Mingyuan Zou

Identifying genes involved in cancer is crucial for understanding the underlying molecular mechanisms of the disease and developing effective treatment strategies. Differential expression analysis (DEA) is the predominant method used to identify cancer‐related genes. This approach involves comparing gene expression levels between different samples, such as cancerous and non‐cancerous tissues, to identify genes that are significantly upregulated or downregulated in cancer. DEA is based on the commonly believed assumption that genes upregulated in cancerous tissues have the potential to function as oncogenes. Their expression levels often correlate with cancer advancement and unfavorable prognosis, whereas downregulated genes display the opposite correlation. However, contrary to the prevailing belief, our analysis utilizing The Cancer Genome Atlas (TCGA) databases revealed that the upregulated or downregulated genes in cancer do not always align with cancer progression or prognosis. These findings emphasize the need for alternative approaches for identifying cancer‐related genes that may be more accurate and effective. To address this need, we compared the effectiveness of machine learning (ML) methods with that of traditional DEA in the identification of cancer‐related genes. ML algorithms have the advantage of being able to analyze large‐scale genomic data and identify complex patterns that may go unnoticed by traditional methods. Our results demonstrated that ML methods significantly outperformed DEA in the screening of cancer‐related genes.

Background: Multiple organ injury and dysfunction often occurs in acute critical illness and adversely affects survival. However, in patients who survive, organ function usually recovers without permanent damage. It is, therefore, likely that there are reversible mechanisms, but this is poorly understood in the pathogenesis of multiple organ dysfunction syndrome (MODS). Aims: Based on our knowledge of extracellular histones and pneumolysin, as endogenous and exogenous pore-forming toxins, respectively, here we clarify if the extent of cell membrane disruption and recovery is important in MODS. Methods: This is a combination of retrospective clinical studies of a cohort of 98 patients from an intensive care unit (ICU) in a tertiary hospital, with interventional animal models and laboratory investigation. Results: In patients without septic shock and/or disseminate intravascular coagulation (DIC), circulating histones also strongly correlated with sequential organ failure assessment (SOFA) scores, suggesting their pore-forming property might play an important role. In vivo, histones or pneumolysin infusion similarly caused significant elevation of cell damage markers and multiple organ injury. In trauma and sepsis models, circulating histones strongly correlated with these markers, and anti-histone reagents significantly reduced their release. Comparison of pneumolysin deletion and its parental strain-induced sepsis mouse model showed that pneumolysin was not essential for sepsis development, but enhanced multiple organ damage and reduced survival time. In vitro, histones and pneumolysin treatment disrupt cell membrane integrity, resulting in changes in whole-cell currents and elevated intracellular Ca²⁺ to lead to Ca²⁺ overload. Cell-specific damage markers, lactate dehydrogenase (LDH), alanine aminotransferase (ALT), and cardiac troponin I (cTnI), were released from damaged cells. Once toxins were removed, cell membrane damage could be rapidly repaired and cellular function recovered. Conclusion: This work has confirmed the importance of pore-forming toxins in the development of MODS and proposed a potential mechanism to explain the reversibility of MODS. This may form the foundation for the development of effective therapies.

Unc-5 netrin receptor A (UNC5A), a netrin family receptor, plays a key role in neuronal development and subsequent differentiation. Recently, studies have found that UNC5A plays an important role in multiple cancers, such as bladder cancer, non-small cell lung carcinoma, and colon cancer but its pan-cancer function is largely unknown. Herein, the R software and multiple databases or online websites (The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx), The Tumor Immune Estimation Resource (TIMER), The Gene Set Cancer Analysis (GSCA), Gene Expression Profiling Interactive Analysis (GEPIA), and cBioPortal etc.) were utilized to examine the role of UNC5A in pan-cancer. UNC5A was found to be highly expressed across multiple human cancer tissues and cells, was linked to clinical outcomes of patients, and was a potential pan-cancer biomarker. The mutational landscape of UNC5A exhibited that patients with UNC5A mutations had poorer progress free survival (PFS) in head and neck squamous cell carcinoma (HNSC) and prostate adenocarcinoma (PRAD). Furthermore, UNC5A expression was associated with tumor mutation burden (TMB), neoantigen, tumor microenvironment (TME), tumor microsatellite instability (MSI), immunomodulators, immune infiltration, DNA methylation, immune checkpoint (ICP) genes, and drug responses. Our results suggest the potential of UNC5A as a pan-cancer biomarker and an efficient immunotherapy target, which may also guide drug selection for some specific cancer types in clinical practice.

The emergence of drug-resistant bacteria emphasizes the urgent need for novel antibiotics. The antimicrobial peptide TS shows extensive antibacterial activity in vitro and in vivo, especially in gram-negative bacteria; however, its antibacterial mechanism is unclear. Here, we find that TS without hemolytic activity disrupts the integrity of the outer bacterial cell membrane by displacing divalent cations and competitively binding lipopolysaccharides. In addition, the antimicrobial peptide TS can inhibit and kill E. coli by disintegrating the bacteria from within by interacting with bacterial DNA. Thus, antimicrobial peptide TS’s multiple antibacterial mechanisms may not easily induce bacterial resistance, suggesting use as an antibacterial drug to be for combating bacterial infections in the future.

In recent decades, selectively inducing tumor vascular thrombosis, followed by necrosis of tumor tissues has been a promising and potential anticancer strategy. In this report, we prepared a kind of vascular targeting drug that consists of anti-neuropilin-1 monoclonal antibody (anti-NRP-1 mAb) and truncated tissue factor (tTF). Anti-NRP-1 mAb could guide tTF to the surface of tumor vascular endothelial cells and lead to subsequent vascular embolization. This vascular targeting drug, which is also one of the antibody drug conjugates, was generated using a coupling method with water-soluble 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide and N-hydroxysulfosuccimide. Afterwards, in-vitro and in-vivo assays were performed to characterize its potential coagulation ability and antitumor activity. In-vitro experiments indicated that tTF-anti-NRP-1 monoclonal antibody (tTF–mAb) retained both the targeting activity of anti-NRP-1 mAb and the procoagulant activity of tTF. Live imaging system was used to assess its biodistribution and tumor-binding capability, which also yielded promising results. Furthermore, in-vivo studies showed that tTF–mAb was capable of significantly inducing tumor vascular thrombosis and inhibiting tumor growth in nude mice bearing subcutaneous xenografts, and histopathologic changes were rarely observed in normal organs.