Wenjing Zhu

The roles of the small nucleolar RNA host gene family in ovarian cancer

Ovarian cancer is one of the most malignant tumors in women. Long noncoding RNAs have been demonstrated to regulate multiple biological processes, including cell proliferation, migration, apoptosis, and drug resistance, in various cancers. Small nucleolar RNA (snoRNA) host genes (SNHGs) are a group of long noncoding RNAs. Studies have reported that SNHGs are aberrantly expressed in many kinds of cancers and are associated with poor patient prognosis. In ovarian cancer, SNHGs play critical roles in the development and progression of ovarian cancer via different pathways. However, there is a lack of systematic reports on the research progress of SNHGs in ovarian cancer. Therefore, we reviewed the studies on the roles of SNHGs in the early diagnosis, development, and treatment of ovarian cancer and explored the underlying mechanisms to provide new insights into the treatment of ovarian cancer.

Identification of a novel nine‐SnoRNA signature with potential prognostic and therapeutic value in ovarian cancer

AbstractBackgroundIncreasing evidence has been confirmed that small nucleolar RNAs (SnoRNAs) play critical roles in tumorigenesis and exhibit prognostic value in clinical practice. However, there is short of systematic research on SnoRNAs in ovarian cancer (OV).Material/Methods379 OV patients with RNA‐Seq and clinical parameters from TCGA database and 5 paired clinical OV tissues were embedded in our study. Cox regression analysis was used to identify prognostic SnoRNAs and construct prediction model. SNORic database was adopted to examine the copy number variation of SnoRNAs. ROC curves and KM plot curves were applied to validate the prognostic model. Besides, the model was validated in 5 paired clinical tissues by real‐time PCR, H&E staining and immunohistochemistry.ResultsA prognostic model was constructed on the basis of SnoRNAs in OV patients. Patients with higher RiskScore had poor clinicopathological parameters, including higher age, larger tumor size, advanced stage and with tumor status. KM plot analysis confirmed that patients with higher RiskScore had poorer prognosis in subgroup of age, tumor size, and stage. 7 of 9 SnoRNAs in the prognostic model had positive correlation with their host genes. Moreover, 5 of 9 SnoRNAs in the prognostic model correlated with their CNVs, and SNORD105B had the strongest correction with its CNVs. ROC curve showed that the RiskScore had excellent specificity and accuracy. Further, results of H&E staining and immunohistochemistry of Ki67, P53 and P16 confirmed that patients with higher RiskScore are more malignant.ConclusionsIn summary, we identified a nine‐SnoRNAs signature as an independent indicator to predict prognosis of OV, providing a prospective prognostic biomarker and potential therapeutic targets for ovarian cancer.