Current Medicinal Chemistry

:Cardiovascular disease (CDV) represents the major cause of death globally. Atherosclerosis, as the primary cause of CVD, is a chronic immune-inflammatory disorder with complex multifactorial pathophysiology encompassing oxidative stress, enhanced immune-inflammatory cascade, endothelial dysfunction, and thrombosis. An initiating event in atherosclerosis is the subendothelial accumulation of low-density lipoprotein (LDL), followed by the localization of macrophages to fatty deposits on blood vessel walls, forming lipid-laden macrophages (foam cells) that secrete compounds involved in plaque formation. Given the fact that foam cells are one of the key culprits that underlie the pathophysiology of atherosclerosis, special attention has been paid to the investigation of the efficient therapeutic approach to overcome the dysregulation of metabolism of cholesterol in macrophages, decrease the foam cell formation and/or to force its degradation. Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a secretory serine proteinase that has emerged as a significant regulator of the lipid metabolism pathway. PCSK9 activation leads to the degradation of LDL receptors (LDLRs), increasing LDL cholesterol (LDL-C) levels in the circulation. PCSK9 pathway dysregulation has been identified as one of the mechanisms involved in atherosclerosis. In addition, microRNAs (miRNAs) are investigated as important epigenetic factors in the pathophysiology of atherosclerosis and dysregulation of lipid metabolism. This review article summarizes the recent findings connecting the role of PCSK9 in atherosclerosis and the involvement of various miRNAs in regulating the expression of PCSK9-related genes. We also discuss PCSK9 pathway-targeting therapeutic interventions based on PCSK9 inhibition, and miRNA levels manipulation by therapeutic agents.

:While a congestive heart failure patient will ultimately need an assist device or even a replacement heart as the disease progresses, not every patient is qualified for such advanced therapy. Such patients awaiting better circulatory support benefit from positive inotropes in the meantime as palliative care. These agents are often prescribed in patients with acute decompensated heart failure, with reduced left ventricular ejection fraction and symptoms of organ dysfunction. Although positive inotropes, for example, digoxin, dobutamine, milrinone, levosimendan, etc., are successfully marketed and in use, a lot of their adverse effects, like arrhythmias, hypotension, and even sudden cardiac death, are rather encouraging further research on the development of novel positive inotropes. This review has investigated the molecular mechanisms of some of these adverse effects in terms of the proteins they target, followed by research on newer targets. Studies from 2013-2023 that have reported new small molecules with positive inotropic effects have been revisited in order to determine the progress made so far in drug discovery.

Aims:Mechanism of fibroblasts in skin melanoma (SKME) revealed by single-cell RNA sequencing data.

Background:SKME is responsible for more than 80% of skin-related cancer deaths. Cancer-associated fibroblasts (CAFs) generate inflammatory factors, growth factors and extracellular matrix proteins to facilitate cancer cell growth, metastasis, drug resistance and immune exclusion. However, molecular mechanisms of CAFs in SKME are still lacking.

Objective:Our goal was to reveal the role of CAFs in SKME.

Methods:We downloaded the single-cell RNA sequencing (scRNA-seq) dataset from the Gene Expression Omnibus (GSE215120) database. Then, the Seurat package was applied to analyze the single-cell atlas of SKME data, and cell subsets were annotated with the CellMarker database. The molecular mechanisms of CAFs in SKME were disclosed via differential gene expression and enrichment analysis, Cellchat and SCENIC methods.

Results:Using scRNA-seq data, three SKME cases were used and downscaled and clustered to identify 11 cell subgroups and 5 CAF subsets. The enrichment of highly expressed genes among the 5 CAF subsets suggests that cell migration-inducing hyaluronan-binding protein (CEMIP) + fibroblasts and naked cuticle homolog 1 (NKD1) + fibroblasts were closely associated with epithelial to mesenchymal transition. Cellchat analysis revealed that CAF subpopulations promoted melanocyte proliferation through Jagged1 (JAG1)-Notch homolog 1 (NOTCH1), JAG1-NOTCH3 and migration through pleiotrophin (PTN)-syndecan-3 (SDC3) receptor-ligand pairs. The SCENIC analysis identified that most of the transcription factors in each CAF subpopulation played a certain role in the metastasis of melanoma and were highly expressed in metastatic SKME samples. Specifically, we observed that CEMIP+ fibroblasts and NKD1+ fibroblasts had potential roles in participating in immune therapy resistance. Collectively, we uncovered a single-- cell atlas of SKME and revealed the molecular mechanisms of CAFs in SKME development, providing a base for immune therapy and prognosis assessment.

Conclusion:Our study reveals that 5 CAFs in SKME have a promoting effect on melanocyte proliferation and metastasis. More importantly, CEMIP+ fibroblasts and NKD1+ fibroblasts displayed close connections with immune therapy resistance. These findings help provide a good basis for future immune therapy and prognosis assessment targeting CAFs in SKME.

Background:Gastric cancer is one of the most common malignant tumours of the gastrointestinal tract, which has a significant negative impact on human health.

Aims:CCL chemokines play important roles in a variety of tumor microenvironments; nevertheless, gastric cancer has surprisingly limited associations with CCL chemokines.

Methods:In our study, we comprehensively utilized bioinformatics analysis tools and databases such as cBioPortal, UALCAN, GEPIA, GeneMANIA, STRING, and TRRUST to clarify the clinical significance and biology function of CCL chemokines in gastric cancer.

Results:The mRNA expression levels of CCL1/3/4/5/7/8/14/15/18/20/21/22/26 were up-regulated, while the mRNA expression levels of CCL2/11/13/16/17/19/23/24/25/28 were down-regulated. The chemokine significantly associated with the pathological stage of gastric cancer is CCL2/11/19/21. In gastric cancer, the expression level of CCL chemokines was not associated with disease-free survival, but low expression of CCL14 was significantly associated with longer overall survival. Therein, associated with the regulation of CCL chemokines are only 10 transcription factors (RELA, NFKB1, STAT6, IRF3, REL, SPI1, STAT1, STAT3, JUN and SP1). The major biological process and functional enrichment of CCL chemokines are to induce cell-directed migration.

Conclusion:These results may indicate that CCL chemokines may be immunotherapeutic targets and promising prognostic biomarkers for gastric cancer.

Aims:The aims of this study were to determine hub genes in glaucoma through multiple machine learning algorithms.

Background:Glaucoma has afflicted many patients for many years, with excessive pressure in the eye continuously damaging the nervous system and leading to severe blindness. An effective molecular diagnostic method is currently lacking.

Objective:The present study attempted to reveal the molecular mechanism and gene regulatory network of hub genes in glaucoma, followed by an attempt to reveal the drug-gene-disease network regulated by hub genes.

Methods:A microarray sequencing dataset (GSE9944) was obtained through the Gene Expression Omnibus database. The differentially expressed genes in Glaucoma were identified. Based on these genes, we constructed three machine learning models for feature training, Random Forest model (RF), Least absolute shrinkage and selection operator regression model (LASSO), and Support Vector Machines model (SVM). Meanwhile, Weighted Gene Co-Expression Network Analysis (WGCNA) was performed for GSE9944 expression profiles to identify Glaucoma-related genes. The overlapping genes in the four groups were considered as hub genes of Glaucoma. Based on these genes, we also constructed a molecular diagnostic model of Glaucoma. In this study, we also performed molecular docking analysis to explore the gene-drug network targeting hub genes. In addition, we evaluated the immune cell infiltration landscape in Glaucoma samples and normal samples by applying CIBERSORT method.

Results:8 hub genes were determined: ATP6V0D1, PLEC, SLC25A1, HRSP12, PKN1, RHOD, TMEM158 and GSN. The diagnostic model showed excellent diagnostic performance (area under the curve=1). GSN might positively regulate T cell CD4 naïve as well as negatively regulate T cell regulation (Tregs). In addition, we constructed gene-drug networks in an attempt to explore novel therapeutic agents for Glaucoma.

Conclusion:Our results systematically determined 8 hub genes and established a molecular diagnostic model that allowed the diagnosis of Glaucoma. Our study provided a basis for future systematic studies of Glaucoma pathogenesis.