The lncRNA PVT1 promotes invasive growth of lung adenocarcinoma cells by targeting miR-378c to regulate SLC2A1 expression

Emerging insights: miRNA modulation of ferroptosis pathways in lung cancer

The newly discovered programmed iron-dependent necrosis, ferroptosis, is a novel pathway that is controlled by iron-dependent lipid peroxidation and cellular redox changes. It can be triggered intrinsically by low antioxidant enzyme activity or extrinsically by blocking amino acid transporters or activating iron transporters. The induction of ferroptosis involves the activation of specific proteins, suppression of transporters, and increased endoplasmic reticulum (ER) stress (a condition in which the ER, a crucial organelle involved in protein folding and processing, becomes overwhelmed by an accumulation of misfolded or unfolded proteins. This situation disrupts the normal functioning of the ER, leading to a cellular stress response known as the unfolded protein response), leading to lipid peroxidation byproduct accumulation and toxic reactive oxygen species (ROS), which are highly reactive molecules derived from diatomic oxygen and include various forms such as superoxide (O₂⁻), hydroxyl radicals (•OH), and hydrogen peroxide (H₂O₂). Ferroptosis is closely associated with signaling molecules in lung cancer, including epidermal growth factor receptor (EGFR), mitogen-activated protein kinase (MAPK), hypoxia-inducible factor 1-alpha (HIF-1α), and P53, and is regulated by epigenetic factors such as microRNAs (miRNAs). miRNAs are small non-coding RNA molecules that regulate gene expression by binding to target messenger RNAs (mRNAs), leading to translational repression or degradation. Several miRNAs have been found to modulate ferroptosis by targeting key genes involved in iron metabolism, lipid peroxidation, and antioxidant defense pathways. The research on ferroptosis has expanded to target its role in lung cancer treatment and resistance prevention. This review encapsulates the significance of ferroptosis in lung cancer. Understanding the mechanisms and implications of ferroptosis in lung cancer cells may lead to targeted therapies exploiting cancer cell vulnerabilities to ferroptosis Also, improving treatment outcomes, and overcoming resistance.

A Novel ceRNET Relying on the lncRNA JPX, miR-378a-3p, and Its mRNA Targets in Lung Cancer

Lung cancer is the leading cause of cancer-related death worldwide. Non-coding RNAs are emerging as critical players for the onset and progression of cancer. Analyses of three different datasets revealed that the lncRNA JPX was overexpressed in adenocarcinoma tissues in comparison to normal lungs, as expected for an oncogene. Intriguingly, the predicted binding miR-378a-3p showed a significant inverse correlation with JPX expression. The lncRNA/miRNA physical interaction was validated by reporter vectors. Then, the oncogenic activity of JPX, the tumor-suppressive role of miR-378a-3p, and the contribution of their functional interaction to cancer hallmarks were demonstrated using assays for cell proliferation, migration, invasion, and 3D-spheroid formation. Finally, molecular circuits were investigated by boosting the expression of both JPX and miR-378a-3p, singularly and in combination, demonstrating that JPX counteracted miR-378a-3p silencing activity toward its oncogenic targets GLUT1, NRP1, YY1, and Wnt5a. Overall, the data unveil a novel ceRNET (competing endogenous RNA network), wherein JPX acts as a ceRNA by binding to miR-378a-3p, thus reducing the miRNA silencing activity toward its downstream targets, and eliciting oncogenic pathways driving lung cancer. The knowledge of the network may pave the way to develop new diagnostic panels, and innovative RNA-targeted and RNA-based therapeutic strategies.

PVT1 lncRNA in lung cancer: A key player in tumorigenesis and therapeutic opportunities

The lncRNA PVT1 has emerged as a pivotal component in the intricate landscape of cancer pathogenesis, particularly in lung cancer. PVT1, situated in the 8q24 chromosomal region, has garnered attention for its aberrant expression patterns in lung cancer, correlating with tumor progression, metastasis, and poor prognosis. Numerous studies have unveiled the diverse mechanisms PVT1 contributes to lung cancer pathogenesis. It modulates critical pathways, such as cell proliferation, apoptosis evasion, angiogenesis, and epithelial-mesenchymal transition. PVT1's interactions with other molecules, including microRNAs and proteins, amplify its oncogenic influence. Recent advancements in genomic and epigenetic analyses have also illuminated the intricate regulatory networks that govern PVT1 expression. Understanding PVT1's complex involvement in lung cancer holds substantial clinical implications. Targeting PVT1 presents a promising avenue for developing novel diagnostic biomarkers and therapeutic interventions. This abstract encapsulates the expanding knowledge regarding the oncogenic role of PVT1 in lung cancer, underscoring the significance of further research to unravel its complete mechanistic landscape and exploit its potential for improved patient outcomes.

Multi-task prediction-based graph contrastive learning for inferring the relationship among lncRNAs, miRNAs and diseases

MOTIVATION

Identifying the relationships among long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and diseases is highly valuable for diagnosing, preventing, treating and prognosing diseases. The development of effective computational prediction methods can reduce experimental costs. While numerous methods have been proposed, they often to treat the prediction of lncRNA-disease associations (LDAs), miRNA-disease associations (MDAs) and lncRNA-miRNA interactions (LMIs) as separate task. Models capable of predicting all three relationships simultaneously remain relatively scarce. Our aim is to perform multi-task predictions, which not only construct a unified framework, but also facilitate mutual complementarity of information among lncRNAs, miRNAs and diseases.

RESULTS

In this work, we propose a novel unsupervised embedding method called graph contrastive learning for multi-task prediction (GCLMTP). Our approach aims to predict LDAs, MDAs and LMIs by simultaneously extracting embedding representations of lncRNAs, miRNAs and diseases. To achieve this, we first construct a triple-layer lncRNA-miRNA-disease heterogeneous graph (LMDHG) that integrates the complex relationships between these entities based on their similarities and correlations. Next, we employ an unsupervised embedding model based on graph contrastive learning to extract potential topological feature of lncRNAs, miRNAs and diseases from the LMDHG. The graph contrastive learning leverages graph convolutional network architectures to maximize the mutual information between patch representations and corresponding high-level summaries of the LMDHG. Subsequently, for the three prediction tasks, multiple classifiers are explored to predict LDA, MDA and LMI scores. Comprehensive experiments are conducted on two datasets (from older and newer versions of the database, respectively). The results show that GCLMTP outperforms other state-of-the-art methods for the disease-related lncRNA and miRNA prediction tasks. Additionally, case studies on two datasets further demonstrate the ability of GCLMTP to accurately discover new associations. To ensure reproducibility of this work, we have made the datasets and source code publicly available at https://github.com/sheng-n/GCLMTP.

Transcriptome profiling and ceRNA network of small extracellular vesicles from resting and degranulated mast cells

Aim: This study aimed to investigate the transcriptomic characteristics and interactions between competitive endogenous RNAs (ceRNAs) within small extracellular vesicles (sEVs) derived from mast cells (MCs). Methods: Transcriptome sequencing analyzed lncRNA, circRNA and mRNA expression in resting and degranulated MC-derived sEVs. Constructed ceRNA regulatory network through correlation analysis and target gene prediction. Results: Differentially expressed 1673 mRNAs, 173 lncRNAs and 531 circRNAs were observed between resting and degranulated MCs-derived sEVs. Enrichment analysis revealed involvement of neurodegeneration, infection and tumor pathways. CeRNA networks included interactions between lncRNA-miRNA, circRNA-miRNA and miRNA-mRNA, targeting genes in the hippo and wnt signaling pathways linked to tumor immune regulation. Conclusion: This study provides valuable insights into MC-sEV molecular mechanisms, offering significant data resources for further investigations.

DARS2 overexpression is associated with PET/CT metabolic parameters and affects glycolytic activity in lung adenocarcinoma

BACKGROUND

This study investigated the correlation between the expression of DARS2 and metabolic parameters of 18F-FDG PET/CT, and explored the potential mechanisms of DARS2 affecting the proliferation and glycolysis of lung adenocarcinoma (LUAD) cells.

METHODS

This study used genomics and proteomics to analyze the difference in DARS2 expression between LUAD samples and control samples. An analysis of 62 patients with LUAD who underwent 18F-FDG PET/CT examinations before surgery was conducted retrospectively. The correlation between DARS2 expression and PET/CT metabolic parameters, including SUVmax, SUVmean, MTV, and TLG, was examined by Spearman correlation analysis. In addition, the molecular mechanism of interfering with DARS2 expression in inhibiting LUAD cell proliferation and glycolysis was analyzed through in vitro cell experiments.

RESULTS

DARS2 expression was significantly higher in LUAD samples than in control samples (p < 0.001). DARS2 has high specificity (98.4%) and sensitivity (95.2%) in the diagnosis of LUAD. DARS2 expression was positively correlated with SUVmax, SUVmean, and TLG (p < 0.001). At the same time, the sensitivity and specificity of SUVmax in predicting DARS2 overexpression in LUAD were 88.9% and 65.9%, respectively. In vitro cell experiments have shown that interfering with DARS2 expression can inhibit the proliferation and migration of LUAD cells, promote cell apoptosis, and inhibit the glycolytic activity of tumor cells by inhibiting the expression of glycolytic related genes SLC2A1, GPI, ALDOA, and PGAM1.

CONCLUSIONS

Overexpression of DARS2 is associated with metabolic parameters on 18F-FDG PET/CT, which can improve LUAD diagnosis accuracy. DARS2 may be a useful biomarker to diagnose, prognosis, and target treatment of LUAD patients.

The long non-coding RNA PVT1 promotes tumorigenesis of cutaneous squamous cell carcinoma via interaction with 4EBP1

The long non-coding RNA (lncRNA) plasmacytoma variant translocation 1 (PVT1) plays an oncogenic role in multiple cancers due to its high expression. However, the expression and associated regulatory mechanisms of PVT1 in cutaneous squamous cell carcinoma (cSCC) remain unclear. Our results revealed that PVT1 was highly upregulated in cSCC tissues and cSCC cell lines. To determine the functional role of PVT1 in cSCC, we constructed a stable knockdown cell model of PVT1 in the A431 and COLO16 cell lines using a lentiviral approach. Xenograft tumor experiments of nude mice in vivo, and colony formation, CCK-8, and EdU assays in vitro demonstrated that knockdown of PVT1 could widely suppress cell proliferation in vivo and in vitro. In addition, PVT1 knockdown induced cell cycle arrest and promoted apoptosis, as detected by flow cytometry analysis. Wound healing and transwell assays revealed that PVT1 knockdown significantly inhibited the migration and invasion of CSCC cell lines. To gain insight into the tumorigenic mechanism and explore the potential target molecules of PVT1, we employed label-free quantitative proteomic analysis. The GO, KEGG enrichment, and protein-protein interaction (PPI) networks suggested that 4E-binding protein 1 (4EBP1) is the possible downstream target effector of PVT1, which was validated by western blot analysis. PVT1 silencing markedly decreased 4EBP1 protein expression levels and directly bound 4EBP1 in the cytoplasm of cSCC cells. 4EBP1 overexpression counteracted the effects of PVT1 knockdown on tumorigenesis in cSCC cells, including cell proliferation, apoptosis, migration, and invasion. Our findings provide strong evidence that PVT1 is an oncogene which plays a role in tumorigenesis of cSCC, that PVT1 may interact with 4EBP1 in the cytoplasm as an underlying mechanism in cSCC carcinogenesis, and that PVT1 combined with 4EBP1 may serve as a potential new therapeutic target for cSCC.

LDAformer: predicting lncRNA-disease associations based on topological feature extraction and Transformer encoder

The identification of long noncoding RNA (lncRNA)-disease associations is of great value for disease diagnosis and treatment, and it is now commonly used to predict potential lncRNA-disease associations with computational methods. However, the existing methods do not sufficiently extract key features during data processing, and the learning model parts are either less powerful or overly complex. Therefore, there is still potential to achieve better predictive performance by improving these two aspects. In this work, we propose a novel lncRNA-disease association prediction method LDAformer based on topological feature extraction and Transformer encoder. We construct the heterogeneous network by integrating the associations between lncRNAs, diseases and micro RNAs (miRNAs). Intra-class similarities and inter-class associations are presented as the lncRNA-disease-miRNA weighted adjacency matrix to unify semantics. Next, we design a topological feature extraction process to further obtain multi-hop topological pathway features latent in the adjacency matrix. Finally, to capture the interdependencies between heterogeneous pathways, a Transformer encoder based on the global self-attention mechanism is employed to predict lncRNA-disease associations. The efficient feature extraction and the intuitive and powerful learning model lead to ideal performance. The results of computational experiments on two datasets show that our method outperforms the state-of-the-art baseline methods. Additionally, case studies further indicate its capability to discover new associations accurately.

lncRNA PVT1: a novel oncogene in multiple cancers

Long noncoding RNAs are involved in epigenetic gene modification, including binding to the chromatin rearrangement complex in pre-transcriptional regulation and to gene promoters in gene expression regulation, as well as acting as microRNA sponges to control messenger RNA levels in post-transcriptional regulation. An increasing number of studies have found that long noncoding RNA plasmacytoma variant translocation 1 (PVT1) plays an important role in cancer development. In this review of a large number of studies on PVT1, we found that PVT1 is closely related to tumor onset, proliferation, invasion, epithelial–mesenchymal transformation, and apoptosis, as well as poor prognosis and radiotherapy and chemotherapy resistance in some cancers. This review comprehensively describes PVT1 expression in various cancers and presents novel approaches to the diagnosis and treatment of cancer.

MicroRNAs in the Regulation of Solute Carrier Proteins Behind Xenobiotic and Nutrient Transport in Cells

Altered metabolism, such as aerobic glycolysis or the Warburg effect, has been recognized as characteristics of tumor cells for almost a century. Since then, there is accumulating evidence to demonstrate the metabolic reprogramming of tumor cells, addiction to excessive uptake and metabolism of key nutrients, to support rapid proliferation and invasion under tumor microenvironment. The solute carrier (SLC) superfamily transporters are responsible for influx or efflux of a wide variety of xenobiotic and metabolites that are needed for the cells to function, as well as some medications. To meet the increased demand for nutrients and energy, SLC transporters are frequently dysregulated in cancer cells. The SLCs responsible for the transport of key nutrients for cancer metabolism and energetics, such as glucose and amino acids, are of particular interest for their roles in tumor progression and metastasis. Meanwhile, rewired metabolism is accompanied by the dysregulation of microRNAs (miRNAs or miRs) that are small, noncoding RNAs governing posttranscriptional gene regulation. Studies have shown that many miRNAs directly regulate the expression of specific SLC transporters in normal or diseased cells. Changes of SLC transporter expression and function can subsequently alter the uptake of nutrients or therapeutics. Given the important role for miRNAs in regulating disease progression, there is growing interest in developing miRNA-based therapies, beyond serving as potential diagnostic or prognostic biomarkers. In this article, we discuss how miRNAs regulate the expression of SLC transporters and highlight potential influence on the supply of essential nutrients for cell metabolism and drug exposure toward desired efficacy.

Angiogenic Factor-Based Signature Predicts Prognosis and Immunotherapy Response in Non-Small-Cell Lung Cancer

Non-small-cell lung cancer (NSCLC) is one of the most common malignancies, and specific molecular targets are still lacking. Angiogenesis plays a central regulatory role in the growth and metastasis of malignant tumors and angiogenic factors (AFs) are involved. Although there are many studies comparing AFs and cancer, a prognostic risk model for AFs and cancer in humans has not been reported in the literature. This study aimed to identify the key AFs closely related to the process of NSCLC development, and four genes have been found, C1QTNF6, SLC2A1, PTX3, and FSTL3. Then, we constructed a novel prognostic risk model based on these four genes in non-small-cell lung cancer (NSCLC) and fully analyzed the relationship with clinical features, immune infiltration, genomes, and predictors. This model had good discrimination and calibration and will perform well in predicting the prognosis of treatment in clinical practice.

Prognostic Risk Signature and Comprehensive Analyses of Endoplasmic Reticulum Stress-Related Genes in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the main pathological subtype of non-small-cell lung cancer. Endoplasmic reticulum stress (ERS) has been found to be involved in multiple tumor-related biological processes. At present, a comprehensive analysis of ERS-related genes in LUAD is still lacking. A total of 1034 samples from TCGA and GEO were used to screen differentially expressed genes. Further, Random Forest algorithm was utilized to screen characteristic genes related to prognosis. Then, LASSO Cox regression was used to construct a prognostic signature. Taking the median of signature score as the threshold, patients were separated into high-risk (HR) group and low-risk (LR) group. Tumor mutation burden (TMB), immune cell infiltration, cancer stem cell infiltration, expression of HLA, and immune checkpoints of the two risk groups were analyzed. TIDE score was used to evaluate the response of the two risk groups to immunotherapy. Finally, the gene expression was verified in clinical tissues with RT-qPCR. An eight-gene signature (ADRB2, AGER, CDKN3, GJB2, SFTPC, SLC2A1, SLC6A4, and SSR4) was constructed. TMB and cancer stem cell infiltration were higher in the HR group than the LR group. TIDE score and expression level of HLA were higher in the LR group than the HR group. Expression level of immune checkpoints, including CD28, CD27, IDO2, and others, were higher in the LR group. Multiple drugs approved by FAD, targeting ERS-related genes, were available for the treatment of LUAD. In summary, we established a stable prognostic model based on ERS-related genes to help the classification of LUAD patients and looked for new treatment strategies from aspects of immunity, tumor mutation, and tumor stem cell infiltration.

All-Trans Retinoic Acid Enhances Chemosensitivity to 5-FU by Targeting miR-378c/E2F7 Axis in Colorectal Cancer

Colorectal carcinoma (CRC), a life-threatening malignancy, has been found to present resistance to 5-fluorouracil (5-FU) and cause a poor prognosis for patients. Previous studies have proved that all-trans retinoic acid (ATRA) could inhibit the development of CRC cells. In addition, miR-378c was discovered to exert a vital role in various cancers. In this study, we utilized MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide), transwell assay, and flow cytometry to confirm that ATRA was able to enhance the inhibitory effects of 5-FU on HCT116 cells effectively by promoting cell apoptosis. Then, ENCORI database (http://starbase.sysu.edu.cn/) was employed to predict that miR-378c was downregulated dramatically in CRC and E2F7 was the direct target of miR-378c. QRT-PCR (quantitative real-time polymerase chain reaction) was conducted to verify that the expression level of miR-378c was decreased while E2F7 expression was upregulated in CRC tissues compared with para-carcinoma tissues. Additionally, treatment of 5-FU combined with ATRA could increase miR-378c expression, whereas it decreased the expression of E2F7. Dual-Luciferase Reporter assay results revealed that miR-378c could regulate the load of E2F7 by binding to its 3′UTR directly. Furthermore, miR-378c inhibitor or vector with E2F7 partially counteracted the effects of 5-FU combined with ATRA on viability, migration, invasion, and apoptosis of HCT116 cells. In conclusion, our study aims to confirm that ATRA enhances chemosensitivity to 5-FU of patients with CRC and expound the potential molecular mechanisms.