Deciphering the Oncogenic Role of VPS28 Modulated by miR-491-5p in Breast Cancer Cells Using In Silico and Functional Analysis

Identification and validation of diagnostic alternative splicing events in tumor-educated platelets for non-small cell lung cancer in patients with ground-glass opacity: a multicenter study

Background

The diagnostic potential of tumor-educated platelets (TEPs) across various cancer types has gained increasing recognition; however, the relationship between alternative splicing (AS) events in TEPs and tumor development remains understudied. Early detection of non-small cell lung cancer (NSCLC) in ground-glass opacities (GGOs) is critical for improving patient outcomes, yet current methods lack sufficient accuracy. Our research identified diagnostic-related alternative splicing events (DASEs) in TEPs, revealing several promising biomarkers for NSCLC, specifically in patients presenting with GGOs.

Methods

Patients with GGOs from two hospitals were prospectively enrolled [Hospital 1-Platelet (H1-P) and Hospital 2-Tissue (H2-T) in the validation cohort; Hospital 2-Platelet (H2-P) in the test cohort]. Benign/malignant diagnosis of GGOs was confirmed by pathological examination according to the World Health Organization (WHO) classification. TEPs from the H1-P cohort were collected for transcriptome sequencing and AS analysis. Chi-square tests, least absolute shrinkage and selection operator (LASSO) regression analysis, and protein-protein interaction (PPI) network were used for the preliminary screening of DASEs. Pathological tissue from the H2-T cohort was collected to validate the diagnostic efficacy of hub DASEs in NSCLC against the pathological gold standard. Moreover, TEPs from the H2-P cohort were used to assess the predictive performance of hub DASEs for GGOs using receiver operating characteristic (ROC) curves. Decision curve analysis (DCA) was used to determine whether diagnosing NSCLC in the GGOs population via hub DASEs could benefit patients.

Results

A total of 285 patients with GGOs were enrolled, including 151 NSCLC and 128 inflammatory nodules confirmed by pathological examination. Thirteen DASEs were screened with the chi-square test and LASSO regression analysis to identify diagnostic TEP AS markers for GGOs NSCLC. The PPI network identified four hub diagnostic-related alternative splice genes (DASGs) (TMEM219, MPV17, FIBP, and VPS28). Pathological tissues and platelets were collected to validate the four hub DASEs of these four hub DASGs. MXE-32112-TMEM219 yielded an area under the curve (AUC) of 0.82 [95% confidence interval (CI): 0.729-0.902], with a sensitivity of 83.33% and a specificity of 80.00%; RI-3259-VPS28 yielded an AUC of 0.77 (95% CI: 0.677-0.870) with a sensitivity of 93.33% and a specificity of 78.33%; and RI-3641-MPV17 yielded an AUC of 0.82 (95% CI: 0.728-0.901) with a sensitivity of 90.00% and a specificity of 80.00%. The DCA results suggested that using hub DASEs in diagnosing NSCLC in individuals with GGOs could provide benefits.

Conclusions

The specific diagnostic AS events (MXE-32112-TMEM219, RI-3259-VPS28, and RI-3641-MPV17) identified in TEP samples demonstrated high sensitivity and specificity for diagnosing NSCLC in patients with GGOs. These findings suggest that TEP-related AS events may serve as non-invasive biomarkers to guide biopsy decisions for NSCLC in GGOs, reducing unnecessary procedures.

Ultrasound Genomics Reveals a Signature for Predicting Breast Cancer Prognosis and Therapy Response

Background: Breast cancer (BC) in women is the most common malignancy worldwide, but there is still a lack of validated tools to accurately assess patient prognosis and response to available chemotherapy treatment regimens. Method: We collected ultrasound images and transcriptome data of BC from our breast center and public database. Key ultrasound features were then identified by using the support vector machine (SVM) algorithm and correlated with prognostic genes. Long-term survival-related genes were identified through differential expression analysis, and a prognostic evaluation model was established by using Cox regression. In addition, VPS28 from the model was identified as a promising biomarker for BC. Results: Using univariate logistic regression and SVM algorithms, we identified 12 ultrasound features significantly associated with chemotherapy response. Subsequent correlation and differential expression analyses linked 401 genes to these features, from which five key signature genes were derived using Lasso and multivariate Cox regression models. This signature not only facilitates the stratification of patients into risk-specific treatment pathways but also predicts their chemotherapy response, thus supporting personalized medicine in clinical settings. Notably, VPS28, in the signature, emerged as a significant biomarker, strongly associated with poor prognosis, greater tumor invasiveness, and differing expression across demographic groups. Conclusion: In this study, we use ultrasound genomics to reveal a signature that can provide an effective tool for prognostic assessment and predicting chemotherapy response in patients with BC.

Mechanism to disrupt ESCRT-mediated intracellular trafficking through Vps28-small molecules interaction: an in silico approach

The ESCRT (Endosomal Sorting Complex Required for Transport) machinery comprising protein complexes ESCRT-0 to ESCRT-III and Vps4 plays a pivotal role in intracellular trafficking, a process of endocytosing cell surface proteins into the cell for various biological activities. The ESCRT protein complexes are sequentially assembled which interact amongst each other to form a functional ESCRT machinery. Deregulation of these events are shown to be involved in various disease development including tumor formation and viral infections. Recently upregulation of a crucial ESCRT protein, Vps28 has been shown to be implicated in tumor formation. However, Vps28 in ESCRT-I interacts with Vps36 in ESCRT-II to function as a connecting protein during ESCRT machinery formation. Until now biomolecular approaches to inhibit the formation/assembly of ESCRT machinery have not been developed. Hence, we hypothesized that disrupting Vps28/Vps36 interaction would prevent assembly of ESCRT machinery and offer therapeutic potential to restrict disease development and progression. To address this, we utilized a virtual screening approach using a flavonoid-based library to identify potential small molecule inhibitors that can bind to Vps28 active site. Based on the binding affinity, top-hit compounds were identified. Molecular dynamics simulations set over a 500 ns timescale demonstrated the stability of the Vps28-small molecule complexes. Per-residue decomposition analysis using Molecular Mechanics/Poisson-Boltzmann surface area highlighted the significant contributions of active site residues Asn189, Arg190, Arg193 and Asn210 in Vps28 for interaction with small molecules. Absorption, Distribution, Metabolism, Excretion, and Toxicity analysis for toxicity evaluation indicates that molecules Z0131, H0194, Z0199 and DQ00112 exhibited physicochemical properties suitable for drug development.

The Tumor Suppressor Roles and Mechanisms of MiR-491 in Human Cancers

MicroRNAs (miRNAs) are short non-coding RNAs that bind to the 3' untranslated region (3'' UTR) of target mRNAs to control gene expression post-transcriptionally. Recent indications have highlighted their important roles in a variety of pathophysiological conditions as well as human malignancies. Dysregulated miRNAs act as tumor suppressor genes or oncogenes in a variety of cancers. MiR-491 has been shown to have a major effect on tumorigenesis in multiple malignancies through binding to specific genes and signaling cascades, thereby preventing cancer progression. This review provides an overview of miR-491 expression in regulatory mechanisms and biological procedures of tumor cells, as well as the prospective possible treatment effects of various types of human cancers.