Overexpression of BASP1 Indicates a Poor Prognosis in Head and Neck Squamous Cell Carcinoma

Molecular Docking of Seaweed-Derived Drug Fucoxanthin Against the Monkeypox Virus

Background The monkeypox virus (MPXV) is classified as a zoonotic virus of the Poxviridae family, resulting from the MPXV strain of the Orthopoxvirus genus. Seaweeds, or marine macroalgae, are abundant reservoirs of bioactive compounds that demonstrate diverse biological properties, such as antiviral actions. In the field of computational analysis, in silico analysis refers to the use of computer-based methods to study and assess biological systems and processes. To forecast the binding affinity and interaction between the discovered chemical and the target proteins of the MPXV, a molecular docking analysis was conducted. Aim The research aims to conduct an in silico examination of a protein-ligand interaction of a drug produced from seaweed that targets the MPXV.  Methodology Protein Data Bank (PDB) and PubChem databases provided MPXV methyltransferase and fucoxanthin ligand compounds. AutoDockTools 1.5.7 calculated the molecular docking using the Lamarckian genetic algorithm. Autogrid created a grid box around target 8B07 active site hotspot residues. Each docked molecule's docking parameters were obtained from 100 docking experiments with a maximum of 2.5 × 106 energy evaluations, a 0.02 mutation rate, and a 0.8 crossover rate. The population comprised 250 randomly selected volunteers. PyMOL was utilized to observe ligand fragment interactions. Results The binding energy of the ligand fucoxanthin was -5.46 kcal/mol. Fucoxanthin interacts with receptor molecules via hydrogen bonding at the amino acid level: Chain A: PHE188 and TYR189; and Chain B: LYS33, GLN37, GLY38, GLY96, ARG97, PHE115, PRO202, and SER203. The higher the negative docking score, the stronger the binding affinity between the receptor and ligand molecules, indicating that bioactive substances are more effective. Conclusion The findings of this study indicate that fucoxanthin, a pharmaceutical derivative generated from seaweed, had antiviral activity against the MPXV. This conclusion was reached based on protein-ligand interactions.

Delving into the Heterogeneity of Different Breast Cancer Subtypes and the Prognostic Models Utilizing scRNA-Seq and Bulk RNA-Seq

Background: Breast cancer (BC) is the most common malignancy in women with high heterogeneity. The heterogeneity of cancer cells from different BC subtypes has not been thoroughly characterized and there is still no valid biomarker for predicting the prognosis of BC patients in clinical practice. Methods: Cancer cells were identified by calculating single cell copy number variation using the inferCNV algorithm. SCENIC was utilized to infer gene regulatory networks. CellPhoneDB software was used to analyze the intercellular communications in different cell types. Survival analysis, univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis were used to construct subtype specific prognostic models. Results: Triple-negative breast cancer (TNBC) has a higher proportion of cancer cells than subtypes of HER2+ BC and luminal BC, and the specifically upregulated genes of the TNBC subtype are associated with antioxidant and chemical stress resistance. Key transcription factors (TFs) of tumor cells for three subtypes varied, and most of the TF-target genes are specifically upregulated in corresponding BC subtypes. The intercellular communications mediated by different receptor–ligand pairs lead to an inflammatory response with different degrees in the three BC subtypes. We establish a prognostic model containing 10 genes (risk genes: ATP6AP1, RNF139, BASP1, ESR1 and TSKU; protective genes: RPL31, PAK1, STARD10, TFPI2 and SIAH2) for luminal BC, seven genes (risk genes: ACTR6 and C2orf76; protective genes: DIO2, DCXR, NDUFA8, SULT1A2 and AQP3) for HER2+ BC, and seven genes (risk genes: HPGD, CDC42 and PGK1; protective genes: SMYD3, LMO4, FABP7 and PRKRA) for TNBC. Three prognostic models can distinguish high-risk patients from low-risk patients and accurately predict patient prognosis. Conclusions: Comparative analysis of the three BC subtypes based on cancer cell heterogeneity in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy for BC patients.

Single-cell RNA sequencing analysis to explore immune cell heterogeneity and novel biomarkers for the prognosis of lung adenocarcinoma

Background: Single-cell RNA sequencing is necessary to understand tumor heterogeneity, and the cell type heterogeneity of lung adenocarcinoma (LUAD) has not been fully studied.

Method: We first reduced the dimensionality of the GSE149655 single-cell data. Then, we statistically analysed the subpopulations obtained by cell annotation to find the subpopulations highly enriched in tumor tissues. Monocle was used to predict the development trajectory of five subpopulations; beam was used to find the regulatory genes of five branches; qval was used to screen the key genes; and cellchart was used to analyse cell communication. Next, we used the differentially expressed genes of TCGA-LUAD to screen for overlapping genes and established a prognostic risk model through univariate and multivariate analyses. To identify the independence of the model in clinical application, univariate and multivariate Cox regression were used to analyse the relevant HR, 95% CI of HR and p value. Finally, the novel biomarker genes were verified by qPCR and immunohistochemistry.

Results: The single-cell dataset GSE149655 was subjected to quality control, filtration and dimensionality reduction. Finally, 23 subpopulations were screened, and 11-cell subgroups were annotated in 23 subpopulations. Through the statistical analysis of 11 subgroups, five important subgroups were selected, including lung epithelial cells, macrophages, neuroendocrine cells, secret cells and T cells. From the analysis of cell trajectory and cell communication, it is found that the interaction of five subpopulations is very complex and that the communication between them is dense. We believe that these five subpopulations play a very important role in the occurrence and development of LUAD. Downloading the TCGA data, we screened the marker genes of these five subpopulations, which are also the differentially expressed genes in tumorigenesis, with a total of 462 genes, and constructed 10 gene prognostic risk models based on related genes. The 10-gene signature has strong robustness and can achieve stable prediction efficiency in datasets from different platforms. Two new molecular markers related to LUAD, HLA-DRB5 and CCDC50, were verified by qPCR and immunohistochemistry. The results showed that HLA-DRB5 expression was negatively correlated with the risk of LUAD, and CCDC50 expression was positively correlated with the risk of LUAD.

Conclusion: Therefore, we identified a prognostic risk model including CCL20, CP, HLA-DRB5, RHOV, CYP4B1, BASP1, ACSL4, GNG7, CCDC50 and SPATS2 as risk biomarkers and verified their predictive value for the prognosis of LUAD, which could serve as a new therapeutic target.

PROL1 is essential for xenograft tumor development in mice injected with the human prostate cancer cell-line, LNCaP, and modulates cell migration and invasion

Background and objective

A growing body of literature suggests modulated expression of members of the opiorphin family of genes (PROL1, SMR3A and SMR3B) is associated with cancer. Recently, overexpression of PROL1 was shown to be associated with prostate cancer, with evidence of a role in overcoming the hypoxic barrier that develops as tumors grow. The primary goal of the present studies was to support and expand evidence for a role of PROL1 in the development and progression of prostate cancer.

Material and methods

We engineered knock-out of the opiorphin gene, PROL1, in LNCaP, an androgen-sensitive, human prostate cancer derived, cell-line. Using xenograft assays, we compared the ability of injected LNCaP PROL1 knock-out cell-lines to develop tumors in both castrated and intact male mice with the parental LNCaP and LNCaP PROL1 overexpressing cell-lines. We used RNAseq to compare global gene expression between the parental and LNCaP PROL1 knock-out cell-lines. Wound closure and 3D spheroid invasion assays were used to compare cell motility and migration between parental LNCaP cells and LNCaP cells overexpressing of PROL1.

Results

The present studies demonstrate that LNCaP cell-lines with consisitutive knock-out of PROL1 fail to develop tumors when injected into both castrated and intact male mice. Using RNAseq to compare global gene expression between the parental and LNCaP PROL1 knock-out cell-lines, we confirmed a role for PROL1 in regulating molecular pathways associated with angiogenesis and tumor blood supply, and also identified a potential role in pathways related to cell motility and migration. Through the use of wound closure and 3D spheroid invasion assays, we confirmed that overexpression of PROL1 in LNCaP cells leads to greater cell motility and migration compared to parental cells, suggesting that PROL1 overexpression results in a more invasive phenotype.

Conclusion

Overall, our studies add to the growing body of evidence that opiorphin-encoding genes play a role in cancer development and progression. PROL1 is essential for establishment and growth of tumors in mice injected with LNCaP cells, and we provide evidence that PROL1 has a possible role in progression towards a more invasive, metastatic and castration resistant prostate cancer (PrCa).

BASP1 is up-regulated in tongue squamous cell carcinoma and associated with a poor prognosis

OBJECTIVE

To study the relationship between expression of brain acid soluble protein 1 (BASP1) in tongue squamous cell carcinoma (TSCC) tissue and the clinicopathological characteristics and prognosis of patients with TSCC.

METHODS

Western blotting was performed to detect BASP1 expression in fresh-frozen specimens of tumor tissue and adjacent normal tissue obtained from 6 patients with TSCC. Immunohistochemical methods were used to detect BASP1 expression in 100 paraffin-embedded specimens of TSCC tissue. The chi-square test was used to analyze the association between BASP1 expression and a variety of clinicopathological parameters. A Kaplan-Meier analysis and the Cox proportional hazard model were used to further evaluate the impact of BASP1 on patient survival.

RESULTS

The Oncomine database showed that BASP1 expression was increased in TSCC tissues. The PrognoScan and GEPIA databases suggested that a high level of BASP1 expression is related to a poor prognosis for patients with head and neck cancer. Experimental results showed that when compared to normal tissues adjacent to a cancer, BASP1 was more highly expressed in the TSCC tissues. Univariate and multivariate Cox regression analyses showed that BASP1 expression and the tumor's stage may be independent risk factors that affect the growth and prognosis of TSCC. A survival analysis showed that patients with a low level of BASP1 expression had a higher survival rate.

CONCLUSION

Overexpression of BASP1 was found to be associated with distant node metastasis and a poor prognosis among patents with TSCC. BASP1 could possibly serve as a molecular marker for diagnosing and treating the disease.

High BASP1 Expression is Associated with Poor Prognosis and Promotes Tumor Progression in Human Lung Adenocarcinoma

BASP1 is involved in signal transduction and cytoskeleton formation and plays a tumor-promoting or tumor-suppressing role in cancers. We found BASP1 was overexpressed in lung adenocarcinoma tissues and promoted the proliferation and migration of lung adenocarcinoma cells. The mechanism may be related to inhibition of cell apoptosis and abnormal activation of the Wnt/β-catenin pathway and epithelial-mesenchymal transformation. BASP1 is associated with poor prognosis in lung adenocarcinoma.