Neuroendocrine gene subsets are uniquely dysregulated in prostate adenocarcinoma.
Nicole M NaranjoAnne KennedyAnna TestaCecilia E VerrilloAdrian D AltieriRhonda KeanD Craig HooperJindan YuJonathan ZhaoOliver AbinaderMaxwell W PicklesAdam HawkinsWilliam K KellyRamkrishna MitraLucia R LanguinoPublished in: Cancer biology & therapy (2024)
Prostate cancer has heterogeneous growth patterns, and its prognosis is the poorest when it progresses to a neuroendocrine phenotype. Using bioinformatic analysis, we evaluated RNA expression of neuroendocrine genes in a panel of five different cancer types: prostate adenocarcinoma, breast cancer, kidney chromophobe, kidney renal clear cell carcinoma and kidney renal papillary cell carcinoma. Our results show that specific neuroendocrine genes are significantly dysregulated in these tumors, suggesting that they play an active role in cancer progression. Among others, synaptophysin (SYP), a conventional neuroendocrine marker, is upregulated in prostate adenocarcinoma (PRAD) and breast cancer (BRCA). Our analysis shows that SYP is enriched in small extracellular vesicles (sEVs) derived from plasma of PRAD patients, but it is absent in sEVs derived from plasma of healthy donors. Similarly, classical sEV markers are enriched in sEVs derived from plasma of prostate cancer patients, but weakly detectable in sEVs derived from plasma of healthy donors. Overall, our results pave the way to explore new strategies to diagnose these diseases based on the neuroendocrine gene expression in patient tumors or plasma sEVs.
Keyphrases
- prostate cancer
- gene expression
- radical prostatectomy
- benign prostatic hyperplasia
- squamous cell carcinoma
- genome wide
- papillary thyroid
- end stage renal disease
- poor prognosis
- locally advanced
- squamous cell
- prognostic factors
- ejection fraction
- peritoneal dialysis
- transcription factor
- childhood cancer
- binding protein
- kidney transplantation
- patient reported outcomes
- long non coding rna
- breast cancer risk
- data analysis
- bioinformatics analysis