RNA-seq Reveals the Overexpression of IGSF9 in Endometrial Cancer.
Zonggao ShiChunyan LiLaura TarwaterJun LiYang LiWilliam KalineyDarshan S ChandrashekarM Sharon StackPublished in: Journal of oncology (2018)
We performed RNA-seq on an Illumina platform for 7 patients with endometrioid endometrial carcinoma for which both tumor tissue and adjacent noncancer tissue were available. A total of 66 genes were differentially expressed with significance level at adjusted p value < 0.01. Using the gene functional classification tool in the NIH DAVID bioinformatics resource, 5 genes were found to be the only enriched group out of that list of genes. The gene IGSF9 was chosen for further characterization with immunohistochemical staining of a larger cohort of human endometrioid carcinoma tissues. The expression level of IGSF9 in cancer cells was significantly higher than that in control glandular cells in paired tissue samples from the same patients (p = 0.008) or in overall comparison between cancer and the control (p = 0.003). IGSF9 expression is higher in patients with myometrium invasion relative to those without invasion (p = 0.015). Reanalysis of RNA-seq dataset from The Cancer Genome Atlas shows higher expression of IGSF9 in endometrial cancer versus normal control and expression was associated with poor prognosis. These results suggest IGSF9 as a new biomarker in endometrial cancer and warrant further studies on its function, mechanism of action, and potential clinical utility.
Keyphrases
- endometrial cancer
- rna seq
- poor prognosis
- single cell
- long non coding rna
- genome wide
- genome wide identification
- end stage renal disease
- papillary thyroid
- high throughput
- chronic kidney disease
- machine learning
- squamous cell carcinoma
- dna methylation
- newly diagnosed
- deep learning
- genome wide analysis
- cell death
- cell migration
- ejection fraction
- peritoneal dialysis
- prognostic factors
- squamous cell
- pi k akt
- lymph node metastasis