High lncSNHG15 expression may predict poor cancer prognosis: a meta-analysis based on the PRISMA and the bio-informatics analysis

Diagnostic Accuracy of Exosomal Long Noncoding RNAs in Diagnosis of NSCLC: A Meta-Analysis

PURPOSE

Globally, non-small cell lung cancer (NSCLC) is the primary cause of cancer-related mortality, both early and accurate diagnosis are essential for effective treatment and improved patient outcomes. Exosomal noncoding RNAs (ncRNAs) have emerged as promising biomarkers for NSCLC diagnosis. This meta-analysis aims to assess the diagnostic accuracy of exosomal long noncoding RNAs (lncRNAs) for diagnosing NSCLC.

METHODS

A comprehensive literature search was conducted to identify relevant studies that assessed the diagnostic performance of exosomal lncRNAs in NSCLC. Quality assessment and data extraction were performed independently by two reviewers. Pooled sensitivity, specificity, and other relevant diagnostic parameters were calculated using a bivariate random-effects model. Subgroup analyses and meta-regression were conducted to explore potential sources of heterogeneity.

RESULTS

Sixteen studies, comprising 1843 NSCLC cases and 1298 controls, were included in this meta-analysis. The pooled sensitivity and specificity of nine exosomal lncRNAs for diagnosing NSCLC were 0.74 [95% confidence interval (CI) 0.69-0.79] and 0.78 (95% CI 0.68-0.85). The pooled area under the receiver operating characteristic curve (AUC) for fifteen lncRNAs was 0.80 (95% CI 0.768-0.831). Meta-regression could not find any source for interstudy heterogeneity.

CONCLUSION

Exosomal lncRNAs, particularly AL139294.1, GAS5, LUCAT1, and SOX2-OT, have excellent diagnostic accuracy and promising diagnostic potential in NSCLC. Therefore, they can be used as diagnostic tools for early detection of NSCLC.

Development of a nomogram to predict the prognosis of patients with secondary bone tumors in the intensive care unit: a retrospective analysis based on the MIMIC IV database

PURPOSE

The present study aimed to develop a nomogram to predict the prognosis of patients with secondary bone tumors in the intensive care unit to facilitate risk stratification and treatment planning.

METHODS

We used the MIMIC IV 2.0 (the Medical Information Mart for Intensive Care IV) to retrieve patients with secondary bone tumors as a study cohort. To evaluate the predictive ability of each characteristic on patient mortality, stepwise Cox regression was used to screen variables, and the selected variables were included in the final Cox proportional hazard model. Finally, the performance of the model was tested using the decision curve, calibration curve, and receiver operating characteristic (ROC) curve.

RESULTS

A total of 1028 patients were enrolled after excluding cases with missing information. In the training cohort, albumin, APSIII (Acute Physiology Score III), chemotherapy, lactate, chloride, hepatic metastases, respiratory failure, SAPSII (Simplified Acute Physiology Score II), and total protein were identified as independent risk factors for patient death and then incorporated into the final model. The model showed good and robust prediction performance.

CONCLUSION

We developed a nomogram prognostic model for patients with secondary bone tumors in the intensive care unit, which provides effective survival prediction information.

Long noncoding RNA SNHG15: A promising target in human cancers

As oncogenes or tumor suppressor genes, lncRNAs played an important role in tumorigenesis and the progression of human cancers. The lncRNA SNHG15 has recently been revealed to be dysregulated in malignant tumors, suggesting the aberrant expression of which contributes to clinical features and regulates various oncogenic processes. We have selected extensive literature focused on SNHG15 from electronic databases, including studies relevant to its clinical significance and the critical events in cancer-related processes such as cell proliferation, apoptosis, autophagy, metastasis, and drug resistance. This review summarized the current understanding of SNHG15 in cancer, mainly focusing on the pathological features, known biological functions, and underlying molecular mechanisms. Furthermore, SNHG15 has been well-documented to be an effective diagnostic and prognostic marker for tumors, offering novel therapeutic interventions in specific subsets of cancer cells.

Association between small nucleolar RNA host gene expression and survival outcome of colorectal cancer patients: A meta-analysis based on PRISMA and bioinformatics analysis

Introduction

Growing evidence shows that long non-coding RNA small nucleolar RNA host genes (lncRNA SNHGs) enact an pivotal regulatory roles in the shorter survival outcome of colorectal cancer (CRC). However, no research has systematically evaluated the correlation among lncRNA SNHGs expression and survival outcome of CRC. This research indented to screen whether exist potential prognostic effect of lncRNA SNHGs in CRC patientss using comprehensive review and meta-analysis.

Methods

Systematic searches were performed from the six relevant databases from inception to October 20, 2022. The quality of published papers was evaluated in details. We pooled the hazard ratios (HR) with 95% confidence interval (CI) through direct or indirect collection of effect sizes, and odds ratios (OR) with 95% CI by collecting effect sizes within articles. Detailed downstream signaling pathways of lncRNA SNHGs were summarized in detail.

Results

25 eligible publications including 2,342 patients were finally included to appraise the association of lncRNA SNHGs with prognosis of CRC. Elevated lncRNA SNHGs expression was revealed in colorectal tumor tissues. High lncSNHG expression means bad survival prognosis in CRC patients (HR=1.635, 95% CI: 1.405-1.864, P<0.001). Additionally, high lncRNA SNHGs expression was inclined to later TNM stage (OR=1.635, 95% CI: 1.405-1.864, P<0.001), distant lymph node invasion, distant organ metastasis, larger tumor diameter and poor pathological grade. Begg's funnel plot test using the Stata 12.0 software suggested that no significant heterogeneity was found.

Conclusion

Elevated lncRNA SNHGs expression was revealed to be positively correlated to discontented CRC clinical outcome and lncRNA SNHG may act as a potential clinical prognostic index for CRC patients.

LncRNA NEAT1-miR-101-3p/miR-335-5p/miR-374a-3p/miR-628-5p-TRIM6 axis identified as the prognostic biomarker for lung adenocarcinoma via bioinformatics and meta-analysis

BACKGROUND

Overexpression of the tripartite motif containing 6 (TRIM6) is associated with dismal prognosis in cancer patients, but its exact roles in lung adenocarcinoma (LUAD) have not been reported.

METHODS

The roles of TRIM6 are identified by using The Cancer Genome Atlas (TCGA), TIMER2, Gene Expression Omnibus (GEO), etc., and the regulatory networks and related-prognostic biomarkers of TRIM6 are identified via the ENCORI and LNCAR databases in the LUAD progression.

RESULTS

TRIM6 expression level in LUAD tissues was significantly increased. TRIM6 over-expression level in LUAD patients was associated with smoking, clinical stage, histological type, lymph node metastasis, TP53 mutation and dismal prognosis, and related to prognosis-related age, race, sex, clinical stage and tumor purity of LUAD patients. TRIM6 overexpression was associated with the levels of CD8+ T cells, macrophages, neutrophils and myeloid dendritic cells, and correlated with the levels of LUAD immune cell markers CD8A, IRF5, CD163, VSIG4, MS4A4A, ITGAM, HLA-DPA1, NRP1, ITGAX, etc. TRIM6 might influence the progression of LUAD by regulating homologous recombination, oocyte meiosis, and ubiquitin-mediated proteolysis. LUAD patients with overexpression of miR-101-3p, miR-335-5p, miR-374a-3p, miR-628-5p, and NEAT1 had a poor prognosis.

CONCLUSIONS

NEAT1-miR-101-3p/335-5p/374a-3p/628-5p-TRIM6 network, which we constructed from our results, might be an important factor in the dismal prognosis of LUAD patients.

Small nucleolar RNA and its potential role in breast cancer - A comprehensive review

Small Nucleolar RNAs (snoRNAs) are known for their canonical functions, including ribosome biogenesis and RNA modification. snoRNAs act as endogenous sponges that regulate miRNA expression. Thus, precise snoRNA expression is critical for fine-tuning miRNA expression. snoRNAs processed into miRNA-like sequences play a crucial role in regulating the expression of protein-coding genes similar to that of miRNAs. Recent studies have linked snoRNA deregulation to breast cancer (BC). Inappropriate snoRNA expression contributes to BC pathology by facilitating breast cells to acquire cancer hallmarks. Since snoRNAs show significant differential expression in normal and cancer conditions, measuring snoRNA levels could be useful for BC prognosis and diagnosis. The present article provides a comprehensive overview of the role of snoRNAs in breast cancer pathology. More specifically, we have discussed the regulation, biological function, signaling pathways, and clinical utility of abnormally expressed snoRNAs in BC. Besides, we have also discussed the role of snoRNA host genes in breast tumorigenesis and emerging and future research directions in the field of snoRNA and cancer.