An integrated approach to infer cross-talks between intracellular protein transport and signaling pathways

Community Detection in Protein-Protein Interaction Networks and Applications

The ability to identify and characterize not only the protein-protein interactions but also their internal modular organization through network analysis is fundamental for understanding the mechanisms of biological processes at the molecular level. Indeed, the detection of the network communities can enhance our understanding of the molecular basis of disease pathology, and promote drug discovery and disease treatment in personalized medicine. This work gives an overview of recent computational methods for the detection of protein complexes and functional modules in protein-protein interaction networks, also providing a focus on some of its applications. We propose a systematic reformulation of frequently adopted taxonomies for these methods, also proposing new categories to keep up with the most recent research. We review the literature of the last five years (2017-2021) and provide links to existing data and software resources. Finally, we survey recent works exploiting module identification and analysis, in the context of a variety of disease processes for biomarker identification and therapeutic target detection. Our review provides the interested reader with an up-to-date and self-contained view of the existing research, with links to state-of-the-art literature and resources, as well as hints on open issues and future research directions in complex detection and its applications.

Identification of Primary and Metastatic Lung Cancer-Related lncRNAs and Potential Targeted Drugs Based on ceRNA Network

Lung cancer metastasis is the leading cause of poor prognosis and death for patients. Long noncoding RNAs (lncRNAs) have been validated the close correlation with lung cancer metastasis, but few comprehensive analyses have reported the specific association between lncRNA and cancer metastasis, especially via both competing endogenous RNA (ceRNA) regulatory relationships and functional regulatory networks. Here, we constructed primary and metastatic ceRNA networks, identified 12 and 3 candidate lncRNAs for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) respectively and excavated some drugs that might have potential therapeutic effects on lung cancer progression. In summary, this study systematically analyzed the competitive relationships and regulatory mechanism of the repeatedly dysregulated lncRNAs in lung cancer carcinogenesis and metastasis, and provided a new idea for screening potential therapeutic drugs for lung cancer.

Fucosyltransferase 4 shapes oncogenic glycoproteome to drive metastasis of lung adenocarcinoma

BACKGROUND

Aberrant fucosylation plays a critical role in lung cancer progression. Nevertheless, the key fucosyltransferase with prognostic significance in lung cancer patients, the enzyme's intracellular targets, and complex molecular mechanisms underlying lung cancer metastasis remain incompletely understood.

METHODS

We performed a large-scale transcriptome-clinical correlation to identify major fucosyltransferases with significant prognostic values. Invasion, migration, cell adhesion assays were performed using lung cancer cells subject to genetic manipulation of FUT4 levels. Genome-wide RNA-seq and immunoprecipitation-mass spectrometry were used to characterize major cellular processes driven by FUT4, as well as profiling its intracellular protein targets. We also performed lung homing and metastasis assays in mouse xenograft models to determine in vivo phenotypes of high FUT4-expressing cancer cells.

FINDINGS

We show that FUT4 is associated with poor overall survival in lung adenocarcinoma patients. High FUT4 expression promotes lung cancer invasion, migration, epithelial-to-mesenchymal transition, and cell adhesion. FUT4-mediated aberrant fucosylation markedly activates multiple cellular processes, including membrane trafficking, cell cycle, and major oncogenic signaling pathways. The effects are independent of receptor tyrosine kinase mutations. Notably, genetic depletion of FUT4 or targeting FUT4-driven pathways diminishes lung colonization and distant metastases of lung cancer cells in mouse xenograft models.

INTERPRETATION

We propose that FUT4 can be a prognostic predictor and therapeutic target in lung cancer metastasis. Our data provide a scientific basis for a potential therapeutic strategy using targeted therapy in a subset of patients with high FUT4-expressing tumors with no targetable mutations.