Background: ITGA3 is a member of the integrin family, a cell surface adhesion molecule that can interact with extracellular matrix (ECM) proteins. The purpose of this study was to explore the significance of ITGA3 expression in the prognosis and clinical diagnosis of breast cancer patients.Methods: Oncomine, the Human Protein Atlas (HPA) and UALCAN were used to analyze the expression of ITGA3 in various cancers. PrognoScan, GEPIA, Kaplan–Meier plotter and Easysurv were utilized to analyze the prognosis of ITGA3 in certain cancers. Based on TCGA data, a receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of ITGA3 expression. cBio-Portal and MethSurv were used to evaluate the genomic mechanism. LinkedOmics, NetworkAnalyst and Metascape were used to build the signaling network. TIMER is a web server for comprehensive analysis of tumor infiltrating immune cells and tumor infiltrating lymphocytes (TILs).Results: The expression of ITGA3 in normal breast tissues was greater than that in breast cancer tissues at both the mRNA and protein levels. High expression of ITGA3 was associated with better prognosis of breast cancer patients. ROC analysis indicated that ITGA3 had significant diagnostic value. Genomic analysis revealed that promoter methylation of ITGA3 leads to transcriptional silencing, which may be one of the mechanisms underlying ITGA3 downregulation in BRCA. Immune infiltration analysis showed that ITGA3 may be involved in the recruitment of immune cells.Conclusions: This study identified ITGA3 as a novel biomarker to estimate the diagnosis and prognosis of breast cancer. In addition, ITGA3 is involved in ECM regulation and immune cell infiltration.

Triple-negative breast cancer (TNBC) has a shorter survival time and higher mortality rate than other molecular subtypes. RSRC2 is a newly discovered tumor suppressor gene. However, the potential functional mechanism of RSRC2 in TNBC remains unknown so far. Multiple bioinformatics databases were used. A Human Transcriptome Array 2.0 analysis, ChIP-seq analysis, ChIP-qPCR, RT-qPCR, Western blot, cell function assays in vitro and a metastatic mouse model in vivo were performed to demonstrate the role of RSRC2 in TNBC. Through the analysis of various databases, RSRC2 expression was the lowest in TNBC tissues compared to other molecular subtypes. The low expression of RSRC2 was associated with a worse prognosis for patients with breast cancer. The transcriptome array, ChIP-seq and bioinformatics analysis identified that GRHL2 and SCIN might have a close relationship with RSRC2. The functional bioinformatics enrichment analysis and functional cell experiments showed that RSRC2 was involved in cell adhesion, cell proliferation, cell migration and invasion. Furthermore, RSRC2 expression suppressed SCIN expression but not GRHL2 expression. SCIN re-expression in the RSRC2 overexpression cells or SCIN knockdown in the RSRC2 knockdown cells reversed the cellular function caused by RSRC2. Mechanistically, RSRC2 transcriptionally inhibited SCIN expression. In summary, our study reveals that RSRC2 acts as a tumor suppressor in TNBC development and progression through negatively regulating SCIN-mediated cell function, thus providing a potential target for TNBC treatment.

Background: Hepatocellular carcinoma (HCC) often presents with satellite nodules, rendering current curative treatments ineffective in many patients. The heterogeneity of HCC is a major challenge in personalized medicine. The emergence of spatial transcriptomics (ST) provides a powerful strategy for delineating the complex molecular landscapes of tumours. Methods: In this study, the heterogeneity of tissue-wide gene expression in tumour and adjacent nonneoplastic tissues using ST technology were investigated. The transcriptomes of nearly 10,820 tissue regions and identified the main gene expression clusters and their specific marker genes (differentially expressed genes, DEGs) in patients were analysed. The DEGs were analysed from two perspectives. First, two distinct gene profiles were identified to be associated with satellite nodules and conducted a more comprehensive analysis of both gene profiles. Their clinical relevance in human HCC was validated with Kaplan–Meier (KM) Plotter. Second, DEGs were screened with The Cancer Genome Atlas (TCGA) database to divide the HCC cohort into high- and low-risk groups according to Cox analysis. HCC patients from the International Cancer Genome Consortium (ICGC) cohort were used for validation. KM analysis was used to compare the overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors for OS. Results: Novel markers for the prediction of satellite nodules were identified and a tumour clusters-specific marker gene signature model (6 genes) for HCC prognosis was constructed. Conclusion: The establishment of marker gene profiles may be an important step towards an unbiased view of HCC, and the 6-gene signature can be used for prognostic prediction in HCC. This analysis will help us to clarify one of the possible sources of HCC heterogeneity and uncover pathogenic mechanisms and novel antitumour drug targets.

Background A hypoxic microenvironment is the most frequent characteristic in tumor microenvironment. Programmed death-ligand 1 (PD-L1) is an important molecule and therapeutic target that mediates the immune response of tumor cells. Previous studies have shown that hypoxia can lead to increased expression of Nucleophosmin 1 (NPM1) and PD-L1. However, the exact regulatory mechanisms of NPM1 and PD-L1 expression under hypoxic conditions are still poorly understood. Methods The relationships among hypoxia, NPM1 and PD-L1 were explored by western blotting, immunofluorescence staining, flow cytometry and chromatin immunoprecipitation-quantitativePCR(ChIP-qPCR). Animal tumor models were established to explore the effect of NPM1 expression on tumor growth. The relationships between NPM1 and breast cancer (BC) clinical features and immune infiltration were revealed by bioinformatics analysis. Results NPM1 mediates increased PD-L1 expression in the hypoxic microenvironment of BC. HIF-1α can increase the expression of NPM1 by activating the p-AKT pathway and binding to the NPM1 promoter. Increased expression of NPM1 can promote tumor growth and inhibit T cell infiltration. Bioinformatics analysis showed that the high expression of NPM1 was associated with poorer survival and immunosuppression in patients with BC. Conclusions The hypoxic microenvironment promotes PD-L1 expression via NPM1 in BC, which may be further associated with the inhibition of tumor immunity. NPM1 may serve as a potential target for modulating PD-L1 immunotherapy.

Prostaglandin E receptor 3 (PTGER3) is involved in a variety of biological processes in the human body and is closely associated with the development and progression of a variety of cancer types. However, the role of PTGER3 in triple‐negative breast cancer (TNBC) remains unclear. In the present study, low PTGER3 expression was found to be associated with poor prognosis in TNBC patients. PTGER3 plays a crucial role in regulating TNBC cell invasion, migration, and proliferation. Upregulation of PTGER3 weakens the epithelial–mesenchymal phenotype in TNBC and promotes ferroptosis both in vitro and in vivo by repressing glutathione peroxidase 4 (GPX4) expression. On the other hand, downregulation of PTGER3 inhibits ferroptosis by increasing GPX4 expression and activating the PI3K‐AKT pathway. Upregulation of PTGER3 also enhances the sensitivity of TNBC cells to paclitaxel. Overall, this study has elucidated critical pathways in which low PTGER3 expression protects TNBC cells from undergoing ferroptosis, thereby promoting its progression. PTGER3 may thus serve as a novel and promising biomarker and therapeutic target for TNBC.