Silencing long intergenic non-protein coding RNA 00987 inhibits proliferation, migration, and invasion of osteosarcoma cells by sponging miR-376a-5p to regulate FNBP1 expression

Identification of Recurrence-associated Gene Signatures and Machine Learning-based Prediction in IDH-Wildtype Histological Glioblastoma

Glioblastoma (GBM) is a highly aggressive brain tumor with frequent recurrence, yet the molecular mechanisms driving recurrence remain poorly understood. Identifying recurrence-associated genes may improve prognosis and treatment strategies. We applied weighted gene co-expression network analysis (WGCNA) to transcriptomic data from IDH-wildtype histological GBM in the CGGA-693 (n = 190) and CGGA-325 (n = 111) cohorts to identify recurrence-associated genes. These genes were validated using RT-qPCR and single-cell RNA sequencing (scRNA-seq) datasets (GSE174554, GSE131928). Their associations with immune cell composition were analyzed. Finally, we evaluated 113 machine learning algorithms to develop a multi-gene predictive model for GBM recurrence, with model performance assessed using receiver operating characteristic (ROC) curves and confusion matrix analysis. We identified eight recurrence-associated genes (CERS2, EML2, FNBP1, ICOSLG, MFAP3L, NPC1, ROGDI, SLAIN1) that were significantly differentially expressed between primary and recurrent GBM. The scRNA-seq analysis revealed cell-type-specific expression patterns, with eight genes predominantly enriched in oligodendrocytes, malignant GBM subtypes, and immune cells. Immune cell deconvolution showed significant alterations in macrophage polarization and NK cell activation in recurrent GBM. Machine learning analysis demonstrated that random forest (RF) was the most effective model, achieving AUC values of 0.998, 0.968, and 0.998 in the training, CGGA-693 validation, and CGGA-325 validation cohorts, respectively, suggesting high predictive accuracy. This study identifies novel recurrence-associated molecular signatures and establishes a machine learning-based predictive model in IDH-wildtype histological GBM.

Hypomethylation-associated LINC00987 downregulation induced lung adenocarcinoma progression by inhibiting the phosphorylation-mediated degradation of SND1

DNA methylation, an epigenetic regulatory mechanism dictating gene transcription, plays a critical role in the occurrence and development of cancer. However, the molecular underpinnings of LINC00987 methylation in the regulation of lung adenocarcinoma (LUAD) remain elusive. This study investigated LINC00987 expression in LUAD patients through analysis of The Cancer Genome Atlas data sets. Quantitative real-time polymerase chain reaction (RT-qPCR) and fluorescence in situ hybridization assays were used to assess LINC00987 expression in LUAD. The bisulfite genomic sequence PCR (BSP) assay was used to determine the methylation levels of the LINC00987 promoter. The interaction between LINC00987 and SND1 was elucidated via immunoprecipitation and RNA pull-down assays. The functional significance of LINC00987 and SND1 in Calu-3 and NCI-H1688 cells was evaluated in vitro through CCK-8, EdU, Transwell, flow cytometry, and vasculogenic mimicry (VM) tube formation assays. LINC00987 expression decreased in LUAD concomitant with hypermethylation of the promoter region, while hypomethylation of the LINC00987 promoter in LUAD tissues correlated with tumor progression. Treatment with 5-Aza-CdR augmented LINC00987 expression and inhibited tumor growth. Mechanistically, LINC00987 overexpression impeded LUAD progression and VM through direct binding with SND1, thereby facilitating its phosphorylation and subsequent degradation. Additionally, overexpression of SND1 counteracted the adverse effects of LINC00987 downregulation on cell proliferation, apoptosis, cell migration, invasion, and VM in LUAD in vitro. In conclusion, this pioneering study focuses on the expression and function of LINC00987 and reveals that hypermethylation of the LINC00987 gene may contribute to LUAD progression. LINC00987 has emerged as a potential tumor suppressor gene in tumorigenesis through its binding with SND1 to facilitate its phosphorylation and subsequent degradation.

Silencing LINC00987 ameliorates adriamycin resistance of acute myeloid leukemia via miR-4458/HMGA2 axis

BACKGROUND

Most patients with acute myeloid leukemia (AML) eventually develop drug resistance, leading to a poor prognosis. Dysregulated long gene non coding RNAs (lincRNAs) have been implicated in chemoresistance in AML. Unfortunately, the effects of lincRNAs which participate in regulating the Adriamycin (ADR) resistance in AML cells remain unclear. Thus, the purpose of this study is to determine LINC00987 function in ADR-resistant AML.

METHODS

In this study, ADR-resistant cells were constructed. LINC00987, miRNAs, and HMGA2 mRNA expression were measured by qRT-PCR. P-GP, BCRP, and HMGA2 protein were measured by Western blot. The proliferation was analyzed by MTS and calculated IC50. Soft agar colony formation assay and TUNEL staining were used to analyze cell colony formation and apoptosis. Xenograft tumor experiment was used to analyze the xenograft tumor growth of ADR-resistant AML.

RESULTS

We found that higher expression of LINC00987 was observed in AML patients and associated with poor overall survival in AML patients. LINC00987 expression was increased in ADR-resistant AML cells, including ADR/MOLM13 and ADR/HL-60 cells. LINC00987 downregulation reduces ADR resistance in ADR/MOLM13 and ADR/HL-60 cells in vitro and in vivo, while LINC00987 overexpression enhanced ADR resistance in MOLM13 and HL-60 cells. Additionally, LINC00987 functions as a competing endogenous RNA for miR-4458 to affect ADR resistance in ADR/MOLM13 and ADR/HL-60 cells. HMGA2 is a target of miR-4458. LINC00987 knockdown and miR-4458 overexpression reduced HMGA2 expression. HMGA2 overexpression enhanced ADR resistance, which reversed the function of LINC00987 silencing in suppressing ADR resistance of ADR/MOLM13 and ADR/HL-60 cells.

CONCLUSIONS

Downregulation of LINC00987 weakens ADR resistance by releasing miR-4458 to deplete HMGA2 in ADR/MOLM13 and ADR/HL-60. Therefore, LINC00987 may act as the therapeutic target for treating chemoresistant AML.

FNBP1 Facilitates Cervical Cancer Cell Survival by the Constitutive Activation of FAK/PI3K/AKT/mTOR Signaling

Cervical cancer is the most prevalent gynecological tumor among women worldwide. Although the incidence and mortality of cervical cancer have been declining thanks to the wide-scale implementation of cytological screening, it remains a major challenge in clinical treatment. High viability is one of the leading causes of the chemotherapeutic resistance in cervical cancers. Formin-binding protein 1 (FNBP1) could stimulate F-actin polymerization beneath the curved plasma membrane in the cell migration and endocytosis, which had previously been well defined. Here, FNBP1 was also demonstrated to play a crucial role in cervical cancer cell survival, and the knockdown of which could result in the attenuation of FAK/PI3K/AKT signaling followed by significant apoptotic accumulation and proliferative inhibition. In addition, the epidermal growth factor (hrEGF) abrogated all the biological effects mediated by the silencing of FNBP1 except for the cell adhesion decrease. These findings indicated that FNBP1 plays a key role in maintaining the activity of focal adhesion kinase (FAK) by promoting cell adhesion. The activated FAK positively regulated downstream PI3K/AKT/mTOR signaling, which is responsible for cell survival. Promisingly, FNBP1 might be a potential target against cervical cancer in combination therapy.

A Novel Oxidative Stress-Related lncRNA Signature That Predicts the Prognosis and Tumor Immune Microenvironment of Breast Cancer

Background

The association between oxidative stress and lncRNAs within the cancer-related researching field has been a controversial subject. At present, the exact function of oxidative stress as well as lncRNAs exert in breast cancer (BC) are still unclear. Therefore, the present study examined the lncRNAs oxidative stress-related in BC.

Methods

Transcriptome data of BC obtained from TCGA (The Cancer Genome Atlas) database were used to generate synthetic matrices. Patients with breast cancer were randomly assigned to training, testing, or combined groups. The prognostic signature of oxidative stress was created using the selection operator Cox regression method, and the difference in prognosis between groups was examined using Kaplan-Meier curves, the accuracy of which was calculated using a receiver-operating characteristic-area through the curve (ROC-AUC) analysis with internal validation. Also, the Gene Set Enrichment Analyses (GSEA) was applied for the analysis of the risk groups. To conclude, the half-maximal inhibitory concentration (IC50) of these groups were investigated by immunoassay assay.

Results

A model based on 7 lncRNAs related to oxidative stress was proposed, and the calibration plots and projected prognosis matched well. For prognosis at 5, 3, and 1 year, the area under the ROC curve (AUC) values were 0.777, 0.777, and 0.759. The functions of target genes identified by GSEA appear to be mainly expressed in metabolism, signal transduction, tumorigenesis, and also the progression. The remarkable differences in IC50 and gene expression between risk groups in this study provide a deep insight for further systemic treatment. Higher macrophage scores were acquired in the high-risk group, of which patients showed more response to conventional chemotherapy drugs, such as AKT inhibitor VIII and Lapatinib, as well as immunotherapy strategies including anti-CD80, TNF SF4, CD276, and NRP1.

Conclusion

The prognosis of breast cancer can be independently predicted by the markers, which sheds light on further research of the specific role of lncRNAs which are oxidative stress-related and clinical treatment of breast cancer.