High BANCR expression is associated with worse prognosis in human malignant carcinomas: an updated systematic review and meta-analysis

Clinicopathological and prognostic value of lncRNA TPT1-AS1 in cancer: a systematic review study and meta-analysis

INTRODUCTION

Aberrant expression of lncRNAs in cancer cells can impact their key phenotypes. We aimed to summarize available evidence on clinicopathological and prognostic value of lncRNA TPT1-AS1 in cancer.

METHODS

A systematic search was performed on Medline and Embase databases using relevant key terms covering lncRNA TPT1-AS1, cancer, and clinical outcomes. The effect size estimates and their 95 % confidence interval (CI) were pooled using random-effects models. Meta- analyses were conducted using STATA 16.0 software.

RESULTS

Seventeen articles met our eligibility criteria. Tumor tissue compared to normal tissue showed increased level of lncRNA TPT1-AS1 expression (pooled standardized mean difference (95 % CI): 0.65 (0.52-0.79)). Overexpression of this lncRNA was a significant predictor for poor prognosis (Pooled log-rank test P-value < 0.001); in patients with high-level of lncRNA TPT1-AS1, the risk of death at five years was 1.40 times greater than their counterparts. The pooled Odds ratios for association lncRNA TPT1-AS1 with tumor stage, tumor size, and lymph node metastasis were 1.94 (95 % CI: 0.90-4.19, 8 studies, I² = 79.6 %), 2.33 (95 % CI: 1.31-4.14, 5 studies, I² = 40.0 %), and 1.89 (95 % CI: 1.08-3.36, 5 studies, I² = 61.7 %), respectively. Regarding the identified potential mechanisms, lncRNA TPT1-AS1 plays a role in cancer growth mainly by sponging miRNAs and regulating their downstream targets or controlling the expression of key cell cycle regulators.

CONCLUSION

In cancer patients, elevated expression of lncRNA TPT1-AS1 might be associated with a shorter Overall Survival, advanced stages, larger tumor size, and lymph node metastasis.

Identification of Prognostic Model Based on Immune-Related LncRNAs in Stage I-III Non-Small Cell Lung Cancer

Background

Long non-coding RNAs (lncRNAs) participate in the regulation of immune response and carcinogenesis, shaping tumor immune microenvironment, which could be utilized in the construction of prognostic signatures for non-small cell lung cancer (NSCLC) as supplements.

Methods

Data of patients with stage I-III NSCLC was downloaded from online databases. The least absolute shrinkage and selection operator was used to construct a lncRNA-based prognostic model. Differences in tumor immune microenvironments and pathways were explored for high-risk and low-risk groups, stratified by the model. We explored the potential association between the model and immunotherapy by the tumor immune dysfunction and exclusion algorithm.

Results

Our study extracted 15 immune-related lncRNAs to construct a prognostic model. Survival analysis suggested better survival probability in low-risk group in training and validation cohorts. The combination of tumor, node, and metastasis staging systems with immune-related lncRNA signatures presented higher prognostic efficacy than tumor, node, and metastasis staging systems. Single sample gene set enrichment analysis showed higher infiltration abundance in the low-risk group, including B cells (p<0.001), activated CD8+ T cells (p<0.01), CD4+ T cells (p<0.001), activated dendritic cells (p<0.01), and CD56+ Natural killer cells (p<0.01). Low-risk patients had significantly higher immune scores and estimated scores from the ESTIMATE algorithm. The predicted proportion of responders to immunotherapy was higher in the low-risk group. Critical pathways in the model were enriched in immune response and cytoskeleton.

Conclusions

Our immune-related lncRNA model could describe the immune contexture of tumor microenvironments and facilitate clinical therapeutic strategies by improving the prognostic efficacy of traditional tumor staging systems.