Potential Biomarker For Breast Cancer Research Articles

Gene Pair Correlation Coefficients in Sphingolipid Metabolic Pathway as a Potential Prognostic Biomarker for Breast Cancer.

Complex diseases such as cancer are usually governed by dynamic and simultaneous modifications of multiple genes. Since sphingolipids are potent bioactive molecules and regulate many important pathophysiological processes such as carcinogenesis, we studied the gene pair correlations of 36 genes (31 genes in the sphingolipid metabolic pathway and 5 genes encoding the sphingosine-1-phosphate receptors) between breast cancer patients and healthy controls. It is remarkable to observe that the gene expressions were widely and strongly correlated in healthy controls but in general lost in breast cancer patients. This study suggests that gene pair correlation coefficients could be applied as a systematic and novel method for the diagnosis and prognosis of breast cancer.

CXCR4 Antagonist AMD3100 Reverses the Resistance to Tamoxifen in Breast Cancer via Inhibiting AKT Phosphorylation

Endocrine therapy is a systemic therapy and has become the main treatment strategy for patients with estrogen receptor (ER)-positive breast cancer. However, tamoxifen resistance has become an insurmountable clinical challenge, and the underlying mechanisms are still poorly understood. In this study, we explored the roles of CXC chemokine receptor type 4 (CXCR4) in tamoxifen-treated breast cancer and tamoxifen resistance. Based on the Gene Expression Omnibus (GEO) database, high expression of CXCR4 was found to be associated with worse overall survival (hazard ratio [HR] = 4.646, p < 0.001) and cancer-specific survival (HR = 4.480, p < 0.001) in tamoxifen-treated breast cancer. CXCR4 was also positively correlated with the level of AKT phosphorylation and the resistance to tamoxifen in breast cancer. AMD3100 is a CXCR4 antagonist and was found to decrease phosphorylated (p)-AKT levels of tamoxifen-resistant cells. The reversal effect of AMD3100 on tamoxifen resistance was also confirmed in vitro and in vivo. Taken together, our study demonstrated that CXCR4 could be a potential prognostic biomarker for tamoxifen-treated breast cancer, and the combination of AMD3100 with tamoxifen could be a more efficacious therapeutic strategy for the treatment of tamoxifen resistance.

Development and validation of a hypoxia-related prognostic signature for breast cancer.

Hypoxia, an important component of the tumor microenvironment, plays a crucial role in the occurrence and progression of cancer. However, to the best of our knowledge, a systematic analysis of a hypoxia-related prognostic signature for breast cancer is lacking and is urgently required. Therefore, in the present study, RNA-seq data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and served as a discovery cohort. Cox proportional hazards regression analysis was performed to construct a 14-gene prognostic signature (PFKL, P4HA2, GRHPR, SDC3, PPP1R15A, SIAH2, NDRG1, BTG1, TPD52, MAFF, ISG20, LALBA, ERRFI1 and VHL). The hypoxia-related signature successfully predicted survival outcomes of the discovery cohort (P<0.001 for the TCGA dataset). Three independent Gene Expression Omnibus databases (GSE10886, GSE20685 and GSE96058) were used as validation cohorts to verify the value of the predictive signature (P=0.007 for GSE10886, P=0.021 for GSE20685, P<0.001 for GSE96058). In the present study, a robust predictive signature was developed for patients with breast cancer, and the findings revealed that the 14-gene hypoxia-related signature could serve as a potential prognostic biomarker for breast cancer.

Integrated Analysis of Key Differentially Expressed Genes Identifies DBN1 as a Predictive Marker of Response to Endocrine Therapy in Luminal Breast Cancer.

Endocrine therapy is the mainstay of adjuvant treatment for patients with luminal breast cancer. Despite ongoing advances in endocrine therapy to date, a proportion of patients ultimately develop endocrine resistance, resulting in failure of therapy and poor prognosis. Therefore, as part of the growing concept of personalised medicine, the need for identification of predictive markers of endocrine therapy response at an early stage, is recognised. The METABRIC series was used to identify differentially expressed genes (DEGs) in term of response to adjuvant endocrine therapy. Drebrin 1 (DBN1) was identified as a key DEG associated with response to hormone treatment. Next, large, well-characterised cohorts of primary luminal breast cancer with long-term follow-up were assessed at the mRNA and protein levels for the value of DBN1 as a prognostic marker in luminal breast cancer, as well as its potential for predicting the benefit of endocrine therapy. DBN1 positivity was associated with aggressive clinicopathological variables and poor patient outcomes. Importantly, high DBN1 expression predicted relapse patients who were subject to adjuvant endocrine treatment. Our results further demonstrate that DBN1 is an independent prognostic marker in luminal breast cancer. Its association with the response to endocrine therapy and outcome provides evidence for DBN1 as a potential biomarker in luminal breast cancer, particularly for the benefit of endocrine treatment. Further functional investigations into the mechanisms underlying sensitivity to endocrine therapy is required.

Quantification of angiogenic factors and their clinicopathological associations in breast cancer.

Breast cancer (BC) is one of the top three common cancers in women, responsible for nearly one-third of all new cancer diagnoses. Angiogenesis plays a crucial role in BC progression. In this study, we aimed to measure the serum concentrations of eight angiogenic factors in BC patients and healthy controls and to assess their correlation with clinicopathological variables. In a case-control study, 62 pathologically confirmed BC patients as well as 54 age-matched controls were recruited. A bead-based immunoassay was used to measure serum levels of VEGF-A, ANG-2, PDGF-AA, PDGF-BB, EGF, TGF-α, HGF, and bFGF. We observed a significant elevation in serum levels of VEGF-A, EGF, and PDGF-AA in BC patients compared with the controls (P < 0.05). Patients with grade III had higher ANG-2 levels compared with those with grades I (P = 0.007) and II of the disease (P = 0.003). In addition, estrogen-positive and progesterone-positive BC patients had higher levels of TGF-α (P < 0.05). The significant elevation of VEGF-A, EGF, and PDGF-AA serum levels in BC patients suggests these cytokines might have diagnostic value as potential biomarkers in BC. Further large-scale studies are needed to generalize these results to all BC patients.

Integrative Analysis of the Doxorubicin-Associated LncRNA-mRNA Network Identifies Chemoresistance-Associated lnc-TRDMT1-5 as a Biomarker of Breast Cancer Progression.

Increasing evidence has revealed close relationships between long non-coding RNAs (lncRNAs) and chemoresistance in multiple types of tumors; however, functional lncRNAs in breast cancer (BC) have not been completely identified. In this study, we aimed to identify novel lncRNAs that might play critical roles in doxorubicn resistance, which could reveal potential biomarkers of BC. Using a BC dataset (GSE81971), we identified 452 lncRNAs that were upregulated and 659 that were downregulated; furthermore, there were 1896 differentially expressed mRNAs, of which 1137 were upregulated and 758 were downregulated in MCF-7/ADR cells compared with the expression in MCF-7 cells. We constructed an lncRNA–mRNA network by integrating probe reannotation and regulatory interactions. To elucidate the key lncRNAs in BC, we further analyzed dysregulated lncRNA–mRNA crosstalk, and six candidate lncRNAs (lnc-TRDMT1-5, ZNF667-AS1, lnc-MPPE1-13, DSCAM-AS1:5, DSCAM-AS1:2, and lnc-CFI-3) were identified. Notably, the expression level of lnc-TRDMT1-5 was significantly upregulated in resistant cells compared with sensitive cells, and its levels were increased in BC tissues compared with adjacent tissues. Levels were positively associated with estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) expression levels. High expression of lnc-TRDMT1-5 predicted poor prognosis in ER-positve and HER2-positive BC patients, especially in patients with chemoresistance. Bioinformatic and functional analysis revealed that lnc-TRDMT1-5 was involved in many crucial pathways in cancer, such as the PI3K/AKT and Wnt signaling pathways. Subcellular localization predicted that lnc-TRDMT1-5 was located in the cytoplasm, and the lncRNA–miRNA–mRNA network showed that lnc-TRDMT1-5 might serve as a regulator in BC. Here, our results demonstrated a dysregulated lncRNA–mRNA network that might provide new treatment strategies for chemoresistant BC, and the results identified a new lncRNA, lnc-TRDMT1-5, with oncogenic and prognostic functions in human BC.

Linc‐ROR promotes the progression of breast cancer and decreases the sensitivity to rapamycin through miR‐194‐3p targeting MECP2

linc‐ROR is reported to be a potential biomarker of breast cancer, but the detailed mechanism of linc‐ROR‐mediated breast cancer regulation has not been fully studied. We aimed to explore how linc‐ROR affects proliferation, metastasis, and drug sensitivity in breast cancer. Cell lines in which linc‐ROR was overexpressed or knocked down were constructed, and the cell proliferation, colony formation, cell migration, and invasion abilities of these lines were explored. A CCK‐8 assay was performed to determine the sensitivity of the breast cancer cells to rapamycin. Next‐generation sequencing was conducted to explore the detailed regulatory mechanism of linc‐ROR; differentially expressed RNAs in the linc‐ROR‐overexpressing cell line compared with the negative control were screened out, and their target genes were chosen to perform Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, protein–protein interaction network analysis, and competing endogenous RNA (ceRNA) network analysis. The ceRNA mechanism of linc‐ROR for miR‐194‐3p, which targets MECP2, was determined through dual‐luciferase reporter assay, RT–qPCR, western blot, and rescue experiments. Finally, we found that linc‐ROR was upregulated in breast tumor tissues. linc‐ROR promoted the cell proliferation, colony formation, cell migration, and invasion of breast cancer and decreased the sensitivity of breast cancer cells to rapamycin. The overexpression of linc‐ROR triggered changes in the whole transcriptome of breast cancer cells, and a total of 85 lncRNAs, 414 microRNAs, 490 mRNAs, and 92 circRNAs were differentially expressed in the linc‐ROR‐overexpressing cell line compared with the negative control. Through a series of bioinformatic analyses, the ‘linc‐ROR/miR‐194‐3p/MECP2’ ceRNA regulatory axis was confirmed to be involved in the linc‐ROR‐mediated progression and drug sensitivity of breast cancer. In conclusion, linc‐ROR serves as an onco‐lncRNA in breast cancer and promotes the survival of breast cancer cells during rapamycin treatment by functioning as a ceRNA sponge for miR‐194‐3p, which targets MECP2.

Mining the prognostic significance of the GINS2 gene in human breast cancer using bioinformatics analysis.

A number of studies have demonstrated the crucial functions of GINS2 within the GINS complex in various types of cancer. However, the molecular mechanisms and prognostic value of GINS2 in breast cancer remain unknown. The present study used; BC-GenExMiner, COSMIC, UCSC Xena, The Human Protein Atlas, GEPIA, cBioPortal, GeneMANIA, TIMER and Oncomine, in order to investigate gene expression, co-expression, clinical parameters and mutations in GINS2 in patients with breast cancer. Furthermore, the present study assessed the prognostic value of GINS2 in patients with breast cancer via the Kaplan-Meier plotter database. The results of the present study demonstrated that the mRNA levels of GINS2 were significantly higher in breast cancer tissue compared with normal tissue. In addition, high mRNA expression levels of GINS2 were associated with high Scarff-Bloom-Richardson status grades, a basal-like status and age (≤51 years); however, it was not associated with lymph node metastasis. The survival analysis revealed that increased GINS2 mRNA levels were associated with a worse prognosis for relapse-free survival in all patients with breast cancer, particularly in those with estrogen receptor-positive and progesterone receptor-positive subtypes. In addition, a positive association between the GINS2, CENPM and MCM4 genes was confirmed. The results of the present study suggest that GINS2 could be used as a potential prognostic biomarker for breast cancer. Nevertheless, further studies are necessary to confirm the effects of GINS2 on the pathogenesis and development of patients with breast cancer.

Long Noncoding RNA Serve as a Potential Predictive Biomarker for Breast Cancer: A Meta-Analysis.

Purpose The detection of long noncoding RNA (lncRNA) is a novel method for breast cancer diagnosis. The purpose of this meta-analysis was to evaluate the clinical significance of lncRNAs in identification of human breast cancer. Methods Electronic databases, including PubMed (176), EMBASE (167), Cochrane Library (4), Web of Science (273), CNKI (41), VIP (18), and wanfang (21), were searched for relevant original articles. Diagnostic capacity of lncRNAs was assessed by pooled sensitivity and specificity, area under the summary receiver operating characteristic curve (AUC), diagnostic odds ratio (DOR), and subgroup and meta-regression analysis. Stata and Meta-Disc software were used to conduct the meta-analysis. Results 33 articles including 4500 cases were identified in our meta-analysis. lncRNAs sustained a high diagnostic efficacy; the pooled sensitivity, specificity, AUC, and DOR of lncRNAs in differentiating BC from controls were 0.74 (95% CI: 0.69-0.78), 0.78 (95% CI: 0.72-0.83), 0.82 (95% CI: 0.79-0.85), and 10.01 (95% CI: 7.13-14.06), respectively. The subgroup analysis showed that the diagnostic efficacy of lncRNAs in Asian populations was higher than that in Caucasians; lncRNAs in BC were lower than those in TNBC and were higher in plasma and serum specimens than in tissues. In addition, heterogeneity was clearly apparent but was not caused by the threshold effect. Conclusion This meta-analysis suggested that lncRNAs might be promising biomarkers for identifying breast cancer, and its clinical application warrants further investigation.

RETRACTED ARTICLE: LncRNA BCRT1 promotes breast cancer progression by targeting miR-1303/PTBP3 axis

BackgroundLong noncoding RNAs (lncRNAs) play crucial roles in tumor progression and are aberrantly expressed in various cancers. However, the functional roles of lncRNAs in breast cancer remain largely unknown.MethodsBased on public databases and integrating bioinformatics analyses, the overexpression of lncRNA BCRT1 in breast cancer tissues was detected and further validated in a cohort of breast cancer tissues. The effects of lncRNA BCRT1 on proliferation, migration, invasion and macrophage polarization were determined by in vitro and in vivo experiments. Luciferase reporter assay and RNA immunoprecipitation (RIP) were carried out to reveal the interaction between lncRNA BCRT1, miR-1303, and PTBP3. Chromatin immunoprecipitation (ChIP) and RT-PCR were used to evaluate the regulatory effect of hypoxia-inducible factor-1α (HIF-1α) on lncRNA BCRT1.ResultsLncRNA BCRT1 was significantly upregulated in breast cancer tissues, which was correlated with poor prognosis in breast cancer patients. LncRNA BCRT1 knockdown remarkably suppressed tumor growth and metastasis in vitro and in vivo. Mechanistically, lncRNA BCRT1 could competitively bind with miR-1303 to prevent the degradation of its target gene PTBP3, which acts as a tumor-promoter in breast cancer. LncRNA BCRT1 overexpression could promote M2 polarization of macrophages, mediated by exosomes, which further accelerated breast cancer progression. Furthermore, lncRNA BCRT1 was upregulated in response to hypoxia, which was attributed to the binding of HIF-1α to HREs in the lncRNA BCRT1 promoter.ConclusionsCollectively, these results reveal a novel HIF-1α/lncRNA BCRT1/miR-1303/PTBP3 pathway for breast cancer progression and suggest that lncRNA BCRT1 might be a potential biomarker and therapeutic target for breast cancer.

Identification of co-expression modules and potential biomarkers of breast cancer by WGCNA.

Breast cancer is a very serious disease that threatens human health. The identification of co-expression modules is conducive to revealing the interaction mechanism between genes. The potential biomarkers identified from the co-expression modules have profound implications for the diagnosis and treatment of breast cancer. According to the clinical staging information, the gene expression data of breast cancer was divided into different stages and analyzed separately. The co-expression modules for each stage were identified by WGCNA. The pathways involved in the co-expression modules of each stage were revealed by KEGG enrichment analysis. Combined with clinical information, 81 core genes were screened from the co-expression modules of each stage. By constructing a support vector machine, it was confirmed that these core genes can effectively distinguish breast cancer samples. The biological functions involved in these core genes are revealed by GO enrichment analysis. Survival analysis showed that the expression of 11 genes had significant effects on the survival of breast cancer patients. These results may provide a reference for the mechanism study of breast cancer.

Construction and Analysis of a Long Non-Coding RNA-Associated Competing Endogenous RNA Network Identified Potential Prognostic Biomarkers in Luminal Breast Cancer.

PurposeTo construct a competing endogenous RNA (ceRNA) topology network of RNA-seq data and micro RNA-seq (miRNA-seq) data to identify key prognostic long non-coding RNA (lncRNAs) in luminal breast cancer, and validate the results by human luminal breast cancer samples.Materials and MethodsThe RNA-seq data and miRNA-seq data of luminal A breast cancer in the The Cancer Genome Atlas (TCGA) database were downloaded and compared with those in the miRcode database to obtain lncRNA–miRNA relationship pairs. Final target genes were predicted by all three databases (miRDB, miRTarBase, and TargetScan), thereby obtaining the miRNA-messenger RNA (miRNA-mRNA) relationship pairs and a ceRNA topology network was constructed, then mRNA enrichment analysis, ceRNA topological and stability analysis, univariate and multivariate Cox regression analysis were performed. Overall survival (OS) was evaluated and the key prognostic RNAs were identified. The expression difference between normal and tumor, as well as the correlation of high expression in tumor with pathological parameters (Ki-67, Grade, tumor diameter) were validated by human breast cancer specimens.ResultsA ceRNA topology network was constructed and six lncRNAs were finally identified (The higher expression of PART1, IGF2.AS, WT1.AS, OIP5.AS1, and SLC25A5.AS1 was associated with poor prognosis while AL035706.1 was adverse) and the poor prognostic ones were higher expressed in tumor tissue and correlated with a higher Ki-67 (>10%), tumor grades (II, III) and tumor diameters (>1.5 cm). Using six lncRNAs, we constructed a prognostic model, which performed well for the classification of prognosis in the module.ConclusionWe identified and verified six biomarkers (OS-predicting) in luminal breast cancer, which significantly enriched the prediction and potential targets of this subtype.

Identification of Metabolic Alterations in Breast Cancer Using Mass Spectrometry-Based Metabolomic Analysis.

Breast cancer (BC) is a major global health issue and remains the second leading cause of cancer-related death in women, contributing to approximately 41,760 deaths annually. BC is caused by a combination of genetic and environmental factors. Although various molecular diagnostic tools have been developed to improve diagnosis of BC in the clinical setting, better detection tools for earlier diagnosis can improve survival rates. Given that altered metabolism is a characteristic feature of BC, we aimed to understand the comparative metabolic differences between BC and healthy controls. Metabolomics, the study of metabolism, can provide incredible insight and create useful tools for identifying potential BC biomarkers. In this study, we applied two analytical mass spectrometry (MS) platforms, including hydrophilic interaction chromatography (HILIC) and gas chromatography (GC), to generate BC-associated metabolic profiles using breast tissue from BC patients. These metabolites were further analyzed to identify differentially expressed metabolites in BC and their associated metabolic networks. Additionally, Chemical Similarity Enrichment Analysis (ChemRICH), MetaMapp, and Metabolite Set Enrichment Analysis (MSEA) identified significantly enriched clusters and networks in BC tissues. Since metabolomic signatures hold significant promise in the clinical setting, more effort should be placed on validating potential BC biomarkers based on identifying altered metabolomes.

MicroRNA-4317 predicts the prognosis of breast cancer and inhibits tumor cell proliferation, migration, and invasion.

Previous researches have indicated that miR-4317 was aberrantly expressed in several tumors. However, the potential role of miR-4317 in breast cancer is still unclear. The aim of this study was to investigate the potential role of miR-4317 in breast cancer. The relative expression levels of miR-4317 were detected in breast cancer tissues and cell lines using qRT-PCR analysis. The Kaplan-Meier survival curve and multivariate Cox regression analyses were used to investigate the prognostic significance of miR-4317 in breast cancer. CCK-8 and Transwell assays were performed to evaluate the effects of miR-4317 on cell proliferation, migration, and invasion. The results showed that miR-4317 expression was decreased in breast cancer tissues and cell lines. Downregulation of miR-4317 was significantly associated with lymph node metastasis, TNM stage, and poor prognosis. Overexpression of miR-4317 inhibited proliferation, migration, and invasion of breast cancer cells, while downregulation of miR-4317 exhibited the opposite effects. MYD88 may be a direct target of miR-4317. The results suggest miR-4317 may play a tumor suppressor role in breast cancer and inhibit proliferation, migration, and invasion of breast cancer cells by targeting MYD88. The findings provide novel evidence of miR-4317 as a potential prognostic biomarker and therapeutic target for breast cancer.

Biomarker Significance of Serum CXCL8, CXCL10 and CXCL16 in Breast Tumors of Iraqi Patients

The biomarker significance of three chemokines (CXCL8, CXCL10 and CXCL16) was evaluated in sera of 45 breast cancer (BC) and 28 benign breast lesion (BBL) patients, as well as 20 control women. Clinical stage and tumor expression of estrogen (ER), progesterone (PgR) and human epidermal growth factor receptor-2 (HER-2) receptors were considered in this evaluation. The results demonstrated that CXCL8, CXCL10 and CXCL16 showed a significant increased median in BC and BBL patients compared to control (CXCL8: 47.3 and 25.7 vs. 15.0; CXCL10: 37.6 and 30.7 vs. 13.1; CXCL16; 27.9 and 25.2 vs. 19.2 pg/ml, respectively). The increased levels of CXCL8 and CXCL16 were more pronounced in triple-negative and HER-2 positive patients, respectively. Binary logistic regression analysis revealed that CXCL8 was a significant predictor of BC, and such prediction was more depicted in triple-negative patients. The receiver operating characteristic analysis also revealed that CXCL8 recorded an area under curve of 0.998 in BC patients. In conclusion, CXCL8 is a potential biomarker for BC, especially when ER, PgR and HER-2 expression is considered. In this context, the predictive significance of CXCL8 in influencing BC progression is suggested in triple-negative patients.

Evaluation of non-coding region sequence variants and mitochondrial haplogroups as potential biomarkers of sporadic breast cancer in individuals of Sri Lankan Sinhalese ethnicity.

Mitochondrial DNA (mtDNA) mutations have been reported to be associated with various diseases, including cancer. The present study investigated the mtDNA non-coding region mutations and mitochondrial haplogroups as potential biomarkers of sporadic breast cancer in Sri Lankan Sinhalese women. Mitochondrial macro-haplogroups were determined using PCR-restriction fragment length polymorphism, whereas non-coding region sequences were determined using Sanger sequencing. The sequence of the non-coding region was also used to confirm haplogroup status. Neither the mutations in the non-coding region nor the mitochondrial haplogroups that were reported as risk factors in other populations, were determined to be potential risk factors for sporadic breast cancer in the present study. Furthermore, several novel mutations were identified in the present matched pairs case-controlled study. The M65a haplogroup with an additional mutation at position 16311 (P=0.0771) and mutations at the ori-b site (P=0.05) were considered a weak risk factor and protective factor, respectively, for sporadic breast cancer in Sinhalese women. Previous studies have indicated the use of mtDNA mutations as a biomarker; however, the present study showed that such biomarkers need to be validated for individual ethnic groups before they can be recommended for use in the prediction of disease.

Use of Lectin-based Affinity Techniques in Breast Cancer Glycoproteomics: A Review.

Changes in glycoprotein content, altered glycosylations, and aberrant glycan structures are increasingly recognized as cancer hallmarks. Because breast cancer is one of the most common causes of cancer deaths in the world, it is highly urgent to find other reliable biomarkers for its initial diagnosis and to learn as much as possible about this disease. In this Review, the applications of lectins to a screening of potential breast cancer biomarkers published during recent years are overviewed. These data provide a deeper insight into the use of modern strategies, technologies, and scientific knowledge in glycoproteomic breast cancer research. Particular attention is concentrated on the use of lectin-based affinity techniques, applied independently or most frequently in combination with mass spectrometry, as an effective tool for the targeting, separation, and reliable identification of glycoprotein molecules. Individual procedures and lectins used in published glycoproteomic studies of breast-cancer-related glycoproteins are discussed. The summarized approaches have the potential for use in diagnostic and predictive applications. Finally, the use of lectins is briefly discussed from the view of their future applications in the analysis of glycoproteins in cancer.

Correlation of sex-determining region Y-box 30 with tumor characteristics and its prognostic value in breast cancer.

ObjectiveSex‐determining region Y‐box 30 (SOX30) suppresses progression of several cancers, whereas its role in breast cancer is unclear. Therefore, we aimed to determine the correlation of SOX30 with tumor characteristics and prognosis in breast cancer patients.MethodsThe tumor samples of 510 breast cancer patients who underwent resection were obtained, and SOX30 expression was analyzed by immunohistochemistry. Clinical characteristics, disease‐free survival (DFS), and overall survival (OS) of breast cancer patients were recorded.ResultsThere were 368 breast cancer patients in SOX30 low‐expression group and 142 in SOX30 high‐expression group. SOX30 was negatively correlated with tumor size (P = .010), tumor (T) stage (P < .001), node (N) stage (P = .001), and tumor, node, metastasis (TNM) stage (P < .001) in breast cancer patients. For prognosis, patients in SOX30 high‐expression group had prolonged DFS (P = .011) and OS (P = .002); moreover, increased SOX30 grade (assessed by semi‐quantitative scoring method assessment) was correlated with better DFS (P = .015) and OS (P = .014). Univariate Cox's regression analysis disclosed that SOX30 high expression was correlated with enhanced DFS (P = .012, hazard ratio (HR) = 0.582) and OS (P = .002, HR = 0.389); however, multivariate Cox's regression analysis revealed that SOX30 could not independently predict DFS (P = .224, HR = 0.766) or OS (P = .087, HR = 0.582) in breast cancer patients, indicating it might interact with other independent predictive factors (such as pathological differentiation, T stage, and N stage) to influence DFS and OS in breast cancer patients.ConclusionSex‐determining region Y‐box 30 is a potential prognostic biomarker in breast cancer, which might contribute to the better outcome of breast cancer patients.

Ubiquitin-like modifier-activating enzyme 7 as a marker for the diagnosis and prognosis of breast cancer.

Ubiquitin-like modifier-activating enzyme 7 (UBA7) is a specific E1-like ubiquitin-activating enzyme involved in interferon-stimulated gene 15 (ISG15) conjugation. UBA7 expression has been reported to be notably decreased in lung cancer. The present study aimed to investigate the changes in UBA7 expression in breast cancer and the association between UBA7 expression and clinical characteristics, and to elucidate the diagnostic and prognostic significance of UBA7 in breast cancer. The clinical data and RNA-sequencing expression values of 1,104 patients with breast cancer were downloaded from The Cancer Genome Atlas database. The associations between UBA7 expression and clinical characteristics were determined using χ2 and Fisher's exact tests. UBA7 expression values were divided into low and high groups using the optimal cut-off value, as determined by the overall survival (OS) value identified via a receiver operating characteristic (ROC) curve analysis, to further study the association between UBA7 expression and clinical characteristics. The diagnostic capability of UBA7 was assessed via ROC analysis, and Kaplan-Meier curve and Cox regression analyses were performed to determine the prognostic value of UBA7. The results demonstrated that UBA7 expression was decreased in breast cancer, and significant differences were observed between groups with regards to vital status, tumor classification, metastasis classification, histological type, sex, molecular subtype, and expression levels of progesterone receptor, estrogen receptor (ER) and human epidermal growth factor receptor 2. Low and high UBA7 expression levels were associated with age, ER expression, menopause status, Tumor-Node-Metastasis classification stage, margin status, vital status, radiation therapy use, OS and relapse-free survival. Furthermore, patients with low UBA7 expression levels had a poor prognosis. UBA7 expression also demonstrated an ability to diagnose patients at all clinical stages. Taken together, the results indicated that UBA7 expression was significantly decreased in breast cancer, and was associated with clinical characteristics and prognosis. Thus, UBA7 can be deemed as a potential biomarker in breast cancer, and may serve as a target in treatment.

Abstract P4-01-05: Circulating ensembles of tumor associated cells for detection of breast cancer

Abstract Background: Mammographic screening for breast cancer offers the possibility of reducing morbidity and mortality from the disease but has economic and safety implications. Thromboembolism is a well-recognized, potentially life-threatening complication of cancer. Detection and characterization of tumour emboli comprising Circulating Ensembles of Tumor Associated Cells (C-ETACs) has however remained largely unstudied, essentially due to the difficulties in their isolation. Here we present for the first time an observational study describing the prevalence of C-ETACs in breast cancer patients and in asymptomatic individuals using a novel, label and hypothesis free process. Methods:15 ml of peripheral blood was collected from 7075 female volunteers including 1582 previously diagnosed cases of breast cancer with definite radiological and histopathological evidence of disease of which 361 were non-metastatic, 792 were metastatic, 425 cases were recently diagnosed and treatment naïve and 1006 patients had received prior treatments. The control population comprised 5493 asymptomatic individuals with age-related increased risk of breast cancer. The control patients underwent mammography and had a BI-RADS category score of 1, consistent with absence of malignancy in the breast. Peripheral blood mononuclear cells from the study population were grown in an epigenetically active cell culture medium with paradoxical cytotoxicity that selectively kills normal cells and confers survival and growth advantage on apoptosis-resistant cells of tumorigenic origin and their emboli, viz., C-ETACs. C-ETACs are defined as clusters comprising Epcam+ and CK+ cells irrespective of CD45 expression. In a subset of 100 samples from breast cancer patients we confirmed that the isolated C-ETACs contained cells that were positive for GCDFP. Results: C-ETACs were detected in 1413 / 1582 cases of breast cancer giving a sensitivity of 89.3%. There were no statistically significant differences between metastatic vs non-metastatic status of the disease or prior treatment. Among the 5493 individuals with unremarkable mammography, C-ETACs were detected in 104 (1.89 %) individuals. These individuals are being followed up prospectively for manifestation of clinical or radiological signs of malignancy of the breast as well as in other organs. Conclusions: Our study shows that heterotypic C-ETACs are a common feature of breast cancer irrespective of type, stage and grade and are almost entirely absent in asymptomatic, mammographically normal individuals. Our results therefore identify a potential biomarker for breast cancer which is specific and sensitive and which satisfies the requirements for the non-invasive, radiation-free detection of breast cancer. As such, it is a candidate for development as a modality for population screening. Citation Format: Timothy Crook, Dadasaheb Akolkar, Pradip Fulmali, Revati Patil, Cynthe Sims, Pooja Fulmali, Vineet Datta, Sachin Apurwa, Ajay Srinivasan, Rajan Datar. Circulating ensembles of tumor associated cells for detection of breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-01-05.