Development and Validation of Novel Biomarkers Related to M2 Macrophages Infiltration by Weighted Gene Co-Expression Network Analysis in Prostate Cancer

Important role and underlying mechanism of non‑SMC condensin I complex subunit G in tumours (Review)

At present, the incidence of tumours is increasing on a yearly basis, and tumourigenesis is usually associated with chromosomal instability and cell cycle dysregulation. Moreover, abnormalities in the chromosomal structure often lead to DNA damage, further exacerbating gene mutations and chromosomal rearrangements. However, the non‑SMC condensin I complex subunit G (NCAPG) of the structural maintenance of chromosomes family is known to exert a key role in tumour development. It has been shown that high expression of NCAPG is closely associated with tumour development and progression. Overexpression of NCAPG variously affects chromosome condensation and segregation during cell mitosis, influences cell cycle regulation, promotes tumour cell proliferation and invasion, and inhibits apoptosis. In addition, NCAPG has been associated with tumour cell stemness, tumour resistance and recurrence. The aim of the present review was to explore the underlying mechanisms of NCAPG during tumour development, with a view towards providing novel targets and strategies for tumour therapy, and through the elucidation of the mechanisms involved, to lay the foundation for future developments in health.

Pla2g5 contributes to viral-like-induced lung inflammation through macrophage proliferation and LA/Ffar1 lung cell recruitment

Macrophages expressing group V phospholipase A2 (Pla2g5) release the free fatty acid (FFA) linoleic acid (LA), potentiating lung type 2 inflammation. Although Pla2g5 and LA increase in viral infections, their role remains obscure. We generated Pla2g5flox/flox mice, deleted Pla2g5 by using the Cx3cr1cre transgene, and activated bone marrow-derived macrophages (BM-Macs) with poly:IC, a synthetic double-stranded RNA that triggers a viral-like immune response, known Pla2g5-dependent stimuli (IL-4, LPS + IFNγ, IL-33 + IL-4 + GM-CSF) and poly:IC + LA followed by lipidomic and transcriptomic analysis. Poly:IC-activated Pla2g5flox/flox;Cx3cr1cre/+ BM-Macs had downregulation of major bioactive lipids and critical enzymes producing those bioactive lipids. In addition, AKT phosphorylation was lower in poly:IC-stimulated Pla2g5flox/flox;Cx3cr1cre/+ BM-Macs, which was not restored by adding LA to poly:IC-stimulated BM-Macs. Consistently, Pla2g5flox/flox;Cx3cr1cre/+ mice had diminished poly:IC-induced lung inflammation, including inflammatory macrophage proliferation, while challenging Pla2g5flox/flox;Cx3cr1cre/+ mice with poly:IC + LA partially restored lung inflammation and inflammatory macrophage proliferation. Finally, mice lacking FFA receptor-1 (Ffar1)-null mice had reduced poly:IC-induced lung cell recruitment and tissue macrophage proliferation, not corrected by LA. Thus, Pla2g5 contributes to poly:IC-induced lung inflammation by regulating inflammatory macrophage proliferation and LA/Ffar1-mediated lung cell recruitment and tissue macrophage proliferation.

Immunotherapeutic value of NUSAP1 associated with bladder cancer through a comprehensive analysis of 33 human cancer cases

To investigate the correlation between nucleolar spindle-associated protein 1 (NUSAP1) and cancer immunotherapy across 33 different types of human cancers. We conducted an analysis of The Cancer Genome Atlas (TCGA) database to retrieve gene expression data and clinical characteristics for 33 different cancer types. The immunotherapy cohorts encompassed GSE67501, GSE78220, and IMvigor210. Relevant information was extracted from the gene expression repository. We assessed the prognostic significance of NUSAP1 by examining various clinical parameters. The single-sample gene-set enrichment analysis (ssGSEA) method was utilized to gauge NUSAP1 activity and to contrast NUSAP1 transcriptome and protein levels. We delved into the correlation between NUSAP1 and various immune processes and components to gain insights into NUSAP1's role. We also discussed coherent pathways associated with NUSAP1 signal transduction and its impact on immunotherapy biomarkers. To authenticate and validate the differential expression patterns of NUSAP1 in bladder tumor tissues versus normal bladder counterparts, we utilized Western blotting (WB), real-time quantitative polymerase chain reaction (RT-qPCR), and immunohistochemistry (IHC) techniques. NUSAP1 exhibits overexpression across a spectrum of malignancies, and its expression levels correlate with overall survival (OS), disease-specific survival, and tumor stage in specific cancer types. Furthermore, NUSAP1 expression is linked to mutations, methylation patterns, and immunotherapy responses in human cancers. Meanwhile, our experiments, involving WB, RT-qPCR, and IHC, consistently demonstrated significantly higher NUSAP1 expression in bladder tumor tissues compared to normal controls. Our study underscores the potential of NUSAP1 as a promising prognostic indicator and immunotherapeutic target for a range of malignant tumors.

Radiotherapy-induced Immune Response Enhanced by Selective HDAC6 Inhibition

Radiotherapy is a curative cancer treatment modality that imparts damage to cellular DNA, induces immunogenic cell death, and activates antitumor immunity. Despite the radiotherapy-induced direct antitumor effect seen within the treated volume, accumulating evidence indicates activation of innate antitumor immunity. Acute proinflammatory responses mediated by anticancer M1 macrophages are observed in the immediate aftermath following radiotherapy. However, after a few days, these M1 macrophages are converted to anti-inflammatory and pro-cancer M2 phenotype, leading to cancer resistance and underlying potential tumor relapse. Histone deacetylase 6 (HDAC6) plays a crucial role in regulating macrophage polarization and innate immune responses. Here, we report targeting HDAC6 function with a novel selective inhibitor (SP-2-225) as a potential therapeutic candidate for combination therapy with radiotherapy. This resulted in decreased tumor growth and enhanced M1/M2 ratio of infiltrating macrophages within tumors. These observations support the use of selective HDAC6 inhibitors to improve antitumor immune responses and prevent tumor relapse after radiotherapy.

A pan-cancer analysis revealing the role of LFNG, MFNG and RFNG in tumor prognosis and microenvironment

BACKGROUND

Fringe is a glycosyltransferase involved in tumor occurrence and metastasis. However, a comprehensive analysis of the Fringe family members lunatic fringe (LFNG), manic fringe (MFNG), radical fringe (RFNG) in human cancers is lacking.

METHODS

In this study, we performed a pan-cancer analysis of Fringe family members in 33 cancer types with transcriptomic, genomic, methylation data from The Cancer Genome Atlas (TCGA) project. The correlation between Fringe family member expression and patient overall survival, copy number variation, methylation, Gene Ontology enrichment, and tumor-infiltrating lymphocytes (TILs) was investigated by using multiple databases, such as cBioPortal, Human Protein Atlas, GeneCards, STRING, MSigDB, TISIDB, and TIMER2. In vitro experiments and immunohistochemical assays were performed to validate our findings.

RESULTS

High expression levels of LFNG, MFNG, RFNG were closely associated with poor overall survival in multiple cancers, particularly in pancreatic adenocarcinoma (PAAD), uveal melanoma (UVM), and brain lower-grade glioma (LGG). Copy number variation analysis revealed that diploid and gain mutations of LFNG was significantly increased in PAAD and stomach adenocarcinoma (STAD), and significantly associated with the methylation levels in promoter regions. Significant differential genes between high and low expression groups of these Fringe family members were found to be consistently enriched in immune response and T cell activation pathway, extracellular matrix adhesion pathway, RNA splicing and ion transport pathways. Correlation between the abundance of tumor-infiltrating lymphocytes (TILs) and LFNG, MFNG, and RFNG expression showed that high LFNG expression was associated with lower TIL levels, particularly in PAAD. In vitro experiment by using pancreatic cancer PANC1 cells showed that LFNG overexpression promoted cell proliferation and invasion. Immunohistochemical assay in 90 PAAD patients verified the expression level of LFNG and its relationship with the prognosis.

CONCLUSIONS

Our study provides a relatively comprehensive understanding of the expression, mutation, copy number, promoter methylation level changes along with prognosis values of LFNG, MFNG, and RFNG in different tumors. High LFNG expression may serve as a poor prognosis molecular marker for PAAD.

Development and validation of a tumor immune cell infiltration-related gene signature for recurrence prediction by weighted gene co-expression network analysis in prostate cancer

Introduction: Prostate cancer (PCa) is the second most common malignancy in men. Despite multidisciplinary treatments, patients with PCa continue to experience poor prognoses and high rates of tumor recurrence. Recent studies have shown that tumor-infiltrating immune cells (TIICs) are associated with PCa tumorigenesis.

Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to derive multi-omics data for prostate adenocarcinoma (PRAD) samples. The CIBERSORT algorithm was used to calculate the landscape of TIICs. Weighted gene co-expression network analysis (WGCNA) was performed to determine the candidate module most significantly associated with TIICs. LASSO Cox regression was applied to screen a minimal set of genes and construct a TIIC-related prognostic gene signature for PCa. Then, 78 PCa samples with CIBERSORT output p-values of less than 0.05 were selected for analysis. WGCNA identified 13 modules, and the MEblue module with the most significant enrichment result was selected. A total of 1143 candidate genes were cross-examined between the MEblue module and active dendritic cell-related genes.

Results: According to LASSO Cox regression analysis, a risk model was constructed with six genes (STX4, UBE2S, EMC6, EMD, NUCB1 and GCAT), which exhibited strong correlations with clinicopathological variables, tumor microenvironment context, antitumor therapies, and tumor mutation burden (TMB) in TCGA-PRAD. Further validation showed that the UBE2S had the highest expression level among the six genes in five different PCa cell lines.

Discussion: In conclusion, our risk-score model contributes to better predicting PCa patient prognosis and understanding the underlying mechanisms of immune responses and antitumor therapies in PCa.

Prognostic Signature Development on the Basis of Macrophage Phagocytosis-Mediated Oxidative Phosphorylation in Bladder Cancer

Background

Macrophages are correlated with the occurrence and progression of bladder cancer (BCa). However, few research has focused on the predictive relevance of macrophage phagocytosis-mediated oxidative phosphorylation (MPOP) with BCa overall survival. Herein, we aimed to propose the targeted macrophage control based on MPOP as a treatment method for BCa immunotherapy.

Methods

The mRNA expression data sets and clinical data of bladder cancer originated from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data set. A systematic study of several GEO data sets found differentially expressed macrophage phagocytosis regulators (DE-MPR) between BCa and normal tissues. To discover overall survival-associated DE-MPR and develop prognostic gene signature with performance validated based on receiver operating curves and Kaplan-Meier curves, researchers used univariate and Lasso Cox regression analysis (ROC). External validation was done with GSE13057 and GSE69795. To clarify its molecular mechanism and immune relevance, GO/KEGG enrichment analysis and tumor immune analysis were used. To find independent bladder cancer prognostic variables, researchers employed multivariate Cox regression analysis. Finally, using TCGA data set, a predictive nomogram was built.

Results

In BCa, a four-gene signature of oxidative phosphorylation composed of PTPN6, IKZF3, HDLBP, and EMC1 was found to predict overall survival. With the MPOP feature, the ROC curve showed that TCGA data set and the external validation data set performed better in predicting overall survival than the traditional AJCC stage. The four-gene signature can identify cancers from normal tissue and separate patients into the high-risk and low-risk groups with different overall survival rates. The four MPOP-gene signature was an independent predictive factor for BCa. In predicting overall survival, a nomogram integrating genetic and clinical prognostic variables outperformed AJCC staging. Multiple oncological features and invasion-associated pathways were identified in the high-risk group, which were also correlated with significantly lower levels of immune cell infiltration.

Conclusion

This paper found the MPOP-feature gene and developed a predictive nomogram capable of accurately predicting bladder cancer overall survival. The above discoveries can contribute to the development of personalized treatments and medical decisions.

Immunotherapeutic Value of Transcription Factor 19 (TCF19) Associated with Renal Clear Cell Carcinoma: A Comprehensive Analysis of 33 Human Cancer Cases

Background

We aimed to study the relationship between transcription factor 19 (TCF19) and cancer immunotherapy in the 33 types of human cancers.

Methods

The Cancer Genome Atlas database was analyzed to obtain the gene expression data and clinical characteristics for the cases of 33 types of cancers. GSE67501, GSE78220, and IMvigor 210 were included in the immunotherapy cohorts. Relevant data were obtained by analyzing the gene expression database. The prognostic value of TCF19 was determined by analyzing various clinical parameters, such as survival duration, age, the stage of the tumor, and sex of the patients. The single-sample gene set enrichment analysis method was used to determine the activity of TCF19 and the method was also used to assess the differences between the TCF19 transcriptome and protein levels. The correlation between TCF19 and various immune processes and elements such as immunosuppressants, stimulants, and major histocompatibility complexes were analyzed to gain insights into the role of TCF19. The coherent paths associated with the process of TCF19 signal transduction and the influence of TCF19 on immunotherapy biomarkers have also been discussed herein. Finally, three independent immunotherapy methods were used to understand the relationship between TCF19 and immunotherapy response.

Results

It was observed that TCF19 was not significantly influenced by the age (5/33), sex (3/33), or tumor stage (3/21) of cancer patients. But the results revealed that TCF19 exhibited a potential prognostic value and could predict the survival rate of the patients. In some cases of this study, the activity and expression of TCF19 were taken at the same level (7/33).

Conclusion

TCF19 is strongly related to immune cell infiltration, immunomodulators, and immunotherapy markers. Our study demonstrated that high expression levels of TCF19 are strongly linked with the immune-related pathways. Nevertheless, it is noteworthy that TCF19 is not significantly associated with immunotherapy response.

Identification of Prostate Cancer Risk Genetics Biomarkers Based on Intergraded Bioinformatics Analysis

Background

Prostate cancer (PCa) is one of the most popular cancer types in men. Nevertheless, the pathogenic mechanisms of PCa are poorly understood. Hence, we aimed to identify the potential genetic biomarker of PCa in the present study.

Methods

High-throughput data set GSE46602 was obtained from the comprehensive gene expression database (GEO) for screening differentially expressed genes (DEGs). The common DEGs were further screened out using The Cancer Genome Atlas (TCGA) dataset. Functional enrichment analysis includes Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to study related mechanisms. The Cox and Lasso regression analyses were carried out to compress the target genes and construct the high-risk and low-risk gene model. Survival analyses were performed based on the gene risk signature model. The CIBERSORT algorithm was performed to clarify the correlation of the high- and low-risk gene model in risk and infiltration of immune cells in PCa.

Results

A total of 385 common DEGs were obtained. The results of functional enrichment analysis show that common DEGs play an important role in PCa. A three-gene signature model (KCNK3, AK5, and ARHGEF38) was established, and the model was significantly associated with cancer-related pathways, overall survival (OS), and tumor microenvironment (TME)-related immune cells in PCa.

Conclusion

This new risk model may contribute to further investigation in the immune-related pathogenesis in progression of PCa.

OShnscc: a novel user-friendly online survival analysis tool for head and neck squamous cell carcinoma based on RNA expression profiles and long-term survival information

Head and neck squamous cell carcinoma (HNSCC), as the most common type (>90%) of head and neck cancer, includes various epithelial malignancies that arise in the nasal cavity, oral cavity, pharynx, and larynx. In 2020, approximately 878 ‍ 000 new cases and 444 000 deaths linked to HNSCC occurred worldwide (Sung et al., 2021). Due to the associated frequent recurrence and metastasis, HNSCC patients have poor prognosis with a five-year survival rate of 40%-50% (Jou and Hess, 2017). Therefore, novel prognostic biomarkers need to be developed to identify high-risk HNSCC patients and improve their disease outcomes.

Establishment of a 4-miRNA Prognostic Model for Risk Stratification of Patients With Pancreatic Adenocarcinoma

Pancreatic adenocarcinomas (PAADs) often remain undiagnosed until later stages, limiting treatment options and leading to poor survival. The lack of robust biomarkers complicates PAAD prognosis, and patient risk stratification remains a major challenge. To address this issue, we established a panel constructed by four miRNAs (miR-4444-2, miR-934, miR-1301 and miR-3655) based on The Cancer Genome Atlas (TCGA) and Human Cancer Metastasis Database (HCMDB) to predicted the prognosis of PAAD patients. Then, a risk prediction model of these four miRNAs was constructed by using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) regression analysis. This model stratified TCGA PAAD cohort into the low-risk and high-risk groups based on the panel-based risk score, which was significantly associated with 1-, 2-, 3-year OS (AUC=0.836, AUC=0.844, AUC=0.952, respectively). The nomogram was then established with a robust performance signature for predicting prognosis compared to clinical characteristics of pancreatic cancer (PC) patients, including age, gender and clinical stage. Moreover, two GSE data were validated the expressions of 4 miRNAs with prognosis/survival outcome in PC. In the external clinical sample validation, the high-risk group with the upregulated expressions of miR-934/miR-4444-2 and downregulated expressions of miR-1301/miR-3655 were indicated a poor prognosis. Furthermore, the cell counting kit-8 (CCK-8) assay, clone formation, transwell and wound healing assay also confirmed the promoting effect of miR-934/miR-4444-2 and the inhibiting effect of miR-1301/miR-3655 in PC cell proliferation and migration. Taken together, we identified a new 4-miRNA risk stratification model could be used in predicting prognosis in PAAD.

Identification of an Aging-Related Gene Signature in Predicting Prognosis and Indicating Tumor Immune Microenvironment in Breast Cancer

Breast cancer (BC) is the most commonly diagnosed malignancy accompanied by high invasion and metastasis features. Importantly, emerging studies have supported that aging is a key clue that participates in the immune state and development of BC. Nevertheless, there are no studies concerning the aging-related genes (AGs) in constructing the prognosis signature of BC. Here, to address this issue, we initially performed a systematic investigation of the associations between AGs and BC prognosis and accordingly constructed a prognosis risk model with 10 AGs including PLAU, JUND, IL2RG, PCMT1, PTK2, HSPA8, NFKBIA, GCLC, PIK3CA, and DGAT1 by using the least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis. Meanwhile, our analysis further confirmed that the nomogram possessed a robust performance signature for predicting prognosis compared to clinical characteristics of BC patients, including age, clinical stage, and TNM staging. Moreover, the risk score was confirmed as an independent prognostic index of BC patients and was potentially correlated with immune scores, estimate score, immune cell infiltration level, tumor microenvironment, immunotherapy effect, and drug sensitivity. Furthermore, in the external clinical sample validation, AGs were expressed differentially in patients from different risk groups, and tumor-associated macrophage markers were elevated in high-risk BC tissues with more co-localization of AGs. In addition, the proliferation, transwell, and wound healing assays also confirmed the promoting effect of DGAT1 in BC cell proliferation and migration. Therefore, this well-established risk model could be used for predicting prognosis and immunotherapy in BC, thus providing a powerful instrument for combating BC.