MCM-2, Ki-67, and EGFR downregulated expression levels in advanced stage laryngeal squamous cell carcinoma

Evaluation of Some Prognostic Biomarkers in Human Papillomavirus-Related Multiphenotypic Sinonasal Carcinoma

Background

Human papillomavirus (HPV)-related multi phenotypic sinonasal carcinoma (HMSC) is a recently described tumor subtype with an unknown prognosis, often misdiagnosed with other sinonasal carcinomas, and associated with high-risk HPV (HR-HPV). The present study aimed to evaluate the expression of vascular endothelial growth factor (VEGF), Bcl-2-associated X protein (BAX), epidermal growth factor receptors (EGFR), ProExTMC, and human telomerase reverse transcriptase (hTERT) and assess their association with survival and clinicopathological characteristics.

Methods

Between 2017 and 2022, 40 HMSC patients underwent surgical resection at the School of Medicine, Zagazig University Hospitals (Zagazig, Egypt). Tissue samples were examined for the presence of HR-HPV; absence of myeloblastosis (MYB), MYB proto-oncogene like 1 (MYBL1), and nuclear factor I/B (NFIB) fusions and the presence of myoepithelial proteins (calponin, S100, SMA), squamous differentiation markers (p63, p40, calponin), VEGF, BAX, ProExTMC, and hTERT by immunohistochemistry. All patients were followed up for about 54 months until death or the last known survival data. Data were analyzed using the Chi square test and Kaplan-Meier method.

Results

The expression of VEGF, hTERT, and ProExTMC was significantly associated with age, advanced tumor stages, lymph node metastasis, tumor size, mortality, relapse, poor disease-free survival (DFS), and overall survival (OS) (P<0.001). BAX expression was significantly associated with tumor size, age, poor DFS, and relapse (P=0.01, P<0.001, P=0.035, and P=0.002, respectively).

Conclusion

HMSC is strongly associated with HR-HPV. The expression of VEGF, EGFR, BAX, hTERT, and ProExTMC is associated with aggressive malignant behavior, poor survival, and poor prognosis, making them novel prognostic biomarkers for targeted therapeutics in HMSC.

Protein expression analysis for predicting recurrent laryngeal squamous cell carcinoma

The expression of a number of proteins plays a major role in predicting recurrent laryngeal squamous cell carcinoma (LSCC). Thus, the aim of the present study was to investigate the expression of 16 selected proteins as prognostic indicators for recurrent and non-recurrent LSCC. Samples from a total of 41 patients with LSCC were investigated by immunohistochemistry. Digital image analysis was performed, and various associated factors were calculated. Histoscore (H-score) and receiver operating characteristic curves were used to divide protein expression in high and low for predicting disease recurrence. Disease-free survival (DFS) curves, crude hazard ratios (HRs) and adjusted HRs were analyzed and compared. Significantly different H-scores were found between the recurrent and non-recurrent groups in terms of pRb and c-Met expression. pRb was expressed at high levels in recurrent LSCC, while c-Met was expressed at low levels. Patients with low pRb expression had a longer DFS than those with high pRb expression (log-rank χ2, 5.161; P=0.023). Patients with high c-Met expression had a longer DFS than those with low c-Met expression (log-rank χ2, 6.441; P=0.011). Moreover, patients with high pRb expression and low c-Met expression had the shortest DFS (log-rank χ2, 11.827; P=0.008). Differentiated histological factors had an impact on the risk of recurrence (Cox regression test; crude HR, 9.53; 95% confidence interval, 1.214-74.819; P=0.032). The present study demonstrated that the grading of differentiated squamous cell carcinoma, pRb and c-Met expression are the most useful prognostic factors for the prediction of recurrent LSCC. These might be further applied as potential markers for clinical use.

DNA replication: Mechanisms and therapeutic interventions for diseases

Accurate and integral cellular DNA replication is modulated by multiple replication-associated proteins, which is fundamental to preserve genome stability. Furthermore, replication proteins cooperate with multiple DNA damage factors to deal with replication stress through mechanisms beyond their role in replication. Cancer cells with chronic replication stress exhibit aberrant DNA replication and DNA damage response, providing an exploitable therapeutic target in tumors. Numerous evidence has indicated that posttranslational modifications (PTMs) of replication proteins present distinct functions in DNA replication and respond to replication stress. In addition, abundant replication proteins are involved in tumorigenesis and development, which act as diagnostic and prognostic biomarkers in some tumors, implying these proteins act as therapeutic targets in clinical. Replication-target cancer therapy emerges as the times require. In this context, we outline the current investigation of the DNA replication mechanism, and simultaneously enumerate the aberrant expression of replication proteins as hallmark for various diseases, revealing their therapeutic potential for target therapy. Meanwhile, we also discuss current observations that the novel PTM of replication proteins in response to replication stress, which seems to be a promising strategy to eliminate diseases.

Novel protein contact points among TP53 and minichromosome maintenance complex proteins 2, 3, and 5

OBJECTIVE

Identify protein contact points between TP53 and minichromosome maintenance (MCM) complex proteins 2, 3, and 5 with high resolution allowing for potential novel Cancer drug design.

METHODS

A next-generation sequencing-based protein-protein interaction method developed in our laboratory called AVA-Seq was applied to a gold-standard human protein interaction set. Proteins including TP53, MCM2, MCM3, MCM5, HSP90AA1, PCNA, NOD1, and others were sheared and ligated into the AVA-Seq system. Protein-protein interactions were then identified in both mild and stringent selective conditions.

RESULTS

Known interactions among MCM2, MCM3, and MCM5 were identified with the AVA-Seq system. The interacting regions detected between these three proteins overlap with the structural data of the MCM complex, and novel domains were identified with high resolution determined by multiple overlapping fragments. Fragments of wild type TP53 were shown to interact with MCM2, MCM3, and MCM5, and details on the location of the interactions were provided. Finally, a mini-network of known and novel cancer protein interactions was provided, which could have implications for fundamental changes in multiple cancers.

CONCLUSION

We provide a high-resolution mini-interactome that could direct novel drug targets and implicate possible effects of specific cancer mutations.

A computational model revealing the immune-related hub genes and key pathways involved in rheumatoid arthritis (RA)

Rheumatoid arthritis (RA) has one of the highest disability rates among inflammatory joint disorders. However, the reason and possible molecular events are still unclear. There are various treatment options available, but no complete cure. To obtain early diagnosis and successful medication in RA, it is necessary to explore gene susceptibility and pathogenic factors. The main intend of our work is to explore the immune-related hub genes with similar functions that are differentially expressed in RA patients. Three datasets such as GSE21959, GSE55457, and GSE77298, were taken to analyze the differently expressed genes (DEGs) among 55 RA and 33 control samples. We obtained 331 upregulated and 275 downregulated DEGs from three Gene Expression Omnibus (GEO) datasets using the R package. Furthermore, a protein-protein interaction network was built for upregulated and downregulated DEGs using Cytoscape. Subsequently, MCODE analysis was performed and obtained the top two modules in each DEG's upregulated and downregulated protein-protein interactions (PPIs) network. CytoNCA and cytoHubba were performed and identified overlapping DEGs. In addition, we narrowed down DEGs by filtering with immune-related genes and identified DE-IRGs. Gene ontology (GO) and KEGG pathway analysis in upregulated and downregulated DEGs were executed with the DAVID platform. Our study obtained the nine most significant DE-IRGs in RA such as CXCR4, CDK1, BUB1, BIRC5, AGTR1, EGFR, EDNRB, KALRN, and GHSR. Among them, CXCR4, CDK1, BUB1, and BIRC5 are overexpressed in RA and may contribute to the pathophysiology of the disease. Similarly, AGTR1, EGFR, EDNRB, KALRN, and GHSR are all low expressed in RA and may have a contribution to pathogenesis. GO, KEGG functional enrichment, and GeneMANIA showed that the dysregulated process of DE-IRGs causes RA development and progression. These findings may be helpful in future studies in RA diagnosis and therapy.