Personalized Drug Therapy: Innovative Concept Guided With Proteoformics.

Personalized medicine can reduce adverse effects, enhance drug efficacy, and optimize treatment outcomes, which represents the essence of personalized medicine in the pharmacy field. Protein drugs are crucial in the field of personalized drug therapy and are currently the mainstay, which possess higher target specificity and biological activity than small-molecule chemical drugs, making them efficient in regulating disease-related biological processes, and have significant potential in the development of personalized drugs. Currently, protein drugs are designed and developed for specific protein targets based on patient-specific protein data. However, due to the rapid development of two-dimensional gel electrophoresis and mass spectrometry, it is now widely recognized that a canonical protein actually includes multiple proteoforms, and the differences between these proteoforms will result in varying responses to drugs. The variation in the effects of different proteoforms can be significant and the impact can even alter the intended benefit of a drug, potentially making it harmful instead of lifesaving. As a result, we propose that protein drugs should shift from being targeted through the lens of protein (proteomics) to being targeted through the lens of proteoform (proteoformics). This will enable the development of personalized protein drugs that are better equipped to meet patients' specific needs and disease characteristics. With further development in the field of proteoformics, individualized drug therapy, especially personalized protein drugs aimed at proteoforms as a drug target, will improve the understanding of disease mechanisms, discovery of new drug targets and signaling pathways, provide a theoretical basis for the development of new drugs, aid doctors in conducting health risk assessments and making more cost-effective targeted prevention strategies conducted by artificial intelligence/machine learning, promote technological innovation, and provide more convenient treatment tailored to individualized patient profile, which will benefit the affected individuals and society at large.

[Research progress on risk prediction of cardiac arrest].

Cardiac arrest (CA) is a serious cardiac event, which has a high incidence and low survival rate at home and abroad. In order to predict the risk of CA in advance, a large number of studies have been conducted by relevant researchers. This paper mainly summarizes the characteristics and research status of the existing analysis and prediction of CA from three aspects: the risk prediction factors of CA, the evaluation index of risk prediction of CA and the early warning scoring system of CA. We hope it can help medical staff to understand the current progress in this field, and provide new ways and methods for predicting the risk of CA.

Antibacterial activity of a polysaccharide isolated from litchi (Litchi chinensis Sonn.) pericarp against Staphylococcus aureus and the mechanism investigation.

The long-term use of antibiotics can cause drug resistance. Natural polysaccharides are a novel means of treating bacterial infections, and the development and utilization of litchi pericarp polysaccharide (LPPs) as a bacteriostatic active substance offer a new research direction for the high-value utilization of litchi by-products. This study revealed that LPPs inhibited Staphylococcus aureus more than Escherichia coli, Listeria monocytogenes, and Salmonella typhimurium, with the minimum inhibitory concentrations of 145, 205, 325, and 445 µg/mL, respectively. The inhibitory activity of LPPs was insignificant for Bacillus subtilis at 505 µg/mL. The assessment of antibacterial mechanisms revealed that LPPs influenced the growth, conductivity, protein, and nucleic acid, reducing sugar, respiratory chain dehydrogenase activity, bacterial lipid peroxidation, intracellular adenosine triphosphate, and extracellular alkaline phosphatase levels of S. aureus. Of note, LPPs could modify the cell wall integrity and cell membrane permeability of S. aureus, resulting in the leakage of intracellular large and small molecules, inhibition of cellular respiratory metabolism, and oxidative losses. These processes exhibited an inhibitory effect and made the bacterium nonfunctional, thereby affecting its growth and metabolism or causing cell death. These findings provide support and insights into the potential application of LPPs as a natural antimicrobial agent.

Ubiquitinomics revealed disease- and stage-specific patterns relevant for the 3PM approach in human sigmoid colon cancers.

Objective: The patients with sigmoid colorectal cancer commonly show high mortality and poor prognosis. Increasing evidence has demonstrated that the ubiquitinated proteins and ubiquitination-mediated molecular pathways influence the growth and aggressiveness of colorectal cancer. It emphasizes the scientific merits of quantitative ubiquitinomics in human sigmoid colon cancer. We hypothesize that the ubiquitinome and ubiquitination-mediated pathway networks significantly differ in sigmoid colon cancers compared to controls, which offers the promise for in-depth insight into molecular mechanisms, discovery of effective therapeutic targets, and construction of reliable biomarkers in the framework of predictive, preventive, and personalized medicine (PPPM; 3P medicine). Methods: The first ubiquitinome analysis was performed with anti-K-ε-GG antibody beads (PTMScan ubiquitin remnant motif [K-ε-GG])-based label-free quantitative proteomics and bioinformatics to identify and quantify ubiquitination profiling between sigmoid colon cancer tissues and para-carcinoma tissues. A total of 100 human sigmoid colon cancer samples that included complete clinical information and the corresponding gene expression data were obtained from The Cancer Genome Atlas (TCGA). Ubiquitination was the main way of protein degradation; the relationships between differentially ubiquitinated proteins (DUPs) and their differently expressed genes (DEGs) and between DUPs and their differentially expressed proteins (DEPs) were analyzed between cancer tissues and control tissues. The overall survival of those DUPs was obtained with Kaplan-Meier method. Results: A total of 1249 ubiquitinated sites within 608 DUPs were identified in human sigmoid colon cancer tissues. KEGG pathway network analysis of these DUPs revealed 35 statistically significant signaling pathways, such as salmonella infection, glycolysis/gluconeogenesis, and ferroptosis. Gene Ontology (GO) analysis of 608 DUPs revealed that protein ubiquitination was involved in 98 biological processes, 64 cellular components, 51 molecule functions, and 26 immune system processes. Protein-protein interaction (PPI) network of 608 DUPs revealed multiple high-combined scores and co-expressed DUPs. The relationship analysis between DUPs and their DEGs found 4 types of relationship models, including DUP-up (increased ubiquitination level) and DEG-up (increased gene expression), DUP-up and DEG-down (decreased gene expression), DUP-down (decreased ubiquitination level) and DEG-up, and DUP-down and DEG-down. The relationship analysis between DUPs and their DEPs found 4 types of relationship models, including DUP-up and DEP-up (increased protein expression), DUP-up and DEP-down (decreased protein expression), DUP-down and DEP-up, and DUP-down and DEP-down. Survival analysis found 46 overall survival-related DUPs in sigmoid colon cancer, and the drug sensitivity of overall survival-related DUPs were identified. Conclusion: The study provided the first differentially ubiquitinated proteomic profiling, ubiquitination-involved signaling pathway network changes, and the relationship models between protein ubiquitination and its gene expression and between protein ubiquitination and its protein expression, in human sigmoid colon cancer. It offers the promise for deep insights into molecular mechanisms of sigmoid colon cancer, and discovery of effective therapeutic targets and biomarkers for patient stratification, predictive diagnosis, prognostic assessment, and personalized treatment in the context of 3P medicine. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00328-2.