Long non-coding RNA SNHG17 may function as a competitive endogenous RNA in diffuse large B-cell lymphoma progression by sponging miR-34a-5p

Deciphering the oncogenic network: how C1QTNF1-AS1 modulates osteosarcoma through miR-34a-5p and glycolytic pathways

Introduction

Osteosarcoma (OS), a prevalent metastatic cancer among young individuals, is associated with a grim prognosis. Long non-coding RNAs (lncRNAs), including C1QTNF1-AS1, are pivotal regulators of cancer cell proliferation and motility. As an oncogene, C1QTNF1-AS1 is implicated in various tumor types, such as colorectal, pancreatic, hepatocellular carcinomas, and OS. The aim of this study was to investigate the functions and underlying mechanisms of C1QTNF1-AS1 in the progression of osteosarcoma.

Methods

This investigation focused on elucidating the functional roles and mechanisms of C1QTNF1-AS1 in OS cells. Bioinformatics tools were utilized to identify the interaction between microRNA miR-34a-5p and C1QTNF1-AS1, as well as the targeting of LDHA and PDK3 by miR-34a-5p. Dual-luciferase reporter assays and RNA immunoprecipitation were employed to validate these interactions. Expression profiles of C1QTNF1-AS1, miR-34a-5p, LDHA, and PDK3 in osteosarcoma cells were analyzed using RT-PCR and western blot analyses, revealing their intricate relationships. The impact of these molecules on OS cell proliferation, invasion, and migration was assessed through CCK-8, Transwell, and Cell scratch assay. Moreover, the effects on aerobic glycolysis in OS cells were examined by quantifying ATP levels, lactate production, glucose uptake capacity, and the extracellular acidification rate.

Results

The findings indicated a significant decrease in C1QTNF1-AS1 expression levels in OS cells compared to normal osteoblasts. A parallel downregulation trend of miR-34a-5p was also observed in OS cells. Silencing C1QTNF1-AS1 led to a marked upregulation of LDHA and PDK3 in OS cells, which was partially attenuated by miR-34a-5p mimics. Functional evaluations demonstrated that suppression of C1QTNF1-AS1 accelerated OS cell growth, motility, invasiveness, and the Warburg effect. Conversely, the overexpression of miR-34a-5p mitigated these stimulatory effects, suggesting a regulatory role in modulating OS progression.

Discussion

Our research emphasizes the critical role of C1QTNF1-AS1 in the pathogenesis of osteosarcoma (OS). We discovered that the downregulation of C1QTNF1-AS1 indirectly upregulates the expression of LDHA and PDK3 by suppressing miR-34a-5p, which functions as a regulator of the Warburg effect. This cascade of events promotes OS progression by enhancing glycolytic metabolism and supplying energy for cancer cell growth, migration, and invasion. These findings suggest a potential therapeutic target and highlight the importance of understanding the regulatory network involving lncRNAs in cancer metabolism and progression.

Correction: Long non-coding RNA SNHG17 may function as a competitive endogenous RNA in diffuse large B-cell lymphoma progression by sponging miR-34a-5p

[This corrects the article DOI: 10.1371/journal.pone.0294729.].

Baseline and interim 18F-FDG PET/CT metabolic parameters predict the efficacy and survival in patients with diffuse large B-cell lymphoma

Introduction

The prognostic value of 18F-FDG PET/CT metabolic parameters, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG), in diffuse large B-cell lymphoma (DLBCL) remains inadequately explored. This study aims to assess the correlation between these parameters and patient outcomes.

Methods

A cohort of 156 DLBCL patients underwent 18F-FDG PET/CT imaging at baseline and after 3-4 cycles of R-CHOP or CHOP-like regimen. The third quartiles of liver uptake values were used as thresholds for calculating MTV and TLG. Patient outcomes were analyzed based on Ann Arbor staging and the 5-PS score. A nomogram was developed to predict overall survival (OS).

Results

Patients with low baseline TLG exhibited significantly better outcomes compared to those with high baseline TLG in both Ann Arbor stages I-II and III-IV (1-year PFS: 78.9% vs. 40%, p=0.016; OS: 94.7% vs. 40%, p=0.005 for stage I-II; 1-year PFS: 74.1% vs. 46.8%, p=0.014; OS: 85.4% vs. 71.8%, p=0.007 for stage III-IV). In interim PET/CT patients with a 5-PS score >3, the high ΔTLG group had superior prognosis (1-year PFS: 82.3% vs. 35.7%, p=0.003; OS: 88.2% vs. 85.7%, p=0.003). The nomogram achieved a C-index of 0.9 for OS prediction.

Discussion

The findings suggest that baseline TLG is a robust prognostic indicator for patients with DLBCL, particularly in early stages, while ΔTLG effectively distinguishes those with favorable outcomes in higher-risk groups. These metabolic parameters from 18F-FDG PET/CT could enhance treatment decision-making and patient management strategies.

Human disease-related long noncoding RNAs: Impact of ginsenosides

Ginsenosides in ginseng are known for their potential health benefits, including antioxidant properties and their potential to exhibit anticancer effects. Besides a various range of coding genes, ginsenosides impose their efficacy by targeting noncoding RNAs. Long noncoding RNA ( lncRNA) has gained significant attention from both basic and clinical oncology fields due to its involvement in various cancer cell activities such as proliferation, apoptosis, metastasis, and autophagy. These events can be achieved either by lncRNA alone or in association with microRNAs or proteins. This review aims to summarize the diverse activities of lncRNAs that are regulated by ginsenosides, focusing on their role in regulating target genes through signaling pathways in human diseases. We highlight the results of studies on the expression profiles of lncRNAs induced by ginsenosides in efforts to inhibit cancer cell proliferation. Finally, we discuss the potential and challenges of utilizing lncRNAs as diagnostic markers for disease treatment.

Should we use nomograms for risk predictions in diffuse large B cell lymphoma patients? A systematic review

Models based on risk stratification are increasingly reported for Diffuse large B cell lymphoma (DLBCL). Due to a rising interest in nomograms for cancer patients, we aimed to review and critically appraise prognostic models based on nomograms in DLBCL patients. A literature search in PubMed/Embase identified 59 articles that proposed prognostic models for DLBCL by combining parameters of interest (e.g., clinical, laboratory, immunohistochemical, and genetic) between January 2000 and 2024. Of them, 40 studies proposed different gene expression signatures and incorporated them into nomogram-based prognostic models. Although most studies assessed discrimination and calibration when developing the model, many lacked external validation. Current nomogram-based models for DLBCL are mainly developed from publicly available databases, lack external validation, and have no applicability in clinical practice. However, they may be helpful in individual patient counseling, although careful considerations should be made regarding model development due to possible limitations when choosing nomograms for prognostication.