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Baicalein inhibits cell proliferation and induces apoptosis in brain glioma cells by downregulating the LGR4-EGFR pathway

Patients diagnosed with brain glioma have a poor prognosis and limited therapeutic options. LGR4 is overexpressed in brain glioma and involved in the tumorigenesis of many tumors. Baicalein (BAI) is a kind of flavonoid that has exhibited anti-tumor effects in various tumors. Nevertheless, the functions and associations of BAI and LGR4 in brain glioma remain unclear. In this study, Gene Expression Profiling Interactive Analysis and Human Protein Atlas databases were used to perform expression and survival analysis of LGR4 in brain glioma patients. Subsequently, the significance of LGR4-EGFR in brain glioma cells (HS683 and KNS89) and brain glioma animal models was explored by RNA interference and subcutaneous transplantation. Additionally, brain glioma cells were treated with BAI to explore the roles and mechanisms of BAI in brain glioma. The results showed that LGR4 was highly expressed in brain glioma and was related to a poor prognosis. LGR4 knockdown repressed the proliferation and EGFR phosphorylation but induced apoptosis in brain glioma cells. However, these effects were reversed by EGFR overexpression and CBL knockdown. In contrast, both in vitro and in vivo experiments revealed that LGR4 overexpression facilitated brain glioma cell malignant behavior and promoted tumor development, but these effects were rescued by BAI and an EGFR inhibitor. Furthermore, si-LGR4 accelerated EGFR protein degradation, while oe-LGR4 exhibited the opposite effect. Without affecting normal cellular viability, BAI inhibited malignant behavior, interacted with LGR4, and blocked the LGR4-EGFR pathway for brain glioma cells. In conclusion, our data suggested that BAI inhibited brain glioma cell proliferation and induced apoptosis by downregulating the LGR4-EGFR pathway, which provides a novel strategy and potential therapeutic targets to treat brain glioma.

Genotype of PAX2-related disorders correlates with kidney and ocular manifestations

PAX2-related disorders encompass renal coloboma syndrome (RCS) and hereditary focal segmental glomerulosclerosis (FSGS) type 7. We retrospectively analyzed 27 Korean patients with PAX2 pathogenic variants detected between 2004 and 2022 and conducted a literature review of 328 cases, including 301 previously reported. In our cohort, 19 had RCS, 4 had FSGS, and 4 had isolated congenital anomalies of the kidneys and urinary tract. Patients were classified by variant type into predicted loss of function (pLoF) and non-pLoF variant groups, and by variant location into paired domain and other sites group. pLoF variants were predominantly associated with RCS, observed in 82% of patients in both our data (18 of 22, P = 0.017) and the literature (140 of 171, P < 0.001). Kidney failure developed in 52% of Korean patients at a median age of 14.5 years, with no difference in kidney survival between variant types. However, the literature review indicated faster progression to kidney failure in patients with pLoF variants (11.0 vs. 24.0 years; pLoF, n = 138 vs. non-pLoF, n = 71; P = 0.002), with no significant difference by variant location. Ocular manifestations were more common, had earlier onset, and were more severe in the pLoF variants group in our cohort (P = 0.038). The literature confirmed a higher prevalence of ocular involvement in patients with pLoF variants (pLoF, n = 175 vs. non-pLoF, n = 88; P < 0.001) and in those with paired domain variants (P = 0.01). pLoF variants in PAX2 were associated with worse kidney and ocular outcomes. These findings support genotype-phenotype correlations, contributing to tailored management in patients with PAX2-related disorders.

Whole-genome sequencing analysis identifies rare, large-effect noncoding variants and regulatory regions associated with circulating protein levels

The contribution of rare noncoding genetic variation to common phenotypes is largely unknown, as a result of a historical lack of population-scale whole-genome sequencing data and the difficulty of categorizing noncoding variants into functionally similar groups. To begin addressing these challenges, we performed a cis association analysis using whole-genome sequencing data, consisting of 1.1 billion variants, 123 million noncoding aggregate-based tests and 2,907 circulating protein levels in ~50,000 UK Biobank participants. We identified 604 independent rare noncoding single-variant associations with circulating protein levels. Unlike protein-coding variation, rare noncoding genetic variation was almost as likely to increase or decrease protein levels. Rare noncoding aggregate testing identified 357 conditionally independent associated regions. Of these, 74 (21%) were not detectable by single-variant testing alone. Our findings have important implications for the identification, and role, of rare noncoding genetic variation associated with common human phenotypes, including the importance of testing aggregates of noncoding variants.

Ion channel traffic jams: the significance of trafficking deficiency in long QT syndrome

A well-balanced ion channel trafficking machinery is paramount for the normal electromechanical function of the heart. Ion channel variants and many drugs can alter the cardiac action potential and lead to arrhythmias by interfering with mechanisms like ion channel synthesis, trafficking, gating, permeation, and recycling. A case in point is the Long QT syndrome (LQTS), a highly arrhythmogenic disease characterized by an abnormally prolonged QT interval on ECG produced by variants and drugs that interfere with the action potential. Disruption of ion channel trafficking is one of the main sources of LQTS. We review some molecular pathways and mechanisms involved in cardiac ion channel trafficking. We highlight the importance of channelosomes and other macromolecular complexes in helping to maintain normal cardiac electrical function, and the defects that prolong the QT interval as a consequence of variants or the effect of drugs. We examine the concept of “interactome mapping” and illustrate by example the multiple protein–protein interactions an ion channel may undergo throughout its lifetime. We also comment on how mapping the interactomes of the different cardiac ion channels may help advance research into LQTS and other cardiac diseases. Finally, we discuss how using human induced pluripotent stem cell technology to model ion channel trafficking and its defects may help accelerate drug discovery toward preventing life-threatening arrhythmias. Advancements in understanding ion channel trafficking and channelosome complexities are needed to find novel therapeutic targets, predict drug interactions, and enhance the overall management and treatment of LQTS patients.

The comprehensive SARS-CoV-2 ‘hijackome’ knowledge base

The continuous evolution of SARS-CoV-2 has led to the emergence of several variants of concern (VOCs) that significantly affect global health. This study aims to investigate how these VOCs affect host cells at proteome level to better understand the mechanisms of disease. To achieve this, we first analyzed the (phospho)proteome changes of host cells infected with Alpha, Beta, Delta, and Omicron BA.1 and BA.5 variants over time frames extending from 1 to 36 h post infection. Our results revealed distinct temporal patterns of protein expression across the VOCs, with notable differences in the (phospho)proteome dynamics that suggest variant-specific adaptations. Specifically, we observed enhanced expression and activation of key components within crucial cellular pathways such as the RHO GTPase cycle, RNA splicing, and endoplasmic reticulum-associated degradation (ERAD)-related processes. We further utilized proximity biotinylation mass spectrometry (BioID-MS) to investigate how specific mutation of these VOCs influence viral–host protein interactions. Our comprehensive interactomics dataset uncovers distinct interaction profiles for each variant, illustrating how specific mutations can change viral protein functionality. Overall, our extensive analysis provides a detailed proteomic profile of host cells for each variant, offering valuable insights into how specific mutations may influence viral protein functionality and impact therapeutic target identification. These insights are crucial for the potential use and design of new antiviral substances, aiming to enhance the efficacy of treatments against evolving SARS-CoV-2 variants.

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