Biomarker For Diagnosis Of Breast Cancer Research Articles

Potential Early Markers for Breast Cancer: A Proteomic Approach Comparing Saliva and Serum Samples in a Pilot Study.

Breast cancer is the second leading cause of death for women in the United States, and early detection could offer patients the opportunity to receive early intervention. The current methods of diagnosis rely on mammograms and have relatively high rates of false positivity, causing anxiety in patients. We sought to identify protein markers in saliva and serum for early detection of breast cancer. A rigorous analysis was performed for individual saliva and serum samples from women without breast disease, and women diagnosed with benign or malignant breast disease, using isobaric tags for relative and absolute quantitation (iTRAQ) technique, and employing a random effects model. A total of 591 and 371 proteins were identified in saliva and serum samples from the same individuals, respectively. The differentially expressed proteins were mainly involved in exocytosis, secretion, immune response, neutrophil-mediated immunity and cytokine-mediated signaling pathway. Using a network biology approach, significantly expressed proteins in both biological fluids were evaluated for protein-protein interaction networks and further analyzed for these being potential biomarkers in breast cancer diagnosis and prognosis. Our systems approach illustrates a feasible platform for investigating the responsive proteomic profile in benign and malignant breast disease using saliva and serum from the same women.

Comprehensive bioinformatics analysis of CYB561 expression in breast cancer: Link between prognosis and immune infiltration

<b>Background:</b> Cytochrome b561 (CYB561) plays a critical role in neuroendocrine function, cardiovascular regulation, and tumor growth; however, the prognostic value of CYB561 in patients with breast cancer and the relationship between CYB561 expression and immune infiltration in breast cancer remain unclear. <b>Methods:</b> The mRNA expression and clinical data of patients with breast cancer were obtained from The Cancer Genome Atlas database. Functional enrichment analysis was used to explore underlying biological functions associated with CYB561. The methylation status of CYB561 was analyzed using the MethSurv database. The enrichment score of immune cell infiltration for CYB561 in breast cancer was calculated using single-sample gene set enrichment analysis. The prognostic value of CYB561 was evaluated using Kaplan-Meier method and Cox regression analysis. Based on the results of the multivariate Cox analysis, a nomogram was constructed to predict the effect of CYB561 expression on overall survival (OS). <b>Results:</b> The results showed that CYB561 was highly expressed in breast cancer tissues. Hypomethylation of CYB561 is associated with an unfavorable prognosis. In multivariate Cox regression analysis, CYB561 was an independent prognostic factor for OS. Functional enrichment analysis indicated that estrogen signaling pathway, inflammatory response, KRAS signaling pathway, epithelial-mesenchymal transition, leukocyte migration, and regulation of lymphocyte activation were strongly enriched in the low CYB561 expression group. Additionally, CYB561 expression was negatively correlated with immune infiltration of B cells, plasmacytoid dendritic cells, dendritic cells, and neutrophils. <b>Conclusion:</b> CYB561 may serve as a potential biomarker for breast cancer diagnosis and prognosis.

Semaphorin 4C accelerates disease progression and enables disease detection in breast cancer

Semaphorins constitute a diverse family of widely expressed transmembrane, diffusible, and GPI-linked proteins with versatile physiologic functions in orchestrating nerve system development, immune homeostasis, angiogenesis, and cell metabolism. Accumulating evidence highlights semaphorins as essential regulators of tumorigenesis by coordinating the cell-cell communications in the tumor microenvironment. Semaphorin 4C (SEMA4C) is a member of the fourth class of semaphorins with high affinity to Plexin-B2 and its interplay with cancer has long been a significant knowledge gap. Here, this perspective summarizes the recent progress in the understanding of SEMA4C in cancer and comprehensively delineates the discovery of SEMA4C in lymphatic vessels of breast cancer, the mechanisms by which SEMA4C promotes the invasiveness, proliferation, metastasis, and drug resistance of breast cancer, and the explorations of leveraging serum SEMA4C in breast cancer detection, highlighting SEMA4C as a critical driver of breast cancer progression, an effective biomarker for breast cancer diagnosis, and potential therapeutic target for breast cancer treatment.

MiR-144 as a novel biomarker in breast cancer diagnosis and treatment

Exosomes naturally carry the biomolecules in the body; they perform this task efficiently without compromising the immune system and by breaking through all the biological barriers, so they can be the best choice for designing and introducing a drug and gene transfer system. Extraction of the exosomes from the cell culture medium was performed by precipitation with an Exoquick kit solution. Nanoparticle specificity analysis was performed using scanning electron microscopy and dynamic light scattering. Trizol reagent (Invitrogen) was used for RNA extraction. Single-strand cDNA synthesis was performed from the miRNA and RT-PCR. Data were analyzed using a threshold cycle comparative method and cell cycle analysis using flow cytometry. Exosomes containing miR-144 can dramatically decrease the expression level of crucial TGF-β pathway genes, SMAD4 and TGF-βR2, in breast cancer cells. Botulinum toxin A inhibits cancer cell growth by inhibiting the TGF-β pathway. The simultaneous combination of engineered exosomes containing miR-144 and bacterial botulinum toxin A has increased effects on inhibiting the TGF-β signaling pathway. It causes cell cycle arrest in breast cancer cells. The present study's findings showed that overexpression of miR-144 in breast tumor cells results in the packaging of miRNA in exosomes derived from these cells. As a result, the exosomal platform for nucleic acid transfer to the cell appears to be an effective transducer for gene transfer to the cell. It could be used as a suitable adjunct to cancer therapeutic studies. Keywords: Breast cancer, botulinum toxin A, exosome, miRNA, biomarker.

Expression Analysis of TREM2 and TC2N Genes in Human Breast Cancer Tissues

Background: Since breast cancer is the most common type of cancer in women around the world, finding new biomarkers for early diagnosis of breast cancer is invaluable. Objectives: This research assessed the mRNA expression of triggering receptors expressed on myeloid cell 2 (TREM2) and tandem C2 domains nuclear protein (TC2N) genes among Iranian patients with breast cancer. Methods: We acquired 50 samples of cancerous breast tumors and corresponding adjacent non-cancerous tissues from Iranian women. The gene expression of TREM2 and TC2N was measured by quantitative real-time polymerase chain reaction (q-RT-PCR). In addition, the association between TREM2 and TC2N levels with various clinicopathologic characteristics was also investigated. Results: The increased levels of TREM2 and TC2N mRNAs were shown in breast cancerous tissues in comparison with adjacent non-cancerous tissues (P &lt; 0.05). Among the clinicopathological characteristics evaluated, tumor size, necrosis, and lymphatic tissue invasion were significantly associated with high TREM2 expression. A significant relationship was also seen between increased TC2N expression and tumor grade. Sensitivity and specificity were shown at 84% and 94%, respectively, for TREM2 and 72% and 100% for TC2N. Conclusions: The data suggest that TREM2 expression, but not TC2N, could be a suitable biomarker for breast cancer diagnosis.

Autoantibodies as biomarkers for breast cancer diagnosis and prognosis.

Breast cancer is the most common cancer in women worldwide and is a substantial public health problem. Screening for breast cancer mainly relies on mammography, which leads to false positives and missed diagnoses and is especially non-sensitive for patients with small tumors and dense breasts. The prognosis of breast cancer is mainly classified by tumor, node, and metastasis (TNM) staging, but this method does not consider the molecular characteristics of the tumor. As the product of the immune response to tumor-associated antigens, autoantibodies can be detected in peripheral blood and can be used as noninvasive, presymptomatic, and low-cost biomarkers. Therefore, autoantibodies can provide a possible supplementary method for breast cancer screening and prognosis classification. This article introduces the methods used to detect peripheral blood autoantibodies and the research progress in the screening and prognosis of breast cancer made in recent years to provide a potential direction for the examination and treatment of breast cancer.

Mucin Level as a Potential Biomarker for Breast Cancer Diagnosis

Background: Breast cancer is the second leading cause of cancer death and a health problem worldwide. Secreted mucins are upregulated in ductal adenocarcinoma of the breast, however, the use of mucin as breast cancer biomarker has not been established before. This study aimed to determine the use of mucin level as a potential biomarker for breast cancer diagnosis. Materials and methods: This was a retrospective, cross-section study involving 40 women subjects with breast cancer. Mucin level was examined with a combination of Alcian blue/periodic acid Schiff (AB/PAS) technique applied to each specimen. The results obtained were statistically analyzed using SPSS.Results: Results of neutral mucin detection showed that among breast cancer subjects, 16 cases (40%) were neutral mucin score (+), 23 cases (57.5%) were neutral mucin score (++), and 1 case (2.5%) was neutral mucin score (+++). Meanwhile, 10 cases (25%) were acid mucin negative, 17 cases (42.5%) were acid mucin score (+), 11 cases (27.5%) were acid mucin score (++), and 2 cases (5%) were acid mucin score (+++). The most frequent type of mucin was the combination of acid and neutral mucin (30 cases; 75%) and neutral mucin were 10 cases (25%). Conclusion: Detection of mucin level can be used as an alternative technique for the diagnosis of breast cancer complementary to other types of special stains. Keywords: AB, PAS, breast cancer, histological grade, mucin level

Electro-plasmonic-assisted biosensing of proteins and cells at the surface of optical fiber

An electro-plasmonic biosensor is used to attract proteins and cells on the surface of a fiber optic probe by controlled biomolecular migration. Concentrating targets on a high performance plasmon-assisted fiber grating sensor leads to a drastic enhancement of the limit of detection. This architecture relies on a biofunctionalized gold coated tilted fiber Bragg grating (TFBG) that operates as a working electrode to enable electrophoresis in the probed medium. The applied electric field triggers the attraction of proteins over a distance of almost 250 μm from the sensor surface, which is more than two orders of magnitude larger than the intrinsic penetration depth of the plasmon wave. Quantitative determination of target analytes was performed by cyclic voltammetry measurements using the gold coated fiber as an electrode, simultaneously with optical transmission measurements of the underlying fiber grating. In our work, these electro-plasmonic optrodes were used against a clinically-relevant biomarker in breast cancer diagnosis, namely HER2 (Human Epidermal Growth Factor Receptor-2). In vitro assays confirm that their limit of detection lies in the subpicomolar range for proteins, which is beyond reach of similar sensors without voltammetry. The improved detection limit is further facilitated by an improvement of the signal-to-noise ratio of the read-out process. Whole cell capture is finally demonstrated by the same micro-system.

Accelerating Breast Cancer Biomarker Discovery by Mass Spectrometry Proteomics and Current Bioinformatics Tools

Across the globe, we can continue to observe a rise in the prevalence of breast cancer. The World Health Organization registered 600,000 cases of death due to breast cancer in 2021 and estimated that there would be 1 in every 8 women diagnosed with breast cancer in the next 10 years. Studies have discovered the role of proteins in the pathways that affect breast cancer but have not found a potential biomarker effective for all types, especially for triple-negative breast cancer. It remains a challenge to detect and treat breast cancer, especially if found in the later uncurable stage. With this, proteomics becomes a practical approach to screening new protein biomarkers for breast cancer diagnosis, therapy, and disease control. Proteomics covers the study of the entire protein, and its modification has been leading the race in breast cancer biomarker discovery made possible through the advancement of mass spectrometry and various bioinformatics tools. The combination has brought novel information being the fastest yet simplest approach for deep, comprehensive, and high throughput approach. This review article will give an overview of these trending online tools for proteomics research while citing examples of their utility with known clinical breast cancer biomarkers.

BC-miR: Monitoring Breast Cancer-Related miRNA Profile in Blood Sera-A Prosperous Approach for Tumor Detection.

Breast cancer is the most frequent cancer with a high fatality rate amongst women worldwide. Diagnosing at an early stage is challenging, and due to the limitations of the currently used techniques, including mammography and imaging diagnostics, it still remains unascertained. Serum biomarkers can be a solution for this as they can be isolated in a less painful, more cost-effective, and minimally invasive manner. In this study, we shed light on the relevant role of multiple microRNAs (miRNAs) as potential biomarkers in breast cancer diagnosis. We monitored the expressional changes of 15 pre-selected miRNAs in a large cohort, including 65 patients with breast cancer and 42 healthy individuals. We performed thorough statistical analyses on the cohort sample set and determined the diagnostic accuracy of individual and multiple miRNAs. Our study reveals a potential improvement in diagnostics by implicating the monitoring of miR-15a+miR-16+miR-221 expression in breast cancer management.

High expression of CCNB1 driven by ncRNAs is associated with a poor prognosis and tumor immune infiltration in breast cancer.

Backgrounds: Breast cancer (BC) is the most frequent cancer diagnosed in women throughout the world. The purpose of this study was to explore new biomarkers for breast cancer diagnosis. CyclinB1 (CCNB1) is found in abundance in a wide range of human malignancies.Material and Methods: We evaluated the transcriptional, survival data and expression levels in tissue data of CCNB1 in patients with breast cancer from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), The Human Protein Atlas (THAP) and Genome Tissue Expression (GTEx) database. A series of in silico analyses were used to investigate at noncoding RNAs (ncRNAs), gene ontology (GO) annotation analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Protein-Protein Interaction (PPI) network. A quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate CCNB1 in BC cell lines.Results: CCNB1 expression was higher in BC tissues than in normal breast tissues. It was significantly related to survival time, tumor mutation burden (TMB), methylated, immune cell infiltration, and the expressed in estrogen receptor (ER) (−), lymphnode (+), and p53 (+) groups in BC. Moreover, The AC026401.3/CCNB1-miR-139-5p axis was discovered as the most promising upstream ncRNA-related pathway of CCNB1 in BC.Conclusion: CCNB1 can be used as an independent predictive factor for BC, indicating that this would be a target for highly precise therapy and a biomarker for the disease.

Eight hub genes as potential biomarkers for breast cancer diagnosis and prognosis: A TCGA-based study.

BACKGROUNDBreast cancer (BC) is the most common malignant tumor in women.AIMTo investigate BC-associated hub genes to obtain a better understanding of BC tumorigenesis.METHODSIn total, 1203 BC samples were downloaded from The Cancer Genome Atlas database, which included 113 normal samples and 1090 tumor samples. The limma package of R software was used to analyze the differentially expressed genes (DEGs) in tumor tissues compared with normal tissues. The cluster Profiler package was used to perform Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of upregulated and downregulated genes. Univariate Cox regression was conducted to explore the DEGs with statistical significance. Protein-protein interaction (PPI) network analysis was employed to investigate the hub genes using the CytoHubba plug-in of Cytoscape software. Survival analyses of the hub genes were carried out using the Kaplan-Meier method. The expression level of these hub genes was validated in the Gene Expression Profiling Interactive Analysis database and Human Protein Atlas database.RESULTSA total of 1317 DEGs (fold change > 2; P < 0.01) were confirmed through bioinformatics analysis, which included 744 upregulated and 573 downregulated genes in BC samples. KEGG enrichment analysis indicated that the upregulated genes were mainly enriched in the cytokine-cytokine receptor interaction, cell cycle, and the p53 signaling pathway (P < 0.01); and the downregulated genes were mainly enriched in the cytokine-cytokine receptor interaction, peroxisome proliferator-activated receptor signaling pathway, and AMP-activated protein kinase signaling pathway (P < 0.01).CONCLUSIONIn view of the results of PPI analysis, which were verified by survival and expression analyses, we conclude that MAD2L1, PLK1, SAA1, CCNB1, SHCBP1, KIF4A, ANLN, and ERCC6L may act as biomarkers for the diagnosis and prognosis in BC patients.

N6-methyladenosine-mediated upregulation of LINC00520 accelerates breast cancer progression via regulating miR-577/POSTN axis and downstream ILK/AKT/mTOR signaling pathway

Various lncRNAs have been reported to be closely associated with cancer initiation and progression in breast cancer (BC), including LINC00520. However, the role and underlying mechanisms by which LINC00520 affects BC aggressiveness have not been fully delineated, and this study aimed to explore this issue. Through performing qRT-PCR analysis, we proved that LINC00520 was significantly upregulated in BC tissues and cells, compared with normal tissues and cells. Higher expression of LINC00520 was closely related to higher tumor grade, poor differentiation and shorter survival in BC patients. Next, the loss-of-function experiments evidenced that silencing LINC00520 suppressed BC cell proliferation, migration and epithelial-mesenchymal transition (EMT) in vitro, and inhibited tumorigenesis in vivo. Interestingly, we found that LINC00520 expression was positively regulated by METTL3-mediated N6-methyladenosine(m6A) modification in BC. Furthermore, we identified the tumor-suppressor miR-577 as the binding target of LINC00520 in BC. Mechanistically, LINC00520 elevated POSTN level via sponging miR-577, resulting in the activation of the downstream tumor-promoting ILK/Akt/mTOR pathway. Finally, the rescuing experiments evidenced that both POSTN knockdown and ILK/Akt/mTOR pathway inhibitor OSU-T315 abrogated the promoting effects of miR-577 ablation on the malignant phenotypes in BC. Collectively, this study firstly verified that LINC00520 acted as a ceRNA of miR-577 to advance BC aggressiveness in a m6A-dependent manner, providing novel biomarkers for BC diagnosis and therapy.

A-Kinase anchor protein 4 (AKAP4) may be considered as a potential early diagnostic breast cancer marker detectable in blood

PurposeBreast cancer is the most common type of cancer-related death in women worldwide. Early diagnosis via cancer screening biomarkers has a major impact on improving clinical outcomes and overall survival leads to better cancer management. Herein, we examined the expression of A-Kinase Anchor Protein 4 (AKAP4) as a Cancer Testis Antigen (CTA) in breast cancer tumors and traced it in the peripheral blood as a possible diagnostic breast cancer marker. Material and methodsTo evaluate the expression of AKAP4 gene nested real-time RT-PCR method with SYBR green dye were used in the peripheral blood and breast tissues of 80 breast cancer patients in comparison with normal controls. ResultsThe data revealed that the existence of AKAP4 gene expression in all the stages of breast cancer in tumor tissues and its subsequent detection in peripheral blood could be regarded as a possible biomarker for breast cancer diagnosis even at the early stages. The AKAP4 expression was detected somewhat in the normal margin of the tumor compared with normal breast tissue with no AKAP4 expression which indicates the bystander effect. The peripheral blood AKAP4 expression was significantly higher in stage IV, nodal involvement, and distant metastasis. ConclusionAKAP4 gene expression analysis in blood could be regarded as a possible early diagnostic biomarker in breast cancer that is an indispensable requirement for better management of cancer.

L-norvaline affects the proliferation of breast cancer cells based on the microbiome and metabolome analysis.

The altered faecal metabolites and microbiota might be involved in the development of breast cancer. We aimed to investigate the effect of differential metabolites on the proliferative activity of breast cancer cells. We collected faecal samples from 14 breast cancer patients and 14 healthy subjects. Untargeted metabolomics analysis, short-chain fatty acid (SCFA) targeted analysis, and 16S rDNA sequencing was performed. The gut metabolite composition of patients changed significantly. Levels of norvaline, glucuronate and galacturonate were lower in the cancer group than in the Control (p < 0.05). 4-Methylcatechol and guaiacol increased (p < 0.05). Acetic acid and butyric acid were lower in the cancer group than in the control group (p < 0.05). Isobutyric acid and pentanoic acid were higher in the cancer group than in the control (p < 0.05). In the genus, the abundance of Rothia and Actinomyces increased in the cancer group, compared with the control group (p < 0.05). The differential microbiotas were clearly associated with differential metabolites but weakly with SCFAs. The abundance of Rothia and Actinomyces was markedly positively correlated with 4-methylcatechol and guaiacol (p < 0.05) and negatively correlated with norvaline (p < 0.05). L-norvaline inhibited the content of Arg-1 in a concentration-dependent manner. Compared with the L-norvaline or doxorubicin hydrochloride (DOX) group, the proliferation abilities of 4T1 cells were the lowest in the L-norvaline combined with DOX (p < 0.05). The apoptosis rate increased (p < 0.05). Faecal metabolites and microbiota were significantly altered in breast cancer. Levels of differential metabolites (i.e. Norvaline) were significantly correlated with the abundance of differential microbiota. L-norvaline combined with DOX could clearly inhibit the proliferation activity of breast cancer cells. This might provide clues to uncover potential biomarkers for breast cancer diagnosis and treatment.

Construction and validation of a prognostic risk model for breast cancer based on protein expression

Breast cancer (BRCA) is the primary cause of mortality among females globally. The combination of advanced genomic analysis with proteomics characterization to construct a protein prognostic model will help to screen effective biomarkers and find new therapeutic directions. This study obtained proteomics data from The Cancer Proteome Atlas (TCPA) dataset and clinical data from The Cancer Genome Atlas (TCGA) dataset. Kaplan–Meier and Cox regression analyses were used to construct a prognostic risk model, which was consisted of 6 proteins (CASPASE7CLEAVEDD198, NFKBP65-pS536, PCADHERIN, P27, X4EBP1-pT70, and EIF4G). Based on risk curves, survival curves, receiver operating characteristic curves, and independent prognostic analysis, the protein prognostic model could be viewed as an independent factor to accurately predict the survival time of BRCA patients. We further validated that this prognostic model had good predictive performance in the GSE88770 dataset. The expression of 6 proteins was significantly associated with the overall survival of BRCA patients. The 6 proteins and encoding genes were differentially expressed in normal and primary tumor tissues and in different BRCA stages. In addition, we verified the expression of 3 differential proteins by immunohistochemistry and found that CDH3 and EIF4G1 were significantly higher in breast cancer tissues. Functional enrichment analysis indicated that the 6 genes were mainly related to the HIF-1 signaling pathway and the PI3K-AKT signaling pathway. This study suggested that the prognosis-related proteins might serve as new biomarkers for BRCA diagnosis, and that the risk model could be used to predict the prognosis of BRCA patients.

Whole-genome circulating tumor DNA methylation landscape reveals sensitive biomarkers of breast cancer.

The changes in circulating tumor DNA (ctDNA) methylation are believed to be early events in breast cancer initiation, which makes them suitable as promising biomarkers for early diagnosis. However, applying ctDNA in breast cancer early diagnosis remains highly challenging due to the contamination of background DNA from blood and low DNA methylation signals. Here, we report an improved way to extract ctDNA, reduce background contamination, and build a whole‐genome bisulfite sequencing (WGBS) library from different stages of breast cancer. We first compared the DNA methylation data of 74 breast cancer patients with those of seven normal controls to screen candidate methylation CpG site biomarkers for breast cancer diagnosis. The obtained 26 candidate ctDNA methylation biomarkers produced high accuracy in breast cancer patients (area under the curve [AUC] = 0.889; sensitivity: 100%; specificity: 75%). Furthermore, we revealed potential ctDNA methylated CpG sites for detecting early‐stage breast cancer (AUC = 0.783; sensitivity: 93.44%; specificity: 50%). In addition, different subtypes of breast cancer could be well distinguished by the ctDNA methylome, which was obtained through our improved ctDNA‐WGBS method. Overall, we identified high specificity and sensitivity breast cancer‐specific methylation CpG site biomarkers, and they will be expected to have the potential to be translated to clinical practice.

HERC5/IFI16/p53 signaling mediates breast cancer cell proliferation and migration

AimsThis study aims to find differentially expressed ubiquitination-related gene(s) and elucidates their biological significance in breast cancer. Main methodsDifferentially expressed genes were profiled in MCF-7 and MDA-MB-231 cells by using PCR array method. Abnormal expression of HERC5 was studied in the cells and in breast cancer specimens via Quantitative Real-time PCR and western blot. Cell proliferation and cell migration abilities were evaluated by using cell counting kits, or through colony formation, wound healing and trans-well assays. HERC5 target proteins were investigated via proteomic, co-immunoprecipitation and western blot methods. Down-stream signaling pathways were investigated through gene expression/knockdown methods. Key findingsHuge increase of HERC5 expression was found in MCF-7 and MDA-MB-231 cells, knockdown of which repressed the cell proliferation and migration. HERC5 interacted with IFI16, mediated IFI16 ISGylation at K274 and facilitated IFI16 proteasomal degradation. IFI16 acted as a tumor suppressor and to some extent mediated the HERC5 function in the breast cancer (BC) cells. HERC5 was negatively correlated with IFI16 protein, while IFI16 was positively correlated to p53 expression at mRNA and protein levels, which indicates a novel signaling pathway — HERC5/IFI16/p53. HERC5 expression was increased in glucose-starved BC cells and in human breast cancer tissues, accompanied with the decrease of IFI16 and P53. SignificanceOur work reveals the abnormal expression of HERC5 and its carcinogenic role in breast cancer cells, which is probably mediated by an HERC5/IFI16/p53 signaling pathway. This work also provides potential diagnostic/therapeutic biomarkers for breast cancer diagnosis and treatment.

Integrated bioinformatics and statistical approaches to explore molecular biomarkers for breast cancer diagnosis, prognosis and therapies.

Integrated bioinformatics and statistical approaches are now playing the vital role in identifying potential molecular biomarkers more accurately in presence of huge number of alternatives for disease diagnosis, prognosis and therapies by reducing time and cost compared to the wet-lab based experimental procedures. Breast cancer (BC) is one of the leading causes of cancer related deaths for women worldwide. Several dry-lab and wet-lab based studies have identified different sets of molecular biomarkers for BC. But they did not compare their results to each other so much either computationally or experimentally. In this study, an attempt was made to propose a set of molecular biomarkers that might be more effective for BC diagnosis, prognosis and therapies, by using the integrated bioinformatics and statistical approaches. At first, we identified 190 differentially expressed genes (DEGs) between BC and control samples by using the statistical LIMMA approach. Then we identified 13 DEGs (AKR1C1, IRF9, OAS1, OAS3, SLCO2A1, NT5E, NQO1, ANGPT1, FN1, ATF6B, HPGD, BCL11A, and TP53INP1) as the key genes (KGs) by protein-protein interaction (PPI) network analysis. Then we investigated the pathogenetic processes of DEGs highlighting KGs by GO terms and KEGG pathway enrichment analysis. Moreover, we disclosed the transcriptional and post-transcriptional regulatory factors of KGs by their interaction network analysis with the transcription factors (TFs) and micro-RNAs. Both supervised and unsupervised learning’s including multivariate survival analysis results confirmed the strong prognostic power of the proposed KGs. Finally, we suggested KGs-guided computationally more effective seven candidate drugs (NVP-BHG712, Nilotinib, GSK2126458, YM201636, TG-02, CX-5461, AP-24534) compared to other published drugs by cross-validation with the state-of-the-art alternatives top-ranked independent receptor proteins. Thus, our findings might be played a vital role in breast cancer diagnosis, prognosis and therapies.

A Crucial Angiogenesis-Associated Gene MEOX2 Could Be a Promising Biomarker Candidate for Breast Cancer.

BackgroundAngiogenesis plays a critical role in the growth and metastasis of breast cancer and angiogenesis inhibition has become an effective strategy for cancer therapy. Our study aimed to clarify the key candidate genes and pathways related to breast cancer angiogenesis.MethodsDifferentially expressed genes (DEGs) in the raw breast cancer (BRCA) gene dataset from the Cancer Genome Atlas (TCGA) database were identified and gene ontology analysis of the DEGs was performed. Hub genes were subsequently determined using the Gene Expression Omnibus database. The expression of the mesenchyme homeobox 2 (MEOX2) in breast cancer cells and tissues was assessed by quantification real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC), respectively. The prognostic value of the MEOX2 gene in breast cancer tissue was evaluated with the Kaplan-Meier plotter.ResultsA total of 61 angiogenesis-related DEGs were identified in the TCGA dataset, among which the gene MEOX2 was significantly down-regulated. GO functional annotation and pathway enrichment analyses showed that MEOX2 was significantly enriched in the regulation of vasculature development. The IHC results confirmed that MEOX2 expression was repressed in breast cancer tissues and the relatively low level indicated the tissue was densely vascularized. Moreover, MEOX2 expression was significantly elevated in breast cancer cells after treatment with cisplatin (DDP) and epirubicin (EPI). Finally, the Kaplan-Meier plotter confirmed that higher expression levels of MEOX2 were related to better overall survival.ConclusionOur study revealed that the angiogenesis-associated gene MEOX2 can be used as a novel biomarker for breast cancer diagnosis and clinical therapy.