Construction of a cuproptosis-associated long non-coding RNA risk prediction model for pancreatic adenocarcinoma based on the TCGA database

Cuproptosis is a recently identified controlled process of cell death that functions in tumor development and treatment. Long non-coding RNAs (lncRNAs) are RNA molecules longer than 200 nucleotides that bind to transcription factors and regulate tumor invasion, penetration, metastasis, and prognosis. However, there are limited data on the function of cuproptosis-associated lncRNAs in pancreatic adenocarcinoma. Utilizing data retrieved from the cancer genome atlas database, we devised a risk prediction model of cuproptosis-associated lncRNAs in pancreatic adenocarcinoma, determined their prognostic significance and relationship with tumor immunity, and screened potential therapeutic drugs. Overall, 178 patients were randomized to a training or test group. We then obtained 6 characteristic cuproptosis-associated lncRNAs from the training group, based on which we constructed the risk prediction model, calculated the risk score, and verified the test group results. Subsequently, we performed differential gene analysis, tumor immunoassays, functional enrichment analysis, and potential drug screening. Finally, we found that the prediction model was highly reliable for the prognostic assessment of pancreatic adenocarcinoma patients. Generally, low risk patients had better outcomes than high risk patients. A tumor immunoassay showed that immunotherapy may benefit high risk patients more as there is a greater likelihood that the tumors could escape the immune system in low-risk patients. Through drug screening, we identified ten drugs that may have therapeutic effects on patients with pancreatic adenocarcinoma. In conclusion, this study constructed a risk prediction model of cuproptosis-associated lncRNAs, which can reliably predict the prognosis of pancreatic adenocarcinoma patients, provided a clinical reference for determining treatment approach, and provided some insights into the associations between lncRNAs and cuproptosis. This provides useful insight to aid in the development of therapeutic drugs for pancreatic adenocarcinoma.

Aberrant brain-expressed X-linked 4 (BEX4) expression is a novel prognostic biomarker in gastric cancer

BACKGROUND

This study aimed to investigate the expression level of X-linked 4 (BEX4) in patients with gastric cancer (GC) and to investigate the prognostic significance of BEX4.

METHODS

The mRNA expression of BEX4 was analyzed using the Cancer Genome Atlas (TCGA) datasets. The relationship between the expression of BEX4 and GC patient survival was assessed using a Kaplan-Meier plot and Log Rank test. Multivariate cox regression analysis was used to evaluate prognostic factor. The diagnostic value of BEX4 expression in GC tissue was determined through receiver operating characteristic (ROC) curve analysis. Gene set enrichment analysis (GSEA) was used to explore BEX-4 related signaling pathways in GC. Furthermore, the Human Protein Atlas (HPA) database and GSE62254 dataset were used for further validation.

RESULTS

BEX4 was expressed at lower level in GC tissues than normal gastric tissues. The lower expression of BEX4 was also validated at protein level in HPA database. The area under the ROC curve for BEX4 expression in normal gastric tissue and GC was 0.791, which presented modest diagnostic value. Kaplan-Meier survival analysis revealed that patients in low BEX4 expression group had a worse prognosis than those with high BEX4 expression (P = .009). Multivariate analysis showed that BEX4 is an independent risk factor for overall survival both in TCGA and GSE62254 (P = .0142, .013, respectively). GSEA identified that the expression of BEX4 was related to DNA replication, RNA polymerase, cell cycle, and P53 signaling pathway.

CONCLUSION

BEX4 is expressed at low levels in GC. BEX4 expression independently predicted poor OS for GC. It is a promising independent molecular predictor for the diagnosis and prognosis of GC.

Human Hematopoietic Signal peptide-containing Secreted 1 (hHSS1) modulates genes and pathways in glioma: implications for the regulation of tumorigenicity and angiogenesis

BACKGROUND

Human Hematopoietic Signal peptide-containing Secreted 1 (hHSS1) is a truly novel protein, defining a new class of secreted factors. We have previously reported that ectopic overexpression of hHSS1 has a negative modulatory effect on cell proliferation and tumorigenesis in glioblastoma model systems. Here we have used microarray analysis, screened glioblastoma samples in The Cancer Genome Atlas (TCGA), and studied the effects of hHSS1 on glioma-derived cells and endothelial cells to elucidate the molecular mechanisms underlying the anti-tumorigenic effects of hHSS1.

METHODS

Gene expression profiling of human glioma U87 and A172 cells overexpressing hHSS1 was performed. Ingenuity® iReport™ and Ingenuity Pathway Analysis (IPA) were used to analyze the gene expression in the glioma cells. DNA content and cell cycle analysis were performed by FACS, while cell migration, cell invasion, and effects of hHSS1 on HUVEC tube formation were determined by transwell and matrigel assays. Correlation was made between hHSS1 expression and specific genes in glioblastoma samples in the TCGA database.

RESULTS

We have clarified the signaling and metabolic pathways (i.e. role of BRCA1 in DNA damage response), networks (i.e. cell cycle) and biological processes (i.e. cell division process of chromosomes) that result from hHSS1effects upon glioblastoma growth. U87-overexpressing hHSS1 significantly decreased the number of cells in the G0/G1 cell cycle phase, and significantly increased cells in the S and G2/M phases (P < 0.05). U87-overexpressing hHSS1 significantly lost their ability to migrate (P < 0.001) and to invade (P < 0.01) through matrigel matrix. hHSS1-overexpression significantly decreased migration of A172 cells (P < 0.001), inhibited A172 tumor-induced migration and invasion of HUVECs (P < 0.001), and significantly inhibited U87 tumor-induced invasion of HUVECs (P < 0.001). Purified hHSS1 protein inhibited HUVEC tube formation. TCGA database revealed significant correlation between hHSS1 and BRCA2 (r = -0.224, P < 0.0005), ADAMTS1 (r = -0.132, P <0.01) and endostatin (r = 0.141, P < 0.005).

CONCLUSIONS

hHSS1-overexpression modulates signaling pathways involved in tumorigenesis. hHSS1 inhibits glioma-induced cell cycle progression, cell migration, invasion and angiogenesis. Our data suggest that hHSS1 is a potential therapeutic for malignant glioblastoma possessing significant antitumor and anti-angiogenic activity.