Comprehensive analysis of clinical prognosis and molecular immune characterization of tropomyosin 4 in pancreatic cancer

Exploring the therapeutic mechanisms and prognostic targets of Biochanin A in glioblastoma via integrated computational analysis and in vitro experiments

Glioblastoma (GBM) is the most aggressive brain tumor and is characterized by a poor prognosis and high recurrence and mortality rates. Biochanin A (BCA) exhibits promising clinical anti-tumor effects. In this study, we aimed to explore the pharmacological mechanisms by which BCA acts against GBM. Network pharmacology was employed to identify overlapping target genes between BCA and GBM. Differentially expressed genes from the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database were visualized using VolcaNose. Interactions among these overlapping genes were analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. Protein-protein interaction networks were constructed using Cytoscape 3.8.1. The Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology enrichment analyses were conducted using the Database for Annotation, Visualization, and Integrated Discovery. Survival analyses for these genes were performed using the GEPIA2 database. The Chinese Glioma Genome Atlas database was used to study the correlations between key prognostic genes. Molecular docking was confirmed using the DockThor database and visualized with PyMol software. Cell viability was assessed via the CCK-8 assay, apoptosis and the cell cycle stages were examined using flow cytometry, and protein expression was detected using western blotting. In all, 63 genes were initially identified as potential targets for BCA in treating GBM. Enrichment analysis suggested that the pharmacological mechanisms of BCA primarily involved cell cycle inhibition, induction of cell apoptosis, and immune regulation. Based on these findings, AKT1, EGFR, CASP3, and MMP9 were preliminarily predicted as key prognostic target genes for BCA in GBM treatment. Furthermore, molecular docking analysis suggested stable binding of BCA to the target protein. In vitro experiments revealed the efficacy of BCA in inhibiting GBM, with an IC50 value of 98.37 ± 2.21 μM. BCA inhibited cell proliferation, induced cell apoptosis, and arrested the cell cycle of GBM cells. Furthermore, the anti-tumor effects of BCA on U251 cells were linked to the regulation of the target protein. We utilized integrated bioinformatics analyses to predict targets and confirmed through experiments that BCA possesses remarkable anti-tumor activities. We present a novel approach for multi-target treatment of GBM using BCA.

Pharmacogenomic Analysis of Combined Therapies against Glioblastoma Based on Cell Markers from Single-Cell Sequencing

Glioblastoma is the most common and aggressive form of primary brain cancer and the lack of viable treatment options has created an urgency to develop novel treatments. Personalized or predictive medicine is still in its infancy stage at present. This research aimed to discover biomarkers to inform disease progression and to develop personalized prophylactic and therapeutic strategies by combining state-of-the-art technologies such as single-cell RNA sequencing, systems pharmacology, and a polypharmacological approach. As predicted in the pyroptosis-related gene (PRG) transcription factor (TF) microRNA (miRNA) regulatory network, TP53 was the hub gene in the pyroptosis process in glioblastoma (GBM). A LASSO Cox regression model of pyroptosis-related genes was built to accurately and conveniently predict the one-, two-, and three-year overall survival rates of GBM patients. The top-scoring five natural compounds were parthenolide, rutin, baeomycesic acid, luteolin, and kaempferol, which have NFKB inhibition, antioxidant, lipoxygenase inhibition, glucosidase inhibition, and estrogen receptor agonism properties, respectively. In contrast, the analysis of the cell-type-specific differential expression-related targets of natural compounds showed that the top five subtype cells targeted by natural compounds were endothelial cells, microglia/macrophages, oligodendrocytes, dendritic cells, and neutrophil cells. The current approach-using the pharmacogenomic analysis of combined therapies-serves as a model for novel personalized therapeutic strategies for GBM treatment.

Research Advances in the Role of the Tropomyosin Family in Cancer

Cancer is one of the most difficult diseases for human beings to overcome. Its development is closely related to a variety of factors, and its specific mechanisms have been a hot research topic in the field of scientific research. The tropomyosin family (Tpm) is a group of proteins closely related to the cytoskeleton and actin, and recent studies have shown that they play an important role in various cancers, participating in a variety of biological activities, including cell proliferation, invasion, and migration, and have been used as biomarkers for various cancers. The purpose of this review is to explore the research progress of the Tpm family in tumorigenesis development, focusing on the molecular pathways associated with them and their relevant activities involved in tumors. PubMed and Web of Science databases were searched for relevant studies on the role of Tpms in tumorigenesis and development and the activities of Tpms involved in tumors. Data from the literature suggest that the Tpm family is involved in tumor cell proliferation and growth, tumor cell invasion and migration, tumor angiogenesis, tumor cell apoptosis, and immune infiltration of the tumor microenvironment, among other correlations. It can be used as a potential biomarker for early diagnosis, follow-up, and therapeutic response of some tumors. The Tpm family is involved in cancer in a close relationship with miRNAs and LncRNAs. Tpms are involved in tumor tissue invasion and migration as a key link. On this basis, TPM is frequently used as a biomarker for various cancers. However, the specific molecular mechanism of its involvement in cancer progression has not been explained clearly, which remains an important direction for future research.

Integrated pan-cancer analysis and experimental verification of the roles of tropomyosin 4 in gastric cancer

Objective

To investigate the function of tropomyosin 4 (TPM4) using pan-cancer data, especially in gastric cancer (GC), using comprehensive bioinformatics analysis and molecular experiments.

Methods

We used UCSC Xena, The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), TIMER2.0, GEPIA, cBioPortal, Xiantao tool, and UALCAN websites and databases for the extraction of pan-cancer data on TPM4. TPM4 expression was investigated with respect to prognosis, genetic alterations, epigenetic alterations, and immune infiltration. RNA22, miRWalk, miRDB, Starbase 2.0, and Cytoscape were used for identifying and constructing the regulatory networks of lncRNAs, miRNAs, and TPM4 in GC. Data from GSCALite, drug bank databases, and Connectivity Map (CMap) were used to analyze the sensitivity of drugs dependent on TPM4 expression. Gene Ontology (GO), enrichment analyses of the Kyoto Encyclopedia of Genes and Genomes (KEGG), wound healing assays, and (Matrigel) transwell experiments were used to investigate the biological functions of TPM4 in GC.

Result

The findings of the comprehensive pan-cancer analysis revealed that TPM4 has a certain diagnostic and prognosis value in most cancers. Alterations in the expression of TPM4, including duplications and deep mutations, and epigenetic alterations revealed that TPM4 expression is related to the expression of DNA methylation inhibitors and RNA methylation regulators at high concentrations. Besides, TPM4 expression was found to correlate with immune cell infiltration, immune checkpoint (ICP) gene expression, the tumor mutational burden (TMB), and microsatellite instability (MSI). Neoantigens (NEO) were also found to influence its response to immunotherapy. A lncRNA-miRNA -TPM4 network was found to regulate GC development and progression. TPM4 expression was related to docetaxel,5-fluorouracil, and eight small molecular targeted drugs sensitivity. Gene function enrichment analyses revealed that genes that were co-expressed with TPM4 were enriched within the extracellular matrix (ECM)-related pathways. Wound-healing and (Matrigel) transwell assays revealed that TPM4 promotes cell migration and invasion. TPM4, as an oncogene, plays a biological role, perhaps via ECM remodeling in GC.

Conclusions

TPM4 is a prospective marker for the diagnosis, treatment outcome, immunology, chemotherapy, and small molecular drugs targeted for pan-cancer treatment, including GC treatment. The lncRNA-miRNA-TPM4network regulates the mechanism underlying GC progression. TPM4 may facilitate the invasion and migration of GC cells, possibly through ECM remodeling.

Comprehensive analysis identifies ARHGEF6 as a potential prognostic and immunological biomarker in lung adenocarcinoma

Lung adenocarcinoma (LUAD), the most common histological type in lung cancer, is one of leading cancers with considerable morbidity/mortality worldwide. Treating LUAD remains an outstanding challenge due to the lack of early diagnosis and the poor therapeutic effects. Rac/Cdc42 guanine nucleotide exchange factor 6 (ARHGEF6), one of cytoskeletal regulators, exerts crucial biological functions in T cell migration. The potential biological role of ARHGEF6 in LUAD has yet to be established. Using multiple bioinformatics tools and statistical methods, we discovered that the mRNA and protein expression level of ARHGEF6 was significantly downregulated in tumor tissues comparing to normal controls. Moreover, ARHGEF6 presented high diagnostic value in LUAD patients (AUC = 0.949), and the patients with low ARHGEF6 expression had more somatic mutations and poor T stage, N stage, clinical prognosis. Experimental validation indicated that ARHGEF6 was low expressed in A549 and PC-9 cells comparing to the normal lung epithelial cells. The overexpression of ARHGEF6 remarkably attenuated the abilities of cell proliferation and colony formation. Furthermore, the immune landscape analysis in TME revealed that ARHGEF6 expression was positively associated with immune cell infiltration and immune checkpoints. Single-cell transcriptome analysis indicated that ARHGEF6 expression was also distributed in immune cell types in TME based on TISCH database. Additionally, differentially expressed genes (DEGs) and functional enrichment analyses uncovered that ARHGEF6 was involved in T cell activation. Finally, LUAD samples were classified two clusters based on DEGs for subgroups analysis. In summary, this study comprehensively uncovered that ARHGEF6 could be identified as a potential prognostic and immunological biomarker in lung adenocarcinoma.

Overexpression of TPM4 is associated with worse prognosis and immune infiltration in patients with glioma

BACKGROUND

Tropomyosin 4 (TPM4), a member of the tropomyosin family, is aberrantly expressed and plays an important role in a variety of cancers. However, studies on TPM4 in glioma patients are currently lacking.

OBJECTIVE

Our study aimed to evaluate the diagnostic and prognostic characteristics of TPM4 in glioma and its correlation with immune infiltration.

METHODS

Bioinformatic analysis was performed to determine whether TPM4 has diagnostic and prognostic value for glioma. The following databases and analytical tools were used to explore the clinical significance of TPM4 in glioma: TCGA, GTEx, GEO, STRING, and TISIDB.

RESULTS

Our study showed that the mRNA and protein expression levels of TPM4 were significantly higher in glioma than in healthy brain tissue. Kaplan-Meier analysis indicated that high expression of TPM4 in glioma correlated with poor prognosis. Univariate Cox analysis indicated that the high expression level of TPM4 in glioma was an independent prognostic characteristic for low overall survival (OS). The areas under the 1-year survival ROC, 2-year survival ROC, and 3-year survival ROC were all greater than 0.8. GO and KEGG enrichment analysis and GSEA showed that humoral immune response and cytokine receptor interaction were significantly enriched in the TPM4 high expression group, where M phase of the cell cycle, neutrophil degranulation, signaling by interleukins, and signaling by rho GTPases were significantly enriched. Furthermore, according to the analysis of immune cell infiltration, TPM4 was associated with tumor infiltration of a variety of immune cells.

CONCLUSIONS

In conclusion, our study suggests that TPM4 may be an effective prognostic biomarker for glioma patients, providing new ideas and research directions for glioma research.

The Tropomyosin Family as Novel Biomarkers in Relation to Poor Prognosis in Glioma

Simple Summary

Due to the malignant features of glioma, current interventions result in limited treatment effects and poor prognoses for all patients. The functions of the tropomyosin (TPM) family in tumors and cancers have been explored. However, striking differences have been observed. This study aims to further our understanding of the effects of TPMs in glioma. Our study explored the expression and prognoses of TPM in glioma, as well as the gene functions of TPMs. High expression of TPM3 and TPM4 were positively correlated with poorer prognosis in glioma, and TPM3 could serve as a novel independent prognostic factor of glioma.

Abstract

(1) Background: The functions of the tropomyosin (TPM) family in tumors and cancers have been explored; however, striking differences have been observed. This study aims to further our understanding of the effects of TPMs in glioma, and find novel biomarkers for glioma. (2) Methods: RNA-seq data were downloaded from TCGA and GTEx. Survival analyses, Cox regression, nomogram, calibration curves, ROC curves, gene function enrichment analyses, and immune cell infiltration analyses were carried out using R. CCK8 assay, while Brdu assay, colony formation assay, and Transwell assay were used to verify the functions of TPM3 in glioma. (3) Results: TPM1/3/4 were significantly more highly expressed in glioma than that in normal tissues, while higher expression of TPM2/3/4 was correlated with a worse overall survival than lower expression of TPM2/3/4. Furthermore, bioinformatic analyses indicated that TPM3/4 could be promoting factors for poorer survival in glioma, but only TPM3 could serve as an independent prognostic factor. Gene function analyses showed that TPMs may be involved in immune responses. Moreover, further experimental investigations verified that TPM3 overexpression enhanced the proliferation and tumorigenicity of glioma. (4) Conclusions: High expression of TPM3/4 was positively correlated with poorer prognosis in glioma, and TPM3 could serve as a novel independent prognostic factor of glioma.

Development and validation of a hypoxia-stemness-based prognostic signature in pancreatic adenocarcinoma

Background: Pancreatic adenocarcinoma (PAAD) is one of the most aggressive and fatal gastrointestinal malignancies with high morbidity and mortality worldwide. Accumulating evidence has revealed the clinical significance of the interaction between the hypoxic microenvironment and cancer stemness in pancreatic cancer progression and therapies. This study aims to identify a hypoxia-stemness index-related gene signature for risk stratification and prognosis prediction in PAAD.

Methods: The mRNA expression-based stemness index (mRNAsi) data of PAAD samples from The Cancer Genome Atlas (TCGA) database were calculated based on the one-class logistic regression (OCLR) machine learning algorithm. Univariate Cox regression and LASSO regression analyses were then performed to establish a hypoxia-mRNAsi-related gene signature, and its prognostic performance was verified in both the TCGA-PAAD and GSE62452 corhorts by Kaplan-Meier and receiver operating characteristic (ROC) analyses. Additionally, we further validated the expression levels of signature genes using the TCGA, GTEx and HPA databases as well as qPCR experiments. Moreover, we constructed a prognostic nomogram incorporating the eight-gene signature and traditional clinical factors and analyzed the correlations of the risk score with immune infiltrates and immune checkpoint genes.

Results: The mRNAsi values of PAAD samples were significantly higher than those of normal samples (p < 0.001), and PAAD patients with high mRNAsi values exhibited worse overall survival (OS). A novel prognostic risk model was successfully constructed based on the eight-gene signature comprising JMJD6, NDST1, ENO3, LDHA, TES, ANKZF1, CITED, and SIAH2, which could accurately predict the 1-, 3-, and 5-year OS of PAAD patients in both the training and external validation datasets. Additionally, the eight-gene signature could distinguish PAAD samples from normal samples and stratify PAAD patients into low- and high-risk groups with distinct OS. The risk score was closely correlated with immune cell infiltration patterns and immune checkpoint molecules. Moreover, calibration analysis showed the excellent predictive ability of the nomogram incorporating the eight-gene signature and traditional clinical factors.

Conclusion: We developed a hypoxia-stemness-related prognostic signature that reliably predicts the OS of PAAD. Our findings may aid in the risk stratification and individual treatment of PAAD patients.

Leukotriene B4 receptor 2 correlates with prognosis and immune infiltration in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. According to reports, leukotriene B4 receptor 2 (LTB4R2, also known as BLT2), a chemokine receptor, is upregulated in different tumors. However, the correlation between BLT2 expression and its prognostic value in ccRCC remains to be explored.

METHODS

This study used the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to evaluate the association between BLT2 expression and the clinical outcome of ccRCC. Based on TIMER2.0, the correlation between BLT2 expression in ccRCC and tumor immune characteristics was evaluated.

RESULTS

The expression of BLT2 in ccRCC was higher than that in normal tissues. Kaplan-Meier survival analysis indicated that high BLT2 expression was significantly correlated with poor overall survival (HR = 1.75, p < 0.001) and disease-specific survival (HR = 1.60, p = 0.014) for patients with ccRCC. In addition, our findings revealed that there was no significant correlation between the M1 marker genes and the expression of BLT2 in ccRCC, while moderate correlations were observed between the BLT2 expression and the M2 marker genes. Tregs and T cell exhaustion marker genes were positively correlated with BLT2 expression in ccRCC (p < 0.001).

CONCLUSION

BLT2 may serve as a novel prognostic biomarker and is related to the shaping of tumor immune microenvironment in ccRCC. The expression of BLT2 potentially contributes to the regulation of TAMs, T cell exhaustion, and Tregs activation in ccRCC, providing new approaches to promote the development of new immunotherapeutic strategies for ccRCC.