric cancer (GC) cells remains unclear. Our previous studies have shown that mesenchymal stem cells (MSCs) exert broad immunosuppressive potential, modulating the activity of cells either in innate or adaptive immune system to promote tumor progress. This study aims to investigate whether GCMSCs regulate the PD-L1 expression in GC cells and explore the specific molecular mechanism. The results have shown that GCMSCs enhanced PD-L1 expression in GC cells resulting in the resistance of GC cells to CD8+ T cells cytotoxicity. However, this resistance was attenuated with IL-8 inhibition. Further studies proved that IL-8 derived from GCMSCs induced PD-L1 expression in GC cells via c-Myc regulated by STAT3 and mTOR signaling pathways. Our data indicated that blocking IL-8 derived from GCMSCs may overcome the immune escape induced by PD-L1 in GC cells and provide a potential strategy to enhance the immunotherapy efficiency in GC.

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“…Kinase inhibitors that affect the active pS62-MYC state include ERK, CDK2, and CDK9 inhibitors [103][104][105][106][107][108][109]. Unfortunately, cancer cells are quite adept at rewiring signaling pathways in response to targeted therapies in order to keep MYC and other signaling substrates active [110][111][112].…”

Section: Serine 62 Phosphorylation and Dephosphorylationmentioning

confidence: 99%

Mission Possible: Advances in MYC Therapeutic Targeting in Cancer

Allen-Petersen¹,

Sears²

2019

BioDrugs

123

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MYC is a master transcriptional regulator that controls almost all cellular processes. Over the last several decades, researchers have strived to define the context-dependent transcriptional gene programs that are controlled by MYC, as well as the mechanisms that regulate MYC function, in an effort to better understand the contribution of this oncoprotein to cancer progression. There are a wealth of data indicating that deregulation of MYC activity occurs in a large number of cancers and significantly contributes to disease progression, metastatic potential, and therapeutic resistance. Although the therapeutic targeting of MYC in cancer is highly desirable, there remain substantial structural and functional challenges that have impeded direct MYC-targeted drug development and efficacy. While efforts to drug the 'undruggable' may seem futile given these challenges and considering the broad reach of MYC, significant strides have been made to identify points of regulation that can be exploited for therapeutic purposes. These include targeting the deregulation of MYC transcription in cancer through small-molecule inhibitors that induce epigenetic silencing or that regulate the G-quadruplex structures within the MYC promoter. Alternatively, compounds that disrupt the DNA-binding activities of MYC have been the long-standing focus of many research groups, since this method would prevent downstream MYC oncogenic activities regardless of upstream alterations. Finally, proteins involved in the post-translational regulation of MYC have been identified as important surrogate targets to reduce MYC activity downstream of aberrant cell stimulatory signals. Given the complex regulation of the MYC signaling pathway, a combination of these approaches may provide the most durable response, but this has yet to be shown. Here, we provide a comprehensive overview of the different therapeutic strategies being employed to target oncogenic MYC function, with a focus on post-translational mechanisms.

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Combined BET bromodomain and CDK2 inhibition in MYC-driven medulloblastoma

Cited by 73 publications

References 49 publications

Perturbation-based gene regulatory network inference to unravel oncogenic mechanisms

Perturbation-based gene regulatory network inference to unravel oncogenic mechanisms

Gastric cancer mesenchymal stem cells derived IL-8 induces PD-L1 expression in gastric cancer cells via STAT3/mTOR-c-Myc signal axis

Mission Possible: Advances in MYC Therapeutic Targeting in Cancer

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