LncRNA USP30-AS1 promotes the survival of acute myeloid leukemia cells by cis-regulating USP30 and ANKRD13A

Unraveling the role of long non-coding RNAs in therapeutic resistance in acute myeloid leukemia: New prospects & challenges

Acute Myeloid Leukemia (AML) is a fatal hematological disease characterized by the unchecked proliferation of immature myeloid blasts in different tissues developed by various mutations in hematopoiesis. Despite intense chemotherapeutic regimens, patients often experience poor outcomes, leading to substandard remission rates. In recent years, long non-coding RNAs (lncRNAs) have increasingly become important prognostic and therapeutic hotspots, due to their contributions to dysregulating many functional epigenetic, transcriptional, and post-translational mechanisms leading to alterations in cell expressions, resulting in increased chemoresistance and reduced apoptosis in leukemic cells. Through this review, I highlight and discuss the latest advances in understanding the major mechanisms through which lncRNAs confer therapy resistance in AML. In addition, I also provide perspective on the current strategies to target lncRNA expressions. A better knowledge of the critical role that lncRNAs play in controlling treatment outcomes in AML will help improve existing medications and devise new ones.

LncRNAs and the cancer epigenome: Mechanisms and therapeutic potential

Long non-coding RNAs (lncRNAs) have emerged as critical regulators of epigenome, modulating gene expression through DNA methylation, histone modification, and/or chromosome remodeling. Dysregulated lncRNAs act as oncogenes or tumor suppressors, driving tumor progression by shaping the cancer epigenome. By interacting with the writers, readers, and erasers of the epigenetic script, lncRNAs induce epigenetic modifications that bring about changes in cancer cell proliferation, apoptosis, epithelial-mesenchymal transition, migration, invasion, metastasis, cancer stemness and chemoresistance. This review analyzes and discusses the multifaceted role of lncRNAs in cancer pathobiology, from cancer genesis and progression through metastasis and therapy resistance. It also explores the therapeutic potential of targeting lncRNAs through innovative diagnostic, prognostic, and therapeutic strategies. Understanding the dynamic interplay between lncRNAs and epigenome is crucial for developing personalized therapeutic strategies, offering new avenues for precision cancer medicine.

Mitophagy related diagnostic biomarkers for coronary in-stent restenosis identified using machine learning and bioinformatics

Percutaneous coronary intervention (PCI) combined with stent implantation is currently one of the most effective treatments for coronary artery disease (CAD). However, in-stent restenosis (ISR) significantly compromises its long-term efficacy. Mitophagy plays a crucial role in vascular homeostasis, yet its role in ISR remains unclear. This study aims to identify mitophagy-related biomarkers for ISR and explore their underlying molecular mechanisms. Through differential gene expression analysis between ISR and Control samples in the combined dataset, 169 differentially expressed genes (DEGs) were identified. Twenty-three differentially expressed mitophagy-related genes (DEMRGs) were identified by intersecting with mitophagy-related genes (MRGs) from the GeneCards, and functional enrichment analysis indicated their significant involvement in mitophagy-related biological processes. Using Weighted Gene Co-expression Network Analysis (WGCNA) and three machine learning algorithms (Logistic-LASSO, RF, and SVM-RFE), LRRK2, and ANKRD13A were identified as mitophagy-related biomarkers for ISR. The nomogram based on these two genes also exhibited promising diagnostic performance for ISR. Gene Set Enrichment Analysis (GSEA) as well as immune infiltration analyses showed that these two genes were closely associated with immune and inflammatory responses in ISR. Furthermore, potential small molecule compounds with therapeutic implications for ISR were predicted using the connectivity Map (cMAP) database. This study systematically investigated mitophagy-related biomarkers for ISR and their potential biological functions, providing new insights into early diagnosis and precision treatment strategies for ISR.

EP300 promotes tumor stemness via epigenetic activation of CRISP3 leading to lobaplatin resistance in triple-negative breast cancer

Lobaplatin shows antitumor activity against a wide range of tumors, including triple-negative breast cancer (TNBC), and has been linked to cancer stem cell pool. Here, we investigated the molecular mechanisms behind lobaplatin resistance and stemness in vitro and in vivo. Two chemoresistance-related GEO data sets (GSE70690 and GSE103115) were included to screen out relevant genes. Cysteine-rich secretory protein 3 (CRISP3) was found to be overexpressed in lobaplatin-resistant TNBC and related to poor diagnosis. CRISP3 expression was significantly correlated with tumor stemness markers in lobaplatin-resistant cells. E1A-associated protein p300 (EP300) regulated CRISP3 expression by affecting the H3K27ac modification of the CRISP3 promoter. In addition, knocking down EP300 curbed the malignant biological behavior of lobaplatin-resistant cells, which was antagonized by CRISP3 overexpression. Collectively, our results highlight the EP300/CRISP3 axis as a key driver of lobaplatin resistance in TNBC and suggest that therapeutic targeting of this axis may be an effective strategy for enhancing platinum sensitivity in TNBC.

Ubiquitin-specific proteases (USPs) in leukemia: a systematic review

BACKGROUND

Leukemia, a type of blood cell cancer, is categorized by the type of white blood cells affected (lymphocytes or myeloid cells) and disease progression (acute or chronic). In 2020, it ranked 15th among the most diagnosed cancers and 11th in cancer-related deaths globally, with 474,519 new cases and 311,594 deaths (GLOBOCAN2020). Research into leukemia's development mechanisms may lead to new treatments. Ubiquitin-specific proteases (USPs), a family of deubiquitinating enzymes, play critical roles in various biological processes, with both tumor-suppressive and oncogenic functions, though a comprehensive understanding is still needed.

AIM

This systematic review aimed to provide a comprehensive review of how Ubiquitin-specific proteases are involved in pathogenesis of different types of leukemia.

METHODS

We systematically searched the MEDLINE (via PubMed), Scopus, and Web of Science databases according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA) to identify relevant studies focusing on the role of USPs in leukemia. Data from selected articles were extracted, synthesized, and organized to present a coherent overview of the subject matter.

RESULTS

The review highlights the crucial roles of USPs in chromosomal aberrations, cell proliferation, differentiation, apoptosis, cell cycle regulation, DNA repair, and drug resistance. USP activity significantly impacts leukemia progression, inhibition, and chemotherapy sensitivity, suggesting personalized diagnostic and therapeutic approaches. Ubiquitin-specific proteases also regulate gene expression, protein stability, complex formation, histone deubiquitination, and protein repositioning in specific leukemia cell types.

CONCLUSION

The diagnostic, prognostic, and therapeutic implications associated with ubiquitin-specific proteases (USPs) hold significant promise and the potential to transform leukemia management, ultimately improving patient outcomes.

Identification and prognostic evaluation of differentially expressed long noncoding RNAs associated with immune infiltration in osteosarcoma

Osteosarcoma is a malignant bone cancer that originates from the bone with the strongest invasiveness. Tumor formation strongly correlates with immune cell infiltration into the tumor immune microenvironment (TIME). Therefore, we aimed to identify TIME-related biomarkers as potential prognostic markers of osteosarcoma. The mRNA and long noncoding RNA (lncRNA) transcriptome data of 88 patients with osteosarcoma and the expression profile of GSE99671 were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus, respectively. Immune infiltration scores and types were evaluated using ESTIMATE and CIBERSORT. A linear model was established to identify the differentially expressed genes (DEGs) and lncRNAs (DElncRNAs). Functional enrichment analysis of DEGs was conducted by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis, and gene set variation analysis. DElncRNAs were analyzed using a weighted gene co-expression network. Least absolute shrinkage and selection operator regression was applied to screen for prognostic markers. Patient survival was predicted by the risk score and analyzed by receiver operating characteristic curve. Clinical features affecting patient survival were assessed. Immune infiltration positively correlated with osteosarcoma patient survival. Different immune cell infiltrates in patients with osteosarcma may serve as prognostic indicators and targets for immunotherapy. In total, 1125 DEGs, 80 DElncRNAs, and 11 pairs of co-expressed lncRNA-mRNAs were identified. DEGs in the three modules were associated with immune infiltration into the TIME. Four DElncRNAs, namely AC015819.1, AC015911.3, AL365361.1, and USP30-AS1, showed good prognostic ability for osteosarcoma and were positively correlated with the immune score. Tumor metastasis and risk scores alone were good prognostic indicators, and a combination of the two variables can better predict the prognosis of osteosarcoma. We identified four lncRNAs, AC015819.1, AC015911.3, AL365361.1, and USP30-AS1, as potential biomarkers for osteosarcoma prognosis.

Identification of hypoxic-related lncRNAs prognostic model for revealing clinical prognostic and immune infiltration characteristic of cutaneous melanoma

BACKGROUND

Cutaneous melanoma (CM) remains a significant threat to human health. There are clues to the potential role of hypoxia in CM progression. However, the role of hypoxia-related lncRNAs (HRLs) in CM has not been clarified.

METHODS

We obtained hypoxia related genes from MSigDB database and subsequently identified HRLs by applying TCGA database. LASSO-univariate and multivariate Cox analysis were used to comprehensively analyze the survival characteristics and HRLs expressions, and a novel HRLs-related prognostic risk model was subsequently established for comprehensive analysis.

RESULTS

The established risk model could evaluate the clinical outcome of CM accurately. The ability of the model-related risk score was also validated as an independent prognostic indicator of CM. Immune infiltration, TMB analysis, drug sensitivity analysis and immunotherapy evaluation were conducted to comprehensively assess the possible causes of the difference in prognosis. The reliability of bioinformatics results was partially verified by RT-qPCR.

CONCLUSION

We established a new HRLs related risk model and discussed the potential role of hypoxia in the development of CM, which provided a novel basis for CM risk stratification.

Comprehensive analyses of mitophagy-related genes and mitophagy-related lncRNAs for patients with ovarian cancer

BACKGROUND

Both mitophagy and long non-coding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC). We sought to explore the characteristics of mitophagy-related gene (MRG) and mitophagy-related lncRNAs (MRL) to facilitate treatment and prognosis of OC.

METHODS

The processed data were extracted from public databases (TCGA, GTEx, GEO and GeneCards). The highly synergistic lncRNA modules and MRLs were identified using weighted gene co-expression network analysis. Using LASSO Cox regression analysis, the MRL-model was first established based on TCGA and then validated with four external GEO datasets. The independent prognostic value of the MRL-model was evaluated by Multivariate Cox regression analysis. Characteristics of functional pathways, somatic mutations, immunity features, and anti-tumor therapy related to the MRL-model were evaluated using abundant algorithms, such as GSEA, ssGSEA, GSVA, maftools, CIBERSORT, xCELL, MCPcounter, ESTIMATE, TIDE, pRRophetic and so on.

RESULTS

We found 52 differentially expressed MRGs and 22 prognostic MRGs in OC. Enrichment analysis revealed that MRGs were involved in mitophagy. Nine prognostic MRLs were identified and eight optimal MRLs combinations were screened to establish the MRL-model. The MRL-model stratified patients into high- and low-risk groups and remained a prognostic factor (P < 0.05) with independent value (P < 0.05) in TCGA and GEO. We observed that OC patients in the high-risk group also had the unfavorable survival in consideration of clinicopathological parameters. The Nomogram was plotted to make the prediction results more intuitive and readable. The two risk groups were enriched in discrepant functional pathways (such as Wnt signaling pathway) and immunity features. Besides, patients in the low-risk group may be more sensitive to immunotherapy (P = 0.01). Several chemotherapeutic drugs (Paclitaxel, Veliparib, Rucaparib, Axitinib, Linsitinib, Saracatinib, Motesanib, Ponatinib, Imatinib and so on) were found with variant sensitivity between the two risk groups. The established ceRNA network indicated the underlying mechanisms of MRLs.

CONCLUSIONS

Our study revealed the roles of MRLs and MRL-model in expression, prognosis, chemotherapy, immunotherapy, and molecular mechanism of OC. Our findings were able to stratify OC patients with high risk, unfavorable prognosis and variant treatment sensitivity, thus improving clinical outcomes for OC patients.

T2DB: A Web Database for Long Non-Coding RNA Genes in Type II Diabetes

Type II diabetes (T2D) is a growing health problem worldwide due to increased levels of obesity and can lead to other life-threatening diseases, such as cardiovascular and kidney diseases. As the number of individuals diagnosed with T2D rises, there is an urgent need to understand the pathogenesis of the disease in order to prevent further harm to the body caused by elevated blood glucose levels. Recent advances in long non-coding RNA (lncRNA) research may provide insights into the pathogenesis of T2D. Although lncRNAs can be readily detected in RNA sequencing (RNA-seq) data, most published datasets of T2D patients compared to healthy donors focus only on protein-coding genes, leaving lncRNAs to be undiscovered and understudied. To address this knowledge gap, we performed a secondary analysis of published RNA-seq data of T2D patients and of patients with related health complications to systematically analyze the expression changes of lncRNA genes in relation to the protein-coding genes. Since immune cells play important roles in T2D, we conducted loss-of-function experiments to provide functional data on the T2D-related lncRNA USP30-AS1, using an in vitro model of pro-inflammatory macrophage activation. To facilitate lncRNA research in T2D, we developed a web application, T2DB, to provide a one-stop-shop for expression profiling of protein-coding and lncRNA genes in T2D patients compared to healthy donors or subjects without T2D.

Naringenin induces the cell apoptosis of acute myeloid leukemia cells by regulating the lncRNA XIST/miR-34a/HDAC1 signaling

Acute myeloid leukemia (AML) is a life-threatening aggressive malignancy of the bone marrow and has posed a great challenge to the clinic, due to a lack of fully understanding of the molecular mechanism. Histone deacetylase 1 (HDAC1) has been reported to be a therapeutic target for treating AML. Naringenin (Nar) may act as an anti-leukemic agent and suppress the expression of HDACs. However, the potential underlying mechanism of Nar in suppressing the activity of HDAC1 remains unclear. Here, we found that Nar induced the apoptosis, decreased the expression of lncRNA XIST and HDAC1, and increased the expression of microRNA-34a in HL60 cells. Sh-XIST transfection could induce cell apoptosis. On the contrary, the forced expression of XIST might reverse the biological actions of Nar. XIST could sponge miR-34a, which targeted to degrade HDAC1. The forced expression of HDAC1 could effectively reverse the effects of Nar. Thus, Nar can induce cell apoptosis by mediating the expression of lncRNA XIST/miR-34a/HDAC1 signaling in HL60 cells.

A lactate-related LncRNA model for predicting prognosis, immune landscape and therapeutic response in breast cancer

Breast cancer (BC) has the highest incidence rate of all cancers globally, with high heterogeneity. Increasing evidence shows that lactate and long non-coding RNA (lncRNA) play a critical role in tumor occurrence, maintenance, therapeutic response, and immune microenvironment. We aimed to construct a lactate-related lncRNAs prognostic signature (LRLPS) for BC patients to predict prognosis, tumor microenvironment, and treatment responses. The BC data download from the Cancer Genome Atlas (TCGA) database was the entire cohort, and it was randomly assigned to the training and test cohorts at a 1:1 ratio. Difference analysis and Pearson correlation analysis identified 196 differentially expressed lactate-related lncRNAs (LRLs). The univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were used to construct the LRLPS, which consisted of 7 LRLs. Patients could be assigned into high-risk and low-risk groups based on the medium-risk sore in the training cohort. Then, we performed the Kaplan–Meier survival analysis, time-dependent receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. The results indicated that the prognosis prediction ability of the LRLPS was excellent, robust, and independent. Furthermore, a nomogram was constructed based on the LRLPS risk score and clinical factors to predict the 3-, 5-, and 10-year survival probability. The GO/KEGG and GSEA indicated that immune-related pathways differed between the two-risk group. CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore (IPS) showed that low-risk patients had higher levels of immune infiltration and better immunotherapeutic response. The pRRophetic and CellMiner databases indicated that many common chemotherapeutic drugs were more effective for low-risk patients. In conclusion, we developed a novel LRLPS for BC that could predict the prognosis, immune landscape, and treatment response.

An Immune-Related lncRNA Pairing Model for Predicting the Prognosis and Immune-Infiltrating Cell Condition in Human Ovarian Cancer

Ovarian cancer is the second common cancer among the gynecological tumors. It is difficult to be found and diagnosed in the early stage and easy to relapse due to chemoresistance and deficiency in choices of treatment. Therefore, future exploring the biomarkers for diagnosis, treatment, and prognosis prediction of ovarian cancer is significant to women in the world. We downloaded data from TCGA and GTEx and used R “limma” package for analyzing the differentially expressed immune-related lncRNA in ovarian cancer and finally got 7 downregulated and 171 upregulated lncRNA. Then, we paired the differentially expressed immune-related lncRNA and constructed a novel lncRNA pairing model containing 7 lncRNA pairs. Based on the cut-off point with the highest AUC value, 102 patients were selected in high-risk group and 272 in low-risk group. The KM analysis suggested that the patients in the low-risk group had a longer overall survival. Future analysis showed the correlations between risk scores and clinicopathological parameters and infiltrating immune cells. In conclusion, we identified an immune-related lncRNA pairing model for predicting the prognosis and immune-infiltrating cell condition in human ovarian cancer, which thus further can instruct immunotherapy.

Construction of a four-mRNA prognostic signature with its ceRNA network in CESC

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) tumorigenesis involves a combination of multiple genetic alteration processes. Constructing a survival-associated competing endogenous RNA (ceRNA) network and a multi-mRNA-based prognostic signature model can help us better understand the complexity and genetic characteristics of CESC. In this study, the RNA-seq data and clinical information of CESC patients were downloaded from The Cancer Genome Atlas. Differentially expressed mRNAs, lncRNAs and miRNAs were identified with the edgeR R package. A four-mRNA prognostic signature was developed by multivariate Cox regression analysis. Kaplan–Meier survival with the log-rank tests was performed to assess survival rates. The relationships between overall survival (OS) and clinical parameters were evaluated by Cox regression analysis. A survival-associated ceRNA network was constructed with the multiMiR package and miRcode database. Kyoto encyclopedia of genes and genomes (KEGG) analysis and gene ontology analyses were used to identify the functional role of the ceRNA network in the prognosis of CESC. A total of 298 differentially expressed mRNAs, 8 miRNAs, and 29 lncRNAs were significantly associated with the prognosis of CESC. A prognostic signature model based on 4 mRNAs (OPN3, DAAM2, HENMT1, and CAVIN3) was developed, and the prognostic ability of this signature was indicated by the AUC of 0.726. Patients in the high-risk group exhibited significantly worse OS. The KEGG pathways, TGF-β and Cell adhesion molecules, were significantly enriched. In this study, a CESC-associated ceRNA network was constructed, and a multi-mRNA-based prognostic model for CESC was developed based on the ceRNA network, providing a new perspective for cancer pathogenesis research.

lncRNA USP30-AS1 sponges miR-765 and modulates the progression of colon cancer

Background

The incidence and mortality of colon cancer is increasing recently. It is necessary to identify effective biomarkers for the progression and prognosis of colon cancer. To assess the potential of lncRNA USP30-AS1 (USP30-AS1) in serving as the biomarker of colon cancer and unearth the underlying mechanism.

Methods

There were 123 colon cancer patients enrolled. The expression of USP30-AS1 was evaluated with PCR in tissue and cell samples. The clinical significance of USP30-AS1 was assessed with a series of statistical methods, while the CCK8 and Transwell assay were conducted to estimate its biological effect on the colon cancer cellular processes. In mechanism, the interaction of USP30-AS1 with miR-765 was evaluated with the dual-luciferase reporter assay.

Results

In colon cancer tissues, the USP30-AS1 downregulation and the miR-765 upregulation were observed, and there was a negative correlation between the USP30-AS1 expression level and the miR-765 expression level. The downregulation of USP30-AS1 related to the malignant progression and served as an adverse prognostic indicator of colon cancer. The overexpression of USP30-AS1 dramatically suppressed colon cancer cellular processes, which was alleviated by miR-765.

Conclusions

USP30-AS1 predicts the malignancy and prognosis of colon cancer patients. USP30-AS1 suppressed the progression of colon cancer through modulating miR-765.

The Establishment and Experimental Verification of an lncRNA-Derived CD8+ T Cell Infiltration ceRNA Network in Colorectal Cancer

BACKGROUND

Long noncoding RNAs (LncRNA) lead a vital role in colorectal cancer (CRC) development. The infiltrating CD8+ T cell is the main target of immunotherapy. Our study aimed to figure out the potential mechanism of lncRNAs regulating the function of CD8+ T cells in CRC.

METHODS

We collected bulk RNA-seq, miRNA-seq, and single-cell RNA-seq (scRNA-seq) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The cibersort algorithm and correlation analysis were used to estimate the abundance of CD8+ T cells and screened out the most relevant lncRNAs. We used scRNA-seq data to identify the main cell lncRNA expressed. Furthermore, one competing endogenous RNA (ceRNA) network focusing on the potential mechanism of lncRNA-derived CD8+ T cell infiltration was constructed. We established a co-culture system to assess the immunosuppressive function of the lncRNA. And we evaluated the effects of the lncRNA on CD8+ T cell cytotoxicity by flow cytometry, qPCR, and clone formation assay.

RESULTS

Three CD8+ T cell infiltration-related lncRNAs were identified, and LINC00657 was expressed mainly in tumor cells, negatively associated with CD8+ T cell infiltration. Hsa-miRNA-1224-3p and hsa-miRNA-338-5p and SCD, ETS2, UBE2H, and YY1 were identified to construct the ceRNA network. Immunosuppression-related tumor marker CD155 was proved to be positively correlated with LINC00657 and mRNAs in the ceRNA network. In addition, we proved that LINC00657 could impair the cytotoxicity of CD8+ T cells, and its expression was positively associated with CD155 in vitro.

CONCLUSIONS

We successfully constructed an lncRNA-derived CD8+ T cell infiltration ceRNA network in CRC. LINC00657 may play a leading role in the CRC immune escape and could be a novel immunotherapy target.

Immune-relatedlncRNAs can predict the prognosis of acute myeloid leukemia

The immune microenvironment in acute myeloid leukemia (AML) is closely related to patients' prognosis. Long noncoding RNAs (lncRNAs) are emerging as key regulators in immune systems. In this study, we established a prognostic model using an immune-related lncRNA (IRL) signature to predict AML patients' overall survival (OS) through Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analysis. Kaplan-Meier analysis, receiver operating characteristic (ROC) analysis, univariate Cox regression, and multivariate Cox regression analyses further illustrated the reliability of our prognostic model. An IRL signature-based nomogram consisting of other clinical features efficiently predicted the OS of AML patients. The incorporation of the IRL signature improved the ELN2017 risk stratification system's prognostic accuracy. In addition, we found that monocytes and metabolism-related pathways may play a role in AML progression. Overall, the IRL signature appears as a novel effective model for evaluating the OS of AML patients and may be implemented to contribute to the prolonged OS in AML patients.