A seven-nuclear receptor-based prognostic signature in breast cancer

Construction of an oxidative stress-associated genes signature in breast cancer by machine learning algorithms

OBJECTIVE

To construct a prognostic model of a breast cancer-related oxidative stress-related gene (OSRG) signature using machine learning algorithms.

METHODS

The OSRGs of breast cancer were constructed by least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. The Cancer Genome Atlas (TCGA) was used to analyse the gene expression and prognostic value. The Human Protein Atlas was used to analyse the protein expression of hub genes. Receiver operating characteristic analysis, calibration curve and decision curve analysis were used to predict the stability of this model.

RESULTS

The area under the curve of 1-, 3- and 5-year overall survival were 0.751, 0.707 and 0.645 in the TCGA training dataset; and 0.692, 0.678 and 0.602 in the TCGA testing dataset, respectively. Calibration plot showed good agreement between predicted probabilities and observed outcomes. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) pathway analysis indicated that multiple cancer-related pathways were highly enriched in the high-risk group. Immune infiltration analysis showed immune cells and their functions may play a key role in the development and mechanism of breast cancer.

CONCLUSIONS

This new OSRG signature was associated with the immune infiltration and it might be useful in predicting the prognosis in patients with breast cancer.

Prognostic model construction and target identification of Si-Wu-Tang against breast cancer

The targets and mechanisms of Si-Wu-Tang (SWT) against (Breast cancer) BRCA were identified and a survival model and nomogram was construted by network pharmacology, bioinformatic analysis and in vitro experiments. A total of 72 anti-breast cancer SWT targets were selected, among which eleven genes (MAOA、SQLE、CACNA2D1、GLI1、RORB、ITGB3、TACR1、NR3C2、CA3、RBP4 and PTK6) were used to construct a novel prognostic model of breast cancer. The anti-breast cancer activity of SWT was related to the modulation of the receptor tyrosine kinases signaling pathways. Moreover, two compounds, mairin and senkyunone were found to bind directly to ITGB3 and RORB proteins. Finally, mRNA and protein expression of ITGB3 and RORB was observed to be significantly down-regulated after incubation of MCF-7 cells with SWT. Overall, our results indicated that mairin and senkyunone were the key ingredients present in SWT, and ITGB3 as well as RORB proteins were the major targets affected by SWT. The prognostic model can be used to predict the outcome of BRCA patients.

ACAT1-mediated METTL3 acetylation inhibits cell migration and invasion in triple negative breast cancer

Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive disease with poor prognosis. Acetylation modifications affect a great number of biological processes of malignant tumors. The current study aims at revealing the role of acetylation-related mechanism in TNBC progression. Methyltransferase like-3 (METTL3) was found to be downregulated in TNBC cells via quantitative polymerase chain reaction (qPCR) and western blot analyses. Co-Immunoprecipitation (Co-IP) and GST pulldown assays revealed the interaction between acetyl-CoA acetyltransferase 1 (ACAT1) and METTL3. Through further immunoprecipitation (IP) assay, we determined that ACAT1 stabilizes METTL3 protein via inhibiting the degradation of ubiquitin-proteasome. Functionally, ACAT1 inhibits TNBC cell migration and invasion. Moreover, nuclear receptor subfamily 2 group F member 6 (NR2F6) regulates ACAT1 expression at transcriptional level. Finally, we demonstrated that NR2F6/ACAT/METTL3 axis suppresses the migration and invasion of TNBC cells via METTL3. In conclusion, NR2F6 transcriptionally activates ACAT1 and promotes the suppressive effects of ACAT1-mediated METTL3 acetylation on TNBC cell migration and invasion.

Combination Analysis of Ferroptosis and Immune Status Predicts Patients Survival in Breast Invasive Ductal Carcinoma

Ferroptosis is a new form of iron-dependent cell death and plays an important role during the occurrence and development of various tumors. Increasingly, evidence shows a convincing interaction between ferroptosis and tumor immunity, which affects cancer patients' prognoses. These two processes cooperatively regulate different developmental stages of tumors and could be considered important tumor therapeutic targets. However, reliable prognostic markers screened based on the combination of ferroptosis and tumor immune status have not been well characterized. Here, we chose the ssGSEA and ESTIMATE algorithms to evaluate the ferroptosis and immune status of a TCGA breast invasive ductal carcinoma (IDC) cohort, which revealed their correlation characteristics as well as patients' prognoses. The WGCNA algorithm was used to identify genes related to both ferroptosis and immunity. Univariate COX, LASSO regression, and multivariate Cox regression models were used to screen prognostic-related genes and construct prognostic risk models. Based on the ferroptosis and immune scores, the cohort was divided into three groups: a high-ferroptosis/low-immune group, a low-ferroptosis/high-immune group, and a mixed group. These three groups exhibited distinctive survival characteristics, as well as unique clinical phenotypes, immune characteristics, and activated signaling pathways. Among them, low-ferroptosis and high-immune statuses were favorable factors for the survival rates of patients. A total of 34 differentially expressed genes related to ferroptosis-immunity were identified among the three groups. After univariate, Lasso regression, and multivariate stepwise screening, two key prognostic genes (GNAI2, PSME1) were identified. Meanwhile, a risk prognosis model was constructed, which can predict the overall survival rate in the validation set. Lastly, we verified the importance of model genes in three independent GEO cohorts. In short, we constructed a prognostic model that assists in patient risk stratification based on ferroptosis-immune-related genes in IDC. This model helps assess patients' prognoses and guide individualized treatment, which also further eelucidatesthe molecular mechanisms of IDC.

Prognostic implication and immunotherapy response prediction of a ubiquitination-related gene signature in breast cancer

Breast cancer (BC) is one of the most common tumor types and has poor outcomes. In this study, a ubiquitination-related prognostic signature was constructed, and its association with immunotherapy response in BC was explored. A list of ubiquitination-related genes was obtained from the molecular signatures database, and a ubiquitination-related gene signature was obtained by least absolute shrinkage and selection operator Cox regression. The genes, TCN1, DIRAS3, and IZUMO4, had significant influence on BC outcomes. Patients were categorized into two clusters-a high-risk group with poor survival and a low-risk group with greater chances of controlling BC progression. Univariate and multivariate Cox regression analyses revealed that the risk signature was an independent prognostic factor for BC. Gene set enrichment analysis suggested that the high-risk group was enriched in cell cycle and DNA replication pathways. The risk score was positively linked to the tumor microenvironment and negatively correlated with the immunotherapy response. The IC50 values for rapamycin were higher in the low-risk group, whereas those for axitinib, AZD6244, erlotinib, GDC0941, GSK650394, GSK269962A, lapatinib, and PD0325901 were higher in the high-risk group. Therefore, the ubiquitination-related signature is considered a promising tool for predicting a BC patient's immunotherapy response.

MARCKS is a New Prognostic Biomarker in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common type of cancers, but there is still a lack of known biomarkers for the effective diagnosis or prognosis of HCC. Myristoylated alanine-rich C-kinase substrate (MARCKS) is a substrate of protein kinase C, which was located in the cell plasma membrane. The purpose of our study was to evaluate the role of MARCKS in HCC.

Methods

The role of MARCKS in HCC was explored by bioinformatics and experiment.

Results

We demonstrated that MARCKS expression was significantly elevated in HCC datasets of TCGA. MARCKS was up-regulated in tumor sample in HCC. Functional enrichment indicated that MARCKS-related differentially expressed genes (DEGs) were mainly enriched in cell junction tissue, response to growth factors and cell population proliferation. Tumor and ECM-receptor interactions related pathways were enriched by the KEGG. MARCKS expression in HCC patients was higher in females, younger individuals, and those at worse clinical stages. Cox regression analysis showed that MARCKS expression was a risk factor for overall survival and disease-specific survival of patients.

Conclusion

MARCKS was up-regulated in HCC, may play a crucial role in HCCs, and has prognostic value for clinical outcomes.

Dysregulation of B7 family and its association with tumor microenvironment in uveal melanoma

Background

Uveal melanoma (UVM) is the most common primary intraocular malignancy in adults with a poor prognosis. B7 family is an important modulator of the immune response. However, its dysregulation and underlying molecular mechanism in UVM still remains unclear.

Methods

Data were derived from TCGA and GEO databases. The prognosis was analyzed by Kaplan-Meier curve. The ESTIMATE algorithm, CIBERSORT algorithm, and TIMER database were used to demonstrate the correlation between B7 family and tumor immune microenvironment in UVM. Single-cell RNA sequencing was used to detect the expression levels of the B7 family in different cell types of UVM. UVM was classified into different types by consistent clustering. Enrichment analysis revealed downstream signaling pathways of the B7 family. The interaction between different cell types was visualized by cell chat.

Results

The expression level of B7 family in UVM was significantly dysregulated and negatively correlated with methylation level. The expression of B7 family was associated with prognosis and immune infiltration, and B7 family plays an important role in the tumor microenvironment (TME). B7 family members were highly expressed in monocytes/macrophages of UVM compared with other cell types. Immune response and visual perception were the main functions affected by B7 family. The result of cell chat showed that the interaction between photoreceptor cells and immune-related cells was mainly generated by HLA-C-CD8A. CABP4, KCNJ10 and RORB had the strongest correlation with HLA-C-CD8A, and their high expression was significantly correlated with poor prognosis. CABP4 and RORB were specifically expressed in photoreceptor cells.

Conclusions

Dysregulation of the B7 family in UVM is associated with poor prognosis and affects the tumor immune microenvironment. CABP4 and RORB can serve as potential therapeutic targets for UVM, which can be regulated by the B7 family to affect the visual perception and immune response function of the eye, thus influencing the prognosis of UVM.

LEDGF is a new growth factor in fetal serum

Fetal serum supports the immortal growth of mammalian cell lines in culture while adult serum leads to the terminal differentiation and death of cells in culture. Many of the proteins in fetal serum that support the indefinite division and growth of cancerous cell lines remain obscure. The peptides and proteins of fetal versus adult serum were analyzed by liquid chromatography, nano electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS). Three batches of fetal serum contained the Alpha Fetoprotein marker while adult serum batches did not. Insulin (INS), and insulin-like growth factor (ILGF), fibroblast growth factor (FGF), epidermal growth factor (EGF) and platelet derived growth factor (PDGF) were increased in fetal serum. New fetal growth factors including MEGF, HDGFRP and PSIP1 and soluble growth receptors such as TNFR, EGFR, NTRK2 and THRA were discovered. Addition of insulin or the homeotic transcription factor PSIP1, also referred to as Lens Epithelium Derived Growth Factor (LEDGF), partially restored the rounded phenotype of rapidly dividing cells but was not as effective as fetal serum. Thus, a new growth factor in fetal serum, LEDGF/PSIP1, was directly observed by tandem mass spectrometry and confirmed by add back experiments to cell culture media alongside insulin.

A 16-gene signature associated with homologous recombination deficiency for prognosis prediction in patients with triple-negative breast cancer

Homologous recombination deficiency (HRD) commonly occurs in breast cancer, which is the second cause of cancer death in women with a high rate of relapse and poor outcomes. Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Thus, we aim to develop a prognostic signature based on HRD expecting to help improve outcomes in TNBC. The Cancer Genome Atlas (TCGA)–TNBC cohort was divided into the training set and the testing set randomly. Sixteen genes were filtered from the prognostic HRD-associated genes to establish a prognostic model in the training set. Patients were divided into high-risk and low-risk groups based on the median value of the risk score. Prognosis analysis showed that the high-risk group was associated with a worse prognosis in the training set, the testing set, the entire TCGA–TNBC cohort, and the METABRIC–TNBC cohort. The time-dependent receiver operating characteristic curve showed that our model had very good accuracy in the prediction of 1–5-year overall survival in the TCGA–TNBC cohort. Besides, a comparison of the area under curve value and C-index between our model and four published models showed that our model had the best predictive efficiency compared to other models. Subsequently, a nomogram was established. Finally, our finding also indicated that our model was associated with immunoregulation in TNBC and had the potential to be the target for TNBC treatment. Therefore, our findings not only provided a new strategy in the personalized prognosis management of TNBC but also offered new insight into precision treatment in TNBC.

Evidence for shared genetic risk factors between lymphangioleiomyomatosis and pulmonary function

Introduction

Lymphangioleiomyomatosis (LAM) is a rare low-grade metastasising disease characterised by cystic lung destruction. The genetic basis of LAM remains incompletely determined, and the disease cell-of-origin is uncertain. We analysed the possibility of a shared genetic basis between LAM and cancer, and LAM and pulmonary function.

Methods

The results of genome-wide association studies of LAM, 17 cancer types and spirometry measures (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC ratio and peak expiratory flow (PEF)) were analysed for genetic correlations, shared genetic variants and causality. Genomic and transcriptomic data were examined, and immunodetection assays were performed to evaluate pleiotropic genes.

Results

There were no significant overall genetic correlations between LAM and cancer, but LAM correlated negatively with FVC and PEF, and a trend in the same direction was observed for FEV1. 22 shared genetic variants were uncovered between LAM and pulmonary function, while seven shared variants were identified between LAM and cancer. The LAM-pulmonary function shared genetics identified four pleiotropic genes previously recognised in LAM single-cell transcriptomes: ADAM12, BNC2, NR2F2 and SP5. We had previously associated NR2F2 variants with LAM, and we identified its functional partner NR3C1 as another pleotropic factor. NR3C1 expression was confirmed in LAM lung lesions. Another candidate pleiotropic factor, CNTN2, was found more abundant in plasma of LAM patients than that of healthy women.

Conclusions

This study suggests the existence of a common genetic aetiology between LAM and pulmonary function.

The Emerging Role of T-Cell Immunoglobulin Mucin-3 in Breast Cancer: A Promising Target For Immunotherapy

Cancer treatment through immune checkpoint receptor blockade has made significant advances in the recent years. However, resistance to the current immune checkpoint inhibitors (ICIs) has been observed in many patients, who consequently do not respond to these treatments. T-cell immunoglobulin mucin-3 (Tim-3) is a novel immune checkpoint molecule emerging as a potential therapeutic target for cancer immunotherapy. Epidemiologic findings reveal that genetic polymorphisms in the Tim-3 gene are associated with increased susceptibility to breast cancer. In patients with breast cancer, Tim-3 is expressed both on immune and tumor cells. Accumulating evidence demonstrates that Tim-3 can notably affect breast cancer treatment outcome and prognosis. Therefore, Tim-3 is being regarded as a high-potential target for improving breast cancer therapy. In this review, we summarize the role of Tim-3 in breast cancer and the regulation mechanisms of Tim-3 to furnish evidences for future research and therapy.

7SK Acts as an Anti-tumor Factor in Tongue Squamous Cell Carcinoma

Increasing evidence has shown the mechanistic insights about non-coding RNA 7SK in controlling the transcription. However, the biological function and mechanism of 7SK in cancer are largely unclear. Here, we show that 7SK is down-regulated in human tongue squamous carcinoma (TSCC) and acts as a TSCC suppressor through multiple cell-based assays including a migration assay and a xenograft mouse model. The expression level of 7SK was negatively correlated with the size of tumors in the 73 in-house collected TSCC patients. Through combined analysis of 7SK knockdown of RNA-Seq and available published 7SK ChIRP-seq data, we identified 27 of 7SK-regulated genes that were involved in tumor regulation and whose upstream regulatory regions were bound by 7SK. Motif analysis showed that the regulatory sequences of these genes were enriched for transcription factors FOXJ3 and THRA, suggesting a potential involvement of FOXJ3 and THRA in 7SK-regulated genes. Interestingly, the augmented level of FOXJ3 in TSCC patients and previous reports on THRA in other cancers have suggested that these two factors may promote TSCC progression. In support of this idea, we found that 21 out of 27 aforementioned 7SK-associated genes were regulated by FOXJ3 and THRA, and 12 of them were oppositely regulated by 7SK and FOXJ3/THRA. We also found that FOXJ3 and THRA dramatically promoted migration in SCC15 cells. Collectively, we identified 7SK as an antitumor factor and suggested a potential involvement of FOXJ3 and THRA in 7SK-mediated TSCC progression.