LINC00536 knockdown inhibits breast cancer cells proliferation, invasion, and migration through regulation of the miR-4282/centromere protein F axis

PSMD14/E2F1 Axis-Mediated CENPF Promotes the Metastasis of Triple-Negative Breast Cancer Through Inhibiting Ferroptosis

The metastasis of triple-negative breast cancer (TNBC) usually contributes to the failure of treatment. Centromere Protein F (CENPF) can induce proliferation and metastasis in TNBC. Nevertheless, the upstream mechanism of CENPF in BC remains unclear. Western blot and RT-qPCR were employed for testing the levels of PSMD14, E2F1, and CENPF, and cell migration was assessed using the Transwell assay. Additionally, the CCK8 assay was applied to investigate cell viability, and C11-BODIPY 581/591 was applied to assess the lipid ROS level. ChIP and dual luciferase assays were used to examine the association between E2F1 and the CENPF promoter. The interaction between PSMD14 and E2F1 was verified using Co-IP. Knockdown of CENPF could significantly inhibit migration and invasion in TNBC cells. In addition, the silencing of CENPF aggravated arachidonic acid metabolism-induced ferroptosis in TNBC cells. Meanwhile, E2F1 knockdown greatly inhibited the expressions of CENPF and attenuated TNBC cell invasion and migration by decreasing its binding with the CENPF promoter. More importantly, PSMD14 could suppress arachidonic acid metabolism-induced ferroptosis in TNBC cells through the E2F1/CENPF axis. The PSMD14/E2F1 axis-mediated CENPF could promote the metastasis of TNBC by inhibiting arachidonic acid metabolism-induced ferroptosis. This research might bring novel insights into discovering methods for alleviating tumor metastasis in TNBC.

New insights of LncRNAs fingerprints in breast cancer progression: Tumorigenesis, drug resistance, and therapeutic opportunities

Breast cancer (BC) is one of the common female cancers and it is characterized by considerable problems regarding its development and therapy. Long non-coding RNAs (lncRNAs) have been identified as significant modulators in BC development, especially, in tumorigenicity and chemoresistance. We therefore endeavor to present an up-to-date understanding of lncRNAs and their impact on BC progression and treatment, concerning molecular processes, treatment options, and use as a therapeutic opportunity. LncRNAs are novel regulators of genes that cause therapeutic resistance and directly impact the functioning of both coding and non-coding genes in BC patients, but little is known about their mechanisms of actions. Thus, additional study is required to have a deeper understanding of their modes of action and possible roles in BC disease. This study aims to investigate the functions of lncRNAs in the development of BC, with particular attention to their role in tumorigenesis, drug resistance mechanisms, and therapeutic targets. This will help to identify novel therapeutic targets and improve the effectiveness of BC treatment.

A machine learning model revealed that exosome small RNAs may participate in the development of breast cancer through the chemokine signaling pathway

BACKGROUND

Exosome small RNAs are believed to be involved in the pathogenesis of cancer, but their role in breast cancer is still unclear. This study utilized machine learning models to screen for key exosome small RNAs and analyzed and validated them.

METHOD

Peripheral blood samples from breast cancer screening positive and negative people were used for small RNA sequencing of plasma exosomes. The differences in the expression of small RNAs between the two groups were compared. We used machine learning algorithms to analyze small RNAs with significant differences between the two groups, fit the model through training sets, and optimize the model through testing sets. We recruited new research subjects as validation samples and used PCR-based quantitative detection to validate the key small RNAs screened by the machine learning model. Finally, target gene prediction and functional enrichment analysis were performed on these key RNAs.

RESULTS

The machine learning model incorporates six small RNAs: piR-36,340, piR-33,161, miR-484, miR-548ah-5p, miR-4282, and miR-6853-3p. The area under the ROC curve (AUC) of the machine learning model in the training set was 0.985 (95% CI = 0.948-1), while the AUC in the test set was 0.972 (95% CI = 0.882-0.995). RT-qPCR was used to detect the expression levels of these key small RNAs in the validation samples, and the results revealed that their expression levels were significantly different between the two groups (P < 0.05). Through target gene prediction and functional enrichment analysis, it was found that the functions of the target genes were enriched mainly in the chemokine signaling pathway.

CONCLUSION

The combination of six plasma exosome small RNAs has good prognostic value for women with positive breast cancer by imaging screening. The chemokine signaling pathway may be involved in the early stage of breast cancer. It is worth further exploring whether small RNAs mediate chemokine signaling pathways in the pathogenesis of breast cancer through the delivery of exosomes.

Effects of Differentially Methylated CpG Sites in Enhancer and Promoter Regions on the Chromatin Structures of Target LncRNAs in Breast Cancer

Aberrant DNA methylation plays a crucial role in breast cancer progression by regulating gene expression. However, the regulatory pattern of DNA methylation in long noncoding RNAs (lncRNAs) for breast cancer remains unclear. In this study, we integrated gene expression, DNA methylation, and clinical data from breast cancer patients included in The Cancer Genome Atlas (TCGA) database. We examined DNA methylation distribution across various lncRNA categories, revealing distinct methylation characteristics. Through genome-wide correlation analysis, we identified the CpG sites located in lncRNAs and the distally associated CpG sites of lncRNAs. Functional genome enrichment analysis, conducted through the integration of ENCODE ChIP-seq data, revealed that differentially methylated CpG sites (DMCs) in lncRNAs were mostly located in promoter regions, while distally associated DMCs primarily acted on enhancer regions. By integrating Hi-C data, we found that DMCs in enhancer and promoter regions were closely associated with the changes in three-dimensional chromatin structures by affecting the formation of enhancer-promoter loops. Furthermore, through Cox regression analysis and three machine learning models, we identified 11 key methylation-driven lncRNAs (DIO3OS, ELOVL2-AS1, MIAT, LINC00536, C9orf163, AC105398.1, LINC02178, MILIP, HID1-AS1, KCNH1-IT1, and TMEM220-AS1) that were associated with the survival of breast cancer patients and constructed a prognostic risk scoring model, which demonstrated strong prognostic performance. These findings enhance our understanding of DNA methylation's role in lncRNA regulation in breast cancer and provide potential biomarkers for diagnosis.

The Effect of Race/Ethnicity and MED12 Mutation on the Expression of Long Non-Coding RNAs in Uterine Leiomyoma and Myometrium

The objective of this study was to elucidate the expression of long non-coding RNA (lncRNA) in leiomyomas (Lyo) and paired myometrium (Myo) and explore the impact of race and MED12 mutation. Fold change analysis (Lyo/paired Myo) indicated the expression of 63 lncRNAs was significantly altered in the mutated group but not in the non-mutated Lyo. Additionally, 65 lncRNAs exhibited an over 1.5-fold change in the Black but not the White group. Fifteen differentially expressed lncRNAs identified with next-generation sequencing underwent qRT-PCR confirmation. Compared with Myo, the expression of TPTEP1, PART1, RPS10P7, MSC-AS1, SNHG12, CA3-AS1, LINC00337, LINC00536, LINC01436, LINC01449, LINC02433, and LINC02624 was significantly higher, while the expression of ZEB2-AS1, LINC00957, and LINC01186 was significantly lower. Comparison of normal Myo with diseased Myo showed significant differences in the expression of several lncRNAs. Analysis based on race and Lyo MED12 mutation status indicated a significantly higher expression of RPS10P7, SNHG12, LINC01449, LINC02433, and LINC02624 in Lyo from Black patients. The expression of TPTEP1, PART1, RPS10P7, MSC-AS1, LINC00337, LINC00536, LINC01436, LINC01449, LINC02433, and LINC02624 was higher, while LINC01186 was significantly lower in the MED12-mutated group. These results indicate that Lyo are characterized by aberrant lncRNA expression, which is further impacted by race and Lyo MED12 mutation status.