Potential Biomarker For Breast Cancer Research Articles

Identifying CEACAM1 as a potential prognostic biomarker for basal-like breast cancer by bioinformatics analysis and in vitro experiments.

Background: Carcinoembryonic antigen related cell adhesion molecule-1 (CEACAM1) is a very important intercellular adhesion molecule, and its prognostic relevance to breast cancer (BC), especially basal-like breast cancer (BLBC), remains poorly understood. Methods: CEACAM1 mRNA expression data for BC were sourced from the Cancer Genome Atlas (TCGA) database. Kaplan-Meier survival analysis and Cox regression analysis were used to evaluate the prognostic relationship between CEACAM1 expression and BC. Signaling pathways associated with CEACAM1 were analysed using Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Moreover, cell counting kit-8 (CCK-8), flow cytometry, transwell and wound-healing assays were employed to identify the biological functions of CEACAM1 in BLBC. Results: CEACAM1 was correlated with overall survival (OS) of BLBC patients. Compared with the subgroup with better prognosis, the levels of CEACAM1 mRNA expression were significantly lower in the subgroup of BLBC with poorer prognosis. Both univariate and multivariate Cox regression analysis suggested that down-regulation of CEACAM1 expression may be an independent factor for poor prognosis in BLBC patients. GSEA and KEGG analysis revealed that CEACAM1 was negatively related with signaling pathways including extracellular matrix (ECM) receptor interaction, focal adhesion, and cell adhesion. The results of in vitro experiments indicated that CEACAM1 not only induced apoptosis of BLBC cells, but also inhibited the invasive and metastatic ability of cancer cells. Conclusions: CEACAM1 may contribute to improving the OS of BLBC patients due to its ability to inhibit the proliferation and metastasis of cancer cells. Therefore, CEACAM1 could be used as a potential prognostic biomarker and therapeutic target in BLBC.

Comparative profiling by data-independent acquisition mass spectrometry reveals featured plasma proteins in breast cancer: a pilot study.

Breast cancer is known to be influenced by genetic and environmental factors, and several susceptibility genes have been discovered. Still, the majority of genetic contributors remain unknown. We aimed to analyze the plasma proteome of breast cancer patients in comparison to healthy individuals to identify differences in protein expression profiles and discover novel biomarkers. This pilot study was conducted using bioresources from Seoul National University Bundang Hospital's Human Bioresource Center. Serum samples from 10 breast cancer patients and 10 healthy controls were obtained. Liquid chromatography-mass spectrometry analysis was performed to identify differentially expressed proteins. We identified 891 proteins; 805 were expressed in the breast cancer group and 882 in the control group. Gene set enrichment and differential expression analysis identified 30 upregulated and 100 downregulated proteins in breast cancer. Among these, 10 proteins were selected as potential biomarkers. Three proteins were upregulated in breast cancer patients, including cluster of differentiation 44, eukaryotic translation initiation factor 2-α kinase 3, and fibronectin 1. Seven proteins downregulated in breast cancer patients were also selected: glyceraldehyde-3-phosphate dehydrogenase, α-enolase, heat shock protein member 8, integrin-linked kinase, tissue inhibitor of metalloproteinases-1, vasodilator-stimulated phosphoprotein, and 14-3-3 protein gamma. All proteins had been previously reported to be related to tumor development and progression. The findings suggest that plasma proteome profiling can reveal potential diagnostic biomarkers for breast cancer and may contribute to early detection and personalized treatment strategies. A further validation study with a larger sample cohort of breast cancer patients is planned.

Navigating the Intricacies of Tumor Heterogeneity: An Insight into Potential Prognostic Breast Cancer Biomarkers.

Breast cancer is a heterogeneous disease with diverse histological and molecular subtypes. Luminal breast tumors are the most diagnosed subtype. In luminal breast cancer, hormone receptors (including ER, PR, HER2) play a diagnostic and prognostic role. Despite the effectiveness of endocrine therapy in luminal breast tumors, tumor recurrence and resistance occur, and this may highlight evolutionary strategies for survival driven by stemness. In this review we thus consider the association between estrogen signaling and stemness in mediating tumor processes. Many studies report stemness as one of the factors promoting tumor progression. Its association with estrogen signaling warrants further investigation and provides an opportunity for the identification of novel biomarkers which may be used for diagnostic, prognostic, and therapeutic purposes. Breast cancer stem cells have been characterized (CD44+ CD24-) and their role in promoting treatment resistance and tumor recurrence widely studied; however, the complexity of tumor progression which also involve microenvironmental factors suggests the existence of more varied cell phenotypes which mediate stemness and its role in tumor progression.

CirculatingmicroRNAs as potential biomarkers in triple-negative breast cancer: a translational research study of the NACATRINE trial.

Liquid biopsy is increasingly vital in monitoring neoadjuvant breast cancer treatment. This study collected plasma samples at three time points from participants in the Neoadjuvant Carboplatin in Triple Negative Breast Cancer (NACATRINE), analyzing miRNA expression with NanoString's nCounter® Human v3 miRNA assay. In the carboplatin arm, four ct-miRNAs exhibited dynamic changes linked to pathologic complete response, with a combined area under the curve of 0.811. Similarly, the non-carboplatin arm featured four ct-miRNAs with an area under the curve of 0.843. These findings underscore the potential of ct-miRNAs as personalized tools in breast cancer treatment, assisting in predicting treatment response and assessing the risk of relapse. Integrating ct-miRNA analysis into clinical practice can optimize decisions and enhance patient outcomes.

Identification of TMEM178 as a Potential Prognostic Biomarker and Therapeutic Target for Breast Cancer.

The transmembrane protein (TMEM) family plays important roles in cancer. However, the expression pattern and biological roles of TMEM178, a member of TMEM family, remains unclear in breast cancer (BRCA). Methylation and RNA-seq data were obtained to explore methylation level. Expression of TMEM178, methylation inhibitor 5-Aza-CdR was used to verify the effect of methylation status on the expression of TMEM178. We comprehensively investigated the prognostic outcomes, biological functions and effects on immune cell infiltration of the TMEM178 in BRCA using multiple bioinformatics methods. The expression of TMEM178 was downregulated and negatively correlated with the level of DNA methylation and DNA methyltransferase (DNMT1, DNMT3A, and DNMT3B) in BRCA. Consistently, TMEM178 mRNA were confirmed to be downregulated, while upregulated in response to treatment with methylation inhibitor 5-Aza-CdR by RT-qPCR. Patients with high expression of TMEM178 have better prognosis and are more sensitive to targeted drug Pazopanib. Immune infiltration analysis showed that the infiltration levels of CD4+ T cell subsets were reduced in BRAC tissues with high TMEM178 expression, and immunosuppressive molecules of T-cell exhaustion were lower expression level. Hypermethylation of the TMEM178 promoter region was a contributing factor to the downregulation of its expression, and TMEM178 may reflect a prognostic and immunosuppressive situation in BRCA.

DLGAP5 Regulates the Proliferation, Migration, Invasion, and Cell Cycle of Breast Cancer Cells via the JAK2/STAT3 Signaling Axis.

The aim of this study was to discover new biomarkers to detect breast cancer (BC), which is an aggressive cancer with a high mortality rate. In this study, bioinformatic analyses (differential analysis, weighted gene co-expression network analysis, and machine learning) were performed to identify potential candidate genes for BC to study their molecular mechanisms. Furthermore, Quantitative Real-time PCR and immunohistochemistry assays were used to examine the protein and mRNA expression levels of a particular candidate gene (DLGAP5). And the effects of DLGAP5 on cell proliferation, migration, invasion, and cell cycle were further assessed using the Cell Counting Kit-8 assay, colony formation, Transwell, wound healing, and flow cytometry assays. Moreover, the changes in the JAK2/STAT3 signaling-pathway-related proteins were detected by Western Blot. A total of 44 overlapping genes were obtained by differential analysis and weighted gene co-expression network analysis, of which 25 genes were found in the most tightly connected cluster. Finally, NEK2, CKS2, UHRF1, DLGAP5, and FAM83D were considered as potential biomarkers of BC. Moreover, DLGAP5 was highly expressed in BC. The down-regulation of DLGAP5 may inhibit the proliferation, migration, invasion, and cell cycle of BC cells, and the opposite was true for DLGAP5 overexpression. Correspondingly, silencing or overexpression of the DLGAP5 gene inhibited or activated the JAK2/STAT3 signaling pathway, respectively. DLGAP5, as a potential biomarker of BC, may impact the cell proliferation, migration, invasion, cell cycle, and BC development by modulating the JAK2/STAT3 signaling pathway.

Tumor-Associated and Systemic Autoimmunity in Pre-Clinical Breast Cancer among Post-Menopausal Women.

Autoantibodies to tumor-associated antigens (anti-TAA) are potential biomarkers for breast cancer, but their relationship systemic autoimmunity as ascertained though antinuclear antibodies (ANA) is unknown and warrants consideration given the common occurrence of autoimmunity and autoimmune diseases among women. The relationship between anti-TAAs and ANA among women who were later diagnosed with breast cancer and others who remained cancer free in the Women's Health Initiative cohort. The study sample included 145 post-menopausal women with baseline ANA data. A total of 37 ANA-positive women who developed breast cancer (i.e., cases; mean time to diagnosis 6.8 years [SE 3.9]) were matched to a random sample of 36 ANA-negative cases by age and time to diagnosis. An age-matched control sample was selected including 35 ANA-positive and 37 ANA-negative women who did not develop breast cancer (i.e., controls; follow-up time ~13 years [SE 3]). Baseline sera were assessed for Immunoglobulin G (IgG) antibodies, measured by custom microarray for 171 breast and other cancer-associated TAA. We used linear regression to estimate cross-sectional associations of ANA with log-transformed anti-TAA among cases and controls. Most anti-TAA did not vary by ANA status. Two anti-TAA were elevated in ANA-positive compared to ANA-negative cases: anti-PGM3 (p = 0.004) and anti-TTN (p = 0.005, especially in cases up to 7 years before diagnosis, p = 0.002). Anti-TAA antibodies were not generally related to ANA, a common marker of systemic autoimmunity. Associations of ANA with particular antigens inducing autoimmunity prior to breast cancer warrant further investigation.

Integrative bioinformatics analysis of miRNA and mRNA expression profiles identified some potential biomarkers for breast cancer

BackgroundBreast cancer is a common cause of cancer death among women with a complex and heterogeneous picture in histological, molecular and clinical features. The aim of this study was to identify hub gene and their target microRNAs in related pathways for breast cancer.MethodsWe selected screening methods for differentially expressed mRNAs and miRNAs using expression profile data of breast cancer from the cancer genome atlas. Using some databases for annotation, the functional and pathway enrichment for differential expression genes was performed. We selected genes and miRNAs with differential expression pattern. Then we determined target genes for differential expression miRNAs (DEMIs) and intersection between them was selected as differentially expressed miRNA–target genes for breast cancer. In the next step, we constructed miRNA–mRNA regulatory network and protein–protein interaction (PPI) network for more information.ResultsTop 10 DEMIs were identified from miRNA profile. Then, we selected 354 genes as target gene for 10 DEMIs. The miRNA–mRNA and PPI network were constructed, and 10 hub genes and 5 miRNAs identified that some of them are new for breast cancer. Also, miRNA–target genes with differential expressions in this study were all mainly involved in signaling pathways and developmental process.ConclusionThis study identified some candidate biomarkers for breast cancer that they have a potential role in pathways related to breast. These findings can be used for research, early diagnosis and therapeutic goals.

Nano-matrixes propped self-enhanced electrochemiluminescence biosensor for microRNA detection

MicroRNAs (miRNA) are the potential biomarker for breast cancer, a biosensor for detecting miRNA-21 was successfully prepared by covalently linking carbohydrazide (CON4H6) and tris (4,4 ′- dicarboxylic acid-2,2' - bipyridyl) ruthenium dichloride (Ru (dcbpy)32+) as a self-enhanced emitter (Ru–CON4H6). The biosensor was prepared by coating the electrode with mesoporous silica encapsulated Ru–CON4H6 as luminophores (RMSNs) to covalently link a couple of DNA strands (Q1-H2). The RMSNs coated electrode exhibited strong ECL emission due to the intramolecular electron transfer between the electrochemically oxidized Ru (dcbpy)32+ and co-reactant CON4H6. In the presence of target miRNA-21 and an assistant hairpin H1, H2 could be released from the surface through a strand displacement reaction (SDR), and the reserved Q1 could form G-quadruplex upon the addition of K+. The formed G-quadruplex then interacted with Q2-Fc in the presence of Mg2+ to form a DNA complex on the biosensor surface, which quenched the nano-matrixes propped self-enhanced ECL emission through the electron exchange between Fc and electrode or oxidized ECL intermediates. Under optimal conditions, the ECL decrease showed a correlation with target concentration, leading to a biosensing method for sensitive detection of miRNA-21. The proposed ECL method demonstrated a detectable concentration range from 0.1 fM to 1 nM along with a detection limit of 0.03 fM, good accuracy, and acceptable reproducibility, showing that the self-enhanced ECL biosensing strategy supported by nano-matrix provided a new way for the ultrasensitive detection of miRNA, and promoted the development of breast cancer diagnosis.

Dysregulated expression of miR‑367 in disease development and its prospects as a therapeutic target and diagnostic biomarker (Review).

MicroRNA (miR)-367 has a wide range of functions in gene regulation and as such plays a critical role in cell proliferation, differentiation and development, making it an essential molecule in various physiological processes. miR-367 belongs to the miR-302/367 cluster and is located in the intronic region of human chromosome 4 on the 4q25 locus. Dysregulation of miR-367 is associated with various disease conditions, including cancer, inflammation and cardiac conditions. Moreover, miR-367 has shown promise both as a tumor suppressor and a potential diagnostic biomarker for breast, gastric and prostate cancer. The elucidation of the essential role of miR-367 in inflammation, development and cardiac diseases emphasizes its versatility in regulating various physiological processes beyond cancer biology. However, further research is necessary to fully understand the complex regulatory mechanisms involving miR-367 in different physiological and pathological contexts. In conclusion, the versatility and significance of miR-367 makes it a promising candidate for further study and in the development of new diagnostic and therapeutic strategies.

Identification of potential diagnostic and prognostic biomarkers for breast cancer based on gene expression omnibus.

Breast cancer is regarded as a highly malignant neoplasm in the female population, posing a significant risk to women's overall well-being. The prevalence of breast cancer has been observed to rise in China, accompanied by an earlier age of onset when compared to Western countries. Breast cancer continues to be a prominent contributor to cancer-related mortality and morbidity among women, primarily due to its limited responsiveness to conventional treatment modalities. The diagnostic process is challenging due to the presence of non-specific clinical manifestations and the suboptimal precision of conventional diagnostic tests. There is a prevailing uncertainty regarding the most effective screening method and target populations, as well as the specificities and execution of screening programs. To identify diagnostic and prognostic biomarkers for breast cancer. Overlapping differentially expressed genes were screened based on Gene Expression Omnibus (GSE36765, GSE10810, and GSE20086) and The Cancer Genome Atlas datasets. A protein-protein interaction network was applied to excavate the hub genes among these differentially expressed genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, as well as gene set enrichment analyses, were conducted to examine the functions of these genes and their potential mechanisms in the development of breast cancer. For clarification of the diagnostic and prognostic roles of these genes, Kaplan-Meier and Cox proportional hazards analyses were conducted. This study demonstrated that calreticulin, heat shock protein family B member 1, insulin-like growth Factor 1, interleukin-1 receptor 1, Krüppel-like factor 4, suppressor of cytokine signaling 3, and triosephosphate isomerase 1 are potential diagnostic biomarkers of breast cancer as well as potential treatment targets with clinical implications. The screening of biomarkers is of guiding significance for the diagnosis and prognosis of the diseases.

Identification of glycogene-based prognostic signature and validation of B3GNT7 as a potential biomarker and therapeutic target in breast cancer.

Breast cancer is the most common cancer worldwide, with the fifth highest mortality rate among all cancers and high risk of metastasis. However, potential biomarkers and molecular mechanisms underlying the stratification of breast cancer in terms of clinical outcomes remain to be investigated. Therefore, we aimed to find a novel prognostic biomarker and therapeutic target for breast cancer patients. Unsupervised hierarchical clustering was used to perform comprehensive transcriptomic study of total 185 glycogenes in public datasets of breast cancer with clinicopathological and survival information. A glycogene-based signature for subtype classification was discovered using Limma packages, and relevance to four known molecular features was identified by GSVA. Experimental verification was performed and biological functions of B3GNT7 were characterized by quantitative RT-PCR, western blot, transwell assays, and lectin immunofluorescence staining in breast cancer cells. A 23-glycogene signature was identified for the classification of breast cancer. Among the 23 glycogenes, B3GNTs showed significantly positive associations with ER-/Her2- subtype in breast cancer patients (n = 2655). Overexpressed B3GNT7 were correlated with poor prognosis in breast cancer patients based on public datasets. B3GNT7 depletion inhibited cell proliferation, migration, and invasion, and decreased global fucosylation in MDA-MB-231 and HCC1937 breast cancer cells. Herein, we discovered a unique 23-gene signature for breast cancer patient glycogene-type classification. Among these genes, B3GNT7 was shown to be a potential biomarker for unfavorable outcomes and therapeutic target of breast cancer.

Pan-cancer Analysis Identifies AIMP2 as a Potential Biomarker for Breast Cancer.

Aminoacyl tRNA synthetase complex interacting with multifunctional protein 2 (AIMP2) is a significant regulator of cell proliferation and apoptosis. Despite its abnormal expression in various tumor types, the specific functions and effects of AIMP2 on tumor immune cell infiltration, proliferation, and migration remain unclear. To assess AIMP2's role in tumor immunity, we conducted a pan-cancer multi-database analysis using the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Lines Encyclopedia (CCLE) datasets, examining expression levels, prognosis, tumor progression, and immune microenvironment. Additionally, we investigated AIMP2's impact on breast cancer (BRCA) proliferation and migration using cell counting kit 8 (CCK-8) assay, transwell assays, and western blot analysis. Our findings revealed that AIMP2 was overexpressed in 24 tumor tissue types compared to normal tissue and was associated with four tumor stages. Survival analysis indicated that AIMP2 expression was strongly correlated with overall survival (OS) in certain cancer patients, with high AIMP2 expression linked to poorer prognosis in five cancer types. Finally, siRNA-mediated AIMP2 knockdown inhibited BRCA cell proliferation and migration in vitro. In conclusion, our pan-cancer analysis suggests that AIMP2 may play a crucial role in tumor immunity and could serve as a potential prognostic marker, particularly in BRCA.

BRCA1 Promoter Hypermethylation in Malignant Breast Tumors and in the Histologically Normal Adjacent Tissues to the Tumors: Exploring Its Potential as a Biomarker and Its Clinical Significance in a Translational Approach.

The hypermethylation status of the promoter region of the breast cancer 1 (BRCA1), a well-known tumor suppressor gene, has been extensively investigated in the last two decades as a potential biomarker for breast cancer. In this retrospective study, we investigated the prevalence of BRCA1 promoter methylation in 84 human breast tissues, and we correlated this epigenetic silencing with the clinical and histopathological parameters of breast cancer. We used methylation-specific PCR (MSP) to analyze BRCA1 promoter hypermethylation in 48 malignant breast tumors (MBTs), 15 normal adjacent tissues (NATs), and 21 benign breast lesions (BBLs). The results showed that BRCA1 promoter hypermethylation was higher in MBTs (20/48; 41.67%) and NATs (7/15; 46.67%) compared to BBLs (4/21; 19.05%). The high percentage of BRCA1 hypermethylation in the histologically normal adjacent tissues to the tumors (NATs) suggests the involvement of this epigenetic silencing as a potential biomarker of the early genomic instability in NATs surrounding the tumors. The detection of BRCA1 promoter hypermethylation in BBLs reinforces this suggestion, knowing that a non-negligible rate of benign breast lesions was reported to evolve into cancer. Moreover, our results indicated that the BRCA1 promoter hypermethylated group of MBTs exhibited higher rates of aggressive features, as indicated by the SBR III grade (14/19; 73.68%), elevated Ki67 levels (13/16; 81.25%), and Her2 receptor overexpression (5/20; 25%). Finally, we observed a concordance (60%) in BRCA1 promoter hypermethylation status between malignant breast tumors and their paired histologically normal adjacent tissues. This study highlights the role of BRCA1 promoter hypermethylation as a potential useful biomarker of aggressiveness in MBTs and as an early marker of genomic instability in both histological NATs and BBLs.

Comprehensive serum lipidomic analyses reveal potential biomarkers for malignant breast cancer: A case-control study.

Breast cancer is the most worldwide commonly found malignancy among women. The evidence for lipidomic studies of breast cancer in the Chinese population is relatively limited. Our current study aimed to identify peripheral lipids capable of distinguishing adults with and without malignant breast cancer in a Chinese population and to explore the potential lipid metabolism pathways implicated in breast cancer. Lipidomics was performed with an Ultimate 3000 UHPLC system coupled with a Q-Exactive HF MS platform by using the serum of 71 female patients with malignant breast cancer and 92 age-matched (± 2 years) healthy women. The data were uploaded to and processed by the specialized online software Metaboanalyst 5.0. Both univariate and multivariate analyses were carried out for potential biomarker screening. Areas under the receiver-operating characteristic (ROC) curves (AUCs) of identified differential lipids were obtained for evaluating their classification capacity. A total of 47 significantly different lipids were identified by applying the following criteria: false discovery rate-adjusted P < 0.05, variable importance in projection ⩾ 1.0, and fold change ⩾ 2.0 or ⩽ 0.5. Among them, 13 lipids were identified as diagnostic biomarkers with the area under curve (AUC) greater than 0.7. Multivariate ROC curves indicated that AUCs greater than 0.8 could be achieved with 2-47 lipids. Using an untargeted LC-MS-based metabolic profiling approach, our study provides preliminary evidence that extensive dysregulations of OxPCs, PCs, SMs and TAGs were involved in the pathological processes of breast cancer. We provided clues for furtherly investigating the role of lipid alterations in the pathoetiology of breast cancer.

The effect of ferroptosis - related proteins and histone deacetylases1 on neoadjuvant chemotherapy in breast cancer.

Ferroptosis may improve the efficacy of tumor treatment, according to recent evidences. This study is to explore value of histone deacetylases 1 (HDAC1), ATP binding cassette subfamily B member 1 and ferroptosis-related proteins as potential predictive biomarkers. Eighty-two women who received neoadjuvant chemotherapy (NAC) confirmed breast cancer was included. Immunohistochemistry staining of HDAC1, ATP binding cassette subfamily B member 1 and ferroptosis-related proteins was performed in core needle biopsy and tumor resection tissue. Univariate and multivariate logistic regression were conducted to explore the potential biomarkers for breast cancer undergoing NAC. There was a weak positive correlation of HDAC1 level before and after NAC with imaging outcome (R = 0.390, P < .001). The expression of HDAC1 and glutathione peroxidase 4 before NAC was an independent predictor of imaging efficacy (OR = 7.633, CI 1.831-31.821, P < .001; OR = 0.700, CI 0.505-0.971, P < .05, respectively). HDAC1 and Glutathione peroxidase 4 may act as a new predictive biomarker for NAC in breast cancer. And personalized treatment can be provided based on them.

Herpesvirus entry mediator as a potential biomarker in breast cancer compared with conventional cytotoxic T‑lymphocyte‑associated antigen 4.

Breast cancer (BC) is the most common cancer in women worldwide, with 2.3 million cases recorded in 2020. Despite improvements in cancer treatment, patients with BC still succumb to the disease, due to regional and distant metastases when diagnosed at later stages. Several immune checkpoint inhibitors have been approved for BC treatment, based on their expression and role in maintaining immunosurveillance against tumors. The present study aimed to evaluate the expression of 12 immune checkpoints in patients with BC, and assess their role as diagnostic and therapeutic markers. Expression levels were measured using reverse transcription-quantitative polymerase chain reaction. Among the 12 immune markers, herpesvirus entry mediator (HVEM) was found to be significantly upregulated in patients with malignant BC compared to non-malignant controls, with a relative fold change (FC) of 1.46 and P=0.012. A similar finding was observed for cytotoxic T-lymphocyte-associated antigen 4 (CTLA4; FC=1.47 and P=0.035). In addition, receiver operating characteristic curve analysis revealed that HVEM expression allowed significant differentiation between groups, with an area under the curve of 0.74 (P=0.013). Upregulation in both HVEM and CTLA4 was revealed to be significantly associated with the human epidermal growth factor receptor-2 (HER2)-enriched phenotype (FC=3.53, P=0.009 and FC=5.98, P=0.002, respectively), while only HVEM was significantly associated with the triple-negative phenotype (FC=2.07, P=0.016). Furthermore, HVEM was significantly higher in patients with grade III tumors (FC=1.88, P=0.025) and negative vascular invasion (FC=1.67, P=0.046) compared with non-malignant controls. Serum protein levels were assessed by multiplex immunoassay, and a significant increase in HVEM was detected in patients with malignant BC compared with that in non-malignant controls (P=0.035). These data indicated that HVEM may serve as a potential biomarker and target for immunotherapy, especially for certain types of BC.

Machine Learning and miRNAs as Potential Biomarkers of Breast Cancer: A Systematic Review of Classification Methods

This work aims to offer an analysis of empirical research on the automatic learning methods used in detecting microRNA (miRNA) as potential markers of breast cancer. To carry out this study, we consulted the sources of Google Scholar, IEEE, PubMed, and Science Direct using appropriate keywords to meet the objective of the research. The selection of interesting articles was carried out using exclusion and inclusion criteria, as well as research questions. The results obtained in the search were 36 articles, of which PubMed = 14, IEEE = 8, Science Direct = 4, Google Scholar = 10; among them, six were selected, since they met the search perspective. In conclusion, we observed that the machine learning methods frequently mentioned in the reviewed studies were Support Vector Machine (SVM) and Random Forest (RF), the latter obtaining the best performance in terms of precision.

Cytokine-induced apoptosis inhibitor 1: a comprehensive analysis of potential diagnostic, prognosis, and immune biomarkers in invasive breast cancer.

Cytokine-induced apoptosis inhibitor 1 (CIAPIN1) is strictly associated with the incidence and progress of several malignant tumors, but its effect on invasive breast cancer (IBC) remains unclear. We directed to research the potential diagnostic and prognostic significance of CIAPIN1 in IBC. The Cancer Genome Atlas (TCGA) database and Tumor Immune Estimation Resource (TIMER) database were utilized to examine CIAPIN1 expression level in IBC and its relationship with clinicopathological features. The diagnostic value and prognostic importance of CIAPIN1 in IBC were assessed by Kaplan-Meier analysis, Cox regression analysis, receiver operating characteristic (ROC) curve and nomogram model. The STRING database and enrichment analysis were utilized to discover the interacting proteins, biological roles and possible cellular mechanisms related to CIAPIN1. The methylation status of CIAPIN1 was analyzed using MethSurv database and the University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN). By using Spearman correlation assessment, how the expression of CIAPIN1 was related to TP53, immune checkpoint genes and immune cell infiltration was determined. CIAPIN1 mRNA and protein levels were overexpressed in IBC, and significantly correlated with T stage, histological type, age, ER status, PR status and PAM50 (P<0.001). CIAPIN1 overexpression significantly decreased overall survival, distant metastasis free survival (DMFS) and relapse free survival in IBC patients (P<0.001). Similarly, hypermethylation of CIAPIN1 was associated with adverse outcomes in IBC patients. Multivariate Cox analysis identified CIAPIN1 as a potential risk factor for disease specific survival (DSS) and progression free survival (PFS) in individuals with IBC. The outcomes of the ROC curve showed that CIAPIN1 had a better accuracy in predicting ER(-), PR(-) and Asian breast cancer subtypes. Furthermore, there was a substantial correlation between the CIAPIN1 expression level in IBC and immune cell infiltration, TP53, and immune checkpoint genes. The high expression of CIAPIN1 in IBC is significantly related to the infiltration status of various tumor immune cells and the poor prognosis of IBC patients. According to this current study, CIAPIN1 is a promising diagnostic and prognostic marker for IBC.

P13-003-23 The Z Potential of Extracellular Vesicles as a Potential Biomarker of Nutrition and Breast Cancer

P13-003-23 The Z Potential of Extracellular Vesicles as a Potential Biomarker of Nutrition and Breast Cancer