FOXA1 is Prognostic of Triple Negative Breast Cancers by Transcriptionally Suppressing SOD2 and IL6

Unravelling the therapeutic potential of forkhead box proteins in breast cancer: An update (Review)

Breast cancer, a prominent cause of mortality among women, develops from abnormal growth of breast tissue, thereby rendering it one of the most commonly detected cancers in the female population. Although numerous treatment strategies are available for breast cancer, discordance in terms of effective treatment and response still exists. Recently, the potential of signaling pathways and transcription factors has gained substantial attention in the cancer community; therefore, understanding their role will assist researchers in comprehending the onset and advancement of breast cancer. Forkhead box (FOX) proteins, which are important transcription factors, are considered crucial regulators of various cellular activities, including cell division and proliferation. The present study explored several subclasses of FOX proteins and their possible role in breast carcinogenesis, followed by the interaction between microRNA (miRNA) and FOX proteins. This interaction is implicated in promoting cell infiltration into surrounding tissues, ultimately leading to metastasis. The various roles that FOX proteins play in breast cancer development, their intricate relationships with miRNA, and their involvement in therapeutic resistance highlight the complexity of breast cancer dynamics. Therefore, recognizing the progress and challenges in current treatments is crucial because, despite advancements, persistent disparities in treatment effectiveness underscore the need for ongoing research, with future studies emphasizing the necessity for targeted strategies that account for the multifaceted aspects of breast cancer.

Network-based approach elucidates critical genes in BRCA subtypes and chemotherapy response in triple negative breast cancer

Breast cancers (BRCA) exhibit substantial transcriptional heterogeneity, posing a significant clinical challenge. The global transcriptional changes in a disease context, however, are likely mediated by few key genes which reflect disease etiology better than the differentially expressed genes (DEGs). We apply our network-based tool PathExt to 1,059 BRCA tumors across 4 subtypes to identify key mediator genes in each subtype. Compared to conventional differential expression analysis, PathExt-identified genes exhibit greater concordance across tumors, revealing shared and subtype-specific biological processes; better recapitulate BRCA-associated genes in multiple benchmarks, and are more essential in BRCA subtype-specific cell lines. Single-cell transcriptomic analysis reveals a subtype-specific distribution of PathExt-identified genes in multiple cell types from the tumor microenvironment. Application of PathExt to a TNBC chemotherapy response dataset identified subtype-specific key genes and biological processes associated with resistance. We described putative drugs that target key genes potentially mediating drug resistance.

Recurrent composite markers of cell types and states

Determining concise sets of genomic markers that identify cell types and states within tissue ecosystems remains challenging. To address this challenge, we developed Recurrent Composite Markers for Biological Identities with Neighborhood Enrichment (RECOMBINE). Validations of RECOMBINE with simulation and transcriptomics data in bulk, single-cell and spatial resolutions demonstrated the method's ability for unbiased selection of composite markers that characterize biological subpopulations. RECOMBINE captured markers of mouse visual cortex from single-cell RNA sequencing data and provided a gene panel for targeted spatial transcriptomics profiling. RECOMBINE identified composite markers of CD8 T cell states including GZMK ⁺ HAVCR2 ^- effector memory cells associated with anti-PD1 therapy response. The method outperformed differential gene expression analysis in characterizing a rare cell subpopulation within mouse intestine. Using RECOMBINE, we uncovered hierarchical gene programs of inter- and intra-tumoral heterogeneity in breast and skin tumors. In conclusion, RECOMBINE offers a data-driven approach for unbiased selection of composite markers, resulting in improved interpretation, discovery, and validation of cell types and states.

Network-based approach elucidates critical genes in BRCA subtypes and chemotherapy response in Triple Negative Breast Cancer

Breast cancers exhibit substantial transcriptional heterogeneity, posing a significant challenge to the prediction of treatment response and prognostication of outcomes. Especially, translation of TNBC subtypes to the clinic remains a work in progress, in part because of a lack of clear transcriptional signatures distinguishing the subtypes. Our recent network-based approach, PathExt, demonstrates that global transcriptional changes in a disease context are likely mediated by a small number of key genes, and these mediators may better reflect functional or translationally relevant heterogeneity. We apply PathExt to 1059 BRCA tumors and 112 healthy control samples across 4 subtypes to identify frequent, key-mediator genes in each BRCA subtype. Compared to conventional differential expression analysis, PathExt-identified genes (1) exhibit greater concordance across tumors, revealing shared as well as BRCA subtype-specific biological processes, (2) better recapitulate BRCA-associated genes in multiple benchmarks, and (3) exhibit greater dependency scores in BRCA subtype-specific cancer cell lines. Single cell transcriptomes of BRCA subtype tumors reveal a subtype-specific distribution of PathExt-identified genes in multiple cell types from the tumor microenvironment. Application of PathExt to a TNBC chemotherapy response dataset identified TNBC subtype-specific key genes and biological processes associated with resistance. We described putative drugs that target top novel genes potentially mediating drug resistance. Overall, PathExt applied to breast cancer refines previous views of gene expression heterogeneity and identifies potential mediators of TNBC subtypes, including potential therapeutic targets.

In Silico Analysis of Publicly Available Transcriptomic Data for the Identification of Triple-Negative Breast Cancer-Specific Biomarkers

BACKGROUND

Breast cancer is the most common type of cancer among women and is classified into multiple subtypes. Triple-negative breast cancer (TNBC) is the most aggressive subtype, with high mortality rates and limited treatment options such as chemotherapy and radiation. Due to the heterogeneity and complexity of TNBC, there is a lack of reliable biomarkers that can be used to aid in the early diagnosis and prognosis of TNBC in a non-invasive screening method.

AIM

This study aims to use in silico methods to identify potential biomarkers for TNBC screening and diagnosis, as well as potential therapeutic markers.

METHODS

Publicly available transcriptomic data of breast cancer patients published in the NCBI's GEO database were used in this analysis. Data were analyzed with the online tool GEO2R to identify differentially expressed genes (DEGs). Genes that were differentially expressed in more than 50% of the datasets were selected for further analysis. Metascape, Kaplan-Meier plotter, cBioPortal, and the online tool TIMER were used for functional pathway analysis to identify the biological role and functional pathways associated with these genes. Breast Cancer Gene-Expression Miner v4.7 was used to validify the obtained results in a larger cohort of datasets.

RESULTS

A total of 34 genes were identified as differentially expressed in more than half of the datasets. The DEG GATA3 had the highest degree of regulation, and it plays a role in regulating other genes. The estrogen-dependent pathway was the most enriched pathway, involving four crucial genes, including GATA3. The gene FOXA1 was consistently down-regulated in TNBC in all datasets.

CONCLUSIONS

The shortlisted 34 DEGs will aid clinicians in diagnosing TNBC more accurately as well as developing targeted therapies to improve patient prognosis. In vitro and in vivo studies are further recommended to validate the results of the current study.

Comprehensive bioinformatics analysis reveals the significance of forkhead box family members in pancreatic adenocarcinoma

BACKGROUND

Forkhead box proteins (FOXs) play important roles in multiple biological processes; while little is known regarding the role of FOX members in pancreatic adenocarcinoma (PAAD). This study aimed to comprehensively investigate the function of FOX family members in PAAD.

METHODS

Expression and prognostic value of FOXs were analyzed by R language and GEPIA. Genetic alteration and promoter methylation level were analyzed using CBioPortal and UALCAN. Protein-protein interactions and gene functions were analyzed using STRING and DAVID. TIMER and SENESCopedia were utilized to analyze the correlation of FOXs with immune cell infiltration or tumor senescence. Protein levels of FOXs were detected by immunohistochemistry.

RESULTS

Expression of 15 of 50 FOXs were significantly elevated in PAAD. Among these 15 differentially expressed FOXs (DE-FOXs), 4 were significantly associated with the clinical cancer stage and 4 were negatively associated with overall survival. Functions of DE-FOXs were related to epithelial tube morphogenesis, nuclear chromatin, and DNA-binding. Promoter methylation and genomic alterations were not major causes of FOX dysregulation. Most DE-FOX was correlated with diverse immune infiltration cells. Seven of the DE-FOXs were positively related to tumor senescence. The protein levels of FOXM1, FOXP1, and FOXN3 were negatively correlated with OS in the collected PAAD patients.

CONCLUSIONS

FOXM1, FOXP1, and FOXN3 have prognostic value. Seven FOXs were related senescence, whereas most DE-FOXs were related to immune infiltration in PAAD. Our findings are instructive for future research on FOX family and provide novel insights into the selection of FOXs with potential prognostic or therapeutic target value.

The role of FOXA family transcription factors in glucolipid metabolism and NAFLD

Abnormal glucose metabolism and lipid metabolism are common pathological processes in many metabolic diseases, such as nonalcoholic fatty liver disease (NAFLD). Many studies have shown that the forkhead box (FOX) protein subfamily FOXA has a role in regulating glucolipid metabolism and is closely related to hepatic steatosis and NAFLD. FOXA exhibits a wide range of functions ranging from the initiation steps of metabolism such as the development of the corresponding metabolic organs and the differentiation of cells, to multiple pathways of glucolipid metabolism, to end-of-life problems of metabolism such as age-related obesity. The purpose of this article is to review and discuss the currently known targets and signal transduction pathways of FOXA in glucolipid metabolism. To provide more experimental evidence and basis for further research and clinical application of FOXA in the regulation of glucolipid metabolism and the prevention and treatment of NAFLD.

FOXA1 in Breast Cancer: A Luminal Marker with Promising Prognostic and Predictive Impact

The present review focuses on the function of the forkhead protein FOXA1 in breast cancer (BC) in relation to steroid hormone receptors. We explored the currently available analytic approaches for FOXA1 assessment both at gene and protein levels, comparing the differences between the available techniques used for its diagnostic assessment. In addition, we elaborated on data regarding the prognostic and predictive role of this marker in BC based on several studies that evaluated its expression in relation to the outcome and/or response to therapy. FOXA1, similar to the androgen receptor (AR), may have a dual role in BC according to hormonal status. In luminal cancers, its expression contributes to a better prognosis, while in triple-negative breast cancers (TNBC), it implies an adverse outcome. Consequently, we observed that FOXA1-positive expression in a neoadjuvant setting may predict a lack of response in luminal BC as opposed to TNBC, in which FOXA1 allegedly increases its chemosensitivity. In conclusion, considering its accessible and convenient identification by immunohistochemistry, its important impact on prognosis, and its suitability to identify patients with different responses to chemotherapy, we propose that FOXA1 could be tested in routine diagnostics as an additional prognostic and predictive marker in BC.

Gene expression signatures of individual ductal carcinoma in situ lesions identify processes and biomarkers associated with progression towards invasive ductal carcinoma

Ductal carcinoma in situ (DCIS) is considered a non-invasive precursor to breast cancer, and although associated with an increased risk of developing invasive disease, many women with DCIS will never progress beyond their in situ diagnosis. The path from normal duct to invasive ductal carcinoma (IDC) is not well understood, and efforts to do so are hampered by the substantial heterogeneity that exists between patients, and even within patients. Here we show gene expression analysis from > 2,000 individually micro-dissected ductal lesions representing 145 patients. Combining all samples into one continuous trajectory we show there is a progressive loss in basal layer integrity heading towards IDC, coupled with two epithelial to mesenchymal transitions, one early and a second coinciding with the convergence of DCIS and IDC expression profiles. We identify early processes and potential biomarkers, including CAMK2N1, MNX1, ADCY5, HOXC11 and ANKRD22, whose reduced expression is associated with the progression of DCIS to invasive breast cancer.

Progression from ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) remains poorly understood. Here, the authors analyse over 2700 micro-dissected samples using transcriptomics to identify genes that characterise different stages of DCIS to IDC progression, and identify IDC-associated markers within early-stage lesions.

Investigation of the effects of overexpression of jumping translocation breakpoint (JTB) protein in MCF7 cells for potential use as a biomarker in breast cancer

Jumping translocation breakpoint (JTB) gene acts as a tumor suppressor or an oncogene in different malignancies, including breast cancer (BC), where it was reported as overexpressed. However, the molecular functions, biological processes and underlying mechanisms through which JTB protein causes increased cell growth, proliferation and invasion is still not fully deciphered. Our goal is to identify the functions of JTB protein by cellular proteomics approaches. MCF7 breast cancer cells were transfected with sense orientation of hJTB cDNA in HA, His and FLAG tagged CMV expression vector to overexpress hJTB and the expression levels were confirmed by Western blotting (WB). Proteins extracted from transfected cells were separated by SDS-PAGE and the in-gel digested peptides were analyzed by nano-liquid chromatography tandem mass spectrometry (nanoLC-MS/MS). By comparing the proteome of cells with upregulated conditions of JTB vs control and identifying the protein dysregulation patterns, we aim to understand the function of this protein and its contribution to tumorigenesis. Gene Set Enrichment Analysis (GSEA) algorithm was performed to investigate the biological processes and pathways that are associated with the JTB protein upregulation. The results demonstrated four significantly enriched gene sets from the following significantly upregulated pathways: mitotic spindle assembly, estrogen response late, epithelial-to-mesenchymal transition (EMT) and estrogen response early. JTB protein itself is involved in mitotic spindle pathway by its role in cell division/cytokinesis, and within estrogen response early and late pathways, contributing to discrimination between luminal and mesenchymal breast cancer. Thus, the overexpressed JTB condition was significantly associated with an increased expression of ACTNs, FLNA, FLNB, EZR, MYOF, COL3A1, COL11A1, HSPA1A, HSP90A, WDR, EPPK1, FASN and FOXA1 proteins related to deregulation of cytoskeletal organization and biogenesis, mitotic spindle organization, ECM remodeling, cellular response to estrogen, proliferation, migration, metastasis, increased lipid biogenesis, endocrine therapy resistance, antiapoptosis and discrimination between different breast cancer subtypes. Other upregulated proteins for overexpressed JTB condition are involved in multiple cellular functions and pathways that become dysregulated, such as tumor microenvironment (TME) acidification, the transmembrane transport pathways, glycolytic flux, iron metabolism and oxidative stress, metabolic reprogramming, nucleocytosolic mRNA transport, transcriptional activation, chromatin remodeling, modulation of cell death pathways, stress responsive pathways, and cancer drug resistance. The downregulated proteins for overexpressed JTB condition are involved in adaptive communication between external and internal environment of cells and maintenance between pro-apoptotic and anti-apoptotic signaling pathways, vesicle trafficking and secretion, DNA lesions repair and suppression of genes involved in tumor progression, proteostasis, redox state regulation, biosynthesis of macromolecules, lipolytic pathway, carbohydrate metabolism, dysregulation of ubiquitin-mediated degradation system, cancer cell immune escape, cell-to-cell and cell-to-ECM interactions, and cytoskeletal behaviour. There were no significantly enriched downregulated pathways.

Network Analysis Identifies Regulators of Basal-Like Breast Cancer Reprogramming and Endocrine Therapy Vulnerability

Basal-like breast cancer is the most aggressive breast cancer subtype with the worst prognosis. Despite its high recurrence rate, chemotherapy is the only treatment for basal-like breast cancer, which lacks expression of hormone receptors. In contrast, luminal A tumors express ERα and can undergo endocrine therapy for treatment. Previous studies have tried to develop effective treatments for basal-like patients using various therapeutics but failed due to the complex and dynamic nature of the disease. In this study, we performed a transcriptomic analysis of patients with breast cancer to construct a simplified but essential molecular regulatory network model. Network control analysis identified potential targets and elucidated the underlying mechanisms of reprogramming basal-like cancer cells into luminal A cells. Inhibition of BCL11A and HDAC1/2 effectively drove basal-like cells to transition to luminal A cells and increased ERα expression, leading to increased tamoxifen sensitivity. High expression of BCL11A and HDAC1/2 correlated with poor prognosis in patients with breast cancer. These findings identify mechanisms regulating breast cancer phenotypes and suggest the potential to reprogram basal-like breast cancer cells to enhance their targetability. SIGNIFICANCE: A network model enables investigation of mechanisms regulating the basal-to-luminal transition in breast cancer, identifying BCL11A and HDAC1/2 as optimal targets that can induce basal-like breast cancer reprogramming and endocrine therapy sensitivity.

Cancer stem cell transcriptome landscape reveals biomarkers driving breast carcinoma heterogeneity

BACKGROUND

Breast carcinomas are heterogeneous diseases with distinct clinical outcomes and cancer stem cell (CSC) percentages. Exploring breast carcinoma stem cell landscape could help understand the heterogeneity of such cancers with profound clinical relevance.

METHODS

We conducted transcriptional profiling of CSCs and non-stem cancer cells isolated from three triple-negative breast carcinoma cell lines, analyzed the CSC transcriptome landscape that drives breast carcinoma heterogeneity through differentially expressed gene identification, gene ontology (GO) and pathway enrichment analyses as well as network construction, and experimentally validated the network hub gene.

RESULTS

We identified a CSC feature panel consisting of 122 and 381 over-represented and under-expressed genes capable of differentiating breast carcinoma subtypes. We also underpinned the prominent roles of the PI3K-AKT pathway in empowering carcinoma cells with uncontrolled proliferative and migrative abilities that ultimately foster cancer stemness, and revealed the potential promotive roles of ATP6V1B1 on breast carcinoma stemness through functional in vitro studies.

CONCLUSIONS

Our study contributes in identifying a CSC feature panel for breast carcinomas that drives breast carcinoma heterogeneity at the transcriptional level, which provides a reservoir for diagnostic marker and/or therapeutic target identification once experimentally validated as demonstrated by ATP6V1B1.

Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer

Background

Breast cancer is a heterogeneous disease. Compared with other subtypes of breast cancer, triple-negative breast cancer (TNBC) is easy to metastasize and has a short survival time, less choice of treatment options. Here, we aimed to identify the potential biomarkers to TNBC diagnosis and prognosis.

Material/Methods

Three independent data sets (GSE45827, GSE38959, GSE65194) were downloaded from the Gene Expression Omnibus (GEO). The R software packages were used to integrate the gene profiles and identify differentially expressed genes (DEGs). A variety of bioinformatics tools were used to explore the hub genes, including the DAVID database, STRING database and Cytoscape software. Reverse transcription quantitative PCR (RT-qPCR) was used to verify the hub genes in 14 pairs of TNBC paired tissues.

Results

In this study, we screened out 161 DEGs between 222 non-TNBC and 126 TNBC samples, of which 105 genes were up-regulated and 56 were down-regulated. These DEGs were enriched for 27 GO terms and two pathways. GO analysis enriched mainly in “cell division”, “chromosome, centromeric region” and “microtubule motor activity”. KEGG pathway analysis enriched mostly in “Cell cycle” and “Oocyte meiosis”. PPI network was constructed and then 10 top hub genes were screened. According to the analysis results of the Kaplan-Meier survival curve, the expression levels of only NUF2, FAM83D and CENPH were associated with the recurrence-free survival in TNBC samples (P < 0.05). RT-qPCR confirmed that the expression levels of NUF2 and FAM83D in TNBC tissues were indeed up-regulated significantly.

Conclusions

The comprehensive analysis showed that NUF2 and FAM83D could be used as potential biomarkers for diagnosis and prognosis of TNBC.

FOXA1 expression in Iraqi women with ER+ breast cancer

Background: Breast cancer (BC) is a heterogeneous disease that can be classified into many subtypes according to histopathological and molecular characteristics. Forkhead box protein A1 (FOXA1) is a transcriptional pioneer factor that opens chromatin allowing estrogen receptor (α-ER) access to its genomic targets. FOXA1 expression is related to luminal BC with a good prognosis. Objectives: The present study is sought to determine the FOXA1 expression in Iraqi women with ER+ BC. Methods: Forty-eight fresh malignant breast tissues were analyzed by immunohistochemistry assay to choose ER+ samples, and then by RT-qPCR to evaluate FOXA1 gene expression. Results: The ER-positive samples were (72.91%) of the total samples, and the molecular subtype of luminal A was the most common with a percentage of 56.25%. It was also noted that the high expression of the FOXA1 gene is highly significant (p<0.05) in Iraqi women with BC when compared with healthy controls. Conclusions: Highly significant FOXA1 expression was found in Iraqi women with BC makes it eligible to be a good predictor or a biomarker for BC.

Functionally analyzing the important roles of hepatocyte nuclear factor 3 (FoxA) in tumorigenesis

Transcriptional factors (TFs) play a central role in governing gene expression under physiological conditions including the processes of embryonic development, metabolic homeostasis and response to extracellular stimuli. Conceivably, the aberrant dysregulations of TFs would dominantly result in various human disorders including tumorigenesis, diabetes and neurodegenerative diseases. Serving as the most evolutionarily reserved TFs, Fox family TFs have been explored to exert distinct biological functions in neoplastic development, by manipulating diverse gene expression. Recently, among the Fox family members, the pilot roles of FoxAs attract more attention due to their functions as both pioneer factor and transcriptional factor in human tumorigenesis, particularly in the sex-dimorphism tumors. Therefore, the pathological roles of FoxAs in tumorigenesis have been well-explored in modulating inflammation, immune response and metabolic homeostasis. In this review, we comprehensively summarize the impressive progression of FoxA functional annotation, clinical relevance, upstream regulators and downstream effectors, as well as valuable animal models, and highlight the potential strategies to target FoxAs for cancer therapies.

Roles and correlation of FOXA1 and ZIC1 in breast cancer

The aim of this study was to evaluate the prognostic role of Forkhead box A1 (FOXA1) in breast cancer and determine the relationship between FOXA1 and zinc finger of the cerebellum 1 (ZIC1). BCIP, GEPIA, and Oncomine databases were used to detect expression of FOXA1 and assess prognostic roles of FOXA1 and ZIC1 in invasive breast tumors. A total of 113 female invasive breast cancer cases were collected to investigate FOXA1 and ZIC1 expression via immunohistochemistry. Twenty pairs of frozen-thawed tumors were used to select reliable indicators via western blotting and real-time quantitative polymerase chain reaction. In addition, Kaplan-Meier curves and Cox regression analysis were performed to analyze the overall survival (OS) and relapse-free survival. Multiple databases showed that FOXA1 expression was elevated in invasive breast cancer and negatively related to ZIC1. BCIP database also displayed a poor prognosis of high FOXA1 and low ZIC1. FOXA1 was positively associated with tumor size, grading, lymph node metastasis, and Tumor Node Metastasis (TNM) staging, while ZIC1 expression was negatively related to grading, lymph node metastasis, and TNM staging. In Kaplan-Meier and Cox regression analysis, FOXA1 negative group and ZIC1 positive group had better OS rate and recurrence-free survival rate. In addition, a joint evaluation showed that "FOXA1- ZIC1+" had the highest OS and relapse-free survival, but "FOXA1+ ZIC1-" had the lowest ones. FOXA1 was negatively related to ZIC1 in breast cancer and they had different roles in clinicopathology and prognosis. Combined examination of FOXA1 and ZIC1 could bring more benefit to breast cancer patients.

Epigenetic profiles capturing breast cancer stemness for triple negative breast cancer control

Aim: Triple-negative breast cancers (TNBCs) contain a higher percentage of breast cancer stem cells (BCSCs) than the other subtypes and lack effective yet safe-targeted therapies. We would like to unveil genes relevant to the therapeutic control of breast cancer stemness at the epigenetic level. Methods: We sequenced the transcriptome of BCSCs isolated from TNBCs, identified genes differentially expressed in these cells and subjected to DNA methylation and established the Bayesian network as well as interactions out of them. Results & conclusion: We presented a core epigenetic BCSC gene panel consisting of eight genes that can be used for BCSCs and TNBCs identification, and revealed the dominant roles of FOXA1 and GATA3 in orchestrating breast cancer heterogeneity and stemness.