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

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

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.

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

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.

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

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.

Multiple therapeutic approaches of glioblastoma multiforme: From terminal to therapy

Glioblastoma multiforme (GBM) is an aggressive brain cancer showing poor prognosis. Currently, treatment methods of GBM are limited with adverse outcomes and low survival rate. Thus, advancements in the treatment of GBM are of utmost importance, which can be achieved in recent decades. However, despite aggressive initial treatment, most patients develop recurrent diseases, and the overall survival rate of patients is impossible to achieve. Currently, researchers across the globe target signaling events along with tumor microenvironment (TME) through different drug molecules to inhibit the progression of GBM, but clinically they failed to demonstrate much success. Herein, we discuss the therapeutic targets and signaling cascades along with the role of the organoids model in GBM research. Moreover, we systematically review the traditional and emerging therapeutic strategies in GBM. In addition, we discuss the implications of nanotechnologies, AI, and combinatorial approach to enhance GBM therapeutics.

Evolving Insights Into the Biological Function and Clinical Significance of Long Noncoding RNA in Glioblastoma

Glioblastoma (GBM) is one of the most prevalent and aggressive cancers worldwide. The overall survival period of GBM patients is only 15 months even with standard combination therapy. The absence of validated biomarkers for early diagnosis mainly accounts for worse clinical outcomes of GBM patients. Thus, there is an urgent requirement to characterize more biomarkers for the early diagnosis of GBM patients. In addition, the detailed molecular basis during GBM pathogenesis and oncogenesis is not fully understood, highlighting that it is of great significance to elucidate the molecular mechanisms of GBM initiation and development. Recently, accumulated pieces of evidence have revealed the central roles of long noncoding RNAs (lncRNAs) in the tumorigenesis and progression of GBM by binding with DNA, RNA, or protein. Targeting those oncogenic lncRNAs in GBM may be promising to develop more effective therapeutics. Furthermore, a better understanding of the biological function and underlying molecular basis of dysregulated lncRNAs in GBM initiation and development will offer new insights into GBM early diagnosis and develop novel treatments for GBM patients. Herein, this review builds on previous studies to summarize the dysregulated lncRNAs in GBM and their unique biological functions during GBM tumorigenesis and progression. In addition, new insights and challenges of lncRNA-based diagnostic and therapeutic potentials for GBM patients were also introduced.

Structural and functional analysis of target recognition by the lymphocyte adaptor protein LNK

The SH2B family of adaptor proteins, SH2-B, APS, and LNK are key modulators of cellular signalling pathways. Whilst SH2-B and APS have been partially structurally and biochemically characterised, to date there has been no such characterisation of LNK. Here we present two crystal structures of the LNK substrate recognition domain, the SH2 domain, bound to phosphorylated motifs from JAK2 and EPOR, and biochemically define the basis for target recognition. The LNK SH2 domain adopts a canonical SH2 domain fold with an additional N-terminal helix. Targeted analysis of binding to phosphosites in signalling pathways indicated that specificity is conferred by amino acids one- and three-residues downstream of the phosphotyrosine. Several mutations in LNK showed impaired target binding in vitro and a reduced ability to inhibit signalling, allowing an understanding of the molecular basis of LNK dysfunction in variants identified in patients with myeloproliferative disease.