Publications by authors named "Jialuo Xu"

Esophageal squamous cell carcinoma (ESCC) accounts for about 90% of esophageal cancer cases. The lack of effective therapeutic targets makes it difficult to improve the overall survival of patients with ESCC. Reticulon 4 Interacting Protein 1 (RTN4IP1) is a novel mitochondrial oxidoreductase.

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The identification of cancer driver genes is crucial for understanding the complex processes involved in cancer development, progression, and therapeutic strategies. Multi-omics data and biological networks provided by numerous databases enable the application of graph deep learning techniques that incorporate network structures into the deep learning framework. However, most existing methods do not account for the heterophily in the biological networks, which hinders the improvement of model performance.

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Article Synopsis
  • The study highlights the complexity of cancer development, which involves genetic abnormalities, and emphasizes the importance of identifying cancer-related genes for early detection and tailored treatments.
  • Recent research has employed advanced graph deep learning techniques to pinpoint cancer driver genes, but issues like network incompleteness can hinder model performance.
  • The proposed method, using self-supervision in graph convolutional networks, improves network structure and predictive accuracy, showing strong results in reliability tests with high AUROC, AUPRC, and F1 scores.
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T-LAK-originated protein kinase (TOPK), a dual specificity serine/threonine kinase, is up-regulated and related to poor prognosis in many types of cancers. Y-box binding protein 1 (YB1) is a DNA/RNA binding protein and serves important roles in multiple cellular processes. Here, we reported that TOPK and YB1 were both highly expressed in esophageal cancer (EC) and correlated with poor prognosis.

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