Bioinformatics analysis of gene expression profile of serous ovarian carcinomas to screen key genes and pathways

Mitotic Functions and Characters of KIF11 in Cancers

Mitosis mediates the accurate separation of daughter cells, and abnormalities are closely related to cancer progression. KIF11, a member of the kinesin family, plays a vital role in the formation and maintenance of the mitotic spindle. Recently, an increasing quantity of data have demonstrated the upregulated expression of KIF11 in various cancers, promoting the emergence and progression of cancers. This suggests the great potential of KIF11 as a prognostic biomarker and therapeutic target. However, the molecular mechanisms of KIF11 in cancers have not been systematically summarized. Therefore, we first discuss the functions of the protein encoded by KIF11 during mitosis and connect the abnormal expression of KIF11 with its clinical significance. Then, we elucidate the mechanism of KIF11 to promote various hallmarks of cancers. Finally, we provide an overview of KIF11 inhibitors and outline areas for future work.

Novel immune-related gene signature for risk stratification and prognosis prediction in ovarian cancer

BACKGROUND

The immune system played a multifaceted role in ovarian cancer (OC) and was a significant mediator of ovarian carcinogenesis. Various immune cells and immune gene products played an integrated role in ovarian cancer (OC) progression, proved the significance of the immune microenvironment in prognosis. Therefore, we aimed to establish and validate an immune gene prognostic signature for OC patients' prognosis prediction.

METHODS

Differently expressed Immune-related genes (DEIRGs) were identified in 428 OC and 77 normal ovary tissue specimens from 9 independent GEO datasets. The Cancer Genome Atlas (TCGA) cohort was used as a training cohort, Univariate Cox analysis was used to identify prognostic DEIRGs in TCGA cohort. Then, an immune gene-based risk model for prognosis prediction was constructed using the LASSO regression analysis, and validated the accuracy and stability of the model in 374 and 93 OC patients in TCGA training cohort and International Cancer Genome Consortium (ICGC) validation cohort respectively. Finally, the correlation among risk score model, clinicopathological parameters, and immune cell infiltration were analyzed.

RESULTS

Five DEIRGs were identified to establish the immune gene signature and divided OC patients into the low- and high-risk groups. In TCGA and ICGC datasets, patients in the low-risk group showed a substantially higher survival rate than high-risk group. Receiver operating characteristic (ROC) curves, t-distributed stochastic neighbor embedding (t-SNE) analysis and principal component analysis (PCA) showed the good performance of the risk model. Clinicopathological correlation analysis proved the risk score model could serve as an independent prognostic factor in 2 independent datasets.

CONCLUSIONS

The prognostic model based on immune-related genes can function as a superior prognostic indicator for OC patients, which could provide evidence for individualized treatment and clinical decision making.

Current Progress and Perspectives of CDC20 in Female Reproductive Cancers

The cancers of the cervix, endometrium, ovary, and breast are great threats to women's health. Cancer is characterized by the uncontrolled proliferation of cells and deregulated cell cycle progression is one of the main causes of malignancy. Agents targeting cell cycle regulators may have potential anti-tumor effects. CDC20 (cell division cycle 20 homologue) is a co-activator of the anaphase-promoting complex/cyclosome (APC/C) and thus acts as a mitotic regulator. In addition, CDC20 serves as a subunit of the mitotic checkpoint complex (MCC) whose function is to inhibit APC/C. Recently, higher expression of CDC20 has been reported in these cancers and was closely associated with their clinicopathological parameters, indicating CDC20 a potential target for cancer treatment that is worth further study. In the present review, we summarized current progress and put forward perspectives of CDC20 in female reproductive cancers.

CDC20 is a novel biomarker for improved clinical predictions in epithelial ovarian cancer

Epithelial ovarian cancer (EOC), a common tumor of the female reproductive system, ranks first in fatalities among gynecological malignancies. Most patients find tumors at late stage and have extremely poor prognoses, which necessitates improvements in early detection. This study applied bioinformatic methods to identify potential biomarkers of EOC. First, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on differentially expressed genes (DEGs) and hub genes, and a protein-protein interaction (PPI) network was constructed. The network of hub genes was analyzed using GeneMANIA, and an analysis of biological processes was constructed with BINGO. Lastly, hub genes were analyzed for EOC-related oncology using the Oncomine and TCGA databases, and the cBioPortal online platform. Overall, cell division cycle 20 (CDC20) was identified as a key gene in EOC. Short hairpin RNA (shRNA) was used to silence CDC20 to explore its effects on EOC cell proliferation, apoptosis and SRY-related HMG-box 2 (SOX2) expression. DEGs were enriched in pathways related to cell cycle signaling, cancer, progesterone-mediated oocyte maturation, Wnt signaling and P53 signaling. Analysis revealed high expression of CDC20 in EOC tissues and a correlation with histology and tumor grade. CDC20 levels are highest in serous adenocarcinoma, when compared to ovarian clear cell carcinoma, ovarian endometrioid carcinoma and mucinous adenocarcinoma. High CDC20 expression within the tumor is associated with poor EOC prognosis. After silencing CDC20, EOC cell proliferation and migration decreased, apoptosis increased, and SOX2 expression decreased. In conclusion, CDC20 is likely a key biomarker of EOC and may act as an upstream regulator of SOX2 to mediate the SOX2 signaling in the progression of EOC. Future application of CDC20 analysis to early detection may improve prognosis, and it has the potential to be a therapeutic target.

Leveraging Genomics, Transcriptomics, and Epigenomics to Understand the Biology and Chemoresistance of Ovarian Cancer

Ovarian cancer is a major cause of fatality due to a gynecological malignancy. This lethality is largely due to the unspecific clinical manifestations of ovarian cancer, which lead to late detection and to high resistance to conventional therapies based on platinum. In recent years, we have advanced our understanding of the mechanisms provoking tumor relapse, and the advent of so-called omics technologies has provided exceptional tools to evaluate molecular mechanisms leading to therapy resistance in ovarian cancer. Here, we review the contribution of genomics, transcriptomics, and epigenomics techniques to our knowledge about the biology and molecular features of ovarian cancers, with a focus on therapy resistance. The use of these technologies to identify molecular markers and mechanisms leading to chemoresistance in these tumors is discussed, as well as potential further applications.

Modelling the Functions of Polo-Like Kinases in Mice and Their Applications as Cancer Targets with a Special Focus on Ovarian Cancer

Polo-like kinases (PLKs) belong to a five-membered family of highly conserved serine/threonine kinases (PLK1-5) that play differentiated and essential roles as key mitotic kinases and cell cycle regulators and with this in proliferation and cellular growth. Besides, evidence is accumulating for complex and vital non-mitotic functions of PLKs. Dysregulation of PLKs is widely associated with tumorigenesis and by this, PLKs have gained increasing significance as attractive targets in cancer with diagnostic, prognostic and therapeutic potential. PLK1 has proved to have strong clinical relevance as it was found to be over-expressed in different cancer types and linked to poor patient prognosis. Targeting the diverse functions of PLKs (tumor suppressor, oncogenic) are currently at the center of numerous investigations in particular with the inhibition of PLK1 and PLK4, respectively in multiple cancer trials. Functions of PLKs and the effects of their inhibition have been extensively studied in cancer cell culture models but information is rare on how these drugs affect benign tissues and organs. As a step further towards clinical application as cancer targets, mouse models therefore play a central role. Modelling PLK function in animal models, e.g., by gene disruption or by treatment with small molecule PLK inhibitors offers promising possibilities to unveil the biological significance of PLKs in cancer maintenance and progression and give important information on PLKs' applicability as cancer targets. In this review we aim at summarizing the approaches of modelling PLK function in mice so far with a special glimpse on the significance of PLKs in ovarian cancer and of orthotopic cancer models used in this fatal malignancy.