SIPL1, Regulated by MAZ, Promotes Tumor Progression and Predicts Poor Survival in Human Triple-Negative Breast Cancer

Turmeric Inhibits MDA-MB-231 Cancer Cell Proliferation, Altering miR-638-5p and Its Potential Targets

Objective

Recent research suggests curcumin extracted from the turmeric plant may inhibit the proliferation of cancer cells by controlling the expression of microRNAs (miRNAs). The effect of phenolic curcumin on miR-638-5p and potential target gene expressions in the triple negative breast cancer (TNBC) cell line MDA-MB-231 was investigated in this study.

Materials and Methods

GSE154255 and GSE40525 datasets were downloaded and analyzed using GEO2R to identify dysregulated miRNAs in TNBC. To find differently expressed genes in breast cancer (BRCA), The Cancer Genome Atlas Program data was examined. Utilizing in silico tools, KEGG, GO, and other enrichment analyses were performed. The databases miRNet, miRTarBase v8.0, and TarBase v.8 were used for miRNA and mRNA matching. Real-time quantitative reverse transcription polymerase chain reaction was used to examine the levels of miRNA and its targets in miRNA mimic transfected/curcumin-treated MDA-MB-231 cultures and controls. The cell viability detection kit-8 method was used to assess cell viability, and the scratch assay was used to conduct migration assessment.

Results

Bioinformatics analysis showed that miR-638-5p was significantly reduced in TNBC patients. Experimental results showed that miR-638-5p was upregulated in MDA-MB-231 treated with curcumin, while the potential target genes of miR-638-5p, CFL1, SIX4, MAZ, and CDH1 were downregulated. Mimic miR-638-5p transfection inhibited MDA-MB-231 cell proliferation and reduced migration and expression of CFL1, SIX4, and MAZ genes was decreased in mimic miR-638-5p transfected cells.

Conclusion

These findings suggest that curcumin exerts its anticancer effects on MDA-MB-231 cells by modulating the expression of miR-638-5p and its possible target genes.

Combination of verteporfin-photodynamic therapy with 5-aza-2'-deoxycytidine enhances the anti-tumour immune response in triple negative breast cancer

Introduction

Triple negative breast cancer (TNBC) is a subtype of breast cancer characterised by its high tumourigenic, invasive, and immunosuppressive nature. Photodynamic therapy (PDT) is a focal therapy that uses light to activate a photosensitizing agent and induce a cytotoxic effect. 5-aza-2'-deoxycytidine (5-ADC) is a clinically approved immunomodulatory chemotherapy agent. The mechanism of the combination therapy using PDT and 5-ADC in evoking an anti-tumour response is not fully understood.

Methods

The present study examined whether a single dose of 5-ADC enhances the cytotoxic and anti-tumour immune effect of low dose PDT with verteporfin as the photosensitiser in a TNBC orthotopic syngeneic murine model, using the triple negative murine mammary tumour cell line 4T1. Histopathology analysis, digital pathology and immunohistochemistry of treated tumours and distant sites were assessed. Flow cytometry of splenic and breast tissue was used to identify T cell populations. Bioinformatics were used to identify tumour immune microenvironments related to TNBC patients.

Results

Functional experiments showed that PDT was most effective when used in combination with 5-ADC to optimize its efficacy. 5-ADC/PDT combination therapy elicited a synergistic effect in vitro and was significantly more cytotoxic than monotherapies on 4T1 tumour cells. For tumour therapy, all types of treatments demonstrated histopathologically defined margins of necrosis, increased T cell expression in the spleen with absence of metastases or distant tissue destruction. Flow cytometry and digital pathology results showed significant increases in CD8 expressing cells with all treatments, whereas only the 5-ADC/PDT combination therapy showed increase in CD4 expression. Bioinformatics analysis of in silico publicly available TNBC data identified BCL3 and BCL2 as well as the following anti-tumour immune response biomarkers as significantly altered in TNBC compared to other breast cancer subtypes: GZMA, PRF1, CXCL1, CCL2, CCL4, and CCL5. Interestingly, molecular biomarker assays showed increase in anti-tumour response genes after treatment. The results showed concomitant increase in BCL3, with decrease in BCL2 expression in TNBC treatment. In addition, the treatments showed decrease in PRF1, CCL2, CCL4, and CCL5 genes with 5-ADC and 5-ADC/PDT treatment in both spleen and breast tissue, with the latter showing the most decrease.

Discussion

To our knowledge, this is the first study that shows which of the innate and adaptive immune biomarkers are activated during PDT related treatment of the TNBC 4T1 mouse models. The results also indicate that some of the immune response biomarkers can be used to monitor the effectiveness of PDT treatment in TNBC murine model warranting further investigation in human subjects.

The Prognostic Value of ASPHD1 and ZBTB12 in Colorectal Cancer: A Machine Learning-Based Integrated Bioinformatics Approach

Introduction: Colorectal cancer (CRC) is a common cancer associated with poor outcomes, underscoring a need for the identification of novel prognostic and therapeutic targets to improve outcomes. This study aimed to identify genetic variants and differentially expressed genes (DEGs) using genome-wide DNA and RNA sequencing followed by validation in a large cohort of patients with CRC. Methods: Whole genome and gene expression profiling were used to identify DEGs and genetic alterations in 146 patients with CRC. Gene Ontology, Reactom, GSEA, and Human Disease Ontology were employed to study the biological process and pathways involved in CRC. Survival analysis on dysregulated genes in patients with CRC was conducted using Cox regression and Kaplan-Meier analysis. The STRING database was used to construct a protein-protein interaction (PPI) network. Moreover, candidate genes were subjected to ML-based analysis and the Receiver operating characteristic (ROC) curve. Subsequently, the expression of the identified genes was evaluated by Real-time PCR (RT-PCR) in another cohort of 64 patients with CRC. Gene variants affecting the regulation of candidate gene expressions were further validated followed by Whole Exome Sequencing (WES) in 15 patients with CRC. Results: A total of 3576 DEGs in the early stages of CRC and 2985 DEGs in the advanced stages of CRC were identified. ASPHD1 and ZBTB12 genes were identified as potential prognostic markers. Moreover, the combination of ASPHD and ZBTB12 genes was sensitive, and the two were considered specific markers, with an area under the curve (AUC) of 0.934, 1.00, and 0.986, respectively. The expression levels of these two genes were higher in patients with CRC. Moreover, our data identified two novel genetic variants-the rs925939730 variant in ASPHD1 and the rs1428982750 variant in ZBTB1-as being potentially involved in the regulation of gene expression. Conclusions: Our findings provide a proof of concept for the prognostic values of two novel genes-ASPHD1 and ZBTB12-and their associated variants (rs925939730 and rs1428982750) in CRC, supporting further functional analyses to evaluate the value of emerging biomarkers in colorectal cancer.

Construction of a breast cancer prognosis model based on alternative splicing and immune infiltration

BACKGROUND

Breast cancer (BC) is the most common malignancy among women in the world. Alternative splicing (AS) is an important mechanism for regulating gene expression and producing proteome diversity, which is closely related to tumorigenesis. Understanding the role of AS in BC may be helpful to reveal new therapeutic targets for clinical interventions.

METHODS

RNA-seq, clinical and AS data of TCGA-BRCA were downloaded from TCGA and TCGA SpliceSeq databases. AS events associated with prognosis were filtered by univariate Cox regression. The AS risk model of BC was built by Lasso regression, random forest and multivariate Cox regression. The accuracy of the AS risk model and clinicopathological factors were evaluated by time-dependent receiver operating characteristic (ROC) curves. The significant factors were used to construct the nomogram model. Tumor microenvironment analysis, immune infiltration and immune checkpoint analysis were performed to show the differences between the high and low AS risk groups. The expression differences of genes of AS events constituting the risk model in tumor tissues and normal tissues were analyzed, the genes with significant differences were screened, and their relationship with prognosis, tumor microenvironment, immune infiltration and immune checkpoint were analyzed. Finally, Pearson correlation analysis was used to calculate the correlation coefficient between splicing factors (SF) and prognostic AS events in TCGA-BRCA. The results were imported into Cytoscape, and the associated network was constructed.

RESULTS

A total of 21,232 genes had 45,421 AS events occurring in TCGA-BRCA, while 1604 AS events were found to be significantly correlated with survival. The BRCA risk model consisted of 5 AS events, (TTC39C|44853|AT*- 2.67) + (HSPBP1|52052|AP*- 4.28) + (MAZ|35942|ES*2.34) + (ANK3|11845|AP*1.18) + (ZC3HAV1|81940|AT*1.59), which were confirmed to be valuable for predicting BRCA prognosis to a certain degree, including ROC curve, survival analysis, tumor microenvironment analysis, immune infiltration and immune checkpoint analysis. Based on this, we constructed a nomogram prediction model composed of clinicopathological features and the AS risk signature. Furthermore, we found that MAZ was a core gene indicating the connection of tumor prognosis and AS events. Ultimately, a network of SF-AS regulation was established to reveal the relationship between them.

CONCLUSIONS

We constructed a nomogram model combined with clinicopathological features and AS risk score to predict the prognosis of BC. The detailed analysis of tumor microenvironment and immune infiltration in the AS risk model may further reveal the potential mechanisms of BC recurrence and development.