Co-expression effect of LLGL2 and SLC7A5 to predict prognosis in ERα-positive breast cancer

A prismatic view of the epigenetic-metabolic regulatory axis in breast cancer therapy resistance

Epigenetic regulation established during development to maintain patterns of transcriptional expression and silencing for metabolism and other fundamental cell processes can be reprogrammed in cancer, providing a molecular mechanism for persistent alterations in phenotype. Metabolic deregulation and reprogramming are thus an emerging hallmark of cancer with opportunities for molecular classification as a critical preliminary step for precision therapeutic intervention. Yet, acquisition of therapy resistance against most conventional treatment regimens coupled with tumor relapse, continue to pose unsolved problems for precision healthcare, as exemplified in breast cancer where existing data informs both cancer genotype and phenotype. Furthermore, epigenetic reprograming of the metabolic milieu of cancer cells is among the most crucial determinants of therapeutic resistance and cancer relapse. Importantly, subtype-specific epigenetic-metabolic interplay profoundly affects malignant transformation, resistance to chemotherapy, and response to targeted therapies. In this review, we therefore prismatically dissect interconnected epigenetic and metabolic regulatory pathways and then integrate them into an observable cancer metabolism-therapy-resistance axis that may inform clinical intervention. Optimally coupling genome-wide analysis with an understanding of metabolic elements, epigenetic reprogramming, and their integration by metabolic profiling may decode missing molecular mechanisms at the level of individual tumors. The proposed approach of linking metabolic biochemistry back to genotype, epigenetics, and phenotype for specific tumors and their microenvironment may thus enable successful mechanistic targeting of epigenetic modifiers and oncometabolites despite tumor metabolic heterogeneity.

Fat mass and obesity-associated protein (FTO) mediated m6A modification of circFAM192A promoted gastric cancer proliferation by suppressing SLC7A5 decay

Gastric cancer (GC) is a common malignant tumor worldwide, especially in East Asia, with high incidence and mortality rate. Epigenetic modifications have been reported to participate in the progression of gastric cancer, among which m6A is the most abundant and important chemical modification in RNAs. Fat mass and obesity-associated protein (FTO) is the first identified RNA demethylase but little is known about its role in gastric cancer. In our study, data from TCGA and clinical samples showed that FTO was highly expressed in gastric cancer tissues. Kaplan-Meier plotter suggested that patients with the high level of FTO had a poor prognosis. In vitro and in vivo experiments confirmed the role of FTO in promoting gastric cancer cell proliferation. Mechanistically, we found that FTO bound to circFAM192A at the specific site and removed the m6A modification in circFAM192A, protecting it from degradation. CircFAM192A subsequently interacted with the leucine transporter solute carrier family 7 member 5 (SLC7A5) and enhancing its stability. As a result, an increased amount of SLC7A5 was on the membrane, which facilitated leucine uptake and activated the mTOR signaling pathway. Therefore, our study demonstrated that FTO promoted gastric cancer proliferation through the circFAM192A/SLC7A5 axis in the m6A-dependent manner. Our study shed new light on the role of FTO in gastric cancer progression.

Cell polarity changes in cancer initiation and progression

Cell polarity, which consists of the morphological, structural, and functional organization of cells along a defined axis, is a feature of healthy cells and tissues. In contrast, abnormal polarity is a hallmark of cancer cells. At the molecular level, key evolutionarily conserved proteins that control polarity establishment and maintenance in various contexts are frequently altered in cancer, but the relevance of these molecular alterations in the oncogenic processes is not always clear. Here, we summarize the recent findings, shedding new light on the involvement of polarity players in cancer development, and discuss the possibility of harnessing cell polarity changes to better predict, diagnose, and cure cancers.

Establishment of a lysosome-related prognostic signature in breast cancer to predict immune infiltration and therapy response

Background

Lysosomes are instrumental in intracellular degradation and recycling, with their functional alterations holding significance in tumor growth. Nevertheless, the precise role of lysosome-related genes (LRGs) in breast cancer (BC) remains elucidated. This study aimed to establish a prognostic model for BC based on LRGs.

Methods

Employing The Cancer Genome Atlas (TCGA) BC cohort as a training dataset, this study identified differentially expressed lysosome-related genes (DLRGs) through intersecting LRGs with differential expression genes (DEGs) between tumor and normal samples. A prognostic model of BC was subsequently developed using Cox regression analysis and validated within two Gene Expression Omnibus (GEO) external validation sets. Further analyses explored functional pathways, the immune microenvironment, immunotherapeutic responses, and sensitivity to chemotherapeutic drugs in different risk groups. Additionally, the mRNA and protein expression levels of genes within the risk model were examined by utilizing the Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases. Clinical tissue specimens obtained from patients were gathered to validate the expression of the model genes via Real-Time Polymerase Chain Reaction (RT-PCR).

Results

We developed a risk model of BC based on five specific genes (ATP6AP1, SLC7A5, EPDR1, SDC1, and PIGR). The model was validated for overall survival (OS) in two GEO validation sets (p=0.00034 for GSE20685 and p=0.0095 for GSE58812). In addition, the nomogram incorporating clinical factors showed better predictive performance. Compared to the low-risk group, the high-risk group had a higher level of certain immune cell infiltration, including regulatory T cells (Tregs) and type 2 T helper cells (Th2). The high-risk patients appeared to respond less well to general immunotherapy and chemotherapeutic drugs, according to the Tumor Immune Dysfunction and Exclusion (TIDE), Immunophenotype Score (IPS), and drug sensitivity scores. The RT-PCR results validated the expression trends of some prognostic-related genes in agreement with the previous differential expression analysis.

Conclusion

Our innovative lysosome-associated signature can predict the prognosis for BC patients, offering insights for guiding subsequent immunotherapeutic and chemotherapeutic interventions. Furthermore, it has the potential to provide a scientific foundation for identifying prospective therapeutic targets.

Analysis of a new therapeutic target and construction of a prognostic model for breast cancer based on ferroptosis genes

Breast cancer, which is the most common malignant tumor among women worldwide and an important cause of death in women. The existing prognostic model for patients with breast cancer is not accurate as breast cancer is resistant to commonly used antitumor drugs. Ferroptosis is a novel mechanism of programmed cell death that depends on iron accumulation and lipid peroxidation. Various studies have confirmed the role of ferroptosis in tumor regulation and ferroptosis is now considered to play an important role in breast cancer development. At present, the association between breast cancer prognosis and ferroptosis-related gene expression remains unclear. Further exploration of this research area may optimize the evaluation and prediction of prognosis of patients with breast cancer and finding of new therapeutic targets. In this study, clinical factors and the expression of multiple genes were evaluated in breast cancer samples from the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database database. Eleven prognostication-related genes (TP63, IFNG, MT3, ANO6, FLT3, PTGS2, SLC1A4, JUN, SLC7A5, CHAC1, and TF) were identified from differentially expressed genes to construct a survival prediction model, which showed a good prediction ability. KEGG pathway analysis revealed that immune-related pathways were the primary pathways. ssGSEA analysis showed significant differences in the distribution of certain immune-related cell subsets, such as CD8+T cells and B cells, and in the expression of multiple immune genes, including type II IFN response and APC coinhibition. In addition, 10 immune targets related to ferroptosis in breast cancer were found: CD276, CD80, HHLA2, LILRA2, NCR3LG1, NECTIN3, PVR, SLAMF9,TNFSF4, and BTN1A1. Using TCGA, new ferroptosis genes related to breast cancer prognosis were identified, a new reliable and accurate prognosis model was developed, and 10 new potential therapeutic targets different from the traditional targeted drugs were identified to provide a reference for improving the poor prognosis of patients with breast cancer.

Comparative Analysis of Transcriptomic Changes including mRNA and microRNA Expression Induced by the Xenoestrogens Zearalenone and Bisphenol A in Human Ovarian Cells

Xenoestrogens are natural or synthetic compounds that mimic the effect of endogenous estrogens and might cause cancer. We aimed to compare the global transcriptomic response to zearalenone (ZEA; mycotoxin) and bisphenol A (BPA; plastic additive) with the effect of physiological estradiol (E2) in the PEO1 human ovarian cell line by mRNA and microRNA sequencing. Estrogen exposure induced remarkable transcriptomic changes: 308, 288 and 63 genes were upregulated (log₂FC > 1); 292, 260 and 45 genes were downregulated (log₂FC < -1) in response to E2 (10 nM), ZEA (10 nM) and BPA (100 nM), respectively. Furthermore, the expression of 13, 11 and 10 miRNAs changed significantly (log₂FC > 1, or log₂FC < -1) after exposure to E2, ZEA and BPA, respectively. Functional enrichment analysis of the significantly differentially expressed genes and miRNAs revealed several pathways related to the regulation of cell proliferation and migration. The effect of E2 and ZEA was highly comparable: 407 genes were coregulated by these molecules. We could identify 83 genes that were regulated by all three treatments that might have a significant role in the estrogen response of ovarian cells. Furthermore, the downregulation of several miRNAs (miR-501-5p, let-7a-2-3p, miR-26a-2-3p, miR-197-5p and miR-582-3p) was confirmed by qPCR, which might support the proliferative effect of estrogens in ovarian cells.