Long noncoding RNA BBOX1-AS1 promotes the progression of gastric cancer by regulating the miR-361-3p/Mucin 13 signaling axis

Comparative urine proteomic study involving papillary thyroid carcinoma and benign thyroid nodules

Introduction

Accurately differentiating benign and malignant lesions is essential for treatment. We aimed to determine differences in urine proteomics between papillary thyroid carcinomas (PTCs) and benign thyroid nodules (BTNs) and identify biomarkers for the differential diagnosis of these diseases.

Methods

We collected 155 specimens. In the discovery group, 30 PTC and 31 BTN specimens were quantitatively compared using liquid chromatography-tandem mass spectrometry (MS). The diagnostic value of each significantly altered protein was calculated in the MS validation comprising 11 PTC and 10 BTN samples. Ultimately, 36 BTN and 37 PTC specimens were used for ELISA validation.

Results and discussion

Overall, 2,479 proteins were used for quantitative analysis. Compared with benign nodules, papillary carcinomas showed significant increases and decreases in the levels of 169 and 27 proteins, respectively. Neck and thyroid tumors were enriched in the disease or function category. More than 100 proteins showed good performance in the area under the receiver operating characteristic curve (>0.8) upon MS validation. Semaphorin-6D showed good performance (AUC = 0.763) in ELISA validation. Urine proteomics is an effective diagnostic tool for distinguishing benign and malignant thyroid diseases. Semaphorin-6D may serve as a disease marker for large-scale validation and use. Additionally, this study identified potential biomarkers that warrant further investigation.

Clinical Significance and Immune Infiltration Analyses of a Novel Nerve-Related lncRNA Signature in Gastric Cancer

Gastric cancer (GC) is a progressive disease with high morbidity and mortality. Accumulating evidence indicated that nervous system-cancer crosstalk can affect the occurrence and progression of GC. However, the role of nerve-related lncRNAs (NRLs) in GC remains largely unexplored. In this study, a total of 441 nerve-related genes were collected from the KEGG database, and two approaches, unsupervised clustering and WGCNA, were employed to identify NRLs. Lasso regression analysis was then used to construct the nerve-related lncRNA signature (NRLS). Based on the expression profiles of 5 lncRNAs, we developed a stable NRLS to predict survival in GC patients, and survival analyses showed significantly shorter overall survival (OS) in patients with high NRLS. In addition, the NRLS was found to be positively correlated with immune characteristics, including tumor-infiltrating immune cells, immune modulators, cytokines and chemokines. We then analyzed the role of NRLS in predicting chemotherapy and immunotherapy responses, and constructed the OS nomogram combining NRLS and other clinical features. In conclusion, we constructed a robust NRLS model to stratify GC patients and predict the outcomes of chemotherapy and immunotherapy. This study can provide a new perspective for future individualized treatment of GC.

Evaluation of vital genes correlated with CD8 + T cell infiltration as prognostic biomarkers in stomach adenocarcinoma

BACKGROUND

Infiltration of CD8 + T cells in the tumor microenvironment is correlated with better prognosis in various malignancies. Our study aimed to investigate vital genes correlated with CD8 + T cell infiltration in stomach adenocarcinoma (STAD) and develop a new prognostic model.

METHODS

Using the STAD dataset, differentially expressed genes (DEGs) were analyzed, and co-expression networks were constructed. Combined with the CIBERSORT algorithm, the most relevant module of WGCNA with CD8 + T cell infiltration was selected for subsequent analysis. The vital genes were screened out by univariate regression analysis to establish the risk score model. The expression of the viral genes was verified by lasso regression analysis and in vitro experiments.

RESULTS

Four CD8 + T cell infiltration-related genes (CIDEC, EPS8L3, MUC13, and PLEKHS1) were correlated with the prognosis of STAD. Based on these genes, a risk score model was established. We found that the risk score could well predict the prognosis of STAD, and the risk score was positively correlated with CD8 + T cell infiltration. The validation results of the gene expression were consistent with TCGA. Furthermore, the risk score was significantly higher in tumor tissues. The high-risk group had poorer overall survival (OS) in each subgroup.

CONCLUSIONS

Our study constructed a new risk score model for STAD prognosis, which may provide a new perspective to explore the tumor immune microenvironment mechanism in STAD.

A review on the role of gamma-butyrobetaine hydroxylase 1 antisense RNA 1 in the carcinogenesis and tumor progression

Gamma-butyrobetaine hydroxylase 1 antisense RNA 1 (BBOX1-AS1), located on human chromosome 11 p14, emerges as a critical player in tumorigenesis with diverse oncogenic effects. Aberrant expression of BBOX1-AS1 intricately regulates various cellular processes, including cell growth, epithelial-mesenchymal transition, migration, invasion, metastasis, cell death, and stemness. Notably, the expression of BBOX1-AS1 was significantly correlated with clinical-pathological characteristics and tumor prognoses, and it could also be used for the diagnosis of lung and esophageal cancers. Through its involvement in the ceRNA network, BBOX1-AS1 competitively binds to eight miRNAs in ten different cancer types. Additionally, BBOX1-AS1 can directly modulate downstream protein-coding genes or act as an mRNA stabilizer. The implications of BBOX1-AS1 extend to critical signaling pathways, including Hedgehog, Wnt/β-catenin, and MELK/FAK pathways. Moreover, it influences drug resistance in hepatocellular carcinoma. The present study provides a systematic review of the clinical significance of BBOX1-AS1's aberrant expression in diverse tumor types. It sheds light on the intricate molecular mechanisms through which BBOX1-AS1 influences cancer initiation and progression and outlines potential avenues for future research in this field.

Prognostic effect of lncRNA BBOX1-AS1 in malignancies: a meta-analysis

Background: With the increasing number of new cancer cases and mortality rates, cancer has become a serious global health problem, but there are no ideal cancer biomarkers for effective diagnosis. Currently, mounting evidence demonstrates that lncRNAs play a fundamental role in cancer progression. BBOX1 anti-sense RNA 1 (BBOX1-AS1) is a recently clarified lncRNA and has been identified as dysregulated in various carcinomas, and it contributes to poor survival in cancer patients. Methods: We thoroughly searched six databases for eligible articles published as of 27, April 2023. The association of BBOX1-AS1 expression levels with prognostic and clinicopathological parameters was assessed by odds ratios (OR) and hazard ratios with 95% CIs. Additionally, we further validated our results utilizing the GEPIA online database. Results: Eight studies comprising 602 patients were included in this analysis. High BBOX1-AS1 expression indicated poor overall survival (OS) (hazard ratios = 2.30, 95% Cl [1.99, 2.67], p < 0.00001) when compared with low BBOX1-AS1 expression. Furthermore, BBOX1-AS1 expression was positively correlated with lymph node metastasis (OR = 3.00, 95% CI [1.71-5.28], p = 0.0001) and advanced tumor stage (OR = 3.74, 95% CI [2.63-5.32], p < 0.00001) for cancer patients. Moreover, BBOX1-AS1 was remarkably upregulated in 12 malignancies, and the elevated BBOX1-AS1 expression predicted poorer OS and worse disease-free survival (DFS) confirmed through the GEPIA online gene analysis tool. Conclusion: The findings highlight that BBOX1-AS1 was significantly associated with detrimental overall survival, disease-free survival, lymph node metastasis and tumor stage; thus, it could act as a novel promising biomarker to predict the clinicopathological characteristics and prognosis for various cancers.