Knockdown of LINC00504 Inhibits the Proliferation and Invasion of Breast Cancer via the Downregulation of miR-140-5p

Pan-cancer investigation of RFX family and associated genes identifies RFX8 as a therapeutic target in leukemia

Background

Several transcription factors and co-factors are encoded by the RFX (Regulatory Factor X) family (RFX1-8) and associated genes (RFXAP and RFXANK). Increasing evidence suggests that the RFX family and associated genes are involved in the development and progression of cancer. However, no prior research has focused on a multi-omic analysis of these genes to evaluate their role in tumor progression.

Methods

Using combined TCGA and GTEx pan-cancer data, we investigated the expression patterns and survival profiles of these ten genes. We then focused on RFX8 to analyze its clinicopathological and therapeutic features. Finally, we conducted experimental validation of RFX8 function in acute myeloid leukemia (AML).

Results

RFX5 and RFXANK showed higher expression levels, while RFX6 showed lower expression levels in most types of cancer, with RFX8 being the most upregulated in LAML. RFX2 and RFXAP demonstrated prognostic significance in eight types of cancer, and RFX8 showed significance in six types of cancer. The expression of these ten genes exhibited specific characteristics in immune subtypes, tumor microenvironment, and stemness. The expression of RFX8 was correlated with various tumor stages, microsatellite instability (MSI), tumor mutation burden (TMB), immune cell infiltration, and immune-checkpoint expression. Additionally, RFX8 was found to regulate tumorigenesis and sensitivity to chelerythrine in AML.

Conclusions

Our work delineated the landscape of the RFX family and associated genes in the pan-cancer context and the specific role of RFX8 in AML. These findings might offer cues for further investigations of these genes in cancer biology.

LncRNAs exhibit subtype-specific expression, survival associations, and cancer-promoting effects in breast cancer

Long non-coding RNAs (lncRNAs) play important roles in cancer progression, influencing processes such as invasion, metastasis, and drug resistance. Their reported cell type-dependent expression patterns suggest the potential for specialized functions in specific contexts. In breast cancer, lncRNA expression has been associated with different subtypes, highlighting their relevance in disease heterogeneity. However, our understanding of lncRNA function within breast cancer subtypes remains limited, warranting further investigation. We conducted a comprehensive analysis using the TANRIC dataset derived from the TCGA-BRCA cohort, profiling the expression, patient survival associations and immune cell type correlations of 12,727 lncRNAs across subtypes. Our findings revealed subtype-specific associations of lncRNAs with patient survival, tumor infiltrating lymphocytes and other immune cells. Targeting of lncRNAs exhibiting subtype-specific survival associations and expression in a panel of breast cancer cells demonstrated a selective reduction in cell proliferation within their associated subtype, supporting subtype-specific functions of certain lncRNAs. Characterization of HER2 + -specific lncRNA LINC01269 and TNBC-specific lncRNA AL078604.2 showed nuclear localization and altered expression of hundreds of genes enriched in cancer-promoting processes, including apoptosis, cell proliferation and immune cell regulation. This work emphasizes the importance of considering the heterogeneity of breast cancer subtypes and the need for subtype-specific analyses to fully uncover the relevance and potential impact of lncRNAs. Collectively, these findings demonstrate the contribution of lncRNAs to the distinct molecular, prognostic, and cellular composition of breast cancer subtypes.

Long noncoding RNAs: glycolysis regulators in gynaecologic cancers

The three most common gynaecologic cancers that seriously threaten female lives and health are ovarian cancer, cervical cancer, and endometrial cancer. Glycolysis plays a vital role in gynaecologic cancers. Several long noncoding RNAs (lncRNAs) are known to function as oncogenic molecules. LncRNAs impact downstream target genes by acting as ceRNAs, guides, scaffolds, decoys, or signalling molecules. However, the role of glycolysis-related lncRNAs in regulating gynaecologic cancers remains poorly understood. In this review, we emphasize the functional roles of many lncRNAs that have been found to promote glycolysis in gynaecologic cancers and discuss reasonable strategies for future research.

Role of non-coding RNAs and exosomal non-coding RNAs in retinoblastoma progression

Retinoblastoma (RB) is a rare aggressive intraocular malignancy of childhood that has the potential to affect vision, and can even be fatal in some children. While the tumor can be controlled efficiently at early stages, metastatic tumors lead to high mortality. Non-coding RNAs (ncRNAs) are implicated in a number of physiological cellular process, including differentiation, proliferation, migration, and invasion, The deregulation of ncRNAs is correlated with several diseases, particularly cancer. ncRNAs are categorized into two main groups based on their length, i.e. short and long ncRNAs. Moreover, ncRNA deregulation has been demonstrated to play a role in the pathogenesis and development of RB. Several ncRNAs, such as miR-491-3p, miR-613,and SUSD2 have been found to act as tumor suppressor genes in RB, but other ncRNAs, such as circ-E2F3, NEAT1, and TUG1 act as tumor promoter genes. Understanding the regulatory mechanisms of ncRNAs can provide new opportunities for RB therapy. In the present review, we discuss the functional roles of the most important ncRNAs in RB, their interaction with the genes responsible for RB initiation and progression, and possible future clinical applications as diagnostic and prognostic tools or as therapeutic targets.

Long Non-Coding LEF1-AS1 Sponge miR-5100 Regulates Apoptosis and Autophagy in Gastric Cancer Cells via the miR-5100/DEK/AMPK-mTOR Axis

DEK and miR-5100 play critical roles in many steps of cancer initiation and progression and are directly or indirectly regulated by most promoters and repressors. LEF1-AS1 as a long non-coding RNA can regulate tumor development through sponge miRNA. The effect and regulatory mechanism of DEK on autophagy and apoptosis in gastric cancer (GC), and the role between miR-5100 and DEK or miR-5100 and LEF1-AS1 are still unclear. Our study found that DEK was highly expressed in gastric cancer tissues and cell lines, and knockdown of DEK inhibited the autophagy of cells, promoted apoptosis, and suppressed the malignant phenotype of gastric cancer. DEK regulates autophagy and apoptosis through the AMPK/mTOR signaling pathway. In addition, miR-5100 inhibits autophagy and promotes apoptosis in GC cells while LEF1-AS1 had the opposite effect. Studies have shown that miR-5100 acts by targeting the 3'UTR of DEK, and LEF1-AS1 regulates the expression of miR-5100 by sponging with mIR-5100. In conclusion, our results found that LEF1-AS1 and miR-5100 sponge function, and the miR-5100/DEK/AMPK/mTOR axis regulates autophagy and apoptosis in gastric cancer cells.

An 11-Gene Signature Based on Treatment Responsiveness Predicts Radiation Therapy Survival Benefit Among Breast Cancer Patients

Purpose

We developed a strategy of building prognosis gene signature based on clinical treatment responsiveness to predict radiotherapy survival benefit in breast cancer patients.

Methods and Materials

Analyzed data came from the public database. PFS was used as an indicator of clinical treatment responsiveness. WGCNA was used to identify the most relevant modules to radiotherapy response. Based on the module genes, Cox regression model was used to build survival prognosis signature to distinguish the benefit group of radiotherapy. An external validation was also performed.

Results

In the developed dataset, MEbrown module with 534 genes was identified by WGCNA, which was most correlated to the radiotherapy response of patients. A number of 11 hub genes were selected to build the survival prognosis signature. Patients that were divided into radio-sensitivity group and radio-resistant group based on the signature risk score had varied survival benefit. In developed dataset, the 3-, 5-, and 10-year AUC of the signature were 0.814 (CI95%: 0.742–0.905), 0.781 (CI95%: 0.682–0.880), and 0.762 (CI95%: 0.626–0.897), respectively. In validation dataset, the 3- and 5-year AUC of the signature were 0.706 (CI95%: 0.523–0.889) and 0.743 (CI95%: 0.595–0.891). The signature had higher predictive power than clinical factors alone and had more clinical prognosis efficiency. Functional enrichment analysis revealed that the identified genes were mainly enriched in immune-related processes. Further immune estimated analysis showed the difference in distribution of immune micro-environment between radio-sensitivity group and radio-resistant group.

Conclusions

The 11-gene signature may reflect differences in tumor immune micro-environment that underlie the differential response to radiation therapy and could guide clinical-decision making related to radiation in breast cancer patients.

Current Research Progress of the Role of LncRNA LEF1-AS1 in a Variety of Tumors

Long non-coding RNAs (lncRNA), as key regulators of cell proliferation and death, are involved in the regulation of various processes in the nucleus and cytoplasm, involving biological developmental processes in the fields of immunology, neurobiology, cancer, and stress. There is great scientific interest in exploring the relationship between lncRNA and tumors. Many researches revealed that lymph enhancer-binding factor 1-antisense RNA 1 (LEF1-AS1), a recently discovered lncRNA, is downregulated in myeloid malignancy, acting mainly as a tumor suppressor, while it is highly expressed and carcinogenic in glioblastoma (GBM), lung cancer, hepatocellular carcinoma (HCC), osteosarcoma, colorectal cancer (CRC), oral squamous cell carcinoma (OSCC), prostatic carcinoma, retinoblastoma, and other malignant tumors. Furthermore, abnormal LEF1-AS1 expression was associated with tumorigenesis, development, survival, and prognosis via the regulation of target genes and signaling pathways. This review summarizes the existing data on the expression, functions, underlying mechanism, relevant signaling pathways, and clinical significance of LEF1-AS1 in cancer. It is concluded that LEF1-AS1 can serve as a novel biomarker for the diagnosis and prognosis of various tumors, thus deserves further attention in the future.

Identification of N6-methylandenosine related LncRNAs biomarkers associated with the overall survival of osteosarcoma

PURPOSE

Osteosarcoma (OS) is a differentiation disease caused by the genetic and epigenetic differentiation of mesenchymal stem cells into osteoblasts. OS is a common, highly malignant tumor in children and adolescents. Fifteen to 20 % of the patients find distant metastases at their first visit. The purpose of our study was to identify biomarkers for tracking the prognosis and treatment of OS to improve the survival rate of patients.

MATERIALS AND METHODS

In this study, which was based on Therapeutically Applicable Research to Generate Effective Treatments (TARGET), we searched for m6A related lncRNAs in OS. We constructed a network between lncRNA and m6A, and built an OS prognostic risk model.

RESULTS

We identified 14,581 lncRNAs by using the dataset from TARGET. We obtained 111 m6A-related lncRNAs through a Pearson correlation analysis. A network was built between lncRNA and m6A genes. Eight m6A-related lncRNAs associated with survival were identified through a univariate Cox analysis. A selection operator (LASSO) Cox regression was used to construct a prognostic risk model with six genes (RP11-286E11.1, LINC01426, AC010127.3, DLGAP1-AS2, RP4-657D16.3, AC002398.11) obtained through least absolute shrinkage. We also discovered upregulated levels of DLGAP1-AS2 and m6A methylation in osteosarcoma tissues/cells compared with normal tissues/osteoblasts cells.

CONCLUSION

We constructed a risk score prognosis model of m6A-related lncRNAs (RP11-286E11.1, LINC01426, AC010127.3, DLGAP1-AS2, RP4-657D16.3, AC002398.11) using the dataset downloaded from TRAGET. We verified the value of the model by dividing all samples into test groups and training groups. However, the role of m6A-related lncRNAs in osteosarcoma needs to be further researched by cell and in vivo studies.