Immune Infiltrates In Breast Cancer Research Articles

Comprehensive analysis of the expression level, prognostic value, and immune infiltration of cuproptosis-related genes in human breast cancer.

As a novel cell death form, cuproptosis results from copper combining with lipidated proteins in the tricarboxylic acid cycle. To the best of our knowledge no study has yet comprehensively analyzed the relationship between cuproptosis-related genes and breast cancer. The expression, prognostic value, mutations, chemosensitivity, and immune infiltration of cuproptosis-related genes in breast carcinoma patients were analyzed, PPI networks were constructed, and enrichment analyses were performed based on these genes. TIMER, UALCAN, Kaplan-Meier plotter, Human Protein Atlas, cBioPortal, STRING, GeneMANIA, DAVID, and R program v4.0.3 were used to accomplish the analyses above. Compared to normal breast tissues, FDX1, LIAS, LIPT1, DLD, DLAT, PDHA1, MTF1, and GLS were down-regulated in breast cancer tissues, while CDKN2A was up-regulated. High expression of FDX1, LIAS, DLD, DLAT, MTF1, GLS, and CDKN2A were associated with favorable overall survival. Cuproptosis-related genes showed a high alteration rate (51.3%) in breast cancer, contributing to worse clinical outcomes. The expression levels of FDX1, LIPT1, DLD, DLAT, PDHA1, PDHB, MTF1, GLS, and CDKN2A were associated positively with 1 or more immune cell infiltrations in breast cancer. Patients with high levels of B cell, CD4+ T cell, CD8+ T cell, and dendritic cell infiltration had a higher survival rate at 10 years. This study comprehensively investigated relationships between cuproptosis and breast cancer by bioinformatic analyses. We found that cuproptosis-related genes were generally lowly expressed in breast carcinoma tissue. As the critical gene of cuproptosis, high expression of FDX1 was related to favorable prognoses in breast cancer patients; thus, it might be a potential prognostic marker. Moreover, genes associated with cuproptosis were linked to immune infiltration in breast cancer and this relationship affected the prognosis of breast cancer.

Prognostic value of PLEKHA4 and its correlation with tumor-infiltrating immune cells in breast cancer: a comprehensive study based on bioinformatics and clinical analysis validation.

Pleckstrin homology containing family A, number 4 (PLEKHA4) plays a role in a number of biological processes in human cells, including cell polarization, growth, and proliferation. However, the relationship between PLEKHA4 expression and survival in breast cancer (BC) remains unclear. The aim of this study is to investigate the potential of PLEKHA4 as a prognostic indicator in BC. We obtained gene expression profiles of BC and normal tissues from the Tumor Immune Estimation Resource (TIMER), UALCAN web. Immunohistochemistry (IHC) staining was performed to investigate the protein expression and prognostic value of PLEKHA4 in BC patients. The prognostic value was analyzed using Kaplan-Meier curve analysis and Cox regression analysis in R software after downloading The Cancer Genome Atlas (TCGA) databases. The correlations between PLEKHA4 and tumor immune infiltrates were investigated via gene set variation analysis (GSVA). Signaling pathways related to PLEKHA4 expression were identified by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Both bioinformatics and IHC results showed that PLEKHA4 was expressed at low levels in BC tissues compared with the adjacent tissues. Furthermore, the expression of PLEKHA4 was negatively correlated with ages (χ2=6.394, P=0.01), molecular subtype (χ2=15.606, P=0.001), lymph node metastasis (χ2=13.753, P=0.004), tumor-node-metastasis (TNM) stage (χ2=22.616, P<0.001). Kaplan-Meier curves implicated low expression of PLEKHA4 was associated with worse survival of BC patients [hazard ratio (HR) =0.46, P=0.01]. Cox regression models showed that low PLEKHA4 expression could be an independent risk factor for BC (HR =0.911, P=0.006). The results of gene set enrichment analysis (GSEA) showed that cell cycle, Notch signaling pathway, nuclear factor erythroid 2-related factor 2 (NRF2) signaling pathway, and Rho GTPases were highly enriched in the low PLEKHA4 expression group, as identified by GO and KEGG. Additionally, in BC, PLEKHA4 expression displayed a positive correlation with the infiltration of natural killer (NK) cells (P<0.001), CD8+ T cells (P<0.001), B cells (P<0.001), neutrophils (P<0.001), and dendritic cells (DCs) (P<0.001). The findings indicate that PLEKHA4 is an independent prognostic biomarker associated with key signaling pathways and immune infiltration in BC. Targeting PLEKHA4 may contribute to improving immunotherapy for BC.

SEMA7A as a Novel Prognostic Biomarker and Its Correlation with Immune Infiltrates in Breast Cancer.

The role of Semaphorin 7a (SEMA7A) in the initiation and progression of different types of cancerous lesions has been extensively studied. However, the prognostic significance of SEMA7A, specifically in breast cancer (BC), lacks clarity. We conducted an evaluation on the relationship between SEMA7A and the prognosis, immune invasion and tumor mutation burden in different types of cancer by analyzing data from The Cancer Genome Atlas database. The present study focused on investigating the expression level, mutation, immune correlation and coexpression of SEMA7A in BC, utilizing various databases such as the University of Alabama at Birmingham Cancer data analysis portal, cBioPortal and tumor immune estimation resource. Survival analysis was carried out using the Kaplan-Meier Plotter. Furthermore, we employed the R software package to generate receiver operating characteristic (ROC) curves and nomograms. Notably, P<0.05 was considered to indicate statistical significance. Using pancancer analysis, it has been observed that the expression of SEMA7A is elevated in various types of cancer and is strongly correlated with the prognosis of different cancer types. SEMA7A also exhibits a significant association with the tumor mutation burden of diverse types of cancer. Moreover, SEMA7A displays a notable increase in BC cases, and was indicated to have a substantial association with the abundance of immune infiltration. In-depth survival analysis demonstrated that elevated levels of SEMA7A expression are notably linked to shorter overall survival and distant metastasis-free survival among patients with BC. The efficiency of SEMA7A as a reliable prognostic biomarker for BC has been substantiated by the validation of ROC curves and nomograms. SEMA7A has the potential to function as a prognostic indicator for BC, and its correlation with immune infiltration in BC is significant.

Identification of new subtypes of breast cancer based on vasculogenic mimicry related genes and a new model for predicting the prognosis of breast cancer

Breast cancer is a malignant tumor that poses a serious threat to women's health, and vasculogenic mimicry (VM) is strongly associated with bad prognosis in breast cancer. However, the relationship between VM and immune infiltration in breast cancer and the underlying mechanisms have not been fully studied. On the basis of the Cancer Genome Atlas (TCGA), Fudan University Shanghai Cancer Center (FUSCC) database, GSCALite database, and gene set enrichment analysis (GSEA) datasets, we investigated the potential involvement of VM-related genes in the development and progression of breast cancer. We analyzed the differential expression, mutation status, methylation status, drug sensitivity, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoints, tumor microenvironment (TME), and immune cell infiltration levels associated with VM-related genes in breast cancer. We created two VM subclusters out of breast cancer patients using consensus clustering, and discovered that patients in Cluster 1 had better survival outcomes compared to those in Cluster 2. The infiltration levels of T cells CD4 memory resting and T cells CD8 were higher in Cluster 1, indicating an immune-active state in this cluster. Additionally, we selected three prognostic genes (LAMC2, PIK3CA, and TFPI2) using Lasso, univariate, and multivariate Cox regression and constructed a risk model, which was validated in an external dataset. The prognosis of patients is strongly correlated with aberrant expression of VM-related genes, which advances our knowledge of the tumor immune milieu and enables us to identify previously unidentified breast cancer subtypes. This could direct more potent immunotherapy approaches.

Identification of HOXC Gene Family as Prognostic and Immune-Related Biomarkers in Breast Cancer Through mRNA Transcriptional Profile and Experimental Validation.

Breast cancer (BC) is the most common malignancy in women worldwide, and more effective biomarkers are urgently needed for the prevention and treatment of BC. Our study aimed to investigate the role of the HOXC gene family (HOXCs) and its relationship with the immune response in BC. The differential expression of HOXCs and its clinical prognostic significance in BC were explored using bioinformatics analysis, and the cBioPortal database was used to evaluate the genetic mutation profile of the HOXCs in BC. The results indicated that the expression levels of HOXC4, 10, 11, 12, and 13 were significantly increased in BC tissues compared with the normal tissues, and expressions of these genes were closely associated with BC stage, among them, high expression levels of HOXC10 and HOXC13 predicted poor outcome in BC patients. In addition, to elucidate the essential role of HOXCs in the tumor microenvironment and immunotherapeutic response of BC, the impact of HOXCs on the regulation of immune infiltration in BC was comprehensively assessed. The result showed thatHOXC10 and HOXC13 expressions were significantly positively linked with the infiltration levels of CD8+T cell and M1 macrophage, while they werenegatively related to Mast and Natural killer cells, suggesting the important influence of HOXCs on regulating tumor immunity in BC patients. Lastly, the RT-qPCR assay was employed to validate HOXCs expression in samples of BC patients. In conclusion, HOXCs may be a promising prognostic indicator and couldregulate the immune infiltration in BC patients, thus being apromising targeted immunotherapy for BC.

Matrix Metalloproteinase 1 Acts as an Independent Prognostic Biomarker Correlated with Immune Infiltration in Breast Cancer

Matrix metalloproteinase 1 (MMP1) is overexpressed in multiple human tumors. However, the role of MMP1 in breast cancer (BRCA) has not been explored. The relationship between MMP1 expression and immune cell infiltration was conducted using Tumor Immune Estimation Resource (TIMER, &lt;ext-link ext-link-type="uri" xlink:href="https://cistrome.shinyapps.io/timer/"&gt;https://cistrome.shinyapps.io/timer/&lt;/ext-link&gt;), and the survival curve was plotted using Kaplan-Meier with log-rank test. The influence of MMP1 on immune infiltration, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, immunologic infiltration analysis, and drug sensitivity were conducted through R 4.2.0. Immunohistochemistry (IHC) and immunofluorescence (IF) were used to verify MMP1 expression in BC and the correlation between MMP1 and CD20, CD86 immune cells. MMP1 was overexpressed in BRCA tumors (P &lt; 0.05), and its high expression was related to poor prognosis (P = 0.01). In addition, MMP1 was an independent prognostic biomarker in BRCA. Our findings provide information to further understand the biological functions and signaling pathways of MMP1 in BRCA. IHC and IF have proven the relationship between MMP1 and BRCA. These results implied a critical role of MMP1 in the prognosis and immune infiltration of BRCA. In addition, MMP1 expression participated in regulating multiple oncogenes and tumorigenesis.

Integrative analysis based on the cell cycle-related genes identifies TPX2 as a novel prognostic biomarker associated with tumor immunity in breast cancer.

This study aims to identify the essential cell cycle-related genes associated with prognosis in breast cancer (BRCA), and to verify the relationship between the central gene and immune infiltration, so as to provide detailed and comprehensive information for the treatment of BRCA. Gene expression profiles (GSE10780, GSE21422, GSE61304) and the Cancer Genome Atlas (TCGA) BRCA data were used to identify differentially expressed genes (DEGs) and further functional enrichment analysis. STRING and Cytoscape were employed for the protein-protein interaction (PPI) network construction. TPX2 was viewed as the crucial prognostic gene by the Survival and Cox analysis. Furthermore, the connection between TPX2 expression and immune infiltrating cells and immune checkpoints in BRCA was also performed by the TIMER online database and R software. A total of 18 cell cycle-related DEGs were identified in this study. Subsequently, an intersection analysis based on TCGA-BRCA prognostic genes and the above DEGs identified three genes (TPX2, UBE2C, CCNE2) as crucial prognostic candidate biomarkers. Moreover, we also demonstrated that TPX2 is closely associated with immune infiltration in BRCA and a positive relation between TPX2 and PD-L1 expression was firstly detected. These results revealed that TPX2 is a potential prognostic biomarker and closely correlated with immune infiltration in BRCA, which could provide powerful and efficient strategies for breast cancer immunotherapy.

Exploration of a noninvasive radiomics classifier for breast cancer tumor microenvironment categorization and prognostic outcome prediction

Rationale and Objectives: Breast cancer progression and treatment response are significantly influenced by the tumor microenvironment (TME). Traditional methods for assessing TME are invasive, posing a challenge for patient care. This study introduces a non-invasive approach to TME classification by integrating radiomics and machine learning, aiming to predict the TME status using imaging data, thereby aiding in prognostic outcome prediction. Materials and MethodsUtilizing multi-omics data from The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA), this study employed CIBERSORT and MCP-counter algorithms analyze immune infiltration in breast cancer. A radiomics classifier was developed using a random forest algorithm, leveraging quantitative features extracted from intratumoral and peritumoral regions of Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) scans. The classifer’s ability to predict diverse TME states were and their prognostic implications were evaluated using Kaplan-Meier survival curves. ResultsThree distinct TME states were identified using RNA-Seq data, each displaying unique prognostic and biological characteristics. Notably, patients with increased immune cell infiltration showed significantly improved prognoses (P < 0.05). The classifier, comprising 24 radiomic features, demonstrated high predictive accuracy (AUC of training set = 0.960, 95 % CI: 0.922, 0.997; AUC of testing set = 0.853, 95 % CI: 0.687, 1.000) in differentiating these TME states. Predictions from the classifier also correlated significantly with overall patient survival (P < 0.05). ConclusionThis study offers a detailed analysis of the complex TME states in breast cancer and presents a reliable, noninvasive radiomics classifier for TME assessment. The classifer’s accurate prediction of TME status and its correlation with prognosis highlight its potential as a tool in personalized breast cancer treatment, paving the way for more individualized and less invasive therapeutic strategies.

Expression and Clinical Significance of NUDCD1, PI3K/AKT/mTOR Signaling Pathway-Related Molecules and Immune Infiltration in Breast Cancer

BackgroundNUDCD1 (NudC Domain Containing 1) performs an essential function in biological processes such as cell progression, migration, cell cycle, and intracellular material transport. Many solid tumors express it highly, which is a prospective biomarker and therapeutic approach. However, the expression and clinical importance of NUDCD1 across breast cancer is unclear. MethodsThe expressions of NUDCD1 in breast cancers and normal breast tissues were studied utilizing the TIMER database and immunohistochemical analysis. Subsequently, we validate the association between the expression of NUDCD1 and clinicopathologic features and prognosis of breast cancer. The immunohistochemical experiments of pathway-related molecules were done on 214 breast cancer tissue microarrays. The investigation of correlation between NUDCD1 expression and tumor immune infiltration was subsequently conducted. ResultsThrough the utilization of bioinformatics analysis and immunohistochemical experiments, it was determined that NUDCD1 exhibited upregulation within breast cancer. Furthermore, it was discovered that an elevated expression of NUDCD1 may potentially be linked to a worse prognosis in breast cancer. Our study reveals that the PI3K/AKT/mTOR signaling pathway may perform a function in NUDCD1 regulating breast cancer progression via enrichment analysis. Furthermore, the expression of NUDCD1 may be associated with the degree of immunological infiltration. ConclusionThe expression of NUDCD1 was explored to be elevated in breast cancer and was observed to be correlated with a poorer prognosis. p-AKT, PI3K, AKT, mTOR, and p-mTOR expression levels underwent significant elevation in breast cancer. The function of NUDCD1 within breast cancer might be associated with the PI3K/AKT/mTOR signaling pathway.

Low expression of KLRB1 predicts poor survival outcomes and is associated with immune infiltration in breast cancer.

KLRB1 is downregulated in various cancer types. Nevertheless, the specific involvement of KLRB1 in the context of breast cancer (BRCA) has not been fully elucidated. This research aimed to explore its clinical value in BRCA. A dataset comprising 1,109 BRCA samples and 113 healthy samples was retrieved from The Cancer Genome Atlas (TCGA) database to establish the association between KLRB1 expression and pan-cancer. Subsequently, an analysis was executed to explore the link between KLRB1 and BRCA. T-tests and Chi-squared tests were conducted to assess the expression of KLRB1 and its clinical implications in BRCA. The prognosis-predictive value of KLRB1 in BRCA was assessed using the Kaplan-Meier method and Cox regression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses screened biological pathways to analyze the association between the immune infiltration level and KLRB1 expression in BRCA. Lastly, the conclusion was validated through quantitative polymerase chain reaction (qPCR), immunohistochemistry (IHC), and Cell Counting Kit-8 (CCK8) assays. KLRB1 exhibited low expression in patients with BRCA. Furthermore, KLRB1 demonstrated strong diagnostic potential, as indicated by an area under curve (AUC) of 0.712. Kaplan-Meier survival and Cox regression analyses indicated that attenuated expression of KLRB1 was independently linked to unfavorable clinical outcomes. GO and KEGG enrichment analyses were performed on the top 10 genes that exhibited positive and negative correlations with KLRB1. Analysis of genes positively correlated with KLRB1 revealed associations with signaling receptor activator activity, lymphocyte proliferation, mononuclear cell proliferation, leukocyte proliferation, receptor-ligand activity, immunoglobulin binding, and hematopoietic cell lineage signaling pathway. KLRB1 expression exhibited significant correlations with all immune cells. Furthermore, qPCR and IHC outcomes demonstrated that KLRB1 was significantly downregulated in BRCA tissues. CCK8 findings showed a decrease in the proliferation of BRCA MCF7 cells upon knockout of KLRB1. This research investigated the mechanism and potential therapeutic target of the KLRB1 gene in BRCA. By analyzing the expression and function of the KLRB1 gene, the study aims to find its significant role in the onset and progression of BRCA. This research endeavors to offer novel strategies and approaches for treating BRCA.

Vasculogenic mimicry regulates immune infiltration and mutational status of the tumor microenvironment in breast cancer to influence tumor prognosis.

Vasculogenic mimicry (VM) refers to the direct formation of microcirculatory ducts by invasive malignant tumors via cellular phenotypic transformation. However, there is a lack of VM-based biomarkers for breast cancer. We obtained transcriptomic expression data, single cell sequencing data, and clinical data of patients from The Cancer Genome Atlas Program (TCGA) database and GEO database, performed single cell analysis to obtain specific type annotations of breast cancer cells and analyzed their spatial expression analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analyses as well as Gene Set Enrichment Analysis (GSEA) analyses were performed to clarify the biological pathways and tumor functional enrichment relationships of the major expressed genes of VM in the breast cancer bulk data specimens. VM biomarkers were constructed. Meanwhile, the relationship between VM scores and tumor immune infiltration in breast cancer was analyzed using MCPcounter and ssGSEA methods. In addition, we assessed the specific relationship between NDRG1, a key VM gene in breast cancer, and tumor colonization, adhesion and invasion by biological experiments in breast cancer cell lines. The main cell types of breast cancer (BRCA) samples were annotated by single cell transcriptome analysis. Most of the VM-high group was present in epithelial cells, whereas the VM-low group was present in immune and stromal cells. Multiple tumor pathways such as TGFβ p53 and MAPK were closely associated with VM-mediated breast cancer infiltration and invasion. A prognostic model of breast cancer based on VM key genes was constituted. Prognostic stratification of breast cancer was successfully achieved for the TCGA-BRCA and GSE58812 datasets. Through immune infiltration analysis, we found that differential expression of VM markers was associated with multiple immune cell regulation. In MDA-MB-231 and MDA-MB-453 cell lines, we found that the NDRG1 gene significantly promoted colony formation of breast cancer cells. Our constructed VM-related gene-based model of breast cancer biology holds promise for prognostic prediction and patient stratification of breast cancer. This may provide a potentially clinically valuable aid in promoting a deeper understanding of the biological regulation of VM in breast cancer and exploring the specific mechanisms of tumor angiogenesis and breast cancer development.

KNSTRN Is a Prognostic Biomarker That Is Correlated with Immune Infiltration in Breast Cancer and Promotes Cell Cycle and Proliferation

Kinetochore-localized astrin/SPAG5-binding protein (KNSTRN) promotes the progression of bladder cancer and lung adenocarcinoma. However, its expression and biological function in breast cancer remain largely unknown. Therefore, this study aimed to analyze KNSTRN expression, prognoses, correlation with immune infiltration, expression-associated genes, and regulated signaling pathways to characterize its role in regulating the cell cycle using both bioinformatics and in vitro functional experiments. Analyses of The Cancer Genome Atlas, Gene Expression Omnibus, TIMER, and The Human Protein Atlas databases revealed a significant upregulation of KNSTRN transcript and protein levels in breast cancer. Kaplan–Meier survival analyses demonstrated a significant association between high expression of KNSTRN and poor overall survival, relapse-free survival, post-progression survival, and distant metastases-free survival in patients with breast cancer. Furthermore, multivariate Cox regression analyses confirmed that KNSTRN is an independent prognostic factor for breast cancer. Immune infiltration analysis indicated a positive correlation between KNSTRN expression and T regulatory cell infiltration while showing a negative correlation with Tgd and natural killer cell infiltration. Gene set enrichment analysis along with single-cell transcriptome data analysis suggested that KNSTRN promoted cell cycle progression by regulating the expression of key cell cycle proteins. The overexpression and silencing of KNSTRN in vitro, respectively, promoted and inhibited the proliferation of breast cancer cells. The overexpression of KNSTRN enhanced the expression of key cell cycle regulators, including CDK4, CDK6, and cyclin D3, thereby accelerating the G1/S phase transition and leading to aberrant proliferation of breast cancer cells. In conclusion, our study demonstrates that KNSTRN functions as an oncogene in breast cancer by regulating immune response, promoting G1/S transition, and facilitating breast cancer cell proliferation. Moreover, KNSTRN has potential as a molecular biomarker for diagnostic and prognostic prediction in breast cancer.

UTP23 Is a Promising Prognostic Biomarker and Is Associated with Immune Infiltration in Breast Cancer.

Breast cancer is one of the malignant tumors with a high incidence and mortality rate among women worldwide, and its prevalence is increasing year by year, posing a serious health risk to women. UTP23 (UTP23 Small Subunit Processome Component) is a nucleolar protein that is essential for ribosome production. As we all know, disruption of ribosome structure and function results in improper protein function, affecting the body's normal physiological processes and promoting cancer growth. However, little research has shown a connection between UTP23 and cancer. We analyzed the mRNA expression of UTP23 in normal tissue and breast cancer using The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database, and the protein expression of UTP23 using The Human Protein Atlas (HPA) database. Next, we examined the relationship between UTP23 high expression and Overall Survival (OS) using Kaplan-Meier Plotters and enriched 980 differentially expressed genes in UTP23 high and low expression samples using GO/KEGG and GSEA to identify potential biological functions of UTP23 and signaling pathways that it might influence. Finally, we also investigated the relationship between UTP23 and immune infiltration and examined the effect of UTP23 on the proliferation of human breast cancer cell lines by knocking down UTP23. We found that UTP23 levels in breast cancer patient samples were noticeably greater than those in healthy individuals and that high UTP23 levels were strongly linked with poor prognoses (P = 0.008). Functional enrichment analysis revealed that UTP23 expression was connected to the humoral immune response. Besides, UTP23 expression was found to be positively correlated with immune cell infiltration. Furthermore, UTP23 knockdown has been shown to inhibit the proliferation of human breast cancer cells MDA-MB-231 and HCC-1806. Taken together, our study demonstrated that UTP23 is a promising target in detecting and treating breast cancer and is intimately linked to immune infiltration.

Integrated Bioinformatics Analysis to Identify a Novel Four-Gene Prognostic Model of Breast Cancer and Reveal Its Association with Immune Infiltration.

Liquid-liquid phase separation (LLPS) impact immune signaling in cancer and related genes have shown prognostic value in breast cancer (BRCA). However, the crosstalk between LLPS and immune infiltration in BRCA remain unclear. Therefore, we aimed to develop a novel prognostic model of BRCA related to LLPS and immune infiltration. BRCA-related, liquid-liquid phase separation (LLPS)-related genes, and differentially expressed genes (DEGs) were identified using public databases. Mutation and drug sensitivity analyses were performed using Gene Set Cancer Analysis database. Univariate cox regression and LASSO Cox regression were used for the construction and verification of prognostic model. Kaplan-Meier analysis was performed to evaluate overall survival (OS). Gene set variation analysis was conducted to analyze key pathways. CIBERSORT was used to assess immune infiltration and its correlation with prognostic genes was determined through Pearson analysis. A total of 6056 BRCA-associated genes, 3775 LLPS-associated genes, and 4049 DEGs, resulting in 314 overlapping genes. Twenty-eight prognostic genes were screened, and some of them were mutational and related to drug sensitivity Subsequently, a prognostic model comprising L1CAM, EVL, FABP7, and CST1 was built. Patients in high-risk group had shorter OS than those in low-risk group. The infiltrating levels of CD8+ T cells, macrophages M0, macrophages M2, dendritic cells activated, and mast cells resting was altered in high-risk group of breast cancer patients compared to low-risk group. L1CAM, EVL, FABP7, and CST1 were related to these infiltrating immune cells. L1CAM, EVL, FABP7, and CST1 were potential diagnostic biomarkers and therapeutic targets for BRCA.

SOX13 is a novel prognostic biomarker and associates with immune infiltration in breast cancer.

The transcription factor, SOX13 is part of the SOX family. SOX proteins are crucial in the progression of many cancers, and some correlate with carcinogenesis. Nonetheless, the biological and clinical implications of SOX13 in human breast cancer (BC) remain rarely known. We evaluated the survival and expression data of SOX13 in BC patients via the UNLCAL, GEPIA, TIMER, and Kaplan-Meier plotter databases. Immunohistochemistry (IHC) was used to verify clinical specimens. The gene alteration rates of SOX13 were acquired on the online web cBioportal. With the aid of the TCGA data, the association between SOX13 mRNA expression and copy number alterations (CNA) and methylation was determined. LinkedOmics was used to identify the genes that co-expressed with SOX13 and the regulators. Immune infiltration and tumor microenvironment evaluations were assessed by ImmuCellAI and TIMER2.0 databases. SOX13 correlated drug resistance analysis was performed using the GDSC2 database. Higher SOX13 expression was discovered in BC tissues in comparison to normal tissues. Moreover, increased gene mutation and amplification of SOX13 were found in BC. Patients with increased SOX13 expression levels showed worse overall survival (OS). Cox analysis showed that SOX13 independently served as a prognostic indicator for poor survival in BC. Further, the expression of SOX13 was also confirmed to be correlated with tumor microenvironment and diverse infiltration of immune cells. In terms of drug sensitivity analysis, we found higher expression level of SOX13 predicts a high IC50 value for most of 198 drugs which predicts drug resistance. The present findings demonstrated that high expression of SOX13 negatively relates to prognosis and SOX13 plays an important role in cancer immunity. Therefore, SOX13 may potentially be adopted as a biomarker for predicting BC prognosis and infiltration of immune cells.

Expression of transferrin receptor 1 and β1-integrins correlates with estrogen receptor status and immune infiltration in breast cancer

To study of transferrin receptor 1 (CD71) expression by primary breast cancer cells in correlation with tumor cell phenotype. Determination of BC phenotype: immunohistochemical staining method (immunofluorescence). Antibodies to ER (estrogen receptors), KL-1 (pancytokeratin), CD71 (transferrin receptor), CD29 (β1-integrins). CD45, CD3, CD4, CD8, CD20 infiltration was also evaluated. ZEISS microscope (AXIOSKOP; Germany), method of G.J. Hammerling et al. Statistical processing: IBM-SPSS Statistics v.21. 63% of BC cases had CD71+ phenotype. CD71-mosaic tumors were observed in 14.4%. β1-integrin expression was monomorphic in 51.6% of cases and mosaic in 38.7%. 85% of ER-positive tumors were CD71-positive with a monomorphic type of reaction; p=0.014. Among ER-negative tumors, CD71-negative reactions were 2-fold more frequent and the monomorphic type was less frequent. ER-positive tumors were CD29-positive in 73%; p=0.031. 45.5% of ER+ tumors were CD29-monomorphic. Among ER-negative tumors, the frequency of CD29-monomorphic tumors was 55%. Significant infiltration by CD3+ cells was predominant in CD71-positive tumors; p=0.016. In the CD29-monomorphic phenotype, CD45+ infiltration was 31.3%, and in the mosaic phenotype, 67.1%. BC aberrantly expresses transferrin receptors, β1-integrins. CD71 expression is associated with ER expression. ER-positive tumors are often monomorphic for CD71. Prominent CD3+ infiltration was present in CD71+ tumors. Expression of β1-integrins correlated with ER+ status and weak immune infiltration.

Exploring the prognostic value of S100A11 and its association with immune infiltration in breast cancer

Breast cancer (BC) is a severe danger to women’s lives and health globally. S100A11 is aberrantly expressed in many carcinomas and serves a crucial function in cancer development. However, the role of S100A11 in BC is unclear. In this study, we utilized multiple databases and online tools, including the TCGA database, cBioPortal, and STRING, to evaluate the significance of S100A11 in BC prognosis and immune infiltration. We found that S100A11 was considerably more abundant in BC tissues. Survival analysis indicated that individuals with S100A11 high expression of BC had shorter overall survival. Multivariate Cox regression analysis revealed that high S100A11 expression independently influenced the poor outcome of patients with BC (HR = 1.738, 95%CI 1.197–2.524). Our nomogram incorporating five factors, including S100A11, age, clinical stage, N, and M, was developed to anticipate the survival probability in BC prognosis. The model demonstrated good consistency and accuracy. Furthermore, the mutation rete of S100A11 was 14%. Survival analysis suggested that breast cancer patients with S100A11 mutation had a worse prognosis. KEGG pathway enrichment analysis revealed that S100A11 may be mainly involved in the IL-17 signaling pathway. Finally, we discovered a correlation between S100A11 expression and immune cell infiltration on BC. S100A11 expression was positively associated with 17 immune checkpoint-related genes. In conclusion, this study indicates that S100A11 may contribute to a worse prognosis for BC and potentially has a significant impact through its influence on immune cell infiltration and the IL-17 signaling pathway.

Identification of an exosome-related signature associated with prognosis and immune infiltration in breast cancer

Exosomes, nanosized vesicles, play a vital role in breast cancer (BC) occurrence, development, and drug resistance. Hence, we proceeded to study the potential prognostic value of exosome-related genes and their relationship to the immune microenvironment in BC. 121 exosome-related genes were provided by the ExoBCD database, and 7 final genes were selected to construct the prognostic signature. Besides, the expression levels of the 7 exosome-related genes were validated by the experiment in BC cell lines. Based on the signature, BC patients from the training and validation cohorts were separated into low- and high-risk groups. Subsequently, the R clusterProfiler package was applied to identify the distinct enrichment pathways between high-risk groups and low-risk groups. The relevance of the tumor immune microenvironment and exosome-related gene risk score were analyzed in BC. Eventually, the different expression levels of immune checkpoint-related genes were compared between the two risk groups. Based on the risk model, the low-risk groups were identified with a higher survival rate both in the training and validation cohorts. A better overall survival was revealed in patients with higher scores evaluated by the estimation of stromal and immune cells in malignant tumor tissues using expression (ESTIMATE) algorithm. Subsequently, BC patients with lower risk scores were indicated by higher expression levels of some immune checkpoint-related genes and immune cell infiltration. Exosomes are closely associated with the prognosis and immune cell infiltration of BC. These findings may contribute to improving immunotherapy and provide a new vision for BC treatment strategies.

PROS1, a clinical prognostic biomarker and tumor suppressor, is associated with immune cell infiltration in breast cancer: A bioinformatics analysis combined with experimental verification

BackgroundPROS1 is an encoding gene that can generate protein S. This protein is a glycoprotein found in plasma that conducts physiological functions with vitamin K. However, the impact of its expression remains absent in the progression and prognosis of breast cancer (BC). MethodsIn this study, we comprehensively explored the expression of PROS1 in BC and its relationship with BC patient survival, prognosis, and other clinicopathological features. We investigated how PROS1 influenced the malignant biological behavior of BC cells. A series of enrichment analyses were conducted, and the immune landscape was explored in BC affected by PROS1. We also determined correlations between PROS1 and common drug sensitivities used for BC treatments. ResultsPROS1 had low expression in BC, which tended to result in poor survival of BC patients. Overexpressed PROS1 inhibited the migration and invasion of BC cells as well as the epithelial–mesenchymal transition process by downregulating SNAIL. Functional enrichment analyses revealed that PROS1 was more active in extracellular matrix (ECM) organization and structural constituent, ECM-receptor interaction, and other pathways with its related genes. PROS1 was also found to affect immune activity, including various immune cells infiltrating BC. BC patients with high PROS1 expression tended to have lower IC50 values of three common medications and obtained better efficacy. ConclusionsPROS1 can become a promising prognostic factor and a possible therapeutic target in BC patients and suppress BC cell metastatic potential. In addition, PROS1 is a crucial factor in immune infiltration in BC.

Overexpression of ferritin light chain as a poor prognostic factor for breast cancer.

Ferritin light chain (FTL) is involved in tumor progression, but the specific molecular processes by which FTL affects the development of breast cancer (BRCA) have remained unknown. In this research, the clinicopathological significance of FTL overexpression in BRCA was investigated. To investigate the role of FTL in BRCA, we utilized multiple online databases to analyse FTL expression levels in BRCA. Next, we reviewed the expression and localization of the FTL protein in BRCA by immunohistochemistry (IHC), Western blot (WB) and immunofluorescence (IF) staining. To assess the impact of FTL on patient prognosis, we conducted Kaplan‒Meier, univariate and multivariate survival analyses. The relationship between FTL and immune infiltration in BRCA was also analysed in the TISCH and SangerBox databases. MTT, malondialdehyde (MDA) and reactive oxygen species (ROS) assays were carried out to investigate the molecular mechanisms of FTL action in BRCA cells. FTL was significantly upregulated in BRCA compared to normal tissues. Its expression significantly linked to histological grade (P = 0.038), PR expression (P = 0.021), Her2 expression (P = 0.012) and Ki-67 expression (P = 0.040) in patients with BRCA. Furthermore, the expression of the FTL protein was higher in the BRCA cell lines than in the normal breast cells and mainly localized in the cytoplasm. Compared to patients with a low level of FTL expression, patients with a high level of FTL expression showed lower overall survival (OS). More convincingly, univariate and multivariate statistical analyses revealed that FTL expression (P = 0.000), ER expression (P = 0.036) and Her2 expression (P = 0.028) were meaningful independent prognostic factors in patients with BRCA. FTL was associated with immune infiltration in BRCA. Functional experiments further revealed that FTL knockdown inhibited the capacity of proliferation and increased the level of oxidative stress in BRCA cells. Overexpression of FTL was associated with the progression of BRCA. FTL overexpression may become a biomarker for the evaluation of poor prognosis in patients with BRCA.