Involvement of a Transcription factor, Nfe2, in Breast Cancer Metastasis to Bone

DDIT3 is associated with breast cancer prognosis and immune microenvironment: an integrative bioinformatic and immunohistochemical analysis

DNA damage-inducible transcript 3 (DDIT3) is a transcription factor central to apoptosis, differentiation, and stress response. DDIT3 has been extensively studied in cancer biology. However, its precise implications in breast cancer progression and its interaction with the immune microenvironment are unclear. In this study, we utilized a novel multi-omics integration strategy, combining bulk RNA sequencing, single-cell sequencing, spatial transcriptomics and immunohistochemistry, to explore the role of DDIT3 in breast cancer and establish the correlation between DDIT3 and poor prognosis in breast cancer patients. We identified a robust prognostic signature, including six genes (unc-93 homolog B1, TLR signaling regulator, anti-Mullerian hormone, DCTP pyrophosphatase 1, mitochondrial ribosomal protein L36, nuclear factor erythroid 2, and Rho GTPase activating protein 39), associated with DDIT3. This signature stratified the high-risk patient groups, characterized by increased infiltration of the regulatory T cells and M2-like macrophages and fibroblast growth factor (FGF)/FGF receptor signaling activation. Notably, the high-risk patient group demonstrated enhanced sensitivity to immunotherapy, presenting novel therapeutic opportunities. Integrating multi-omics data helped determine the spatial expression pattern of DDIT3 in the tumor microenvironment and its correlation with immune cell infiltration. This multi-dimensional analysis provided a comprehensive understanding of the intricate interplay between DDIT3 and the immune microenvironment in breast cancer. Overall, our study not only facilitates understanding the role of DDIT3 in breast cancer but also offers innovative insights for developing prognostic models and therapeutic strategies. Identifying the DDIT3-related prognostic signature and its association with the immune microenvironment provided a promising avenue for personalized breast cancer treatment.

ELF3 plays an important role in defining TRAIL sensitivity in breast cancer by modulating the expression of decoy receptor 2 (DCR2)

BACKGROUND

TRAIL protein on binding to its cognate death receptors (DR) can induce apoptosis specifically in breast tumor cells sparing normal cells. However, TRAIL also binds to decoy receptors (DCR) thereby inhibiting the apoptotic pathways thus causing TRAIL resistance. Also, one of the barriers due to which TRAIL-based therapy could not become FDA-approved might be because of resistance to therapy. Therefore, in the current study we wanted to explore the role of transcription factors in TRAIL resistance with respect to breast cancer.

METHODS

Microarray data from TRAIL-sensitive (TS) and TRAIL-resistant (TR) MDA-MB-231 cells were reanalyzed followed by validation of the candidate genes using quantitative PCR (qPCR), immunoblotting and immunofluorescence technique. Overexpression of the candidate gene was performed in MDA-MB-231 and MCF7 cells followed by cell viability assay and immunoblotting for cleaved caspase-3. Additionally, immunoblotting for DCR2 was carried out. TCGA breast cancer patient survival was used for Kaplan-Meier (KM) plot.

RESULTS

Validation of the candidate gene i.e. ELF3 using qPCR and immunoblotting revealed it to be downregulated in TR cells compared to TS cells. ELF3 overexpression in MDA-MB-231 and MCF7 cells caused reversal of TRAIL resistance as observed using cell viability assay and cleaved caspase-3 immunoblotting. ELF3 overexpression also resulted in DCR2 downregulation in the MDA-MB-231 and MCF7 cells. Furthermore, KM analysis found high ELF3 and low DCR2 expression to show better patient survival in the presence of TRAIL.

CONCLUSION

Our study shows ELF3 to be an important factor that can influence TRAIL-mediated apoptosis in breast cancer. Also, ELF3 and DCR2 expression status should be taken into consideration while designing strategies for successful TRAIL-based therapy.

Combining bulk and scRNA-seq to explore the molecular mechanisms governing the distinct efferocytosis activities of a macrophage subpopulation in PDAC

Pancreatic ductal adenocarcinoma (PDAC), a very aggressive tumour, is currently the third leading cause of cancer-related deaths. Unfortunately, many patients face the issue of inoperability at the diagnostic phase leading to a quite dismal prognosis. The onset of metastatic processes has a crucial role in the elevated mortality rates linked to PDAC. Individuals with metastatic advances receive only palliative therapy and have a grim prognosis. It is essential to carefully analyse the intricacies of the metastatic process to enhance the prognosis for individuals with PDAC. Malignancy development is greatly impacted by the process of macrophage efferocytosis. Our current knowledge about the complete range of macrophage efferocytosis activities in PDAC and their intricate interactions with tumour cells is still restricted. This work aims to resolve communication gaps and pinpoint the essential transcription factor that is vital in the immunological response of macrophage populations. We analysed eight PDAC tissue samples sourced from the gene expression omnibus. We utilized several software packages such as Seurat, DoubletFinder, Harmony, Pi, GSVA, CellChat and Monocle from R software together with pySCENIC from Python, to analyse the single-cell RNA sequencing (scRNA-seq) data collected from the PDAC samples. This study involved the analysis of a comprehensive sample of 22,124 cells, which were classified into distinct cell types. These cell types encompassed endothelial and epithelial cells, PDAC cells, as well as various immune cells, including CD4+ T cells, CD8+ T cells, NK cells, B cells, plasma cells, mast cells, monocytes, DC cells and different subtypes of macrophages, namely C0 macrophage TGM2+, C1 macrophage PFN1+, C2 macrophage GAS6+ and C3 macrophage APOC3+. The differentiation between tumour cells and epithelial cells was achieved by the implementation of CopyKat analysis, resulting in the detection and categorization of 1941 PDAC cells. The amplification/deletion patterns observed in PDAC cells on many chromosomes differ significantly from those observed in epithelial cells. The study of Pseudotime Trajectories demonstrated that the C0 macrophage subtype expressing TGM2+ had the lowest level of differentiation. Additionally, the examination of gene set scores related to efferocytosis suggested that this subtype displayed higher activity during the efferocytosis process compared to other subtypes. The most active transcription factors for each macrophage subtype were identified as BACH1, NFE2, TEAD4 and ARID3A. In conclusion, the examination of human PDAC tissue samples using immunofluorescence analysis demonstrated the co-localization of CD68 and CD11b within regions exhibiting the presence of keratin (KRT) and alpha-smooth muscle actin (α-SMA). This observation implies a spatial association between macrophages, fibroblasts, and epithelial cells. There is variation in the expression of efferocytosis-associated genes between C0 macrophage TGM2+ and other macrophage cell types. This observation implies that the diversity of macrophage cells might potentially influence the metastatic advancement of PDAC. Moreover, the central transcription factor of different macrophage subtypes offers a promising opportunity for targeted immunotherapy in the treatment of PDAC.

Chromatin Accessibility Landscape of Human Triple-negative Breast Cancer Cell Lines Reveals Variation by Patient Donor Ancestry

African American (AA) women have an excessive risk of developing triple-negative breast cancer (TNBC). We employed Assay for Transposase-Accessible Chromatin using sequencing to characterize differences in chromatin accessibility between nine commonly used TNBC cell lines derived from patients of European and African ancestry. Principal component and chromosome mapping analyses of accessibility peaks with the most variance revealed separation of chromatin profiles by patient group. Motif enrichment and footprinting analyses of disparate open chromatin regions revealed differences in transcription factor activity, identifying 79 with ancestry-associated binding patterns (FDR < 0.01). AA TNBC cell lines exhibited increased accessibility for 62 transcription factors associated with epithelial-to-mesenchymal transition, cancer stemness/chemotherapeutic resistance, proliferation, and aberrant p53 regulation, as well as KAISO, which has been previously linked to aggressive tumor characteristics in AA patients with cancer. Differential Assay for Transposase-Accessible Chromatin signal analysis identified 1,596 genes located within promoters of differentially open chromatin regions in AA-derived TNBC, identifying DNA methyltransferase 1 as the top upregulated gene associated with African ancestry. Pathway analyses with these genes revealed enrichment in several pathways, including hypoxia. Culturing cells under hypoxia showed ancestry-specific stress responses that led to the identification of a core set of AA-associated transcription factors, which included members of the Kruppel-like factor and Sp subfamilies, as well as KAISO, and identified ZDHHC1, a gene previously implicated in immunity and STING activation, as the top upregulated AA-specific gene under hypoxia. Together, these data reveal a differential chromatin landscape in TNBC associated with donor ancestry. The open chromatin structure of AA TNBC may contribute to a more lethal disease.

SIGNIFICANCE

We identify an ancestry-associated open chromatin landscape and related transcription factors that may contribute to aggressive TNBC in AA women. Furthermore, this study advocates for the inclusion of diversely sourced cell lines in experimental in vitro studies to advance health equity at all levels of scientific research.

Should I stay or should I go? Spatio-temporal control of cellular anchorage by hematopoietic factors orchestrates tumor metastatic cascade

The term "metastatic cascade" defines a process whereby few tumor cells complete a sequence of steps to leave the primary tumor to reach one or more sites elsewhere in the body, usually through the bloodstream to develop one or several metastases. Due to the nature and plasticity of cancer, unfortunately no specific and functional anti-metastatic drugs are available. In this Commentary, we are highlighting how four essential factors are able to induce adhesion-to-suspension transition (herein referred to as AST) in human cancer cells and how this process may play a key role in tumor metastasis. We further underlined the potential role of hematopoietic transcriptional regulators in reprogramming anchorage dependency of cells, supporting the possible targeting of AST factors as promising therapeutic strategy to overcome metastasis in solid tumor cells.

A novel super-enhancer-related gene signature predicts prognosis and immune microenvironment for breast cancer

BACKGROUND

This study targeted at developing a robust, prognostic signature based on super-enhancer-related genes (SERGs) to reveal survival prognosis and immune microenvironment of breast cancer.

METHODS

RNA-sequencing data of breast cancer were retrieved from The Cancer Genome Atlas (TCGA), 1069 patients of which were randomly assigned into training or testing set in 1:1 ratio. SERGs were downloaded from Super-Enhancer Database (SEdb). After which, a SERGs signature was established based on the training set, with its prognostic value further validated in the testing set. Subsequently, we identified the potential function enrichment and tumor immune infiltration of the model. Moreover, in vitro experiments were completed to further explore the biological functions of ZIC2 gene (one of the risk genes in the prognostic model) in breast cancer.

RESULTS

A risk score system of prognostic value was constructed with 6 SERGs (ZIC2, NFE2, FOXJ1, KLF15, POU3F2 and SPIB) to find patients in high-risk group with significantly worse prognosis in both training and testing sets. In addition, a multivariate regression was established via integrating the 6 genes with age and N stage, indicating well performance by calibration, time-dependent receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Further analysis demonstrated that tumor-associated pathological processes and pathways were significantly enriched in the high-risk group. In general, the novel SERGs signature could be applied to screen breast cancer with immunosuppressive microenvironment for the risk score was negatively correlated with ESTIMATE score, tumor-infiltration lymphocytes (such as CD4 + and CD8 + T cell), immune checkpoints and chemotactic factors. Furthermore, down-regulation of ZIC2 gene expression inhibited the cell viability, cellular migration and cell cycle of breast cancer cells.

CONCLUSIONS

The novel SERGs signature could predict the prognosis of breast cancer; and SERGs might serve as potential therapeutic targets for breast cancer.

Animal models of cancer metastasis to the bone

Cancer metastasis is a major cause of mortality from several tumors, including those of the breast, prostate, and the thyroid gland. Since bone tissue is one of the most common sites of metastasis, the treatment of bone metastases is crucial for the cure of cancer. Hence, disease models must be developed to understand the process of bone metastasis in order to devise therapies for it. Several translational models of different bone metastatic tumors have been developed, including animal models, cell line injection models, bone implant models, and patient-derived xenograft models. However, a compendium on different bone metastatic cancers is currently not available. Here, we have compiled several animal models derived from current experiments on bone metastasis, mostly involving breast and prostate cancer, to improve the development of preclinical models and promote the treatment of bone metastasis.

The role played by ailanthone in inhibiting bone metastasis of breast cancer by regulating tumor-bone microenvironment through the RANKL-dependent pathway

Introduction: Bone metastasis of breast cancer (BC) is a process in which the disruption of the bone homeostatic microenvironment leads to an increase in osteoclast differentiation. Ailanthus altissima shows an inhibitory effect on osteoclast differentiation. Ailanthone (AIL) refers to a natural compound isolated from Ailanthus altissima, a Chinese herbal medicine, and has effective anti-tumor activity in numerous cell lines. Its impact on bone metastases for BC is yet unclear. Methods: We measured the effect of AIL on MDA-MB-231 cells by wound healing experiments, Transwell and colony formation experiment. Using the Tartrate-resistant Acid Phosphatase (TRAP) staining tests, filamentous (F-actin) staining and bone resorption test to detect the effect of AIL on the osteoclast cell differentiation of the Bone Marrow-derived Macrophages (BMMs), activated by the MDA-MB-231 cell Conditioned Medium (MDA-MB-231 CM) and the Receptor Activator of Nuclear factor-κB Ligand (RANKL),and to explore its possibility Mechanisms. In vivo experiments verified the effect of AIL on bone destruction in breast cancer bone metastasis model mice. Results: In vitro, AIL significantly decrease the proliferation, migration and infiltration abilities of MDA-MB-231 cells at a safe concentration, and also reduced the expression of genes and proteins involved in osteoclast formation in MDA-MB-231 cells. Osteoclast cell differentiation of the BMMs, activated by MDA-MB-231 CM and RANKL, were suppressed by AIL in the concentration-dependent manner. Additionally, it inhibits osteoclast-specific gene and protein expression. It was noted that AIL inhibited the expression of the osteoclast differentiation-related cytokines RANKL and interleukin-1β (IL-1β) that were secreted by the MDA-MB-231 cells after upregulating the Forkhead box protein 3 (FOXP3) expression. Furthermore, AIL also inhibits the expression of the Mitogen-Activated Protein Kinase (MAPK), Phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT), and Nuclear factor-κB Ligand (NF-κB) signaling pathways, which then suppresses the MDA-MB-231CM-induced development of Osteoclasts. Conclusion: Our study shows that AIL blocks osteoclast differentiation in the bone metastasis microenvironment by inhibiting cytokines secreted by BC cells, which may be a potential agent for the treatment of BC and its secondary bone metastasis.

Identification and validation of a novel prognostic signature based on transcription factors in breast cancer by bioinformatics analysis

BACKGROUND

Breast cancer (BRCA) is the leading cause of cancer mortality among women, and it is associated with many tumor suppressors and oncogenes. There is increasing evidence that transcription factors (TFs) play vital roles in human malignancies, but TFs-based biomarkers for BRCA prognosis were still rare and necessary. This study sought to develop and validate a prognostic model based on TFs for BRCA patients.

METHODS

Differentially expressed TFs were screened from 1,109 BRCA and 113 non-tumor samples downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis was used to identify TFs associated with overall survival (OS) of BRCA, and multivariate Cox regression analysis was performed to establish the optimal risk model. The predictive value of the TF model was established using TCGA database and validated using a Gene Expression Omnibus (GEO) data set (GSE20685). A gene set enrichment analysis was conducted to identify the enriched signaling pathways in high-risk and low-risk BRCA patients. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the TF target genes were also conducted separately.

RESULTS

A total of 394 differentially expressed TFs were screened. A 9-TF prognostic model, comprising PAX7, POU3F2, ZIC2, WT1, ALX4, FOXJ1, SPIB, LEF1 and NFE2, was constructed and validated. Compared to those in the low-risk group, patients in the high-risk group had worse clinical outcomes (P<0.001). The areas under the curve of the prognostic model for 5-year OS were 0.722 in the training cohort and 0.651 in the testing cohort. Additionally, the risk score was an independent prediction indicator for BRCA patients both in the training cohort (HR =1.757, P<0.001) and testing cohort (HR =1.401, P=0.001). It was associated with various cancer signaling pathways. Ultimately, 9 overlapping target genes were predicted by 3 prediction nomograms. The GO and KEGG enrichment analyses of these target genes suggested that the TFs in the model may regulate the activation of some classical tumor signaling pathways to control the progression of BRCA through these target genes.

CONCLUSIONS

Our study developed and validated a novel prognostic TF model that can effectively predict 5-year OS for BRCA patients.

Integrated profiling of human pancreatic cancer organoids reveals chromatin accessibility features associated with drug sensitivity

Chromatin accessibility plays an essential role in controlling cellular identity and the therapeutic response of human cancers. However, the chromatin accessibility landscape and gene regulatory network of pancreatic cancer are largely uncharacterized. Here, we integrate the chromatin accessibility profiles of 84 pancreatic cancer organoid lines with whole-genome sequencing data, transcriptomic sequencing data and the results of drug sensitivity analysis of 283 epigenetic-related chemicals and 5 chemotherapeutic drugs. We identify distinct transcription factors that distinguish molecular subtypes of pancreatic cancer, predict numerous chromatin accessibility peaks associated with gene regulatory networks, discover regulatory noncoding mutations with potential as cancer drivers, and reveal the chromatin accessibility signatures associated with drug sensitivity. These results not only provide the chromatin accessibility atlas of pancreatic cancer but also suggest a systematic approach to comprehensively understand the gene regulatory network of pancreatic cancer in order to advance diagnosis and potential personalized medicine applications.

Tumor microenvironment-related multigene prognostic prediction model for breast cancer

Background: Breast cancer is an invasive disease with complex molecular mechanisms. Prognosis-related biomarkers are still urgently needed to predict outcomes of breast cancer patients.

Methods: Original data were download from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The analyses were performed using perl-5.32 and R-x64-4.1.1.

Results: In this study, 1086 differentially expressed genes (DEGs) were identified in the TCGA cohort; 523 shared DEGs were identified in the TCGA and GSE10886 cohorts. Eight subtypes were estimated using non-negative matrix factorization clustering with significant differences seen in overall survival (OS) and progression-free survival (PFS) (P < 0.01). Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed to develop a related risk score related to the 17 DEGs; this score separated breast cancer into low- and high-risk groups with significant differences in survival (P < 0.01) and showed powerful effectiveness (TCGA all group: 1-year area under the curve [AUC] = 0.729, 3-year AUC = 0.778, 5-year AUC = 0.781). A nomogram prediction model was constructed using non-negative matrix factorization clustering, the risk score, and clinical characteristics. Our model was confirmed to be related with tumor microenvironment. Furthermore, DEGs in high-risk breast cancer were enriched in histidine metabolism (normalized enrichment score [NES] = 1.49, P < 0.05), protein export (NES = 1.58, P < 0.05), and steroid hormone biosynthesis signaling pathways (NES = 1.56, P < 0.05).

Conclusions: We established a comprehensive model that can predict prognosis and guide treatment.

Crucial contribution of GPR56/ADGRG1, expressed by breast cancer cells, to bone metastasis formation

From a mouse triple-negative breast cancer cell line, 4T1, we previously established 4T1.3 clone with a high capacity to metastasize to bone after its orthotopic injection into mammary fat pad of immunocompetent mice. Subsequent analysis demonstrated that the interaction between cancer cells and fibroblasts in a bone cavity was crucial for bone metastasis focus formation arising from orthotopic injection of 4T1.3 cells. Here, we demonstrated that a member of the adhesion G-protein-coupled receptor (ADGR) family, G-protein-coupled receptor 56 (GPR56)/adhesion G-protein-coupled receptor G1 (ADGRG1), was expressed selectively in 4T1.3 grown in a bone cavity but not under in vitro conditions. Moreover, fibroblasts present in bone metastasis sites expressed type III collagen, a ligand for GPR56/ADGRG1. Consistently, GPR56/ADGRG1 proteins were detected in tumor cells in bone metastasis foci of human breast cancer patients. Deletion of GPR56/ADGRG1 from 4T1.3 cells reduced markedly intraosseous tumor formation upon their intraosseous injection. Conversely, intraosseous injection of GPR56/ADGRG1-transduced 4T1, TS/A (mouse breast cancer cell line), or MDA-MB-231 (human breast cancer cell line) exhibited enhanced intraosseous tumor formation. Furthermore, we proved that the cleavage at the extracellular region was indispensable for GPR56/ADGRG1-induced increase in breast cancer cell growth upon its intraosseous injection. Finally, inducible suppression of Gpr56/Adgrg1 gene expression in 4T1.3 cells attenuated bone metastasis formation with few effects on primary tumor formation in the spontaneous breast cancer bone metastasis model. Altogether, GPR56/ADGRG1 can be a novel target molecule to develop a strategy to prevent and/or treat breast cancer metastasis to bone.

Extracellular Vesicles in Tumors: A Potential Mediator of Bone Metastasis

As one of the most common metastatic sites, bone has a unique microenvironment for the growth and prosperity of metastatic tumor cells. Bone metastasis is a common complication for tumor patients and accounts for 15-20% of systemic metastasis, which is only secondary to lung and liver metastasis. Cancers prone to bone metastasis include lung, breast, and prostate cancer. Extracellular vesicles (EVs) are lipid membrane vesicles released from different cell types. It is clear that EVs are associated with multiple biological phenomena and are crucial for intracellular communication by transporting intracellular substances. Recent studies have implicated EVs in the development of cancer. However, the potential roles of EVs in the pathological exchange of bone cells between tumors and the bone microenvironment remain an emerging area. This review is focused on the role of tumor-derived EVs in bone metastasis and possible regulatory mechanisms.