Silencing of the cytokine receptor TNFRSF13B: A new therapeutic target for triple-negative breast cancer

A Retrospective Exploratory Analysis for Serum Extracellular Vesicles Reveals APRIL (TNFSF13), CXCL13, and VEGF-A as Prognostic Biomarkers for Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Neoadjuvant chemotherapy (NAC) is widely used as a standard treatment for early-stage triple-negative breast cancer (TNBC). While patients who achieve pathologic complete response (pCR) have a highly favorable outcome, patients who do not achieve pCR have variable prognoses. It is important to identify patients who are most likely to have poor survival outcomes to identify candidates for more aggressive therapeutic approaches after NAC. Many studies have demonstrated that cytokines and growth factors packaged into extracellular vesicles (EVs) have an essential role in tumor progression and drug resistance. In this study, we examined the role of serum-derived EV-associated cytokines as prognostic biomarkers for long-term outcomes in patients who underwent anthracycline-taxane-based NAC. We isolated extracellular vesicles from the serum of 190 TNBC patients who underwent NAC between 2015 and 2018 at Samsung Medical Center. EV-associated cytokine concentrations were measured with ProcartaPlex Immune Monitoring 65-plex panels. The prognostic value of EV-associated cytokines was studied. We found that patients with high EV_APRIL, EV_CXCL13, and EV_VEGF-A levels had shorter overall survival (OS). We further evaluated the role of these selected biomarkers as prognostic factors in patients with residual disease (RD) after NAC. Even in patients with RD, high levels of EV_APRIL, EV_CXCL13, and EV_VEGF-A were correlated with poor OS. In all subgroup analyses, EV_CXCL13 overexpression was significantly associated with poor overall survival. Moreover, multivariate analysis indicated that a high level of EV_CXCL13 was an independent predictor of poor OS. Correlation analysis between biomarker levels in EVs and serum showed that EV_VEGF-A positively correlated with soluble VEGF-A but not CXCL13. An elevated level of soluble VEGF-A was also associated with poor OS. These findings suggest that EV_APRIL, EV_CXCL13, and EV_VEGF-A may be useful in identifying TNBC patients at risk of poor survival outcomes after NAC.

Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis

Background

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the molecular pathogenesis, but the molecular mechanisms of PDAC are still not well understood. The purpose of this study is to further explore the molecular mechanism of PDAC through integrated bioinformatics analysis.

Methods

To identify the candidate genes in the carcinogenesis and progression of PDAC, next-generation sequencing (NGS) data set GSE133684 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and Gene Ontology (GO) and pathway enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using Integrated Interactions Database (IID) interactome database and Cytoscape. Subsequently, miRNA-DEG regulatory network and TF-DEG regulatory network were constructed using miRNet database, NetworkAnalyst database, and Cytoscape software. The expression levels of hub genes were validated based on Kaplan-Meier analysis, expression analysis, stage analysis, mutation analysis, protein expression analysis, immune infiltration analysis, and receiver operating characteristic (ROC) curve analysis.

Results

A total of 463 DEGs were identified, consisting of 232 upregulated genes and 233 downregulated genes. The enriched GO terms and pathways of the DEGs include vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis, and adaptive immune system. Four hub genes (namely, cathepsin B [CCNB1], four-and-a-half LIM domains 2 (FHL2), major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) and tubulin beta 1 class VI (TUBB1)) were obtained via taking interaction of different analysis results.

Conclusions

On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of PDAC and provide potential targets for further investigation.

Identification of PIMREG as a novel prognostic signature in breast cancer via integrated bioinformatics analysis and experimental validation

Background

Phosphatidylinositol binding clathrin assembly protein interacting mitotic regulator (PIMREG) expression is upregulated in a variety of cancers. However, its potential role in breast cancer (BC) remains uncertain.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to gather relevant information. The expression of PIMREG and its clinical implication in BC were assessed by using Wilcoxon rank-sum test. The prognostic value of PIMREG in BC was evaluated through the Cox regression model and nomogram, and visualized by Kaplan-Meier survival curves. Genes/proteins that interact with PIMREG in BC were also identified through GeneMANIA and MaxLink. Gene set enrichment analysis (GSEA) was then performed. The correlations of the immune cell infiltration and immune checkpoints with the expression of PIMREG in BC were explored via TIMER, TISIDB, and GEPIA. Potential drugs that interact with PIMREG in BC were explored via Q-omic. The siRNA transfection, CCK-8, and transwell migration assay were conducted to explore the function of PIMREG in cell proliferation and migration.

Results

PIMREG expression was significantly higher in infiltrating ductal carcinoma, estrogen receptor negative BC, and progestin receptor negative BC. High expression of PIMREG was associated with poor overall survival, disease-specific survival, and progression-free interval. A nomogram based on PIMREG was developed with a satisfactory prognostic value. PIMREG also had a high diagnostic ability, with an area under the curve of 0.940. Its correlations with several immunomodulators were also observed. Immune checkpoint CTLA-4 was significantly positively associated with PIMREG. HDAC2 was found as a potentially critical link between PIMREG and BRCA1/2. In addition, PIMREG knockdown could inhibit cell proliferation and migration in BC.

Conclusions

The high expression of PIMREG is associated with poor prognosis and immune checkpoints in BC. HDAC2 may be a critical link between PIMREG and BRCA1/2, potentially a therapeutic target.

Establishment of a novel cytokine-related 8-gene signature for distinguishing and predicting the prognosis of triple-negative breast cancer

Background

Triple-negative breast cancer (TNBC) is a common carcinoma in women, and the prognosis of TNBC is the worst. Using data from The Cancer Genome Atlas (TCGA) database, we analyzed the functional roles of cytokine-related genes in TNBC.

Methods

The clinical and transcriptome data of TNBC patients were downloaded from TCGA database. A systematical analyses of the data from TCGA database were conducted to screen the prognostic genes and identify the main cytokine-related pathways related to TNBC.

Results

We identified 499 prognostic genes in TNBC patients from TCGA database and the cytokine-related pathways closely related to TNBC. TCGA-TNBC patients were divided into the high-risk cluster (C1) group and the low-risk cluster (C2) group based on the cytokine-related genes. The C1 group patients exhibited tumor metastasis and an advanced tumor stage. The functional analysis revealed that the upregulated differentially expressed genes (DEGs) in the C1 group were mainly associated with the extracellular matrix (ECM)-receptor interaction, stem cell proliferation, focal adhesion, and cyclic adenosine monophosphate (cAMP) signaling pathway, while the downregulated DEGs in the C1 group were mainly associated with cytokine and cytokine receptors, T-helper 17 (Th17) cell differentiation, and primary immunodeficiency. The immune activity of C1 group was lower than that of C2 group, and the identified half-maximal inhibitory concentration scores of 3 chemotherapy drugs (i.e., doxorubicin, methotrexate, and paclitaxel) were lower in C2 group than C1 group. More importantly, we constructed a novel prognostic signature and identified the following 8 genes: CCL25, CXCL13, IL12RB2, IL21, TNFRSF13C, TNFRSF8, CCL7 and GDF5.

Conclusion

The status of the cytokine-related pathway was closely related to tumor classification and immune activity in the TNBC patients. The gene signature of the cytokine-related genes showed an good performance in predicting the prognosis of TNBC patients, and could predict the prognosis of TNBC patients.

The BAFF-APRIL System in Cancer

B cell-activating factor (BAFF; also known as CD257, TNFSF13B, BLyS) and a proliferation-inducing ligand (APRIL; also known as CD256, TNFSF13) belong to the tumor necrosis factor (TNF) family. BAFF was initially discovered as a B-cell survival factor, whereas APRIL was first identified as a protein highly expressed in various cancers. These discoveries were followed by over two decades of extensive research effort, which identified overlapping signaling cascades between BAFF and APRIL, controlling immune homeostasis in health and driving pathogenesis in autoimmunity and cancer, the latter being the focus of this review. High levels of BAFF, APRIL, and their receptors have been detected in different cancers and found to be associated with disease severity and treatment response. Here, we have summarized the role of the BAFF-APRIL system in immune cell differentiation and immune tolerance and detailed its pathogenic functions in hematological and solid cancers. We also highlight the emerging therapeutics targeting the BAFF-APRIL system in different cancer types.

TNFRSF13B is a potential contributor to prostate cancer

Background

Immunodeficiencies are genetic diseases known to predispose an individual to cancer owing to defective immunity towards malignant cells. However, the link between immunodeficiency and prostate cancer progression remains unclear. Therefore, the aim of this study was to evaluate the effects of common genetic variants among eight immunodeficiency pathway-related genes on disease recurrence in prostate cancer patients treated with radical prostatectomy.

Methods

Genetic and bioinformatic analyses on 19 haplotype-tagging single-nucleotide polymorphisms in eight immunodeficiency pathway-related genes were conducted in 458 patients with prostate cancer after receiving radical prostatectomy. Furthermore, the TNFRSF13B was knocked down in 22Rv1 and PC-3 human prostate cancer cell lines via transfecting short hairpin RNAs and cell proliferation and colony formation assays were performed. The molecular mechanisms underlying the effects of TNFRSF13B were further explored by microarray gene expression profiling.

Results

TNFRSF13B rs4792800 was found to be significantly associated with biochemical recurrence even after adjustment for clinical predictors and false discovery rate correction (adjusted hazard ratio 1.78, 95% confidence interval 1.16–2.71, p = 0.008), and the G allele was associated with higher TNFRSF13B expression (p = 0.038). Increased TNFRSF13B expression suggested poor prognosis in four independent prostate cancer datasets. Furthermore, silencing TNFRSF13B expression resulted in decreased colony formation of 22Rv1 and PC-3 cells through modulating the cell cycle and p53 signalling pathways.

Conclusions

The present study suggests the potential role of immunodeficiency pathway-related genes, primarily TNFRSF13B, in prostate cancer progression.

Supplementary information

The online version contains supplementary material available at 10.1186/s12935-022-02590-2.

Ligand-independent oligomerization of TACI is controlled by the transmembrane domain and regulates proliferation of activated B cells

In mature B cells, TACI controls class-switch recombination and differentiation into plasma cells during T cell-independent antibody responses. TACI binds the ligands BAFF and APRIL. Approximately 10% of patients with common variable immunodeficiency (CVID) carry TACI mutations, of which A181E and C172Y are in the transmembrane domain. Residues A181 and C172 are located on distinct sides of the transmembrane helix, which is predicted by molecular modeling to spontaneously assemble into trimers and dimers. In human B cells, these mutations impair ligand-dependent (C172Y) and -independent (A181E) TACI multimerization and signaling, as well as TACI-enhanced proliferation and/or IgA production. Genetic inactivation of TACI in primary human B cells impaired survival of CpG-activated cells in the absence of ligand. These results identify the transmembrane region of TACI as an active interface for TACI multimerization in signal transduction, in particular for ligand-independent signals. These functions are perturbed by CVID-associated mutations.

Establishment and Validation of a Comprehensive Prognostic Model for Patients With HNSCC Metastasis

Objective

To identify biomarkers related to head and neck squamous cell carcinoma (HNSCC) metastasis and establish a prognostic model for patients with HNSCC.

Methods

HNSCC mRNA expression data of metastasis and non-metastatic samples were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. After screening the differentially expressed genes (DEGs) in the two datasets, a prognostic model, including clinical factors and biomarkers, was established, and verified in 36 samples of HNSCC by quantitative real-time transcription (qRT)-PCR. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene sets enrichment analysis (GSEA) were consulted to explore the functions of the DEGs.

Results

In total, 108 DEGs were identified. GSEA, GO, and KEGG analyses showed that these DEGs were mainly involved in the proliferation and metastasis of HNSCC. Six genes that were significantly related to metastasis, immune cell infiltration and prognosis were further identified to construct a prognostic gene signature. The reliability of the gene signature was verified in 36 samples of HNSCC. A prognostic model, including tumor stage, risk level, and a nomogram for prediction were further established. Receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), C-index, and calibration plots showed that the model and nomogram perform well.

Conclusion

We constructed a six-gene signature and a nomogram with high performance in predicting the prognosis of patients with HNSCC metastasis.

Platelet-Expressed TNFRSF13B (TACI) Predicts Breast Cancer Progression

Although treatment options in breast cancer have been improved significantly, predictive biomarkers for disease progression and metastasis are still lacking. Recent studies indicate that several TNF Receptor Superfamily members are involved in breast cancer cell proliferation and survival. Interestingly, TNFRSF13B (TACI) mRNA level were of prognostic relevance in breast cancer patients. In this study we provide evidence for TACI expression on platelets of breast cancer patients. The level of platelet-expressed TACI (pTACI) was significantly increased on platelets derived from breast cancer patients compared to healthy controls. Upon platelet activation, pTACI was downregulated on the platelet surface of healthy donors and breast cancer patients. Of note, inhibition of matrix metalloprotease (MMP) prevented downregulation of pTACI ex vivo, indicating that proteolytic cleavage of pTACI is responsible for reduction of pTACI level. Stimulation of pTACI via BAFF, BAFF 60-mer or APRIL did not influence platelet activation and function. Remarkably, pTACI was particularly regulated during tumor progression in our breast cancer cohort. TACI expression levels on platelets were correlated with clinical parameters including tumor stage, occurrence of metastasis and tumor cell proliferation (Ki67). In conclusion, our data emphasize the potential use of platelets as a liquid biomarker in breast cancer.

A novel prognostic prediction model based on seven immune-related RNAs for predicting overall survival of patients in early cervical squamous cell carcinoma

BACKGROUND

In this study, we aimed to mine immune-related RNAs expressed in early cervical squamous cell carcinoma to construct prognostic prediction models.

METHODS

The RNA sequencing data of 309 cervical squamous cell carcinoma (CSCC) cases, including data of individuals with available clinical information, were obtained from The Cancer Genome Atlas (TCGA) database. We included 181 early-stage CSCC tumor samples with clinical survival and prognosis information (training dataset). Then, we downloaded the GSE44001 gene expression profile data from the National Center for Biotechnology Information Gene Expression Omnibus (validation dataset). Gene ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathway analyses were used to analyze the biological functions of differentially expressed immune-related genes (DEIRGs). We established protein-protein interactions and competing endogenous RNA networks using Cytoscape. Using the Kaplan-Meier method, we evaluated the association between the high- and low-risk groups and the actual survival and prognosis information. Our univariate and multivariate Cox regression analyses screened for independent prognostic factors.

RESULTS

We identified seven prognosis-related signature genes (RBAKDN, CXCL2, ZAP70, CLEC2D, CD27, KLRB1, VCAM1), the expression of which was markedly associated with overall survival (OS) in CSCC patients. Also, the risk score of the seven-gene signature discripted superior ability to categorize CSCC patients into high-risk and low-risk groups, with a observablydifferent OS in the training and validation datasets. We screened two independent prognostic factors (Pathologic N and prognostic score model status) that correlated significantly by univariate and multivariate Cox regression analyses in the TCGA dataset. To further explore the potential mechanism of immune-related genes, we observed associated essential high-risk genes with a cytokine-cytokine receptor interaction.

CONCLUSIONS

This study established an immune-related RNA signature, which provided a reliable prognostic tool and may be of great significance for determining immune-related biomarkers in CSCC.

The TNFSF Members APRIL and BAFF and Their Receptors TACI, BCMA, and BAFFR in Oncology, With a Special Focus in Breast Cancer

Tumor necrosis factor (TNF) superfamily consists of 19 ligands and 29 receptors and is related to multiple cellular events from proliferation and differentiation to apoptosis and tumor reduction. In this review, we overview the whole system, and we focus on A proliferation-inducing ligand (APRIL, TNFSF13) and B cell-activating factor (BAFF, TNFSF13B) and their receptors transmembrane activator and Ca²⁺ modulator (CAML) interactor (TACI, TNFRSF13B), B cell maturation antigen (BCMA, TNFRSF17), and BAFF receptor (BAFFR, TNFRSF13C). We explore their role in cancer and novel biological therapies introduced for multiple myeloma and further focus on breast cancer, in which the modulation of this system seems to be of potential interest, as a novel therapeutic target. Finally, we discuss some precautions which should be taken into consideration, while targeting the APRIL–BAFF system.