Current Medicinal Chemistry - Online First

Ovarian cancer (OV) is one of the deadliest gynecologic cancers, and approximately 75% of serous ovarian cancer (SOC) patients are diagnosed at advanced stages due to the lack of effective biomarkers.

Immunogenic cell death (ICD) has been investigated in many comprehensive studies, and the role of ICD in ovarian cancer and its impact on immunotherapy is not yet known.

The NMF clustering analysis was employed to categorize OV samples into different subgroups. Survival, mutation, and CNV analyses were performed in these clusters. ESTIMATE, CIBERSORT, TIDE, and drug sensitivity analyses (based on GDSC) were also performed on the subtypes. Then, differentially expressed immunogenic cell death genes (DE-ICDGs) in OV were obtained by crossing the DEGs between cluster3 vs. cluster1, DEGs from the TCGA-GTEx dataset, and DEGs from the GSE40595 dataset. Functional enrichment analysis of DE-ICDGs was then performed. The signature genes related to the prognosis of OV in three OV datasets were excavated by drawing Kaplan-Meier curves. Finally, quantitative real-time PCR (qRT-PCR) was performed to verify the expression trends of the signature genes.

The NMF clustering analysis categorized OV samples into three distinct groups according to the expression levels of ICDGs, with differential analysis indicating that Cluster3 represented the subgroup with high ICD expression. Mutation and CNV analysis did not differ significantly between clusters, but Amp and Del's numbers did. Immuno-infiltration analysis revealed that cluster3 showed significant differences from cluster1 and cluster2. Immunotherapy and drug sensitivity analysis showed differences in immunotherapy and chemotherapy sensitivity between the clusters. The DEGs in cluster3 vs. cluster1, TCGA-GTEx dataset and GSE40595 dataset were intersected to obtain a total of 71 DE-ICDGs, and functional enrichment result suggested that the DE-ICDGs were significantly correlated with inflammatory response, complement system and positive regulation of cytokine production. 2 DE-ICDGs (FN1 and LUM) were identified that were associated with OV prognosis and were validated significantly down-regulated in the SOC group with PCR.

We identified ICD-associated subtypes of OV and mined 2 OV prognostic genes (FN1 and LUM) associated with ICD, which may have important implications for OV prognosis and therapy.

As the leading cause of cancer-related deaths globally, colorectal cancer (CRC) ranks third in prevalence. Gene Expression Omnibus (GEO) offers clinicians and bioinformaticians an accessible platform for genomic research across various cancer types, with a particular emphasis on CRC.

We aim to uncover key genes and pathways in the Chinese CRC population.

We identified differentially expressed genes (DEGs) in CRC utilizing four microarray datasets sourced from the GEO database, all specifically from the Chinese population. Functional enrichment analysis was conducted to uncover the molecular mechanisms at play in CRC. The PPI network and CytoHubba tools were employed to identify key genes linked to CRC, with further validation through databases such as Gene Expression Profiling Interactive Analysis (GEPIA), ONCOMINE, and the Human Protein Atlas (HPA).

Our analysis identified 188 DEGs with overlapping significance, comprising 97 up-regulated and 91 down-regulated genes. Gene Ontology (GO) analysis indicated that up-regulated DEGs were predominantly involved in the extracellular space. In contrast, the down-regulated ones were linked to bicarbonate transport and extracellular exosomes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis highlighted the involvement of up-regulated DEGs in cytokine-cytokine receptor interactions and the TNF signaling pathway. In contrast, the down-regulated genes were associated with nitrogen metabolism and bicarbonate reclamation in the proximal tubule. Notably, the transcriptional levels of CCL20, CDC20, CXCL1, CXCL2, CXCL5, NEK2, and PPBP were elevated in CRC tissues compared to normal tissues. In addition, CXCL12 showed a decreased expression. Additionally, the translational levels of CDC20 and PPBP were found to be higher in CRC tissues.

Eight genes (CCL20, CDC20, CXCL1, CXCL12, CXCL2, CXCL5, NEK2, and PPBP) were identified as potential diagnostic indicators for CRC. The identified pathways, such as cytokine-cytokine receptor interactions and TNF signaling, along with nitrogen metabolism and bicarbonate reclamation in the proximal tubule, are hypothesized to have a role in the genesis and progression of CRC. This study provides unique insights into the etiology and progression of CRC within the Chinese population.

Intellectual disability (ID) is characterized by impairments in cognitive functioning and adaptive behavior. Globally, it affects 1-3% of the general population, with an increased prevalence in consanguineous families. It is a clinically heterogeneous disorder that can manifest as a variable phenotype. Intellectual developmental disorder and retinitis pigmentosa (IDDRP) is a rare syndrome in which patients present with both ID and retinitis pigmentosa.

This study examined a consanguineous family to identify disease-associated pathogenic mutations and elucidate their potential functional impact in patients with IDDRP.

Clinical assessment of the patients revealed characteristics consistent with both intellectual disability (ID) and retinitis pigmentosa. Individuals affected by IDDRP were subjected to whole exome sequencing (WES), and the identified candidate pathogenic variants were validated by Sanger sequencing. Computational analyses were conducted to evaluate the impact of these mutations on the protein structure and function.

WES identified a protein-truncating variant, c.2605A>T (p.Lys869Ter), in the S-phase cyclin A-associated protein in the endoplasmic reticulum (SCAPER) gene. SCAPER has previously been reported to cause IDDRP. In silico analyses revealed structural and interactional alterations in the SCAPER protein. This variant is novel in the Pakistani population and has not been previously reported. This variant exhibits an autosomal recessive mode of inheritance and segregates among the investigated affected and unaffected family members.

The present study expands the spectrum of disease-causing variants in SCAPER and will contribute to a better understanding of the genetic etiology of IDDRP.

Hormone signaling plays a significant role in cancerogenesis. This review presents a comprehensive analysis of FDA-approved drugs, as well as recent clinical trials of drugs acting on hormone signaling pathways. It discusses traditional methods of hormonal cancer therapy and identifies new mechanisms in cancer hormonal signaling. The review has made use of the databases Clinicaltrials.gov and PubMed to find new trends in the development of anti-cancer drugs and related hormonal-dependent mechanisms of breast cancer.

A search of the Drugs@FDA database was conducted to identify pharmaceutical agents approved by the FDA for the treatment of hormone-dependent breast tumors. The clinical trials for these drugs were obtained from ClinicalTrials.gov. The search was expanded from 2018 to early 2024. The keywords used in the search for information were breast cancer, hormonal signaling pathways, luminal types of breast cancer, and hormone-dependent breast cancer. The drug targets, pharmacological information, and clinical data were obtained from the PubMed database.

An analysis of the ClinicalTrials.gov database revealed that the pharmacokinetic direction has significant potential for the discovery of new drugs. The metabolites of SERMs metabolites and their combination have the potential to enhance the efficiency of prodrug. Small molecules can penetrate through the blood-brain-barrier, making them a promising avenue for treating brain metastasis. New SERDs, such as ZB716, exhibit superior oral bioavailability compared to fulvestrant, which is solely administered via injection. The investigation of the signaling hormonal pathways of BC allows for the enhancement of personalised anti-cancer therapy and the overcoming of resistance. Consequently, the specific mechanism of action of ARV-471 (the PROTAC group) enhances sensitivity to drug-resistant targets and affects non-enzymatic functions. Furthermore, PROTACs exhibit markedly enhanced target selectivity in comparison to traditional inhibitors. The combination of endocrine therapy for breast cancer with compounds that target mTOR, PI3K, CDK4/6, and other pathways holds considerable promise. The combination of letrozole with everolimus demonstrated the most promising outcome, with a median progression-free survival period of 22 months, a significant improvement over the 9-month median progression-free survival observed in monotherapy with letrozole.

It is evident that traditional endocrine treatments play a pivotal role in the management of HR+ BC. However, the emergence of resistance necessitates the development of novel therapeutic strategies. These strategies should be based on pharmacokinetics, further investigation of the molecular signaling pathways of BC, such as new SERMs, SERDs, PROTACs, as well as new drug groups, like SERCAs, CERANs, SHERPAs. Combination therapy represents the most promising avenue for BC treatment. While PROTAC combination with new monotherapeutic agents for BC treatment has yet to be investigated, we believe that such combinations have the potential to make the treatment more selective, effective, and personalised in the future.

This study aimed to construct a diagnostic risk model for Bipolar Disorder (BD) using inflammation-related genes (IRGs) and to explore the role of immune cell infiltration in BD pathogenesis.

BD datasets (GSE23848, GSE124326, GSE39653, and GSE46449) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the edgeR package. The intersection of DEGs and IRGs was defined as differentially expressed IRGs. A LASSO regression model was used to identify optimal biomarkers, which were then utilized to construct a diagnostic risk model. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic accuracy of the biomarkers. Internal validation was performed with GSE124326, while external validation utilized GSE23848, GSE39653, and GSE46449. The xCell module in the IOBR package was employed to assess immune cell infiltration proportions. The relationship between IRGs, the diagnostic risk model, and immune cell dynamics was further analyzed.

A total of 2345 DEGs were identified in GSE124326. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicated that inflammatory pathways are critically involved in BD pathogenesis. A total of 69 BD-related IRGs were identified. Six key IRGs (IL33, DNASE1L3, IL2RA, CD70, CLEC5A, and SLPI) were identified through LASSO regression analysis and used to develop a diagnostic risk model. Internal and external validations confirmed the robust diagnostic performance of the risk model. Immuno-infiltration analysis showed significant differences in immune cell infiltration between BD patients and healthy controls. The diagnostic risk model and four potential biomarkers (DNASE1L3, IL2RA, CD70, and SLPI) showed strong correlations with various immune cell types.

A diagnostic risk model for BD was constructed based on IRGs, highlighting the critical role of immune cell infiltration in BD pathogenesis.

Endothelial dysfunction (ED) results from impaired vascular endothelial cell function, disrupting key processes such as hemostasis, vascular tone regulation, vasculogenesis, angiogenesis, and inflammation. These processes are mediated by a complex signaling network involving hormones, cytokines, and chemokines. ED is recognized as a major contributor to the onset and progression of several micro- and macrovascular diseases, including diabetes. Our previous study demonstrated that the polyphenol Rosolic acid (RA) protects against endoplasmic reticulum (ER) stress-induced ED in vitro by activating nuclear factor erythroid 2-related factor 2 (Nrf2). Additionally, RA enhanced the proliferation and survival of pancreatic β-cells in a co-culture model with endothelial cells under ER stress conditions.

In this study, we investigated RA's protective effects against diabetes-induced ED using high-fat diet (HFD)-fed and streptozotocin-induced type-2 diabetic rat models. We evaluated RA’s impact on vascular function and metabolic parameters in these models.

RA significantly mitigated diabetes-induced ED in the aortic tissues of HFD-fed diabetic Wistar rats. RA treatment improved glucose tolerance and reduced hyperlipidemia, showing efficacy comparable to the anti-diabetic drug Gliclazide. Moreover, RA elevated Nrf2 levels and its downstream target genes in aortic tissues while reducing ED markers such as Intercellular Adhesion Molecule 1 (ICAM1), vascular cell adhesion molecule 1 (VCAM1), and endothelin-1.

These findings highlight RA as a promising therapeutic agent for diabetes and its associated vascular complications, with potential for broader clinical applications.