Integrated Bioinformatic Analysis of the Expression and Prognosis of Caveolae-Related Genes in Human Breast Cancer

Identification of the role of MED6 in the development and prognosis of lung adenocarcinoma based on multi-omics profiling

Background: Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Recent studies have highlighted the importance of Mediator complex subunits in cancer, but their specific roles in LUAD are still unclear. Methods: The CRISPR-Cas9 loss-of-function data was used to assess gene dependency in cell growth. RNA-seq data were analyzed to evaluate the prognostic value of Mediator subunits and explore their downstream pathways. Single-cell sequencing data were utilized to examine the tumor microenvironment in LUAD. A drug sensitivity analysis was performed to identify potential therapeutic options. Results: Mediator complex subunit 6 (MED6) was found to influence tumor cell growth in LUAD. Additionally, MED6 expression levels were associated with patient prognosis. MED6-positive tumor cells showed more active interactions with other cells in the LUAD microenvironment, promoting tumor progression. Based on MED6 expression, drugs such as paclitaxel, afatinib, and brivanib were identified as potential treatments. Conclusions: This study revealed the role of MED6 in LUAD and its potential as a biomarker. Our findings suggest that MED6 has an effect on LUAD progression and provide valuable insights for patient stratification and personalized treatment strategies.

Unveiling the prognostic value of ARID3A in breast cancer through bioinformatic analysis

Objective

Identifying reliable prognostic markers for breast cancer is crucial for improving survival rates and reducing mortality. Recent studies highlight the AT-rich interactive domain-containing protein (ARID) family, particularly ARID3A, as influential in cancer progression, though its specific role in breast cancer remains unclear. This study investigates ARID3A's expression, prognostic relevance, clinicopathological correlations, co-expression profiles, and protein-protein interactions in breast cancer.

Methods

ARID3A mRNA and protein expression levels were analyzed using UALCAN, GEPIA databases, and immunohistochemistry from our hospital samples. Clinical prognostic parameters and survival data were examined through bioinformatics tools, including GEPIA, Bc-GenExMiner, and BEST. Subtype-specific expression and co-expression, particularly with REXO1, were evaluated using LinkedOmics, TIMER, and bc-GenExMiner. Functional enrichment analysis was conducted via LinkedOmics. Protein-protein interactions (PPI) were established using GeneMANIA and STRING, with validation through molecular docking using Cluspro.

Results

Elevated ARID3A expression was associated with poor prognosis in breast cancer, particularly in Luminal and HER2-positive subtypes. A positive correlation with REXO1 was identified, and enrichment analysis emphasized ARID3A's involvement in immune-related pathways, such as "interferon gamma production" and "primary immunodeficiency." PPI network and docking studies identified TP53 as a potential binding partner, suggesting a novel interaction influencing tumor progression.

Conclusion

These findings indicate that ARID3A may serve as a prognostic biomarker and therapeutic target in breast cancer, providing insights into its involvement in oncogenic pathways and interactions, particularly with TP53, that may drive cancer development and progression.

Propofol reduces breast cancer cell stemness via FOXO3/SOX2 axis

Objective: Propofol is a common intravenous anesthetic in cancer resection surgery, which is considered to exhibit anti-tumor effect in various cancer types. This study was aimed at investigating the role and mechanism of propofol in breast cancer stemness and proliferation. Methods: The breast cancer cells with propofol treatment were sequenced. The expression of FOXO3 in propofol treated cells was detected by RT-qPCR and Western blot. The CSC properties were analyzed by screen cells with ESA+CD44+CD24-/low through flow cytometry and the proliferation capacity were also detected. The expression correlation of FOXO3 and target genes were detected by western blot. The potential binding site of FOXO3 on SOX2 was predicted by JASPAR and verified by dual-luciferase reporter assay and ChIP assay. Results: FOXO3 was found to be upregulated in propofol 24h-treated cells. Propofol could inhibit the capacity of breast cancer cell stemness and proliferation by upregulation FOXO3, which inhibited SOX2 expression transcriptionally. Conclusion: In this study, we uncovered the role of propofol-FOXO3-SOX2 in breast cancer cell stemness and proliferation, which might serve as potential targets for breast cancer therapy.

Integration of CRISPR/dCas9-Based methylation editing with guide positioning sequencing identifies dynamic changes of mrDEGs in breast cancer progression

Dynamic changes in DNA methylation are prevalent during the progression of breast cancer. However, critical alterations in aberrant methylation and gene expression patterns have not been thoroughly characterized. Here, we utilized guide positioning sequencing (GPS) to conduct whole-genome DNA methylation analysis in a unique human breast cancer progression model: MCF10 series of cell lines (representing benign/normal, atypical hyperplasia, and metastatic carcinoma). By integrating with mRNA-seq and matched clinical expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), six representative methylation-related differentially expressed genes (mrDEGs) were identified, including CAVIN2, ARL4D, DUSP1, TENT5B, P3H2, and MMP28. To validate our findings, we independently developed and optimized the dCas9-DNMT3L-DNMT3A system, achieving a high efficiency with a 98% increase in methylation at specific sites. DNA methylation levels significantly increased for the six genes, with CAVIN2 at 67.75 ± 1.05%, ARL4D at 53.29 ± 6.32%, DUSP1 at 57.63 ± 8.46%, TENT5B at 44.00 ± 5.09%, P3H2 at 58.50 ± 3.90%, and MMP28 at 49.60 ± 5.84%. RT-qPCR confirmed an inverse correlation between increased DNA methylation and gene expression. Most importantly, we mimicked tumor progression in vitro, demonstrating that transcriptional silencing of the TENT5B promotes cell proliferation in MCF10A cells owing to the crosstalk between hypermethylation and histone deacetylation. This study unveils the practical implications of DNA methylation dynamics of mrDEGs in reshaping epigenomic features during breast cancer malignant progression through integrated data analysis of the methylome and transcriptome. The application of the CRISPR/dCas9-based methylation editing technique elucidates the regulatory mechanisms and functional roles of individual genes within the DNA methylation signature, providing valuable insights for understanding breast cancer pathogenesis and facilitating potential therapeutic approaches in epigenome editing for patients with breast cancer.

The Clinical Prediction Value of the Ubiquitination Model Reflecting the Microenvironment Infiltration and Drug Sensitivity in Breast Cancer

The ubiquitin-proteasome system influences cancer progression through multiple mechanisms. Due to the extensive proteasomal modifications observed in cancer tissues, ubiquitination is closely related to various biological functions with cancer. However, the roles of ubiquitin-related genes (UbRGs) in breast cancer (BC) have not been thoroughly investigated. In this study, we retrieved 763 reliable UbRGs and identified a potential prognostic signature for breast cancer patients. Additionally, we analyzed eight overall survival-associated UbRGs using univariate Cox proportional hazard regression in the Cancer Genome Atlas (TCGA) database. Subsequently, we used Lasso-Cox risk regression analysis to generate prognostic characteristics of UbRGs associated with overall survival (OS), validated in an external cohort (GSE158309). Next, we compared differences in tumor microenvironment and drug sensitivity between subgroups, describing the potential impact of UbRGs on the landscape of the tumor immune microenvironment and their predictive significance for therapeutic resistance to different strategies. Furthermore, a nomogram model containing eight genes, histology, subtype, T status, N status, and the American Joint Committee on Cancer (AJCC) stage was constructed. Finally, in vitro and in vivo experiments validated the effects of FBXL6 and PDZRN3 on breast cancer development. In conclusion, we demonstrate that ubiquitin-related genes are closely associated with breast cancer prognosis, immune environment, and drug sensitivity. Our results offer a new insight into breast cancer treatment.

Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical data

Objective

Classification tasks are an open challenge in the field of biomedicine. While several machine-learning techniques exist to accomplish this objective, several peculiarities associated with biomedical data, especially when it comes to omics measurements, prevent their use or good performance achievements. Omics approaches aim to understand a complex biological system through systematic analysis of its content at the molecular level. On the other hand, omics data are heterogeneous, sparse and affected by the classical "curse of dimensionality" problem, i.e. having much fewer observation, samples (n) than omics features (p). Furthermore, a major problem with multi-omics data is the imbalance either at the class or feature level. The objective of this work is to study whether feature extraction and/or feature selection techniques can improve the performances of classification machine-learning algorithms on omics measurements.

Methods

Among all omics, metabolomics has emerged as a powerful tool in cancer research, facilitating a deeper understanding of the complex metabolic landscape associated with tumorigenesis and tumor progression. Thus, we selected three publicly available metabolomics datasets, and we applied several feature extraction techniques both linear and non-linear, coupled or not with feature selection methods, and evaluated the performances regarding patient classification in the different configurations for the three datasets.

Results

We provide general workflow and guidelines on when to use those techniques depending on the characteristics of the data available. To further test the extension of our approach to other omics data, we have included a transcriptomics and a proteomics data. Overall, for all datasets, we showed that applying supervised feature selection improves the performances of feature extraction methods for classification purposes. Scripts used to perform all analyses are available at: https://github.com/Plant-Net/Metabolomic_project/.

Expression Profiles of Dopamine-Related Genes and miRNAs Regulating Their Expression in Breast Cancer

This study aimed to assess the expression profile of messenger RNA (mRNA) and microRNA (miRNA) related to the dopaminergic system in five types of breast cancer in Polish women. Patients with five breast cancer subtypes were included in the study: luminal A (n = 130), luminal B (n = 196, including HER2-, n = 100; HER2+, n = 96), HER2+ (n = 36), and TNBC (n = 43); they underwent surgery, during which tumor tissue was removed along with a margin of healthy tissue (control material). The molecular analysis included a microarray profile of mRNAs and miRNAs associated with the dopaminergic system, a real-time polymerase chain reaction preceded by reverse transcription for selected genes, and determinations of their concentration using enzyme-linked immunosorbent assay (ELISA). The conducted statistical analysis showed that five mRNAs statistically significantly differentiated breast cancer sections regardless of subtype compared to control samples; these were dopamine receptor 2 (DRD2), dopamine receptor 3 (DRD3), dopamine receptor 25 (DRD5), transforming growth factor beta 2 (TGF-β-2), and caveolin 2 (CAV2). The predicted analysis showed that hsa-miR-141-3p can regulate the expression of DRD2 and TGF-β-2, whereas hsa-miR-4441 is potentially engaged in the expression regulation of DRD3 and DRD5. In addition, the expression pattern of DRD5 mRNA can also be regulated by has-miR-16-5p. The overexpression of DRD2 and DRD3, with concomitant silencing of DRD5 expression, confirms the presence of dopaminergic abnormalities in breast cancer patients. Moreover, these abnormalities may be the result of miR-141-3P, miR-16-5p, and miR-4441 activity, regulating proliferation or metastasis.

A mechanosensitive caveolae-invadosome interplay drives matrix remodelling for cancer cell invasion

Invadosomes and caveolae are mechanosensitive structures that are implicated in metastasis. Here, we describe a unique juxtaposition of caveola clusters and matrix degradative invadosomes at contact sites between the plasma membrane of cancer cells and constricting fibrils both in 2D and 3D type I collagen matrix environments. Preferential association between caveolae and straight segments of the fibrils, and between invadosomes and bent segments of the fibrils, was observed along with matrix remodelling. Caveola recruitment precedes and is required for invadosome formation and activity. Reciprocally, invadosome disruption results in the accumulation of fibril-associated caveolae. Moreover, caveolae and the collagen receptor β1 integrin co-localize at contact sites with the fibrils, and integrins control caveola recruitment to fibrils. In turn, caveolae mediate the clearance of β1 integrin and collagen uptake in an invadosome-dependent and collagen-cleavage-dependent mechanism. Our data reveal a reciprocal interplay between caveolae and invadosomes that coordinates adhesion to and proteolytic remodelling of confining fibrils to support tumour cell dissemination.

Amelioration of Cholesterol Rich diet-induced Impaired Cognition in AD Transgenic Mice by an LXR Agonist TO901317 Is Associated with the Activation of the LXR-β-RXR-α-ABCA1 Transmembrane Transport System and Improving the Composition of Lipid Raft

BACKGROUND

It has been reported that LXR agonist can inhibit Aβ generation and alleviate Aβ-induced various adverse reactions in vivo and in vitro experiments, but the mechanisms have not been clarified. The study aimed to observe the effect of LXR agonist TO901317 on the cognitive function of AD transgenic mice fed with cholesterol-rich diet (CRD), and to explore the possible mechanism. Methods: 32 male 6-month-old double transgenic AD mice were enrolled and randomly divided into 4 groups: control (normal diet) group, CRD treatment group, TO901317 treatment group and GSK2033 treatment group. After 3 month, Morris water maze was for the changes of spatial exploration and memory ability; ELISA was for detecting the production of Aβ42 in the brain; the concentration of total cholesterol (TC), low density lipoprotein (LDL) and high density lipoprotein (HDL) in serum were detected by cholesterol enzyme colorimetry; Finally, the expression of LXR-β, RXR-α, ABCA1, caveolin-1, BACE1 and APP at protein level in the brains was measured by Western blotting.

RESULTS

Compared with the control group, the learning, memory ability and spatial exploration ability of the mice were more significantly serious in the CRD group (P<0.05); The contents of TC and LDL in the serum and the production of Aβ42 in the brains were significantly increased (P<0.05), but HDL was remarkably decreased (P<0.05); The protein levels of LXR-β, RXR-α and ABCA1 were also significantly decreased (P<0.05); The expression of caveolin-1, APP and BACE1 were evidently increased (P<0.05). However, after treatment with TO901317, the impaired learning and memory and spatial exploration ability of the mice were significantly improved (P<0.05); The contents of TC and LDL in serum and the production of Aβ42 in the brains were significantly decreased (P<0.05), but HLD was increased (P<0.05); The protein levels of LXR-β, RXR-α, ABCA1were all significantly increased (P<0.05), while, the expression of caveolin-1, APP and BACE1 were all significantly decreased (P<0.05). All the changes were reversed by GSK2033 (P<0.05).

CONCLUSIONS

TO901317 attenuated the more serious impairment of spatial exploration, learning and memory in transgenic AD mice induced by CRD, and the mechanism may be that TO901317 could activate the LXR-β/RXR-α/ABCA1 transmembrane transport system, promote the cholesterol efflux, and decreased caveolin-1, APP and BACE1, further reduce Aβ42 in the brains.