Potential Biomarker For Breast Cancer Research Articles

MiRNA-1246, HOTAIR, and IL-39 signature as potential diagnostic biomarkers in breast cancer.

The molecular alterations in noncoding RNA can lead to a cellular storm that is correlated to higher mortality and morbidity rates and contributes to the progression and metastasis of cancer. Herein, we aim to evaluate the expression levels and correlations of microRNA-1246 (miR-1246), HOX transcript antisense RNA (HOTAIR), and interleukin-39 (IL-39) in patients with breast cancer (BC). In this study, 130 participants were recruited, including 90 breast cancer patients and 40 healthy control participants. Serum levels of miR-1246 and HOTAIR expression were assessed by quantitative real-time polymerase chain reaction (qRT-PCR). Also, the level of IL-39 expression was evaluated using a Western blot. All BC participants demonstrated a remarkable elevation in miR-1246 and HOTAIR expression levels. Moreover, IL-39 expression levels demonstrated a noticeable decline in BC patients. Furthermore, the differential expression fold of miR-1246 and HOTAIR revealed a strong positive correlation among breast cancer patients. In addition, a negative relationship between the IL-39 and the miR-1246 and HOTAIR differential expression was also noticed. This study revealed that HOTAIR/miR-1246 exerts an oncogenic impact in patients with breast cancer. The expression levels of circulation miR-1246, HOTAIR, and IL-39 could be considered early diagnostic biomarkers in BC patients.

Screening of Breast Cancer from Sweat Samples Analyzed by 2-Dimensional Gas Chromatography-Mass Spectrometry: A Preliminary Study.

Breast cancer (BC) remains one of the most commonly diagnosed malignancies in women. There is increasing interest in the development of non-invasive screening methods. Volatile organic compounds (VOCs) emitted through the metabolism of cancer cells are possible novel cancer biomarkers. This study aims to identify the existence of BC-specific VOCs in the sweat of BC patients. Sweat samples from the breast and hand area were collected from 21 BC participants before and after breast tumor ablation. Thermal desorption coupled with two-dimensional gas chromatography and mass spectrometry was used to analyze VOCs. A total of 761 volatiles from a homemade human odor library were screened on each chromatogram. From those 761 VOCs, a minimum of 77 VOCs were detected within the BC samples. Principal component analysis showed that VOCs differ between the pre- and post-surgery status of the BC patients. The Tree-based Pipeline Optimization Tool identified logistic regression as the best-performing machine learning model. Logistic regression modeling identified VOCs that distinguish the pre-and post-surgery state in BC patients on both the breast and hand area with sensitivities close to 1. Further, Shapley additive explanations and the probe variable method identified the most important and pertinent VOCs distinguishing pre- and post-operative status which are mostly of distinct origin for the hand and breast region. Results suggest the possibility to identify endogenous metabolites linked to BC, hence proposing this innovative pipeline as a stepstone to discovering potential BC biomarkers. Large-scale studies in a multi-centered VOC analysis setting must be carried out to validate obtained findings.

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

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

Zinc finger and SCAN domain-containing protein 18 is a potential DNA methylation-modified tumor suppressor and biomarker in breast cancer.

Zinc finger and SCAN domain-containing protein 18 (ZSCAN18) has been investigated as a putative biomarker of multiple human cancers. However, the expression profile, epigenetic modification, prognostic value, transcription regulation, and molecular mechanism of ZSCAN18 in breast cancer (BC) remain unknown. In the study, we present an integrated analysis of ZSCAN18 in BC based on public omics datasets with the use of multiple bioinformatics tools. Genes potentially regulated through restoration of ZSCAN18 expression in MDA-MB-231 cells were investigated to identify pathways associated with BC. We observed that ZSCAN18 was downregulated in BC and mRNA expression was significantly correlated with clinicopathological parameters. Low expression of ZSCAN18 was found in the HER2-positive and TNBC subtypes. High expression of ZSCAN18 was associated with good prognosis. As compared to normal tissues, the extent of ZSCAN18 DNA methylation was greater with fewer genetic alterations in BC tissues. ZSCAN18 was identified as a transcription factor that might be involved in intracellular molecular and metabolic processes. Low ZSCAN18 expression was associated with the cell cycle and glycolysis signaling pathway. Overexpression of ZSCAN18 inhibited mRNA expression of genes associated with the Wnt/β-catenin and glycolysis signaling pathways, including CTNNB1, BCL9, TSC1, and PFKP. ZSCAN18 expression was negatively correlated with infiltrating B cells and dendritic cells (DCs), as determined by the TIMER web server and reference to the TISIDB. ZSCAN18 DNA methylation was positively correlated with activated B cells, activated CD8+ and CD4+ T cells, macrophages, neutrophils, and activated DCs. Moreover, five ZSCAN18-related hub genes (KDM6B, KAT6A, KMT2D, KDM1A, and HSPBP1) were identified. ZSCAN18, ZNF396, and PGBD1 were identified as components of a physical complex. ZSCAN18 is a potential tumor suppressor in BC, as expression is modified by DNA methylation and associated with patient survival. In addition, ZSCAN18 plays important roles in transcription regulation, the glycolysis signaling pathway, and the tumor immune microenvironment.

Proteomics analysis of human breast milk by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) coupled with mass spectrometry to assess breast cancer risk.

Breast cancer (BC) is one of the most common cancers and one of the most common causes for cancer-related mortality. Discovery of protein biomarkers associated with cancer is considered important for early diagnosis and prediction of the cancer risk. Protein biomarkers could be investigated by large-scale protein investigation or proteomics, using mass spectrometry (MS)-based techniques. Our group applies MS-based proteomics to study the protein pattern in human breast milk from women with BC and controls and investigates the alterations and dysregulations of breast milk proteins in comparison pairs of BC versus control. These dysregulated proteins might be considered potential future biomarkers of BC. Identification of potential biomarkers in breast milk may benefit young women without BC, but who could collect the milk for future assessment of BC risk. Previously we identified several dysregulated proteins in different sets of human breast milk samples from BC patients and controls using gel-based protein separation coupled with MS. Here, we performed 2D-PAGE coupled with nano-liquid chromatography-tandem MS (nanoLC-MS/MS) in a small-scale study on a set of six human breast milk pairs (three BC samples vs. three controls) and we identified several dysregulated proteins that have potential roles in cancer progression and might be considered potential BC biomarkers in the future.

Abstract 2051: MDN1, a novel potential early biomarker for endocrine resistant breast cancer

Abstract Midasin (MDN1) is a chaperone protein required for maturation and nuclear export of pre-ribosomal RNA. Recent investigation regarding the mutational status of MDN1 in breast cancer (BC) revealed an increased tumor mutational burden in BC patients. Interestingly, our previously published work demonstrated significantly high MDN1 protein levels in AI-resistant mammospheres. Therefore, we investigated the overall status of MDN1 in the TCGA database in breast cancer tumors and identified MDN1 expression in breast cancer cells that were sensitive or resistant to AIs. The purpose of this study was to evaluate whether there is an association between MDN1 expression or mutation status to examine if MDN1 functions as an early high-risk indicator for breast cancers resistant to AIs or endocrine therapy. Using the cBioportal for Cancer Genomics, in silico analysis was conducted and BC patients with altered MDN1 status demonstrated several clinical attributes that were significantly associated with higher mutation counts (Kruskal Wallis test, p value = 1.41 × 10-10 and q value = 4.11 × 10-9); MSI sensor score, (p value = 2.74 × 10-5 and q value = 2.27 × 10-4); and Fraction Altered Genome score (p value = 2.37 × 10-3 and q value = 0.011). Next, aneuploidy in breast cancer significantly evolved and was positively correlated with higher MDN1 expression (Spearman: 0.64, p value = 3.92 × 10-122). Compared to the other BC subtypes, MDN1 was significantly elevated in basal breast cancer (Chi square test p value < 10.0 × 10-10, q value = 4.11 × 10-9) and significantly higher in deceased versus living BC patients. The DepMap breast cancer cell line database analysis also revealed significantly increased MDN1 expression in both ER+/HER2- cell lines (p value = 7.93 × 10-3; 12 cell lines) and in ER-/HER2- cell lines (p value = 2.88 × 10-2; 31 cell lines). Primary and metastatic BC cell lines were compared and MDN1 expression was significantly higher in metastatic BC cells (p value = 8.04 × 10-5; 33 metastatic cell lines). Likewise, AI-resistant cell lines exhibited altered MDN1 expression compared to their sensitive counterparts. Additionally, there was a statistically significant association between higher ER copy number and increased MDN1 expression in BC cell lines (p value = 1.44 × 10-3; 61 cell lines). Further in-depth analysis of proteins that were coexpressed in MDN1-altered tumors revealed a panel of genes (MSH2, MSH6, RBM15, FOXM1,CCNE2, and CHEK1) that could represent a signature of early markers of AI-resistant BC since there was a positive correlation between MDN1 expression and associated pathways. In conclusion, increased expression of MDN1 in BC tumors or cells may serve as preliminary marker to predict resistance to endocrine therapy due to its significant association with genes such as MSH2, MSH6 and FOXM1 that are strongly established as indicators of endocrine resistance. This work was supported by NIH grant # SC1GM126617 and U54MD007582. Citation Format: Afia Ohemeng, Akash Gupta, Bipika Banjara, Mounika M. Pamukuntla, Manasa Kotina, A Michael Davidson, Syreeta L. Tilghman. MDN1, a novel potential early biomarker for endocrine resistant breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2051.

Abstract 3433: Global proteomic analysis of urine using a label-free LC-MS/MS approach identifies potential biomarkers of metastatic breast cancer

Abstract Introduction: Breast cancer (BC) is a complex heterogenous disease and is a leading cause of death in women. Following primary BC therapy ~40% of patients will develop metastatic BC (MBC) and 60-70% of the recurrent disease will occur at distant sites. Median survival of MBC patients with distant recurrence is ~2-3 yr. While the early detection and monitoring of BC progression are essential to improve prognosis and reduce BC-related mortality, there is a lack of surveillance strategies for monitoring patients for distant recurrence of MBC. The aim of our study was to identify urinary biomarkers for detection and monitoring of MBC. Method: We have conducted a comparative label-free LC-MS/MS analysis of the urinary proteome of patients with MBC and healthy age-matched controls (HC). A hybrid quadrupole time of flight (Q-Tof™) mass spectrometer was used for urine analysis via liquid chromatography (LC) with tandem mass spectrometry (MS/MS). Three different database search algorithms were used for peptide identification including MASCOT, Protein Lynx Global Server and Ion Accounting software. Only peptides detected in at least two out of three replicated LC-MS experiments were counted towards protein identification. Identified candidate biomarkers were validated via ELISA assays. Results: Using this approach, we identified ~400 urinary proteins of which ~104 and 89 were unique to the MBC and HC groups, respectively. Upregulated proteins in the MBC cohort were associated with angiogenesis, apoptosis, proteolysis, ECM regulation, and cell adhesion pathways. Using bioinformatic and in silico approaches, we identified a specific metastasis signature comprised of CALB1, S100A8, ZAG, VTN and TN. Diagnostic accuracies of these candidate markers were validated using independent training and validation sets according to the REMARK criteria. Urinary VTN (uVTN) and uTN levels correlated significantly with disease status in MBC patients when compared to patients with locally invasive BC and HC. Interestingly, a small subset of patients with bone metastasis also had significantly higher uVTN levels. A multiplexed marker panel of uVTN and uTN could discriminate between HC and MBC groups (AUC=0.831, P<0.001). Blinded testing indicated that uVTN levels (cutoff>1018 ng/ml) could discriminate (AUC=0.782, P<0.006) between MBC and HC. Longitudinal analysis of samples from MBC patients indicated a strong correlation between uVTN levels and disease status. Conclusions: Our findings suggest that uVTN and uTN have the potential to serve as biomarkers for the detection of MBC. While validation in larger cohorts is necessary, these results may be useful in the development of noninvasive diagnostic tests for monitoring BC progression and recurrence. [Supported by: the Advanced Medical Research Foundation, the Jo Ann Webb Fund for Angiogenesis Research and the S. Elizabeth O’Brien Trust] Citation Format: Roopali Roy, Elisa Schunkert, Petra Olivova, Martin Gilar, Scott Geromanos, Guo-Zhong Li, John Gebler, Adelle Dagher, Andrew El-Hayek, Rama Aldakhlallah, David Zurakowski, Susan Pories, Marsha A. Moses. Global proteomic analysis of urine using a label-free LC-MS/MS approach identifies potential biomarkers of metastatic breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3433.

Peripheral blood mononuclear cell derived biomarker detection using eXplainable Artificial Intelligence (XAI) provides better diagnosis of breast cancer

The incidence and mortality rate of breast cancer increases yearly by an average of 1.44 % and 0.23 %, respectively. Till 2021, there were 7.8 million women who had been diagnosed with breast cancer within 5 years. Biopsies of tumors are often expensive and invasive and raise the risk of serious complications like infection, excessive bleeding, and puncture damage to nearby tissues and organs. Early detection biomarkers are often variably expressed in different patients and may even be below the detection level at an early stage. Hence PBMC that shows alteration in gene profile as a result of interaction with tumor antigens may serve as a better early detection biomarker. Also, such alterations in immune gene profile in PBMCs are more prone to detection despite variability in different breast cancer mutants.This study aimed to identify potential diagnostic biomarkers for breast cancer using eXplainable Artificial Intelligence (XAI) on XGBoost machine learning (ML) models trained on a binary classification dataset containing the expression data of PBMCs from 252 breast cancer patients and 194 healthy women.After effectively adding SHAP values further into the XGBoost model, ten important genes related to breast cancer development were discovered to be effective potential biomarkers. Our studies showed that SVIP, BEND3, MDGA2, LEF1-AS1, PRM1, TEX14, MZB1, TMIGD2, KIT, and FKBP7 are key genes that impact model prediction. These genes may serve as early, non-invasive diagnostic and prognostic biomarkers for breast cancer patients.

Can Caspase-3 act as a potential prognostic biomarker in breast cancer? - A retrospective pilot study in central India

Background: Caspase-3 is involved in the apoptosis induced by many agents, including antineoplastic drugs in cancers. Loss of caspase-3 expression and activity has been reported in primary human breast cancers. It is suggested that it might promote tumour development by preventing and reducing senescence. It was a retrospective observational pilot study aimed to evaluate the prognostic potential role of caspase-3 in breast cancer patients.Method: It was a retrospective observational pilot study in which fifty breast cancer patients were enrolled. Haematoxylin and eosin-stained slides of the cases were screened to obtain the best paraffin block for IHC, on which immunohistochemical expression of caspase-3 marker was done and studied. It was correlated with the known prognostic markers of breast cancer.Results: Out of 21 cases with moderate caspase-3 staining, 85.7% cases were grade III and 14.2% were grade II. From 16 cases with strong caspase-3 staining, 75% cases were grading III followed by 25% cases of grade II. There was no significant correlation between caspase-3 staining with histological grade, size of tumour, lymph node involvement, ER, PR and Her2/neu status (p=0.68, 0.24, 0.20, 0.68, 0.45 and 0.11 respectively). Correlation of survival was significantly associated with lymph node involvement (p=0.01) while it was insignificant for tumour size and histological grade (p=0.36 and 0.42 respectively).Conclusion: The survival of breast cancer patients was correlated only with lymph node metastasis. It was better with smaller number of lymph node involvement. While, Caspase-3 did not have any direct association with prognostic markers of breast carcinoma like tumour size, grade of tumour, lymph node and ER, PR and HER-2/neu status. It can be probably used as a prognostic biomarker in future if bigger study is able to establish the significance in breast cancer.

Integrated analysis of coexpression and a tumor-specific ceRNA network revealed a potential prognostic biomarker in breast cancer.

Breast cancer, a type of tumor associated with high heterogeneity, is top among the common malignancies threatening women's health worldwide. Emerging evidence suggests that competing endogenous RNA (ceRNA) plays a role in the molecular biological mechanisms related to the occurrence and development of cancer. However, the effect of the ceRNA network on breast cancer, especially the long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) regulatory network, has not been fully studied. To explore potential prognostic markers of breast cancer under ceRNA network, we first extracted the breast cancer expression profiles of lncRNAs, miRNAs and mRNAs and their corresponding clinical data from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) database. Next, we selected breast cancer-related candidate genes by intersection of the differential expression analysis and the weighted gene coexpression network analysis (WGCNA). Then, we studied the interactions among lncRNAs, miRNAs, and mRNAs by means of multiMiR and starBase and then constructed a ceRNA network of 9 lncRNAs, 26 miRNAs, and 110 mRNAs. We established a prognostic risk formula by means of multivariable Cox regression analysis. Based on public databases and evaluated via modeling, we identified the HOX antisense intergenic RNA (HOTAIR)-miR-130a-3p-high mobility group-box 3 (HMGB3) axis as a potential prognostic marker in breast cancer through a prognostic risk model we established using multivariable Cox analysis. For the first time, the potential interactions among HOTAIR, miR-130a-3p, and HMGB3 in the tumorigenesis were clarified, and these may provide novel prognostic value for breast cancer treatment.

A Comprehensive Analysis Revealing FBXW9 as a Potential Prognostic and Immunological Biomarker in Breast Cancer.

The WD40 repeat-containing F-box proteins (FBXWs) family belongs to three major classes of F-box proteins. Consistent with the function of other F-box proteins, FBXWs are E3 ubiquitin ligases to mediate protease-dependent protein degradation. However, the roles of several FBXWs remain elusive. In the present study, via integrative analysis of transcriptome profiles from The Cancer Genome Atlas (TCGA) datasets, we found that FBXW9 was upregulated in the majority of cancer types, including breast cancer. FBXW expression was correlated with the prognosis of patients with various types of cancers, especially for FBXW4, 5, 9, and 10. Moreover, FBXWs were associated with infiltration of immune cells, and expression of FBXW9 was associated with poor prognosis of patients receiving anti-PD1 therapy. We predicted several substrates of FBXW9, and TP53 was the hub gene in the list. Downregulation of FBXW9 increased the expression of p21, a target of TP53, in breast cancer cells. FBXW9 was also strongly correlated with cancer cell stemness, and genes correlated with FBXW9 were associated with several MYC activities according to gene enrichment analysis in breast cancer. Cell-based assays showed that silencing of FBXW9 inhibited cell proliferation and cell cycle progression in breast cancer cells. Our study highlights the potential role of FBXW9 as a biomarker and promising target for patients with breast cancer.

The Role of ATG4A Clinical Implication and Potential Function in Breast Cancer

We studied the clinical implication and potential function of ATG4A in breast cancer by using publicly accessible patient data. The mRNA and protein levels of ATG4A were up-regulated in breast cancer tissues compared with normal breast tissues. ATG4A is a potential marker for prognosis, diagnosis and therapeutic target for breast cancer. Autophagy is a conservative catabolic process for cell homeostasis. The mechanism of autophagy in tumors is very complicated, since it can either promote or inhibit the occurrence and development of tumor according to different tumor stages and types. The purpose of this study was to investigate the clinical significance of an autophagy-related gene ATG4A in breast cancer. Transcriptional expression profiles of ATG4A between breast cancer tissues and normal tissues were retrieved from the Cancer Genome Atlas (TCGA). The ATG4A protein level was assessed by the Human Protein Atlas. The co-expression genes with ATG4A expression were analyzed using the LinkedOmics database. Protein–protein interaction (PPI) networks were constructed by the STRING. Paired t-test and Mann-Whitney U-test were used to determine the differences between breast cancer tissues and adjacent normal tissues. Kaplan–Meier curves and log rank tests were conducted for survival analysis. The expression of ATG4A in breast cancer tissues was significantly upregulated than those in adjacent normal tissues. Increased ATG4A mRNA expression was positively associated with lymph node metastases (P <0.05), ER positive (P <0.001), PR positive (P <0.001), HER-2 positive (P <0.05) and over 60 years of age (P <0.005). Compared with breast cancer patients with LumA, LumB and HER-2 positive subtypes, the expression of ATG4A mRNA in breast cancer patients with Basal was significantly lower (P <0.001). Kaplan–Meier survival analysis showed that the OS (P <0.001), DSS (P = 0.017) and PFI (P = 0.020) of breast cancer patients with high ATG4A mRNA expression were significantly shorter than those with low ATG4A mRNA expression. GO and KEGG analysis showed that Endocytosis might be a signal pathway involved in the occurrence and development of breast cancer by ATG4A. Furthermore, we found that RPL4, RPL11, RPL14, RPL29 and RPS9 may be the potential interacting genes of ATG4A in breast cancer by PPI analysis. ATG4A may be a potential diagnostic, prognostic biomarker and therapeutic target gene for breast cancer at the mRNA and protein levels.

Potential Role of Circulating miRNAs for Breast Cancer Management in the Neoadjuvant Setting: A Road to Pave.

Recently, circulating microRNAs (miRNAs) have emerged as potential non-invasive biomarkers for breast cancer (BC) management. In the context of BC patients undergoing neoadjuvant chemotherapy (NAC), the possibility of obtaining repeated, non-invasive biological samples from patients before, during, and after treatment is incredibly convenient and provides the opportunity to investigate circulating miRNAs as diagnostic, predictive, and prognostic tools. The present review aims to summarize major findings in this setting, thus highlighting their potential applicability in daily clinical practice and their possible limitations. In all the contexts (diagnostic, predictive, and prognostic), circulating miR-21-5p and miR-34a-5p have emerged as the most promising non-invasive biomarkers for BC patients undergoing NAC. Specifically, their high baseline level could discriminate between BC patients and healthy controls. On the other hand, in predictive and prognostic investigations, low circulating miR-21-5p and miR-34a-5p levels may identify patients with better outcomes, in terms of both treatment response and invasive disease-free survival. However, the findings in this field have been very heterogeneous. Indeed, pre-analytical and analytical variables, as well as factors related to patients, may explain the inconsistency among different study results. Thus, further clinical trials, with more precise patient inclusion criteria and more standardized methodological approaches, are definitely needed to better define the potential role of these promising non-invasive biomarkers.

Overview of Adductomics in Toxicology.

Adductomics is epidemiology at the molecular level. Untargeted adductomics compares levels of chemical adducts on albumin, hemoglobin, and DNA between healthy and exposed individuals. The goal is to determine a cause-and-effect relationship between chemical exposure and illness. Chemical exposures are not necessarily due to synthetic chemicals but are often due to oxidation products of naturally occurring lipids, for example, 4-hydroxynonenal and acrolein produced by lipid peroxidation of arachidonic and linoleic acids. The preferred method used in adductomics is ultra-high pressure liquid chromatography coupled to with nanoelectrospray tandem mass spectrometry. The mass of the adduct indicates its structure and identifies the chemical. The advantages of molecular epidemiology include information about the many toxicants to which a person is exposed over a period of weeks or months and the relative exposure levels. The disadvantage is the absence of information about the mechanism of toxicity. Untargeted adductomics examines albumin and hemoglobin adducts, which serve as biomarkers of exposure but do not identify the proteins and genes responsible for the toxicity. Targeted adductomics is used when the origin of the toxicity is known. This can be either an adducted protein, such as the butyrylcholinesterase protein modified by nerve agents, or a toxicant, such as acetaminophen. Untargeted adductomics methods have identified potential protein adduct biomarkers of breast cancer, colorectal cancer, childhood leukemia, and lung cancer. Adductomics is a new research area that offers structural insights into chemical exposures and a platform for the discovery of disease biomarkers. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Concomitant analyses of intratumoral microbiota and genomic features reveal distinct racial differences in breast cancer

Racial disparities are most accentuated among Black women as their lifetime risk of breast cancer incidence is lower than white and Asian women but their breast cancer related mortality is the highest among all races. Black women are more likely to develop triple-negative breast cancer at a younger age and harbor more aggressive tumors. In addition to tumor-centric alterations, tumor growth is also influenced by multiple other tumor microenvironment-related features, including resident immune cells and microbiota. Hence, in this study, we conduct concurrent genomic and metagenomic analyses, and uncover distinctive intratumoral microbial community compositions and tumor immune microenvironment-related traits in breast tumors from Asian, Black and white women. Interestingly, unique racially associated genomic nodes are found in the breast tumors from Asian, Black and white women. Examination of the cellular heterogeneity show differential enrichment of 11 out of 64 immune and stroma cell types in the breast tumors from different racial groups. In terms of microbial diversity, significant differences are revealed in alpha and beta-diversity measures. Intriguingly, potential race-specific microbial biomarkers of breast cancer are identified which significantly correlate with genes involved with tumor aggressiveness, angiogenesis, tumor cell migration and metastasis as well as oncogenic pathways-GLI and Notch. Investigating the metabolic features of intratumoral microbes, we find a significant differential enrichment of environmental information processing pathways, oncogenic pathways, and lipid metabolism pathways. Concomitantly investigating tumor-centric, tumor immune microenvironment-related and microbial alterations, our study provides a comprehensive understanding of racial disparities in breast cancer and warrants further exploration.

Screening potential lncRNA biomarkers for breast cancer and colorectal cancer combining random walk and logistic matrix factorization.

Breast cancer and colorectal cancer are two of the most common malignant tumors worldwide. They cause the leading causes of cancer mortality. Many researches have demonstrated that long noncoding RNAs (lncRNAs) have close linkages with the occurrence and development of the two cancers. Therefore, it is essential to design an effective way to identify potential lncRNA biomarkers for them. In this study, we developed a computational method (LDA-RWLMF) by integrating random walk with restart and Logistic Matrix Factorization to investigate the roles of lncRNA biomarkers in the prognosis and diagnosis of the two cancers. We first fuse disease semantic and Gaussian association profile similarities and lncRNA functional and Gaussian association profile similarities. Second, we design a negative selection algorithm to extract negative LncRNA-Disease Associations (LDA) based on random walk. Third, we develop a logistic matrix factorization model to predict possible LDAs. We compare our proposed LDA-RWLMF method with four classical LDA prediction methods, that is, LNCSIM1, LNCSIM2, ILNCSIM, and IDSSIM. The results from 5-fold cross validation on the MNDR dataset show that LDA-RWLMF computes the best AUC value of 0.9312, outperforming the above four LDA prediction methods. Finally, we rank all lncRNA biomarkers for the two cancers after determining the performance of LDA-RWLMF, respectively. We find that 48 and 50 lncRNAs have the highest association scores with breast cancer and colorectal cancer among all lncRNAs known to associate with them on the MNDR dataset, respectively. We predict that lncRNAs HULC and HAR1A could be separately potential biomarkers for breast cancer and colorectal cancer and need to biomedical experimental validation.

Detection of Calreticulin as a Candidate Prognostic Biomarker in Invasive Breast Carcinoma from a Biological Scaffold-Based 3D Co-culture System

Introduction: Breast cancer is the most common cancer in women and the world’s second leading cause of death in women, after lung cancer. Calreticulin (CRT), an endoplasmic reticulum (ER) multipurpose protein, has been proposed as a potential biomarker for breast cancer. However, reports on the correlation between CRT expression and cell invasiveness in breast cancer micro-tissues are scarce. Thus, in the current study, we analyzed the potential correlation between CRT and invasiveness of breast cancer in a biological scaffold-based 3D co-culture system. Methods: MCF7, MDA-MB-231 and MCF-10A breast cell lines were co-cultured in a 3-dimensional (3D) system with MRC-5 lung fibroblast cell line in the cell density ratio of 3:1. Thereafter, calreticulin gene and protein expression levels were determined based on quantitative reverse transcription-polymerase chain reaction (RT-qPCR) and immunohistochemistry, respectively. Moreover, via RT-qPCR analysis, the gene expression levels of calreticulin-related candidate metastasis genes in breast cancer micro-tissues were carried out. Results: The results showed occasional foci of lumen-like morphology in the non-cancerous breast micro-tissues and the formation of solid clusters for breast cancer micro-tissues. Moreover, immunohistochemistry results revealed protein expression of calreticulin in non-cancerous and cancerous breast micro-tissues with cytoplasmic and nucleic acid localizations. It was found that PCMT1 and ER-α genes were significantly downregulated (p < 0.01) in invasive breast cancer micro-tissues. Conclusion: This study suggests that CRT and CRT-related candidate metastasis genes may potentially serve as prognostic biomarkers in invasive breast carcinoma.

Identification of KCNK1 as a potential prognostic biomarker and therapeutic target of breast cancer.

Breast cancer is the most common malignant cancer and is the second most common cause of cancer-related deaths among females worldwide. Thus, it warrants the urgent development of new therapeutic targets and strategies. Potassium channels are aberrantly expressed in various tumors and are related to tumor progression. However, studies on potassium channels in breast cancer remain limited. First, The Cancer Genome Atlas (TCGA) and Gene Set Enrichment Analysis (GSEA) were used to screen the differentially expressed potassium channels in breast cancer. Several other databases were utilized for further data analysis and visualization, including Gene Expression Profiling Interactive Analysis 2 (GEPIA2), Human Protein Atlas (HPA), GeneMANIA, Tumor Immune Estimation Resource 2 (TIMER2), Catalog of Somatic Mutations in Cancer (COSMIC), cBioPortal, and UCSC Xena tool. Besides, cell proliferation was detected by cell counting kit-8 (CCK8) and 5-Ethynyl-20-deoxyuridine (EdU), and cell migration was detected by wound healing and Transwell assays after knocking down KCNK1. Furthermore, the effect of KCNK1 knockdown on the sensitivity of breast cancer cells to paclitaxel was also evaluated. KCNK1 was overexpressed in breast cancer. Higher KCNK1 expression predicted an unfavorable prognosis. Moreover, the abnormal expression of KCNK1 was attributed to promoter hypomethylation of KCNK1 in breast cancer. Besides, cell proliferation and migration were significantly inhibited post-KCNK1 silencing, while KCNK1 knockdown significantly increased breast cancer cell sensitivity to paclitaxel. Taken together, our findings demonstrated that KCNK1 is a potential prognostic biomarker and therapeutic target of breast cancer. Thus, targeting KCNK1 might help synergize with paclitaxel function in breast cancer treatment.

Unraveling Roles of miR-27b-3p as a Potential Biomarker for Breast Cancer in Malay Women via Bioinformatics Analysis.

Abnormal miRNA expression has been associated with breast cancer. Knowing miRNA and its target genes gives a better understanding of the biological mechanism behind the development of breast cancer. Here, we evaluated the potential prognostic and predictive values of miRNAs in breast cancer development by analyzing Malay women with breast cancer expression profiles. Seven differentially expressed miRNAs (DEMs) were subjected to miRNA‒target interaction network analysis (MTIN). A comprehensive MTIN was developed by integrating the information on miRNA and target gene interactions from five independent databases, including DIANA-TarBase, miRTarBase, miRNet, miRDB, and DIANA-microT. To understand the role of miRNAs in the progress of breast cancer, functional enrichment analysis of the miRNA target genes was conducted, followed by survival analysis to assess the prognostic values of the miRNAs and their target genes. In total, 1416 interactions were discovered among seven DEMs and 1274 target genes with a confidence score (CS) > 0.8. The overall survival analysis of the three most DEMs revealed a significant association of miR-27b-3p with poor prognosis in the TCGA breast cancer patient cohort. Further functional analysis of 606 miR-27b-3p target genes revealed their involvement in cancer-related processes and pathways, including the progesterone receptor signaling pathway, PI3K-Akt pathway, and EGFR transactivation. Notably, six high-confidence target genes (BTG2, DNAJC13, GRB2, GSK3B, KRAS, and UBR5) were discovered to be associated with worse overall survival in breast cancer patients, underscoring their essential roles in breast cancer development. Thus, we suggest that miR-27b-3p has significant potential as a biomarker for detecting breast cancer and can provide valuable understanding regarding the molecular mechanisms of the disease.

Comprehensive analysis of the PTPN13 expression and its clinical implication in breast cancer.

Protein tyrosine phosphatases non-receptor 13 (PTPN13) could be a potential biomarker in breast cancer (BRCA), but its genetic variation and biological significance in BRCA remain undefined. Hereon, we comprehensively investigated the clinical implication of PTPN13 expression/gene mutation in BRCA. In our study, a total of 14 cases of triple-negative breast cancers (TNBC) treated with neoadjuvant therapy were enrolled, and post-operation TNBC tissues were collected for next-generation sequencing (NGS) analysis (422 genes including PTPN13). According to the disease-free survival (DFS) time, 14 TNBC patients were divided into Group A (long-DFS) and Group B (short-DFS). The NGS data displayed that the overall mutation rate of PTPN13 was 28.57% as the third highest mutated gene, and PTPN13 mutations appeared only in Group B with short-DFS. In addition, The Cancer Genome Atlas (TCGA) database demonstrated that PTPN13 was lower expressed in BRCA than in normal breast tissues. However, PTPN13 high expression was identified to be related to a favorable prognosis in BRCA using data from the Kaplan-Meier plotter. Moreover, Gene Set Enrichment Analysis (GSEA) revealed that PTPN13 is potentially involved in interferon signaling, JAK/STAT signaling, Wnt/β-catenin signaling, PTEN pathway, and MAPK6/MAPK4 signaling in BRCA. This study provided evidence that PTPN13 might be a tumor suppressor gene and a potential molecular target for BRCA, and genetic mutation and/or low expression of PTPN13 predicted an unfavorable prognosis in BRCA. The anticancer effect and molecular mechanism of PTPN13 in BRCA may be associated with some tumor-related signaling pathways.