Integrating Genetic and Transcriptomic Data to Reveal Pathogenesis and Prognostic Markers of Pancreatic Adenocarcinoma

PABPC1 promotes cell proliferation and metastasis in pancreatic adenocarcinoma by regulating COL12A1 expression

BACKGROUND

The expression of cytoplasmic poly (A) binding protein-1 (PABPC1) has been reported in multiple cancer types. This protein is known to modulate cancer progression. However, the effects of PABPC1 expression in pancreatic adenocarcinoma (PAAD) have not been investigated. Here, we investigate the regulatory targets and molecular mechanisms of PABPC1 in PAAD.

METHODS

PABPC1 and collagen type XII α1 chain (COL12A1) expression in PAAD and their role in tumor prognosis and tumor stage were investigated using The Cancer Genome Atlas database analysis. After silencing PABPC1, messenger RNA sequencing and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. The expression of differentially expressed genes (DEGs), cell viability, apoptosis, and cell migration and invasion were explored using reverse transcription-quantitative polymerase chain reaction, Cell Counting Kit-8 assay, flow cytometry assay, and transwell assay, respectively. The relationship between PABPC1 and COL12A1 expression was assessed by Pearson's correlation analysis. The regulatory function of COL12A1 in PABPC1-affected BXPC3 cell behavior was studied after COL12A1 was overexpressed.

RESULTS

PABPC1 and COL12A1 expression was upregulated in patients with PAAD and was linked to poor prognosis. Four hundred and seventy-four DEGs were observed in BXPC3 cells after PABPC1 silencing. GO and KEGG analyses revealed that the top 10 DEGs were enriched in cell adhesion pathways. Additionally, PABPC1 silencing inhibited cell viability, migration, and invasion and accelerated apoptosis in BXPC3 cells. PABPC1 silencing increased AZGP1 and ARHGAP30 expression and decreased CAV1 and COL12A1 expression in BXPC3 cells. PABPC1 positively mediated COL12A1 expression, whereas PABPC1 knockdown induced the inhibition of BXPC3 cell proliferation, migration, and invasion.

CONCLUSION

The results of this study indicate that PABPC1 may function as a tumor promoter in PAAD, accelerating BXPC3 cell proliferation and metastasis by regulating COL12A1 expression.

Recurrence- and Malignant Progression-Associated Biomarkers in Low-Grade Gliomas and Their Roles in Immunotherapy

Despite a generally better prognosis than high-grade glioma (HGG), recurrence and malignant progression are the main causes for the poor prognosis and difficulties in the treatment of low-grade glioma (LGG). It is of great importance to learn about the risk factors and underlying mechanisms of LGG recurrence and progression. In this study, the transcriptome characteristics of four groups, namely, normal brain tissue and recurrent LGG (rLGG), normal brain tissue and secondary glioblastoma (sGBM), primary LGG (pLGG) and rLGG, and pLGG and sGBM, were compared using Chinese Glioma Genome Atlas (CGGA) and Genotype-Tissue Expression Project (GTEx) databases. In this study, 296 downregulated and 396 upregulated differentially expressed genes (DEGs) with high consensus were screened out. Univariate Cox regression analysis of data from The Cancer Genome Atlas (TCGA) yielded 86 prognostically relevant DEGs; a prognostic prediction model based on five key genes (HOXA1, KIF18A, FAM133A, HGF, and MN1) was established using the least absolute shrinkage and selection operator (LASSO) regression dimensionality reduction and multivariate Cox regression analysis. LGG was divided into high- and low-risk groups using this prediction model. Gene Set Enrichment Analysis (GSEA) revealed that signaling pathway differences in the high- and low-risk groups were mainly seen in tumor immune regulation and DNA damage-related cell cycle checkpoints. Furthermore, the infiltration of immune cells in the high- and low-risk groups was analyzed, which indicated a stronger infiltration of immune cells in the high-risk group than that in the low-risk group, suggesting that an immune microenvironment more conducive to tumor growth emerged due to the interaction between tumor and immune cells. The tumor mutational burden and tumor methylation burden in the high- and low-risk groups were also analyzed, which indicated higher gene mutation burden and lower DNA methylation level in the high-risk group, suggesting that with the accumulation of genomic mutations and epigenetic changes, tumor cells continued to evolve and led to the progression of LGG to HGG. Finally, the value of potential therapeutic targets for the five key genes was analyzed, and findings demonstrated that KIF18A was the gene most likely to be a potential therapeutic target. In conclusion, the prediction model based on these five key genes can better identify the high- and low-risk groups of LGG and lay a solid foundation for evaluating the risk of LGG recurrence and malignant progression.