SKA3, negatively regulated by miR-128-3p, promotes the progression of non-small-cell lung cancer

SKA3 promotes lung adenocarcinoma progression via the EGFR/E2F1/SKA3/integrin β1 signaling loop

Spindle and kinetochore-associated complex subunit 3 (SKA3) contributes to tumor growth and metastasis, but its specific roles have not been clearly elucidated. In this study, we found that SKA3 contributed to lung adenocarcinoma (LUAD) progression by interacting with integrin β1. The expression characteristics of SKA3 in LUAD patients were analyzed by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets and validated in 33 paired LUAD tissues by immunohistochemistry. Our data confirmed that SKA3 was a crucial regulator of LUAD progression and was associated with worse patient survival. In vitro and in vivo studies showed that SKA3 increased cell migration and invasion. Mechanistically, it was demonstrated that SKA3 could bind to integrin β1 and promote its activation, which further promoted the activation of EGFR. As a positive feedback loop, the activation of EGFR in turn promoted the expression of SKA3 via E2F1-mediated transcriptional regulation. Inhibition of EGFR with AZD9291 blocked SKA3 signaling induced by E2F1. These results indicated that SKA3 was crucial for the activation of EGFR and its downstream signaling pathway. Our findings uncovered the oncogenic role of SKA3 in LUAD progression and elucidated a novel EGFR/E2F1/SKA3/integrin β1 signaling loop, providing a potential SKA3-directed therapeutic strategy for LUAD patients.

Pan-Cancer Analysis Reveals SKA3 as a Potential Diagnostic and Prognostic Biomarker

SKA3, an important factor in cell cycle regulation, is involved in spindle assembly and kinetochore function, playing a critical role in maintaining cancer cell proliferation and division. However, its specific roles and regulatory mechanisms in cancer remain not fully understood. Large-scale datasets from multiple public databases, including The Cancer Genome Atlas and Genotype-Tissue Expression, covering various cancer types, were integrated. Systematic analysis revealed that SKA3 exhibits aberrant expression patterns in multiple cancers and is significantly associated with tumor progression and poor patient prognosis in certain cancers. We explored the status of SKA3 gene mutation, gene amplification and promoter region methylation in various tumors. In the context of immunotherapy, we assessed the value of SKA3 in cancer. Analyzing the correlation between SKA3 expression levels and immune checkpoints and immune cell infiltration, we discovered that SKA3 could serve as a novel immunotherapy biomarker across multiple cancers, guiding clinical immunotherapy decisions. Finally, SKA3 knockdown inhibited lung adenocarcinoma cell proliferation and metastasis. In conclusion, this study provides new insights into the role of SKA3 in cancer and offers significant theoretical and experimental evidence for its development as a diagnostic and prognostic biomarker.

A miRNA-disease association prediction model based on tree-path global feature extraction and fully connected artificial neural network with multi-head self-attention mechanism

BACKGROUND

MicroRNAs (miRNAs) emerge in various organisms, ranging from viruses to humans, and play crucial regulatory roles within cells, participating in a variety of biological processes. In numerous prediction methods for miRNA-disease associations, the issue of over-dependence on both similarity measurement data and the association matrix still hasn't been improved. In this paper, a miRNA-Disease association prediction model (called TP-MDA) based on tree path global feature extraction and fully connected artificial neural network (FANN) with multi-head self-attention mechanism is proposed. The TP-MDA model utilizes an association tree structure to represent the data relationships, multi-head self-attention mechanism for extracting feature vectors, and fully connected artificial neural network with 5-fold cross-validation for model training.

RESULTS

The experimental results indicate that the TP-MDA model outperforms the other comparative models, AUC is 0.9714. In the case studies of miRNAs associated with colorectal cancer and lung cancer, among the top 15 miRNAs predicted by the model, 12 in colorectal cancer and 15 in lung cancer were validated respectively, the accuracy is as high as 0.9227.

CONCLUSIONS

The model proposed in this paper can accurately predict the miRNA-disease association, and can serve as a valuable reference for data mining and association prediction in the fields of life sciences, biology, and disease genetics, among others.

SKA3 targeted therapies in cancer precision surgery: bridging bench discoveries to clinical applications - review article

Spindle and kinetochore-associated complex subunit 3 (SKA3) is a microtubule-binding subcomplex of the outer kinetochore, which plays a vital role in proper chromosomal segregation and cell division. Recently, SKA3 have been demonstrated its oncogenic role of tumorigenesis and development in cancers. In this review, the authors comprehensively deciphered SKA3 in human cancer from various aspects, including bibliometrics, pan-cancer analysis, and narrative summary. The authors also provided the top 10 predicted drugs targeting SKA3. The authors proposed that SKA3 was a potential target and brought new therapeutic opportunities for cancer patients.

Comprehensive analysis of circulating cell-free RNAs in blood for diagnosing non-small cell lung cancer

Early screening and detection of non-small cell lung cancer (NSCLC) is crucial due to the significantly low survival rate in advanced stages. Blood-based liquid biopsy is non-invasive test to assistant disease diagnosis, while cell-free RNA is one of the promising biomarkers in blood. However, the disease related signatures have not been explored completely for most cell-free RNA transcriptome sequencing (cfRNA-Seq) datasets. To address this gap, we developed a comprehensive cfRNA-Seq pipeline for data analysis and constructed a machine learning model to facilitate noninvasive early diagnosis of NSCLC. The results of our study have demonstrated the identification of differential mRNA, lncRNAs and miRNAs from cfRNA-Seq, which have exhibited significant association with development and progression of lung cancer. The classifier based on gene expression signatures achieved an impressive area under the curve (AUC) of up to 0.9, indicating high specificity and sensitivity in both cross-validation and independent test. Furthermore, the analysis of T cell and B cell immune repertoire extracted from cfRNA-Seq have provided insights into the immune status of cancer patients, while the microbiome analysis has revealed distinct bacterial and viral profiles between NSCLC and normal samples. In our future work, we aim to validate the existence of cancer associated T cell receptors (TCR)/B cell receptors (BCR) and microorganisms, and subsequently integrate all identified signatures into diagnostic model to improve the prediction accuracy. This study not only provided a comprehensive analysis pipeline for cfRNA-Seq dataset but also highlights the potential of cfRNAs as promising biomarkers and models for early NSCLC diagnosis, emphasizing their importance in clinical settings.

Transcription factor ZEB1 regulates PLK1-mediated SKA3 phosphorylation to promote lung cancer cell proliferation, migration and cell cycle

Lung cancer (LC) is one of the most common malignancies worldwide with low 5-year survival rate. The mechanism of spindle and kinetochore-associated complex subunit 3 (SKA3) in LC tumorgenesis remains largely unclear. The expression of SKA3 in LC cells was detected by quantitative PCR. Cell proliferation, migration and cell cycle were evaluated by functional assays including 5-ethynyl-2'-deoxyuridine, wound healing, transwell assays and flow cytometry analysis. Bioinformatics analysis, chromatin immunoprecipitation, luciferase reporter, co-immunoprecipitation and in vitro phosphorylation assays were applied to explore the interactions between zinc finger E-box binding homeobox 1 (ZEB1) and SKA3/polo-like kinase 1 (PLK1). SKA3 is highly expressed in LC cell lines and drives LC cell proliferation, migration and cell cycle. PLK1 also enhances the malignancy of LC cells. PLK1 can mediate SKA3 phosphorylation and enhance the stability of SKA3 protein, thus promoting LC progression. Besides, we found that transcription factor ZEB1 transcriptionally activates SKA3/PLK1 expression, contributing to LC cell malignancy. This study demonstrated that transcription factor ZEB1 modulates PLK1-mediated SKA3 phosphorylation to accelerate LC cell growth, migration and cycle, which might offer novel insight into LC treatment.