TP53, SPOP and PIK3CA Genes Status in Prostate Cancer

Identification of pyroptosis-related lncRNA signature and AC005253.1 as a pyroptosis-related oncogene in prostate cancer

Background

Pyroptosis and prostate cancer (PCa) are closely related. The role of pyroptosis-related long non-coding RNAs (lncRNAs) (PRLs) in PCa remains elusive. This study aimed to explore the relationship between PRL and PCa prognosis.

Methods

Gene expression and clinical signatures were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. A PRL risk prediction model was established by survival random forest analysis and least absolute shrinkage and selection operator regression. Functional enrichment, immune status, immune checkpoints, genetic mutations, and drug susceptibility analyses related to risk scores were performed by the single-sample gene set enrichment analysis, gene set variation analysis, and copy number variation analysis. PRL expression was verified in PCa cells. Cell Counting Kit-8, 5-ethynyl-2′-deoxyuridine, wound healing, transwell, and Western blotting assay were used to detect the proliferation, migration, invasion, and pyroptosis of PCa cells, respectively.

Results

Prognostic features based on six PRL (AC129507.1, AC005253.1, AC127502.2, AC068580.3, LIMD1-AS1, and LINC01852) were constructed, and patients in the high-score group had a worse prognosis than those in the low-score group. This feature was determined to be independent by Cox regression analysis, and the area under the curve of the 1-, 3-, and 5-year receiver operating characteristic curves in the testing cohort was 1, 0.93, and 0.92, respectively. Moreover, the external cohort validation confirmed the robustness of the PRL risk prediction model. There was a clear distinction between the immune status of the two groups. The expression of multiple immune checkpoints was also reduced in the high-score group. Gene mutation proportion in the high-score group increased, and the sensitivity to drugs increased significantly. Six PRLs were upregulated in PCa cells. Silencing of AC005253.1 inhibited cell proliferation, migration, and invasion in DU145 and PC-3 cells. Moreover, silencing of AC005253.1 promoted pyroptosis and inflammasome AIM2 expression.

Conclusions

Overall, we constructed a prognostic model of PCa with six PRLs and identified their expression in PCa cells. The experimental verification showed that AC005253.1 could affect the proliferation, migration, and invasion abilities of PCa cells. Meanwhile, AC005253.1 may play an important role in PCa by affecting pyroptosis through the AIM2 inflammasome. This result requires further research for verification.

MicroRNA Dysregulation in Prostate Cancer

Prostate cancer biology is complex, and needs to be deciphered. The latest evidence reveals the significant role of non-coding RNAs, particularly microRNAs (miRNAs), as key regulatory factors in cancer. Therefore, the identification of altered miRNA patterns involved in prostate cancer will allow them to be used for development of novel diagnostic and prognostic biomarkers. Patients and Methods: We performed a miRNAs transcriptomic analysis, using microarray (10 matched pairs tumor tissue versus normal adjacent tissue, selected based on inclusion criteria), followed by overlapping with TCGA data. A total of 292 miRNAs were differentially expressed, with 125 upregulated and 167 downregulated in TCGA patients’ cohort with PRAD (prostate adenocarcinoma), respectively for the microarray experiments; 16 upregulated and 44 downregulated miRNAs were found in our cohort. To confirm our results obtained for tumor tissue, we performed validation with qRT-PCR at the tissue and plasma level of two selected transcripts, and finally, we focused on the identification of altered miRNAs involved in key biological processes. Results: A common signature identified a panel of 12 upregulated and 1 downregulated miRNA, targeting and interconnected in a network with the TP53, AGO2, BIRC5 gene and EGFR as a core element. Among this signature, the overexpressed transcripts (miR-20b-5p, miR-96-5p, miR-183-5p) and the downregulated miR-542-5p were validated by qRT-PCR in an additional patients’ cohort of 34 matched tumor and normal adjacent paired samples. Further, we performed the validation of the expression level for miR-20b-5p, miR-96-5p, miR-183-5p plasma, on the same patients’ cohort versus a healthy control group, confirming the overexpression of these transcripts in the PRAD group, demonstrating the liquid biopsy as a potential investigational tool in prostate cancer. Conclusion: In this pilot study, we provide evidence on miRNA dysregulation and its association with key functional components of the PRAD landscape, where an important role is acted by miR-20b-5p, miR-542-5p, or the oncogenic cluster miR-183-96-182.