SH2B3, Transcribed by STAT1, Promotes Glioblastoma Progression Through Transducing IL-6/gp130 Signaling to Activate STAT3 Signaling

Cai, Sanjun; Lu, Jian-Xiang; Wang, Yanpei; Shi, Chengmin; Tian, Ye; Wang, Xiangpeng

doi:10.3389/fcell.2021.606527

Cited by 7 publications

(7 citation statements)

References 45 publications

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“…For example, SH2B was predicted to be a PC for both selumetinib and PD318088 as well as a parental node for selumetinib, directly influencing MEKi response. It is highly expressed in GBM, promoting progression through activating STAT3 signaling [35]. It is known to play a critical role in promoting GBM progression and has previously been proposed as a new therapeutic target.…”

Section: Discussionmentioning

confidence: 99%

Integration of Computational Pipeline to Streamline Efficacious Drug Nomination and Biomarker Discovery in Glioblastoma

Maeser,

Gruener,

Galvin

et al. 2024

Cancers

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Glioblastoma multiforme (GBM) is the deadliest, most heterogeneous, and most common brain cancer in adults. Not only is there an urgent need to identify efficacious therapeutics, but there is also a great need to pair these therapeutics with biomarkers that can help tailor treatment to the right patient populations. We built patient drug response models by integrating patient tumor transcriptome data with high-throughput cell line drug screening data as well as Bayesian networks to infer relationships between patient gene expression and drug response. Through these discovery pipelines, we identified agents of interest for GBM to be effective across five independent patient cohorts and in a mouse avatar model: among them are a number of MEK inhibitors (MEKis). We also predicted phosphoglycerate dehydrogenase enzyme (PHGDH) gene expression levels to be causally associated with MEKi efficacy, where knockdown of this gene increased tumor sensitivity to MEKi and overexpression led to MEKi resistance. Overall, our work demonstrated the power of integrating computational approaches. In doing so, we quickly nominated several drugs with varying known mechanisms of action that can efficaciously target GBM. By simultaneously identifying biomarkers with these drugs, we also provide tools to select the right patient populations for subsequent evaluation.

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Section: Discussionmentioning

confidence: 99%

Integration of Computational Pipeline to Streamline Efficacious Drug Nomination and Biomarker Discovery in Glioblastoma

Maeser,

Gruener,

Galvin

et al. 2024

Cancers

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“…PSME4 enhances aggressiveness of HCC via activating mTOR signaling ( Ge et al, 2022 ). It has been documented that SH2B3 contributes to glioblastoma progression by transducing IL-6/gp130/STAT3 signaling ( Cai et al, 2021 ). TTC39C has been screened as an alternative splicing-related mRNA that is implicated in tumor microenvironment and immune infiltration of BRCA mutation patients ( Zhang et al, 2022a ).…”

Section: Discussionmentioning

confidence: 99%

Development of a circHIPK3-based ceRNA network and identification of mRNA signature in breast cancer patients harboring BRCA mutation

Lian

Song

Han³

et al. 2023

PeerJ

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Background Exploring the regulatory network of competing endogenous RNAs (ceRNAs) as hallmarks for breast cancer development has great significance and could provide therapeutic targets. An mRNA signature predictive of prognosis and therapy response in BRCA carriers was developed according to circular RNA homeodomain-interacting protein kinase 3 (circHIPK3)-based ceRNA network. Method We constructed a circHIPK3-based ceRNA network based on GSE173766 dataset and identified potential mRNAs that were associated with BRCA mutation patients within this ceRNA network. A total of 11 prognostic mRNAs and a risk model were identified and developed by univariate Cox regression analysis and the LASSO regression analysis as well as stepAIC method. Genomic landscape was treated by mutect2 and fisher. Immune characteristics was analyzed by ESTIMATE, MCP-counter. TIDE analysis was conducted to predict immunotherapy. The clinical treatment outcomes of BRCA mutation patients were assessed using a nomogram. The proliferation, migration and invasion in breast cancer cell lines were examined using CCK8 assay and transwell assay. Result We found 241 mRNAs within the circHIPK3-based ceRNA network. An 11 mRNA-based signature was identified for prognostic model construction. High risk patients exhibited dismal prognosis, low response to immunotherapy, less immune cell infiltration and tumor mutation burden (TMB). High-risk patients were sensitive to six anti-tumor drugs, while low-risk patient were sensitive to 47 drugs. The risk score was the most effective on evaluating patients’ survival. The robustness and good prediction performance were validated in The Cancer Genome Atlas (TCGA) dataset and immunotherapy datasets, respectively. In addition, circHIPK3 mRNA level was upregulated, and promoted cell viability, migration and invasion in breast cancer cell lines. Conclusion The current study could improve the understanding of mRNAs in relation to BRCA mutation and pave the way to develop mRNA-based therapeutic targets for breast cancer patients with BRCA mutation.

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“…Likewise, elevated expression of LNK was detected in patients with thyroid carcinoma [128]. In glioblastoma patients, elevated expression of LNK predicted worse survival [129]. Similarly, in silico analysis and immunohistochemical study of tissue arrays demonstrated increased LNK expression in patients with high-grade ovarian cancer [130].…”

Section: Lnk In Hormone Receptor-positive Breast Cancermentioning

confidence: 93%

Modulation of JAK-STAT Signaling by LNK: A Forgotten Oncogenic Pathway in Hormone Receptor-Positive Breast Cancer

López-Mejía,

Mantilla-Ollarves,

Rocha-Zavaleta

2023

IJMS

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Breast cancer remains the most frequently diagnosed cancer in women worldwide. Tumors that express hormone receptors account for 75% of all cases. Understanding alternative signaling cascades is important for finding new therapeutic targets for hormone receptor-positive breast cancer patients. JAK-STAT signaling is commonly activated in hormone receptor-positive breast tumors, inducing inflammation, proliferation, migration, and treatment resistance in cancer cells. In hormone receptor-positive breast cancer, the JAK-STAT cascade is stimulated by hormones and cytokines, such as prolactin and IL-6. In normal cells, JAK-STAT is inhibited by the action of the adaptor protein, LNK. However, the role of LNK in breast tumors is not fully understood. This review compiles published reports on the expression and activation of the JAK-STAT pathway by IL-6 and prolactin and potential inhibition of the cascade by LNK in hormone receptor-positive breast cancer. Additionally, it includes analyses of available datasets to determine the level of expression of LNK and various members of the JAK-STAT family for the purpose of establishing associations between expression and clinical outcomes. Together, experimental evidence and in silico studies provide a better understanding of the potential implications of the JAK-STAT-LNK loop in hormone receptor-positive breast cancer progression.

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SH2B3, Transcribed by STAT1, Promotes Glioblastoma Progression Through Transducing IL-6/gp130 Signaling to Activate STAT3 Signaling

Cited by 7 publications

References 45 publications

Integration of Computational Pipeline to Streamline Efficacious Drug Nomination and Biomarker Discovery in Glioblastoma

Integration of Computational Pipeline to Streamline Efficacious Drug Nomination and Biomarker Discovery in Glioblastoma

Development of a circHIPK3-based ceRNA network and identification of mRNA signature in breast cancer patients harboring BRCA mutation

Modulation of JAK-STAT Signaling by LNK: A Forgotten Oncogenic Pathway in Hormone Receptor-Positive Breast Cancer

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