RNA-sequencing for transcriptional profiling of whole blood in early stage and metastatic pancreatic cancer patients.
Sima KalantariBahram KazemiRaheleh RoudiHakimeh ZaliAlberto D'AngeloAshraf MohamadkhaniZahra MadjdAkram PorshamsPublished in: Cell biology international (2022)
We investigated the transcriptional profile of whole blood in early and metastatic stages of pancreatic cancer (PaC) patients to identify potential diagnostic factors for early diagnosis. Blood samples from 18 participants (6 healthy individuals, 6 patients in early stage (I/II) PaC, and 6 patients in metastatic PaC) were analyzed by RNA-sequencing. The expression levels of identified genes were subsequently compared with their expression in pancreatic tumor tissues based on TCGA data reported in UALCAN and GEPIA2 databases. Overall, 331 and 724 genes were identified as differentially expressed genes in early and metastatic stages, respectively. Of these, 146 genes were shared by early and metastatic stages. Upregulation of PTCD3 and UBA52 genes and downregulation of A2M and ARID1B genes in PaC patients were observed from early stage to metastasis. TCGA database showed increasing trend in expression levels of these genes from stage I to IV in pancreatic tumor tissue. Finally, we found that low expression of PTCD3, A2M, and ARID1B genes and high expression of UBA52 gene were positively correlated with PaC patients survival. We identified a four-gene set (PTCD3, UBA52, A2M, and ARID1B) expressed in peripheral blood of early stage and metastatic PaC patients that may be useful for PaC early diagnosis.
Keyphrases
- end stage renal disease
- early stage
- ejection fraction
- newly diagnosed
- small cell lung cancer
- squamous cell carcinoma
- poor prognosis
- peritoneal dialysis
- emergency department
- gene expression
- peripheral blood
- single cell
- cell proliferation
- machine learning
- oxidative stress
- high resolution
- climate change
- radiation therapy
- dna methylation
- transcription factor
- long non coding rna
- big data
- binding protein
- neoadjuvant chemotherapy
- genome wide analysis