Determinants of breast cancer progression

Atorvastatin lowers breast cancer risk by reversing an early tumorigenic signature

Breast cancer remains a significant health challenge with complex molecular mechanisms. While many studies have explored genetic markers in breast carcinogenesis, few have studied the potential impact of pharmacological interventions such as Atorvastatin on its genetic landscape. This study aimed to elucidate the molecular distinctions between normal and tumor-adjacent tissues in breast cancer and to investigate the potential protective role of atorvastatin, primarily known for its lipid-lowering effects, against breast cancer. Searching the Gene Expression Omnibus database identified two datasets, GSE9574 and GSE20437, comparing normal breast tissues with tumor-adjacent samples, which were merged, and one dataset, GSE63427, comparing paired pre- and post-treated patients with atorvastatin. Post-ComBat application showed merged datasets' consistency, revealing 116 DEGs between normal and tumor-adjacent tissues. Although initial GSE63427 data analysis suggested a minimal impact of atorvastatin, 105 DEGs post-treatment were discovered. Thirteen genes emerged as key players, both affected by Atorvastatin and dysregulated in tumor-adjacent tissues. Pathway analysis spotlighted the significance of these genes in processes like inflammation, oxidative stress, apoptosis, and cell cycle control. Moreover, there was a noticeable interaction between these genes and the immunological microenvironment in tumor-adjacent tissues, with Atorvastatin potentially altering the suppressive immune landscape to favor anti-tumor immunity. Survival analysis further highlighted the prognostic potential of the 13-gene panel, with 12 genes associated with improved survival outcomes. The 13-gene signature offers promising insights into breast cancer's molecular mechanisms and atorvastatin's potential therapeutic role. The preliminary findings advocate for an in-depth exploration of atorvastatin's impact on.

Long noncoding RNA SNHG1 promotes breast cancer progression by regulating the miR-641/RRS1 axis

An increasing number of studies have indicated the crucial involvement of long non-coding RNAs (lncRNAs) in the onset and progression of malignancies. However, a complete understanding of the molecular mechanism underlying the effect of abnormally expressed lncRNAs on breast cancer (BC) remains elusive. This study aimed to elucidate the influence of the lncRNA small nucleolar RNA host gene 1 (SNHG1) on BC progression and its underlying mechanism. Our findings revealed a conspicuous up-regulation of SNHG1 in both BC tissues and cells. The downregulation of SNHG1 was observed to inhibit BC cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) processes, while simultaneously promoting apoptosis. Furthermore, dual-luciferase reporter gene and RNA pull-down assays established that SNHG1 targeted miR-641 expression, while miR-641 targeted RRS1. Rescue studies demonstrated that in vitro SNHG1 silencing could be reversed by the miR-641 inhibitor, as well as by RRS1 upregulation. Moreover, in vivo downregulation of SNHG1 was found to inhibit BC growth. Through the inhibition of the miR-641 level, SNHG1 elevated the level of the downstream target RRS1, thereby fostering BC growth, migration, and invasion while inhibiting apoptosis. These findings suggest that SNHG1 may represent a potential therapeutic target for BC treatment.

CMTM7 inhibits breast cancer progression by regulating Wnt/β-catenin signaling

BACKGROUND

Breast cancer is the major cause of death in females globally. Chemokine-like factor like MARVEL transmembrane domain containing 7 (CMTM7) is reported as a tumor suppressor and is involved in epidermal growth factor receptor degradation and PI3K/AKT signaling in previous studies. However, other molecular mechanisms of CMTM7 remain unclear.

METHODS

The expression level of CMTM7 in breast cancer cells and tissues was detected by qRT-PCR and western blot, and the methylation of CMTM7 promoter was detected by BSP sequencing. The effect of CMTM7 was verified both in vitro and in vivo, including MTT, colony formation, EdU assay, transwell assay and wound healing assay. The interaction between CMTM7 and CTNNA1 was investigated by co-IP assay. The regulation of miR-182-5p on CMTM7 and TCF3 on miR-182-5p was detected by luciferase reporter assay and ChIP analysis.

RESULTS

This study detected the hypermethylation levels of the CMTM7 promoter region in breast cancer tissues and cell lines. CMTM7 was performed as a tumor suppressor both in vitro and in vivo. Furthermore, CMTM7 was a direct miR-182-5p target. Besides, we found that CMTM7 could interact with Catenin Alpha 1 (CTNNA1) and regulate Wnt/β-catenin signaling. Finally, transcription factor 3 (TCF3) can regulate miR-182-5p. We identified a feedback loop with the composition of miR-182-5p, CMTM7, CTNNA1, CTNNB1 (β-catenin), and TCF3, which play essential roles in breast cancer progression.

CONCLUSION

These findings reveal the emerging character of CMTM7 in Wnt/β-catenin signaling and bring new sights of gene interaction. CMTM7 and other elements in the feedback loop may serve as emerging targets for breast cancer therapy.

Prediction of potential miRNA-disease associations based on stacked autoencoder

In recent years, increasing biological experiments and scientific studies have demonstrated that microRNA (miRNA) plays an important role in the development of human complex diseases. Therefore, discovering miRNA-disease associations can contribute to accurate diagnosis and effective treatment of diseases. Identifying miRNA-disease associations through computational methods based on biological data has been proven to be low-cost and high-efficiency. In this study, we proposed a computational model named Stacked Autoencoder for potential MiRNA-Disease Association prediction (SAEMDA). In SAEMDA, all the miRNA-disease samples were used to pretrain a Stacked Autoencoder (SAE) in an unsupervised manner. Then, the positive samples and the same number of selected negative samples were utilized to fine-tune SAE in a supervised manner after adding an output layer with softmax classifier to the SAE. SAEMDA can make full use of the feature information of all unlabeled miRNA-disease pairs. Therefore, SAEMDA is suitable for our dataset containing small labeled samples and large unlabeled samples. As a result, SAEMDA achieved AUCs of 0.9210 and 0.8343 in global and local leave-one-out cross validation. Besides, SAEMDA obtained an average AUC and standard deviation of 0.9102 ± /-0.0029 in 100 times of 5-fold cross validation. These results were better than those of previous models. Moreover, we carried out three case studies to further demonstrate the predictive accuracy of SAEMDA. As a result, 82% (breast neoplasms), 100% (lung neoplasms) and 90% (esophageal neoplasms) of the top 50 predicted miRNAs were verified by databases. Thus, SAEMDA could be a useful and reliable model to predict potential miRNA-disease associations.

Hypoxia-induced lncRNA RBM5-AS1 promotes tumorigenesis via activating Wnt/β-catenin signaling in breast cancer

Breast cancer is the most common malignancy among women across the globe. Recent studies have revealed that many long non-coding RNAs (lncRNAs) regulate the Wnt/β-catenin signaling pathway in several types of cancer. Hyperactivation of the Wnt/β-catenin pathway has been extensively presented in breast cancer and is involved in breast cancer progression. However, the underlying molecular mechanism remains elusive. In the current study, we found lncRNA RBM5-AS1 was remarkably upregulated in breast cancer cells and tissues. Overexpression of RBM5-AS1 facilitated proliferation, migration, invasion, EMT, and stemness maintenance of breast cancer cells in vitro and in vivo. Mechanism studies suggested that RBM5-AS1 could be transcriptionally activated by hypoxia-induced RUNX2. Upregulated RBM5-AS1 further activated the Wnt/β-catenin signaling by preventing β-catenin degradation and by helping organize β-catenin-TCF4 transcriptional complex. These findings suggested that RBM5-AS1, a regulator of Wnt/β-catenin signaling, plays a vital role in breast cancer initiation and progression, implicating its potential as a new target for breast cancer treatment.