Potential Biomarker For Breast Cancer Research Articles

Integrated High-Throughput Bioinformatics (Microarray, RNA-Seq, and RNA Interaction) and qRT-PCR Investigation of BMPR1B Axis as a Potential Diagnostic Biomarker of Isfahan Breast Cancer.

According to the bioinformatics analyses and previous studies, bone morphogenetic protein receptor type 1B (BMPR1B) dysregulation could remarkably affect breast cancer (BC) status as a potential biomarker and tumor suppressor. Therefore, the analysis of the expression level of BMPR1B and other relevant biological factors such as microRNAs, long non-coding RNAs, downstream proteins in the relevant signaling pathways, and finding the accurate biological mechanism of BMPR1B could be helpful for a better understanding of BC pathogenicity and discovering the new treatment methods and drugs. R Studio software (4.0.2) was used for microarray data analyses. GSE31448 dataset was downloaded by GEOquery package and analyzed by limma package. STRING and miRWalk online databases and Cytoscape software were used for interaction analyses. Quantitative measurement of BMPR1B expression level was performed by qRT-PCR experiment. Microarray and real-time PCR analysis revealed that BMPR1B has a significant downregulation in the transforming growth factor (TGF)-beta and bone morphogenic protein (BMP) signaling pathways in BC samples. BMPR1B is a potential diagnostic biomarker, regulated by hsa-miR-181a-5p. Also, BMPR1B regulates the function of BMP2, BMP6, SMAD4, SMAD5, and SMAD6 proteins. BMPR1B have a significant role in the development of BC by regulating the potential proteins' function, playing the diagnostic biomarker role, and regulation of TGF-beta and BMP signaling pathways. The high amount of BMPR1B protein helps in increasing the survival rate of the patients.

Novel Association of IGF2BP2 Gene Variants With Altered Risk of Breast Cancer and as Potential Molecular Biomarker of Triple Negative Breast Cancer

BackgroundSeveral studies documented that insulin-like growth factor-2 mRNA-binding protein 2 (IGF2BP2) contributes to carcinogenesis, and 1 report documented the association of IGF2BP2 rs4402960 with increased risk of breast cancer (BC). This study investigated the association of rs4402960 and rs1470579 IGF2BP2 variants with BC and triple negative BC (TNBC). Materials and MethodsThis case-control study included 488 BC patients comprising 130 TNBC and 358 non-TNBC patients, and 476 cancer-free controls. Genomic DNA was obtained from peripheral venous blood, and genotyping was done by allelic exclusion method on real-time PCR. ResultsThe rs440960, but not rs1470579, minor allele was significantly associated with BC, and significantly higher rs4402960 T/T genotype frequency was noted in BC patients than controls; the distribution of rs1470579 genotypes were comparable between BC patients and controls. In contrast, significantly lower rs1470579 minor allele frequency, and reduced rs1470579 A/C and C/C, and rs4402960 T/T genotype frequencies were seen in TNBC cases. Among TNBC cases, rs4402960 and rs1470579 correlated with menses pattern, histological type, breastfeeding, oral contraceptive use and hormonotherapy. Among non-TNBC patients, and rs1470579 correlated significantly with breast feeding, oral contraceptive use, hormonotherapy, and nodal status; rs4402960 also correlated with menses pattern. Two-locus (rs440960-rs1470579) haplotype analysis confirmed the positive association of TC, and negative association of GC and TA haplotypes with BC, while TC and GC haplotypes were negatively associated with TNBC. ConclusionWhereas rs440960 was positively associated with BC, both rs4402960 and rs1470579 were negatively associated with TNBC, suggesting potential diagnostic/prognostic role in BC and its complications.

DRAGON: Determining Regulatory Associations using Graphical models on multi-Omic Networks.

The increasing quantity of multi-omicdata, such as methylomic and transcriptomic profilescollected on the same specimenor even on the same cell, provides a unique opportunity to explore the complex interactions that define cell phenotype and govern cellular responses to perturbations. We propose a network approach based on Gaussian Graphical Models (GGMs) that facilitates the joint analysis of paired omics data. This method, called DRAGON (Determining Regulatory Associations using Graphical models on multi-Omic Networks), calibrates its parameters to achieve an optimal trade-off between the network's complexity and estimation accuracy, while explicitly accounting for the characteristics of each of the assessed omics 'layers.' In simulation studies, we show that DRAGON adapts to edge density and feature size differences between omics layers, improving model inference and edge recovery compared to state-of-the-art methods. We further demonstrate in an analysis of joint transcriptome - methylome data from TCGA breast cancer specimens that DRAGON can identify key molecular mechanisms such as gene regulation via promoter methylation. In particular, we identify Transcription Factor AP-2 Beta (TFAP2B) as a potential multi-omic biomarker for basal-type breast cancer. DRAGON is available as open-source code in Python through the Network Zoo package (netZooPy v0.8; netzoo.github.io).

Serum LAPTM4B as a Potential Diagnostic and Prognostic Biomarker for Breast Cancer.

Lysosome-associated protein transmembrane-4 beta (LAPTM4B) is an integral membrane protein overexpressed in various cancers and may function as a prognostic tumor marker. The present study is aimed at understanding the clinical significance of serum LAPTM4B in breast cancer (BC). Serum LAPTM4B level was evaluated in 426 BC patients, 40 benign breast disease, and 80 healthy controls by ELISA. We used the receiver operator characteristic (ROC) curve to assess the diagnostic significance. 46 BC patients were recruited to monitor the dynamic change of serum LAPTM4B during adjuvant therapy (AT). In addition, sera from a subset of 330 patients undergoing AT, including anti-HER2 treatment, were collected to evaluate the association between LAPTM4B levels and AT efficacy. Descriptive and explorative statistical analyses were used to assess LAPTM4 B's potential as a diagnostic and prognostic marker in BC. Serum LAPTM4B level was significantly increased in BC patients than benign group and controls. It could well discriminate BC from healthy controls with diagnostic accuracy with an AUC of 0.912, a sensitivity of 85.9%, and a specificity of 83.8%. Compared with pre-AT, serum LAPTM4B concentration remarkably decreased after AT. In addition, patients in the invalid response group (PD + SD) showed higher LAPTM4B levels than the valid response group (PR + CR). Our results proposed that serum LAPTM4B had a high diagnostic and prognostic impact as a circulating biomarker in BC.

HMGA1 As a Potential Prognostic and Therapeutic Biomarker in Breast Cancer.

High-mobility group AT-hook1 (HMGA1) protein plays an important role in various diseases. However, the contribution of HMGA1 in breast cancer remains to be tapped. The expression of HMGA1 was analyzed in The Cancer Genome Atlas (TCGA) and TIMER database, and immunohistochemistry was performed in 39 breast cancer (BC) patients. The correlation between HMGA1 expression and prognosis was evaluated using Kaplan-Meier plotter (KM plotter) in patients with breast cancer. Then, cBioPortal and bc-GenExMiner were requisitioned to analyze the contribution of HMGA1 expression to clinical features. In order to reveal the function of HMGA1 in breast cancer cells, enrichment analysis was performed using the clusterProfiler R software package. Moreover, CCK8 assay, EdU assay, and Cell Cycle Assay were performed to assess the proliferation, and transwell assay was used to evaluate cell migration and invasion. Flow cytometry was used to explore the role of HMGA1 on cell apoptosis. After that, the effect of HMGA1 on signaling pathways in BC cells was detected by western blot. HMGA1 was highly expressed in a variety of tumors tissues, including BC. High HMGA1 expression was correlated with poor prognosis in BC patients. Meanwhile, HMGA1 expression was increased in molecular phenotypes with poor prognosis (ER-, PR-, and HER2+) and associated with high-grade group, lymph node metastasis, and NPI (Nottingham Prognostic Index). Further, function analysis revealed HMGA1 was enriched in DNA replication and cell cycle pathways in breast cancer. Moreover, knockdown of HMGA1 caused apoptosis, inhibited proliferation, migration, and invasion of MCF-7 and MDA-MB-231 cells, in which the oncogenic signaling pathway of PI3K/AKT/MMP9 played a critical role. HMGA1 was important for breast cancer progression and was a critical prognostic indicator, prompting a potential therapeutic target of breast cancer.

EIF4G1 Is a Potential Prognostic Biomarker of Breast Cancer.

Breast cancer (BRCA) is one of the most common cancers in women worldwide and a leading cause of death from malignancy. This study was designed to identify a novel biomarker for prognosticating the survival of BRCA patients. The prognostic potential of eukaryotic translation initiation factor 4 gamma 1 (EIF4G1) was assessed using RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) as training cohort and validation set, respectively. The functional enrichment analysis of differentially expressed genes (DEGs) was performed. The relationship between EIF4G1 and tumor microenvironment (TME) was analyzed. Immunotherapy responses were explored by the immunophenoscores (IPS) and tumor immune dysfunction and exclusion (TIDE) score. The Connectivity Map (CMap) was used to discover potentially effective therapeutic molecules against BRCA. Immunohistochemistry (IHC) was applied to compare the protein levels of EIF4G1 in normal and cancer tissues and to verify the prognostic value of EIF4G1. BRCA patients with increased expression of EIF4G1 had a shorter overall survival (OS) in all cohorts and results from IHC. EIF4G1-related genes were mainly involved in DNA replication, BRCA metastasis, and the MAPK signaling pathway. Infiltration levels of CD4+-activated memory T cells, macrophages M0, macrophages M1, and neutrophils were higher in the EIF4G1 high-expression group than those in the EIF4G1 low-expression group. EIF4G1 was positively correlated with T cell exhaustion. Lower IPS was revealed in high EIF4G1 expression patients. Five potential groups of drugs against BRCA were identified. EIF4G1 might regulate the TME and affect BRCA metastasis, and it is a potential prognostic biomarker and therapeutic target for BRCA.

The Role of Oral Fusobacterium nucleatum in Female Breast Cancer: A Systematic Review and Meta-Analysis.

Breast cancer is the world's most prevalent malignancy, with an increasing incidence and a predisposition for postpubertal females from all cultural and ethnic backgrounds. More recently, oral Fusobacterium nucleatum species have been observed in cancerous human breast tissue, drawing attention to the role of microbes in cancer pathogenesis. Investigating oral Fusobacterium nucleatum species as potential biomarkers for female-specific breast cancer. A systematic search in The Central Register of Controlled Trials, EMBASE, EBSCO, NCBI, and MEDLINE databases was undertaken from the 1st January, 1983-31st March, 2022. Articles included were in English and based on women between the ages of 18-96 years with confirmed gingivitis/periodontal disease and breast cancer diagnoses from registered specialists. Authors extracted data independently, and a meta-analysis of risk estimations measuring associations between oral Fusobacterium nucleatum species and female-specific breast cancer was elucidated via calculated relative risks and 95% confidence intervals. AXIS tool analysis revealed 78.70% of articles with a positive correlation between oral Fusobacterium nucleatum and female-specific breast cancer. The risk of breast cancer development increased with significant levels of oral Fusobacterium nucleatum due to gingivitis/periodontitis (relative risk = 1.78, 95% confidence interval = 1.63-1.91). Low-moderate statistical heterogeneity was found (I 2 = 41.39%; P = 0.02), and the importance of periodontal status on breast cancer pathogenesis was determined (relative risk = 1.24, 95% confidence interval = 1.01-1.30). Oral Fusobacterium nucleatum species are a risk factor for breast cancer development, thus elevating their biomarker potentiality.

Long non coding RNA COX10-DT promotes the progression of breast cancer via the COX10-DT/miR-206/BDNF axis

Long noncoding RNAs (lncRNAs) are emerging as critical regulators in the biological development of breast cancer. In this study, we aimed to determine the roles and mechanisms of the lncRNA COX10 divergent transcript (COX10-DT) in breast cancer progression. The relative expression level of COX10-DT was calculated in matched breast cancer tissues and adjacent normal tissues using quantitative real-time PCR. Gain-of-function and loss-of-function approaches further revealed the functions and mechanisms of COX10-DT in breast cancer cells. Clinically, we found that the lncRNA COX10-DT was commonly overexpressed in breast cancer tissues compared to paired peritumoural tissues. Functionally, the lncRNA COX10-DT might promote the proliferation and migration of breast cancer cells. Mechanistically, the lncRNA COX10-DT did not play a role by regulating the expression of its divergent gene COX10 but acted as a competitive endogenous RNA (ceRNA) by directly sponging miR-206, which further regulated the expression of brain-derived neurotrophic factor (BDNF). Taken together, our results proved that the lncRNA COX10-DT could function via the COX10-DT/miR-206/BDNF axis, thereby promoting the development of breast cancer. These findings indicated that the lncRNA COX10-DT might be a potential biomarker and therapeutic target for breast cancer.

PAIP2 is a potential diagnostic and prognostic biomarker of breast cancer and is associated with immune infiltration.

Breast cancer is the second highest incidence of cancer in the world. It is of great significance to find biomarkers to diagnose breast cancer and predict the prognosis of breast cancer patients. PAIP2 is a poly (A) -binding protein interacting protein that regulates the expression of VEGF. However, the possible role of PAIP2 in the progression of breast cancer is still unknown. RT-qRCR and Western blotting were used to verify the expression of PAIP2 in breast cancer cells and normal breast cells. The data of breast cancer samples were obtained in the TCGA database and the HPA database to analyze the expression of PAIP2 in breast cancer samples. Transwell experiment and CCK8 experiment confirmed the changes in the invasion and proliferation ability of PAIP2 after siRNA was down-regulated. Using bioinformatics technology to explore the prognostic value of PAIP2 and its possible biological function, and its effect on tumor immunity and immunotherapy. Studies have shown that PAIP2 has higher expression in breast cancer tissues and breast cancer cells. PAIP2 can promote the proliferation and invasion of breast cancer cells and has significantly high expression in higher tumor stages. The high expression of PAIP2 is associated with better OS in breast cancer patients and is negatively correlated with most chemotherapeutic drug sensitivity and IPS in cancer immunotherapy. Our study explored the potential value of PAIP2 as a biomarker for diagnosis and prognosis and may predict the efficacy of immunotherapy, providing reference for the follow-up study on the role of PAIP2 in breast cancer.

A genome-wide cell-free DNA methylation analysis identifies an episignature associated with metastatic luminal B breast cancer.

Breast cancers of the luminal B subtype are frequent tumors with high proliferation and poor prognosis. Epigenetic alterations have been found in breast tumors and in biological fluids. We aimed to profile the cell-free DNA (cfDNA) methylome of metastatic luminal B breast cancer (LBBC) patients using an epigenomic approach to discover potential noninvasive biomarkers. Plasma cfDNA was analyzed using the Infinium MethylationEpic array in a cohort of 14 women, including metastatic LBBC patients and nontumor controls. The methylation levels of cfDNA and tissue samples were validated with droplet digital PCR. The methylation and gene expression data of 582 primary luminal breast tumors and 79 nontumor tissues were obtained from The Cancer Genome Atlas (TCGA). We found an episignature of 1,467 differentially methylated CpGs that clearly identified patients with LBBC. Among the genes identified, the promoter hypermethylation of WNT1 was validated in cfDNA, showing an area under the ROC curve (AUC) of 0.86 for the noninvasive detection of metastatic LBBC. Both paired cfDNA and primary/metastatic breast tumor samples showed hypermethylation of WNT1. TCGA analysis revealed significant WNT1 hypermethylation in the primary tumors of luminal breast cancer patients, with a negative association between WNT1 methylation and gene expression. In this proof-of-principle study, we discovered an episignature associated with metastatic LBBC using a genome-wide cfDNA methylation approach. We also identified the promoter hypermethylation of WNT1 in cfDNA as a potential noninvasive biomarker for luminal breast cancer. Our results support the use of EPIC arrays to identify new epigenetic noninvasive biomarkers in breast cancer.

Circulating LncRNAs landscape as potential biomarkers in breast cancer.

In Iran, the delay in diagnosis and treatment of breast cancer results in low survival rates. It is essential to characterize new therapeutic targets and prognostic breast cancer biomarkers. The rising evidence suggested that long non-coding RNAs (lncRNAs) expression levels are deregulated in human cancers and can use as biomarkers for the rapid diagnosis of breast cancer. In the present study, a quantitative real-time polymerase chain reaction (qRT-PCR) technique was used to measure 20 oncogenic and tumor suppressor lncRNAs expression levels in whole blood samples of female breast cancer patients and healthy women. Receiver operating characteristic curve (ROC) was used to assess the diagnostic value of each selected lncRNA as a biomarker. The results revealed that some circulating lncRNAs (MEG3, NBAT1, NKILA, GAS5, EPB41L4A-AS2, Z38, and BC040587) were significantly down-regulated in breast cancer patients compared to healthy women. In contrast, other circulating lncRNAs (H19, SPRY4-IT1, XIST, UCA1, AC026904.1, CCAT1, CCAT2, ITGB2-AS, and AK058003) were significantly up-regulated in breast cancer patients compared to controls. It was shown that the expression levels of NKILA, and NBAT1 lncRNAs were related to tumor size, and BC040587 expression level related to age, node metastasis, tumor size, and grade (p< .05). The association between H19 and SPRY4-IT1 lncRNAs with HER-2 was confirmed statistically (p< .05). ROC curves illustrated that the blood levels of SPRY4-IT1, XIST, and H19 lncRNAs have excellent potential in discriminating breast cancer from the healthy controls, showing an AUC of 1.0 (95% CI 1.0-1.0, p= .00), 0.898 (95% CI 0.815-0.981, p= .00), and 0.848 (95% CI 0.701-0.995, p= .01), respectively. In conclusion, the expression levels of circulating H19 and SPRY4-IT1 lncRNAs in breast cancer patients could consider as the prognostic biomarkers and therapeutic targets in breast cancer, because of their excellent power in discriminating breast cancer from healthy individuals and the significant correlation of H19, and SPRY4-IT1 lncRNAs with clinicopathological traits. We also suggest the possible application of BC040587 lncRNA as a diagnostic and prognostic indicator to assess tumor progression in case of verification in larger patients' cohorts.

Optimization of a method for the clinical detection of serum exosomal miR-940 as a potential biomarker of breast cancer

Serum exosomal microRNAs (miRNAs) are potential biomarkers for tumor diagnosis. Clinically, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) can be used to determine the expression of exosomal miRNAs in the serum of breast cancer patients. The prerequisites for obtaining meaningful serum exosomal miRNA data of breast cancer patients include a suitable extraction method for exosomes and RT-qPCR data standardized by internal reference genes. However, the appropriate methods for the extraction of exosomes and the applicability of reference genes for analyzing exosomal miRNAs in breast cancer patients remain to be studied. This study compared the effects of three exosome extraction methods as well as the expression of exosomal miRNA in different initial serum amounts and at different serum states to identify the selection of the best method for serum exosome extraction. Five candidate reference genes including miR-16, miR-484, miR-1228, miR-191 and miR-423 for standardizing serum exosomal miRNAs were screened using five algorithms and were used for the quantification of serum exosomal miR-940. Significant downregulation of serum exosomal miR-940 expression in breast cancer was detected using miR-191 and miR-1228, whereas no significant down or up regulation was observed with miR-484, miR-423 and miR-16. Previous studies have shown that the expression level of miR-940 is downregulated in breast cancer tissues. The absolute quantitative results showed that miR-940 was significantly downregulated in breast cancer serum exosomes, which was consistent with the results from the analysis using miR-191 or miR-1228 as reference genes. Therefore, miR-191 and miR-1228 could serve as reference genes for the relative quantification of serum exosomal miRNAs. This finding indicated the importance of rigorously evaluating the stability of reference genes and standardization for serum exosomal miRNA expression. Moreover, the level of serum exosomal miR-940 in breast cancer could reflect the presence of lymph node metastasis and the status of HER2/neu, which indicates its potential as a biomarker for breast cancer metastasis. In summary, an optimized protocol for the detection of serum exosomal miR-940 as a breast cancer marker was preliminarily established.

Can serum autoantibodies be a potential early detection biomarker for breast cancer in women? A diagnostic test accuracy review and meta-analysis

BackgroundThe increasing incidence of breast cancer necessitates the need to explore alternate screening strategies that circumvent the setbacks of conventional techniques especially among population that report earlier age at diagnosis. Serum autoantibodies is one such potential area of interest. However, their ubiquitous presence across cancer types limits its applicability to any one specific type of cancer. This review was therefore carried out to explore and consolidate available evidence on autoantibodies for early detection of breast cancer and to identify those that demonstrated a higher sensitivity.MethodsA diagnostic test accuracy (DTA) review was carried out to ascertain serum autoantibodies that could be used for early detection of breast cancer among women. All relevant articles that investigated the role of autoantibodies in early detection of breast cancer were included for the review. MEDLINE, Scopus, ProQuest, Ovid SP, and Cochrane Library were searched extensively for eligible studies. Quality of the included studies was assessed using Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool. RevMan 5.3 was used for exploratory and MetaDTA 2019 for hierarchical analyses. The review helped identify the most frequently investigated autoantibodies and a meta-analysis further consolidated the findings.ResultsA total of 53 articles were included for the final analysis that reported over a 100 autoantibodies that were studied for early detection of breast cancer in women. P53, MUC1, HER2, HSP60, P16, Cyclin B1, and c-Myc were the most frequently investigated autoantibodies. Of these P53, MUC1, HER2, and HSP60 exhibited higher summary sensitivity measures. While the individual pooled sensitivity estimates ranged between 10 and 56%, the panel sensitivity values reported across studies were higher with an estimated range of 60–87%.ConclusionFindings from the review indicate a higher sensitivity for an autoantibody panel in comparison to individual assays. A panel comprising of P53, MUC1, HER2, and HSP60 autoantibodies has the potential to be investigated as an early detection biomarker for breast cancer.

The Multifaceted Role of Signal Peptide-CUB-EGF Domain-Containing Protein (SCUBE) in Cancer.

Signal peptide, CUB, and EGF-like domain-containing proteins (SCUBE) are secretory cell surface glycoproteins that play key roles in the developmental process. SCUBE proteins participate in the progression of several diseases, including cancer, and are recognized for their oncogenic and tumor suppressor functions depending on the cellular context. SCUBE proteins promote cancer cell proliferation, angiogenesis, invasion, or metastasis, stemness or self-renewal, and drug resistance. The association of SCUBE with other proteins alters the expression of signaling pathways, including Hedgehog, Notch, TGF-β/Smad2/3, and β-catenin. Further, SCUBE proteins function as potential prognostic and diagnostic biomarkers for breast cancer, renal cell carcinoma, endometrial carcinoma, and nasopharyngeal carcinoma. This review presents key features of SCUBE family members, and their structure and functions, and highlights their contribution in the development and progression of cancer. A comprehensive understanding of the role of SCUBE family members offers novel strategies for cancer therapy.

Panels of circulating microRNAs as potential diagnostic biomarkers for breast cancer: a systematic review and meta-analysis.

Circulating microRNAs (miRNAs) are potential diagnostic biomarkers for breast cancer (BC). The application of miRNA panels could improve the performance of screening tests. Here, we integrated bioinformatic tools and meta-analyses to select circulating miRNAs with high diagnostic accuracy and combined these markers to develop diagnostic panels for BC. Analyses across databases were performed to identify potential BC-related circulating miRNAs. Next, a comprehensive meta-analysis was conducted for each miRNA following the PRISMA guidelines. An electronic and manual search for relevant literature was carried out by two reviewers through PubMed, ScienceDirect, Biomed Central, and Google Scholar. The quality of the included studies was assessed using the QUADAS-2, and the statistical analyses were performed using R software 4.1.1. Finally, the accurate biomarkers confirmed through meta-analyses were combined into diagnostic models for BC. Twenty-seven circulating miRNAs were identified as BC-related by bioinformatic tools. After screening, only 10 miRNAs presented in 45 studies were eligible for meta-analyses. By assessing pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio, 8 miRNAs (miR-21, miR-30b, miR-125b, miR-145, miR221 miR-222, and miR-335) were revealed as promising BC diagnostic biomarkers. Two panels constructed from these miRNAs showed excellent diagnostic accuracy for BC, with areas under the SROC curve of 0.917 and 0.944. We identified 8 potential circulating miRNAs and 2 diagnostic models that are useful for diagnosing BC. However, the established miRNA panels have not been tested in any experimental studies and thus should be validated in large case-control studies for clinical use.

Advanced Fabrication of miRNA-Based Electrochemical Nanobiosensor for Diagnosis of Breast Cancer

Early diagnosis is the key to easy, low cost, and effective treatment of breast cancer. Therefore, studies have been accelerated to identify breast cancer diagnostic biomarkers and diagnose cancer before it progresses. The use of miR-155 as a potential biomarker in breast cancer, which has different levels at different stages of the disease, provides a simple serological test for breast cancer prognosis/diagnosis, follow-up, and treatment. Nanopolymers containing different functional groups that are formed by thiol affinity technique were synthesized by mini emulsion polymerization method and advanced characterization studies were carried out in this study to be used as bioactive layers in the nanobiosensor system for miRNA detection. The working conditions of the electrochemical nanobiosensor in which nanopolymers are used as bioactive layers were optimized. Analytical measurement characteristics and validation studies of the nanobiosensor were determined and analysis was performed on commercial blood serum. The potential of the developed electrochemical biosensor to be used as a medical diagnostic kit was explained by comparing it with commercial miRNA kit currently used for the detection of miR-155. This novel nanobiosensor provide sensitive, reliable, and rapid detection of miR-155 and it can provide the potential for breast cancer early diagnosis, prognosis, and follow-up.

Chloride Intracellular Channel 1 is a Potential Biomarker for Breast Cancer.

PurposeMultiple reports have demonstrated that highly expressed chloride intracellular channel 1 (CLIC1) exists in a range of malignant tumors and is involved in proliferation, invasion, and migration of cancer cells. There are few studies on CLIC1 and breast cancer (BC). The purpose of this research was to evaluate the expression level of CLIC1 in BC and its impact on prognosis of BC patients.Patients and MethodsDifferences in CLIC1 expression levels in 25 pairs of BC and corresponding paracancerous specimens were tested by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot (WB). Immunohistochemistry (IHC) was performed to discuss the relevance between CLIC1 expression in BC tissue chips and clinicopathological parameters of BC patients. The effect of CLIC1 expression on patient prognosis was evaluated by Kaplan–Meier survival curve and Cox regression analysis. Receiver operating characteristic (ROC) curve assessed the diagnostic performance of CLIC1 for BC.ResultsThe experimental results of qRT-PCR and WB demonstrated that CLIC1 was highly expressed in BC tissues. IHC results showed that overexpression of CLIC1 was strictly correlated with tumor size, TNM classification, pathological grade, lymph node metastasis and Ki67. Patients with lower CLIC1 expression had longer overall survival (OS) and progression-free survival (PFS). Cox regression analysis and ROC curve confirmed that CLIC1 could independently influence the prognosis of BC patients and might have diagnostic efficiency.ConclusionOverexpressed CLIC1 is closely related to the progression of BC and the poor prognosis of the patients, suggesting that it may act as a potential biological diagnostic index for BC.

Integrative analysis of plasma metabolomics and proteomics reveals the metabolic landscape of breast cancer

BackgroundBreast cancer (BC) is the most commonly diagnosed cancer. Currently, mammography and breast ultrasonography are the main clinical screening methods for BC. Our study aimed to reveal the specific metabolic profiles of BC patients and explore the specific metabolic signatures in human plasma for BC diagnosis.MethodsThis study enrolled 216 participants, including BC patients, benign patients, and healthy controls (HC) and formed two cohorts, one training cohort and one testing cohort. Plasma samples were collected from each participant and subjected to perform nontargeted metabolomics and proteomics. The metabolic signatures for BC diagnosis were identified through machine learning.ResultsMetabolomics analysis revealed that BC patients showed a significant change of metabolic profiles compared to HC individuals. The alanine, aspartate and glutamate pathways, glutamine and glutamate metabolic pathways, and arginine biosynthesis pathways were the critical biological metabolic pathways in BC. Proteomics identified 29 upregulated and 2 downregulated proteins in BC. Our integrative analysis found that aspartate aminotransferase (GOT1), l-lactate dehydrogenase B chain (LDHB), glutathione synthetase (GSS), and glutathione peroxidase 3 (GPX3) were closely involved in these metabolic pathways. Support vector machine (SVM) demonstrated a predictive model with 47 metabolites, and this model achieved a high accuracy in BC prediction (AUC = 1). Besides, this panel of metabolites also showed a fairly high predictive power in the testing cohort between BC vs HC (AUC = 0.794), and benign vs HC (AUC = 0.879).ConclusionsThis study uncovered specific changes in the metabolic and proteomic profiling of breast cancer patients and identified a panel of 47 plasma metabolites, including sphingomyelins, glutamate, and cysteine could be potential diagnostic biomarkers for breast cancer.

A systemic pan-cancer analysis of MPZL3 as a potential prognostic biomarker and its correlation with immune infiltration and drug sensitivity in breast cancer

BackgroundThis study aimed to analyze the role of myelin protein zero-like 3 (MPZL3), a single membrane glycoprotein, in prognosis, tumor immune infiltration, and drug susceptibility in human cancers.MethodsData regarding MPZL3 were extracted from the TCGA, GTEx, CellMiner, CCLE, TIMER, GSEA, and USCS Xena databases. The expression difference, survival outcomes, DNA methylation, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), tumor microenvironment (TME), immune cell infiltration, and drug sensitivity of MPZL3 were analyzed by R language software. Cell proliferation and drug sensitivity tests were applied to analyze the biological role of MPZL3 and drug sensitivities in breast cancer.ResultsMPZL3 was highly expressed in most cancer types and correlated with unfavorable survival outcomes in several cancers. TMB, MSI, MMR, DNA methylation, and RNA modification played a significant role in mediating MPZL3 dysregulation in cancers, and MPZL3 was closely linked to CD8+ T cells and CD4+ T immune infiltration. The MPML3 mRNA level was associated with protein secretion, the Notch signaling pathway, and heme metabolism. In addition, drug sensitivity analysis and validation also indicated that MPZL3 expression influenced the sensitivity of therapeutics targeting EGFR, ABL, FGFR, etc. Additionally, MPZL3 overexpression contributed to proliferation and drug sensitivity in different subtypes of breast cancer.ConclusionsThis study provides a comprehensive analysis and understanding of the oncogenic roles of the pan-cancer gene MPZL3 across different tumors, including breast cancer. MPZL3 could be a potential prognostic biomarker and therapeutic target for breast cancer.

Chemometric Analysis of Urinary Volatile Organic Compounds to Monitor the Efficacy of Pitavastatin Treatments on Mammary Tumor Progression over Time.

Volatile organic compounds (VOCs) in urine are potential biomarkers of breast cancer. Previously, our group has investigated breast cancer through analysis of VOCs in mouse urine and identified a panel of VOCs with the ability to monitor tumor progression. However, an unanswered question is whether VOCs can be exploited similarly to monitor the efficacy of antitumor treatments over time. Herein, subsets of tumor-bearing mice were treated with pitavastatin at high (8 mg/kg) and low (4 mg/kg) concentrations, and urine was analyzed through solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Previous investigations using X-ray and micro-CT analysis indicated pitavastatin administered at 8 mg/kg had a protective effect against mammary tumors, whereas 4 mg/kg treatments did not inhibit tumor-induced damage. VOCs from mice treated with pitavastatin were compared to the previously analyzed healthy controls and tumor-bearing mice using chemometric analyses, which revealed that mice treated with pitavastatin at high concentrations were significantly different than tumor-bearing untreated mice in the direction of healthy controls. Mice treated with low concentrations demonstrated significant differences relative to healthy controls and were reflective of tumor-bearing untreated mice. These results show that urinary VOCs can accurately and noninvasively predict the efficacy of pitavastatin treatments over time.