Immune Infiltrates In Breast Cancer Research Articles

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.

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.

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.

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.

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.

Copper homeostasis-associated gene PRNP regulates ferroptosis and immune infiltration in breast cancer.

Breast cancer (BRCA) is one of the most common cancers in women. Copper (Cu) is an essential trace element implicated in many physiological processes and human diseases, including BRCA. In this study, we performed bioinformatics analysis and experiments to determine differentially expressed copper homeostasis-associated genes in BRCA. Based on two Gene Expression Omnibus (GEO) datasets, the copper homeostasis-associated gene, prion protein (PRNP), a highly conserved ubiquitous glycoprotein, was significantly down-regulated in BRCA compared to normal tissues. Moreover, PRNP expression predicted a better prognosis in BRCA patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that PRNP was potentially linked with several cancer-associated signaling pathways, including regulation of inflammatory response and oxidative phosphorylation. To validate the biological functions of PRNP, we overexpressed PRNP in BRCA cell lines, MDA-MB-231 and BT-549. CCK8 assay showed that PRNP overexpression significantly increased the sensitivity of gefitinib in BRCA cells. Overexpression of PRNP resulted in increased reactive oxygen species (ROS) production upon gefitinib treatment and ferroptosis selective inhibitor, ferrostatin-1 attenuated the enhanced ROS production effect of PRNP in BRCA cells. PRNP expression was positively correlated with macrophages, Th1 cells, neutrophils, and B cells, while negatively correlated with NK CD56 bright cells and Th17 cells in BRCA. Single-cell analysis showed that PRNP was highly expressed in M1 phenotype macrophages, essential tumor-suppressing cells in the tumor stroma. Therefore, our findings suggest that PRNP may participate in ROS-mediated ferroptosis and is a potential novel therapeutic target of chemotherapy and immunotherapy in BRCA.

CCL20 is a potential therapeutic target associated with immune infiltration in breast cancer.

CCL20 is a chemotactic factor that is involved in immune cell recruitment and cancer progression. However, the role of CCL20 in the prognosis of breast cancer remains unclear. This study analyzed correlations between CCL20 expression and immune infiltration, clinicopathological parameters, and prognosis in breast cancer patients. Correlations between CCL20 expression and clinicopathological parameters, prognosis, and immune infiltration in breast cancer were determined using the TIMER, UALCAN, and PrognoScan databases. Furthermore, gene-gene and protein-protein interactions were determined using GeneMANIA and STING network construction, respectively. CCL20 expression was significantly upregulated in breast cancer and had significant associations with clinicopathological features, including race, sex, age, menopause status, cancer stage, cancer subclass, and nodal metastasis; moreover, patients with higher CCL20 expression exhibited poor prognosis. Meanwhile, CCL20 expression was significantly correlated with the infiltration of immune cells in breast cancer, including monocytes, neutrophils, tumor-associated macrophages, Th1 cells, regulatory T cells, and exhausted T cells. Moreover, the network of CCL20 expression showed the majority genes and proteins were associated with immune reactions. CCL20 is a prognosis-related biomarker in breast cancer on the basis of its correlation with immune infiltration levels and has potential to also be a therapeutic target.

A ceRNA network-mediated over-expression of cuproptosis-related gene SLC31A1 correlates with poor prognosis and positive immune infiltration in breast cancer.

Solute carrier family 31 member 1(SLC31A1) has been reported as the copper importer, and was identified to be involved in the process of "cuproptosis". However, the mechanism of SLC31A1 in breast cancer remains unclear. We examined the expression of SLC31A1 mRNA in breast cancer tissues and cell lines using Real-time PCR. The data for this study were obtained from The Cancer Genome Atlas (TCGA) database and analyzed via R 3.6.3. TIMER, UALCAN, GEPIA2, STRING, Metascape, Kaplan-Meier Plotter, starBase and miRNet websites were used for a comprehensive analysis of SLC31A1. Our study suggested that SLC31A1 mRNA was over-expressed in breast tumor tissue and breast cancer cell lines, and which was closely related to poor relapse-free survival (RFS) and distant metastasis-free survival (DMFS). In addition, we constructed a co-expression network of SLC31A1. Functional enrichment analysis indicated that they were mainly involved in copper ion transport. Interestingly, SLC31A1 expression was positively associated with all m6A-related genes, especially with YTHDF3 (r = 0.479). Importantly, the LINC00511/miR-29c-3p/SLC31A1 axis was identified as the most potential pathway promoting breast cancer progress by affecting copper transport. Furthermore, the expression level of SLC31A1 in breast cancer was positively correlated with tumor immune cell infiltration, immune cell biomarkers and cancer-associated fibroblast (CAF). Up-regulation of SLC31A1 expression and regulation of copper ion transport mediated by LINC00511-miR-29-3p axis is related to poor prognosis and positively correlated with tumor immune infiltration in breast cancer.

LHX2 Is a Potential Biomarker and Associated with Immune Infiltration in Breast Cancer.

Worldwide, breast cancer is the most common malignancy. LHX2, a member of the LIM homeobox gene family and a transcription factor, plays a crucial role in numerous tumors, but the function of LHX2 in breast cancer progression remains unknown. In this study, we show that LHX2 is upregulated in breast cancer tissues and positively correlated with breast cancer progression. Meanwhile, the clinical characteristics of breast cancer and LHX2 expression showed a strong correlation. GSEA showed that a high LHX2 expression may activate the T-cell activation pathway, PI3K/AKT/mTOR signaling pathway, and apoptosis pathway. Moreover, ssGSEA showed that Th1 cells and Th2 cells had a positive correlation with LHX2 expression in breast cancer. Experiments showed that LHX2 promotes the proliferation, colony formation, migration, and invasion of breast cancer cells. Immunohistochemistry and immunofluorescence assays helped to analyze LHX2-associated immune infiltration in breast cancer. A Western blot assay proved that LHX2 activated the PI3K/AKT/mTOR pathway and the apoptosis pathway. A TUNEL assay confirmed that LHX2 inhibited apoptosis. Taken together, LHX2 plays a vital role in breast cancer's progression and prognosis and could be an immune infiltration biomarker for breast cancer, and LHX2 activates the PI3K/AKT/mTOR pathway and apoptosis pathway in breast cancer.

ARHGAP39 is a prognostic biomarker involved in immune infiltration in breast cancer

BackgroundCurrent studies on the role of ARHGAP39 mainly focused on its effect on neurodevelopment. However, there are few studies on the comprehensive analysis of ARHGAP39 in breast cancer.MethodsARHGAP39 expression level was analyzed based on the Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression Project (GTEx), and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database and validated by qPCR in various cell lines and tumor tissues. The prognostic value was analyzed using Kaplan–Meier curve analysis. CCK-8 and transwell assays were conducted to identify the biological function of ARHGAP39 in tumorigenesis. Signaling pathways related to ARHGAP39 expression were identified by the GO and KEGG enrichment analysis and gene set enrichment analysis (GSEA). The correlations between ARHGAP39 and cancer immune infiltrates were investigated via TIMER, CIBERSORT, ESTIMATE and tumor-immune system interactions database (TISIDB).ResultsARHGAP39 was overexpressed in breast cancer and associated with poor survival outcomes. In vitro experiments revealed that ARHGAP39 could facilitate the proliferation, migration, and invasion capability of breast cancer cells. GSEA analysis showed that the main enrichment pathways of ARHGAP39 was immunity-related pathways. Considering the immune infiltration level, ARHGAP39 was negatively associated with infiltrating levels of CD8 + T cell and macrophage, and positively associated with CD4 + T cell. Furthermore, ARHGAP39 was significantly negatively correlated with immune score, stromal score, and ESTIMATE score.ConclusionsOur findings suggested that ARHGAP39 can be used as a potential therapeutic target and prognostic biomarker in breast cancer. ARHGAP39 was indeed a determinant factor of immune infiltration.

O123 Significance of hepatitis A virus cellular receptor-1 (HAVCR1) and its association with tumour immune microenvironment in breast cancer

Abstract Introduction Immunotherapy has an important role in the intervention of breast cancer, but single-agent efficacy of immunotherapy is poor, owing in part to influence of the surrounding tumour microenvironment. Hepatitis A virus cellular receptor-1 (HAVCR1), plays vital roles in immune microenvironment in pancreatic adenocarcinoma, but not clear in breast cancer. The present study aimed to characterize the role of HAVCR1 in immune microenvironment of breast cancer. Methods The Cancer Genome Atlas was used to evaluate functional role of HAVCR1. Kaplan-Meier plotter and Tumor Immune Estimation Resource were applied to illustrate correlation of HAVCR1 with the prognosis and immune infiltration of breast cancer. Results In Pietenpol subtype, high HAVCR1 levels indicated a favourable overall survival (OS) (HR=0.08, 95%CI:0.01-0.61, P=0.0024) in mesenchymal stem–like breast cancer. However, it was connected to worse OS (HR=2.29, 95%CI:1.04-5.04, P=0.035) in immunomodulatory subtype. Significant correlation was found between HAVCR1 expression level and immune infiltration in breast cancer, especially with B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and Dendritic cell (P&amp;lt;0.05), and other immune markers, such as PDCD1 and CTLA4 (P&amp;lt;0.05). Decreased of HAVCR1 in Mesenchymal stem cells, Natural killer T-cells and enriched of B cell, CD4+ memory T-cells, CD8+ T-cells, Type 1 T-helper cells, Type 2 T-helper cells significantly improved the prediction of OS (P&amp;lt;0.05). Decreased impression of HAVCR1 in B cells and CD8+ T-cells were correlated with worse OS (P&amp;lt;0.05). Conclusion HAVCR1 is closely correlated with immune microenvironment and may serve as a potential tumour immunotherapy target for breast cancer.

Performance of a PLK1-based immune risk model for prognosis and treatment response prediction in breast cancer.

Polo-like kinase 1 (PLK1), a serine/threonine-protein kinase, functions as a potent oncogene in the initiation and progression of tumor. The aim of this study is to assess potential correlations between PLK1 expression and immune infiltration in breast cancer (BRCA) and construct a PLK1-based immune risk model applicable for prognosis and treatment response prediction in BRCA. We collected data on PLK1 gene expression in BRCA patients from The Cancer Genome Atlas (TCGA) database. Thereafter, we analyzed the associations of PLK1 expression with immune cell infiltration and immunomodulators, and established a prognostic risk model based on seven PLK1-associated immunomodulator genes and a nomogram for survival prediction. BRCA prognosis, clinical stage progression, and tumor classification were all shown to be substantially correlated with PLK1 expression. The PLK1 gene was significantly enriched in T cell and B cell receptors and molecules of the chemokine signaling pathways. Specifically, PLK1 expression was positively correlated with the CD8+ T cell and regulatory T cell (Tregs) activation and negatively correlated with M2 macrophage infiltration. The seven-genes-based risk model could serve as an independent prognostic factor of BRCA. The risk model was markedly correlated with the expression of programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1; both p < 0.001) immune checkpoints, and tumor mutation burden (TMB). High- and low-risk BRCA patients identified by the risk model responded differently to anti-PD-1 and/or anti-CTLA4 therapy, as well as common chemotherapy drugs, like cisplatin, paclitaxel, and gemcitabine. This PLK1-based immune risk model can effectively predict the prognosis and tumor progression of BRCA, identify gene mutations, and evaluate patient's response toward immunotherapy and chemotherapy regimens.