Current Medicinal Chemistry - Online First

Cartilage oligomeric matrix protein (COMP) is a protein that has been implicated in the development of some tumors, but its exact role in gastric cancer (GC) remains unclear.

The study aims to comprehensively examine COMP in GC and to confirm its effects through experimental methods.

The research harnessed data from the Cancer Genome Atlas (TCGA) to explore the significance of COMP in GC and its potential as a diagnostic tool. The study also examined the regulatory networks involving COMP, including its interactions with immune cells, immune checkpoint genes, tumor mutational burden (TMB), microsatellite instability (MSI), and the stemness index based on mRNA expression (mRNAsi). Additionally, the study explored the relationship between COMP expression and drug sensitivity in GC. Genomic variations of COMP in GC were assessed. The expression of COMP was validated by the GEPIA2 tool and confirmed with quantitative reverse transcription PCR (qRT-PCR) in cell lines (normal human gastric epithelial cells GES-1 and GC cell lines AGS and HGC-27).

Abnormal expression patterns of COMP were observed in various cancers, including GC. Higher levels of COMP in GC were significantly associated with the pathologic T stage and a history of reflux (p < 0.05 for both). Elevated COMP expression was correlated with poorer progression-free survival (PFS) (p = 0.027). COMP expression levels were identified as an independent prognostic factor for GC (p = 0.017). COMP was linked to TCF-dependent signaling in response to ECM receptor interaction, focal adhesion, and other pathways. There was an association between COMP expression and immune infiltration, immune checkpoint genes, TMB/MSI, and mRNAsi in GC. COMP expression was inversely correlated with the sensitivity to several drugs, indicating that higher levels of COMP may reduce the effectiveness of these drugs. COMP was found to be significantly up-regulated in GC cell lines.

COMP could serve as a prognostic biomarker and a potential therapeutic target for the treatment of GC.

Collagen type IV alpha 1 chain (COL4A1), which has been proven to be a potential biomarker in Gastric Cancer (GC), but its role in tumors and the tumor microenvironment (TME) needs further explanation.

We analysed the relationship between COL4A1 and clinical characteristics based on The Cancer Genome Atlas (TCGA) database and verified by tissue microarrays as well as GC cell lines using immunohistochemistry, Q-PCR, Western blot, cell proliferation assays, colony formation assays, cell invasion and migration assays. The immune infiltration and drug sensitivity information between high and low COL4A1 expression were analysed by R package and pRRophetic package. Finally, we established a nomogram based on COL4A1 expression using the bootstrap method.

COL4A1 was overexpressed in gastric carcinoma compared with normal gastric tissue, indicating a poor prognosis of GC patients in the TCGA database which were also validated by GC tissue microarrays. GO, KEGG and hallmark enrichment analyses indicated that COL4A1 was mainly associated with the extracellular matrix than malignant proliferation. By siRNA transfection, we found that COL4A1 knockdown inhibited cell colony formation, invasion and migration but did not affect cell proliferation, similar to previous results. Immune infiltration and drug sensitivity analysis showed that COL4A1 was negatively correlated with antitumor immunity and positively correlated with multidrug resistance. By developing a nomogram model based on 8 risk factors, including COL4A1, patients with better clinical outcomes could be accurately distinguished.

COL4A1 is identified as a prognostic marker and potential therapeutic target in gastric cancer. Its overexpression correlates with poor prognosis, tumor invasion, and immunosuppression. A nomogram based on COL4A1 can predict patient outcomes. Future research should validate these findings and explore targeted therapies.

ZNF280A, a pivotal member of the zinc finger protein family, is significantly involved in vital cellular functions including cell proliferation, programmed cell death, cellular invasion, metastasis, and resistance to therapeutic drugs across various malignancies. However, its comprehensive role in pan-cancer has not been thoroughly investigated.

This research aims to elucidate the oncogenic and immunological functions of ZNF280A across different types of cancer. We conducted an extensive analysis of ZNF280A expression levels, prognostic significance, functional pathways, methylation status, and interactions with immune cells, while also examining immune infiltration patterns and responses to immunotherapy using diverse databases.

Our findings reveal that ZNF280A expression is significantly upregulated in numerous cancers, correlating with adverse patient prognosis. This association appears to be linked to its involvement in key cancer-related pathways, including the Ras signaling pathway, and its correlation with ZNF280A methylation levels, microsatellite instability (MSI), tumor mutational burden (TMB), and the dynamics of immune cells. Notably, ZNF280A seems to undermine anti-tumor immunity and the effectiveness of immunotherapeutic approaches by promoting the infiltration of immune cells and compromising the functionality of cytotoxic T lymphocytes.

These findings suggest that ZNF280A holds promise as a valuable indicator for forecasting patient outcomes and assessing the effectiveness of immunotherapy, thereby opening avenues for further exploration into targeted therapeutic approaches.

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.

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.