Novel gene signatures for prognosis prediction in ovarian cancer

Abstract

Ovarian cancer (OV) is one of the leading causes of cancer deaths in women worldwide. Late diagnosis and heterogeneous treatment result to poor survival outcomes for patients with OV. Therefore, we aimed to develop novel biomarkers for prognosis prediction from the potential molecular mechanism of tumorigenesis. Eight eligible data sets related to OV in GEO database were integrated to identify differential expression genes (DEGs) between tumour tissues and normal. Enrichment analyses discovered DEGs were most significantly enriched in G2/M checkpoint signalling pathway. Subsequently, we constructed a multi‐gene signature based on the LASSO Cox regression model in the TCGA database and time‐dependent ROC curves showed good predictive accuracy for 1‐, 3‐ and 5‐year overall survival. Utility in various types of OV was validated through subgroup survival analysis. Risk scores formulated by the multi‐gene signature stratified patients into high‐risk and low‐risk, and the former inclined worse overall survival than the latter. By incorporating this signature with age and pathological tumour stage, a visual predictive nomogram was established, which was useful for clinicians to predict survival outcome of patients. Furthermore, SNRPD1 and EFNA5 were selected from the multi‐gene signature as simplified prognostic indicators. Higher EFNA5 expression or lower SNRPD1 indicated poorer outcome. The correlation between signature gene expression and clinical characteristics was observed through WGCNA. Drug‐gene interaction was used to identify 16 potentially targeted drugs for OV treatment. In conclusion, we established novel gene signatures as independent prognostic factors to stratify the risk of OV patients and facilitate the implementation of personalized therapies.

Aggressive and recurrent ovarian cancers upregulate ephrinA5, a non-canonical effector of EphA2 signaling duality

“…Yet, the epithelial OC cells display variable ephrinA/ EFNA expression (see Fig. 2 A) and high mRNA expression of EFNA5, encoding the ephrinA5 ligand, has been repeatedly associated to poor survival in OC patients 18 , 20 , 21 . Here we show that ephrinA5 protein levels are high specifically in the most aggressive HGSC and further upregulated transcriptionally upon disease progression.…”

“…High EFNA5 expression has been linked to poor survival in OC patients 18 , 20 , 21 although high ephrin levels in general are more frequently associated to favorable clinical outcome due to the transduction of tumor-suppressive signals upon EphA2-Y588 phosphorylation 12 , 31 . Intrigued by our observation of the opposite clinical association of EFNA5 and EFNA3 in OC TCGA data, we sought to investigate EFNA5 and the corresponding protein ephrinA5 clinically and functionally in HGSC.…”

Identification of a 9-gene signature related to stemness for prognosis in hepatocellular carcinoma basing on weighted gene coexpression network analysis

“…Small nuclear ribonucleoprotein Sm D1 (SNRPD1) is a novel gene signature for prognosis prediction in ovarian cancer (Bao et al, 2020). Overexpression of SNRPD1 is signi cantly associated with poor survival of lung adenocarcinomas (Yi et al, 2020).…”

Comprehensive Analysis of the Expression and Prognostic Value for Snrp Members in Hepatocellular Carcinoma

“…The increasing evidence showed the indispensable role of the splicing components in the initiation, angiogenesis, apoptosis, and invasion in cancers [7][8][9][10] . Relevant researches [11][12][13][14][15] had reported the difference of expression and clinical value of a single SNRP member in different types of cancers. The function of SNRPB as an oncogene served as a potential prognostic factor in HCC [11] .…”

“…Another research [12] displayed the mRNA expression of SNRPB might be a potent therapeutic target in cervical cancer by interfering with the alternaration of the p53 pathway. Besides, the high level of SNRPD1 was identifed as a predictive biomarker for tumorigenesis and poor prognosis of lung adenocarcinoma and ovarian cancer [13,14] . Even, siRNA depletion of SNRPE or SNRPD1, which contributed to cell death by autophagy, led to a marked reduction of cell viability in breast, lung, and melanoma cancer cell lines [15] .…”