In this study, we used the RRA methods to jointly analyzed six GEO ovarian cancer microarrays which contain 201 ovarian cancer and 64 normal samples, identifying 605 DEGs and overlapped them with dysregulated genes of OC cohort from TCGA and GETx portal, finally getting 164 up-regulated and 80 down-regulated genes.
Functional analysis showed that 244 DEGs were significantly enriched in the cell division cycle, to be clear, in the process of the mitotic spindle. Spindle microtubules have been proved to play crucial role in physiological and pathological processes. As for cell division, only when all chromosomes linked to spindle microtubules through kinetochores and the spindle assembly checkpoint is satisfied, this process could step to anaphase. Suraokar et.al found that the mitotic spindle assembly checkpoint and microtubule network were significantly altered in malignant pleural mesothelioma (MPM) while using epothilone-B, a non-taxane small molecule inhibitor targeting the microtubules, could greatly decrease the viability of MPM cell lines . Rogalska et.al compared the anti-proliferative capacity of epothilone B with paclitaxel on ovarian cancer cell line SKOV-3, found that this effect of Epo B was greater than latter. The researches above were consistent with our study that the mitotic spindle process was dysregulated in OC progression, playing important roles in ovarian cancer cell proliferation and tumor development.
PPI network construction of 244 DEGs includes 238 nodes and 1284 edges, among which we identified 3 key modules. Interestingly, the top1 module was also highly associated with spindle microtubules and chromosome kinetochore, confirming the role of cell cycle in OC pathogenesis. The top ten hub genes from the PPI network were also recognized, which are CDC45, CDK1, TOP2A, CDC20, CCNB1, CEP55, UBE2C, HMMR, FOXM1, and TPX2. Among them, CCNB1, UBE2C, CDK1, CEP55 as well as FOXM1 were found overexpressed in high-grade tumors and predicted worse outcomes. Besides, FOXM1, CDC20 and CCNB1were the most frequent altered genes. These genes were reported to closely associated with the BRCA1/2 mutation process of ovarian cancer. It has been reported that females with BRCA1 or BRCA2 mutations were much more susceptible to get ovarian cancer, accounting for the majority of the cohort. Treszezamsky et.al found that BRCA1- and BRCA2-deficient cells are sensitive to Etoposide, which targeting topoisomerase II (TOP2A) and inducing DNA double-strand breaks . High expression of CCNB1 was also observed in BRCA1-mutant cancer and induction of vinblastine targeting CCNB1 could significantly reduce tumor progression. BRCA2 could interact with Filamin A actin-binding protein, further recruiting endosomal sorting complex required for transport (ESCRT)-associated proteins, Alix and Tsg101, and forming CEP55-Alix and CEP55-Tsg101 complexes at the midbody. The disruption of these processes by BRCA2 mutations results in increased cytokinetic defects, in part explain the instability of whole-chromosome in BRCA2-deficient ovarian cancer and propose potential therapeutic target of CEP55. Olaparib, as a PARP inhibitor (PARP-i), has been widely used in BRCA1 or BRCA2 mutated ovarian cancer patients’ treatment. However, Fang et.al found that Olaparib-induced adaptive response could be disrupted by FOXM1 while inhibiting FOXM1 by Thiostrepton could significantly enhance sensitivity to PARP-i. It is noteworthy that other genes were also been reported in previous studies of cancer. Yang et.al reported that CDC45 activated by DNA J heat shock protein family (Hsp40) member A1 (DNAJA1) could be reversed by KNK437 in colorectal cancer. The joint treatment of KNK437 with 5-FU/L-OHP chemotherapy significantly reduced liver metastasis of CRC. Cyclin-dependent kinase 1 (CDK1), a key regulator for cell cycle, was overexpressed in paclitaxel-resistant ovarian cancer and predicted a poor overall survival, while miR-490-3P could reduce CDK1 expression, impeding ovarian cancer cell proliferation  and Alsterpaullone could effectively reverse the drug-resistant trend. Through searching CMap, we found Trichostatin A, pyrvinium and 8-azaguanine negatively correlated to the genomic-wide changes of OC. Trichostatin A has been proved to enhance the apoptotic potential of Palladium nanoparticles and increased the therapeutic potential in cervical cancer. Likewise, co-treatment with BEZ235 and Trichostatin A enhanced autophagic cell death via up-regulating LC3B-II and Beclin-1 expression, finally exerting anti-tumor activity in breast cancer. Pyrvinium was found to inhibit cell autophagy and promote cancer cell death. The combination of pyrvinium with autophagy stimuli improves its toxicity against cancer cells. 8-azaguanine has also been used for treatment of various carcinoma, sarcoma, osteogenic sarcoma, lymphosarcoma and melanoma. Hence, except for cisplatin or PARPi in treating ovarian cancer, such small molecules may also reverse the malignant phenotypes of OC and serve as potential drugs for therapy.
By performing Univariate and multivariate Cox regression analysis, as well as LASSO regression methods for 244 DEGs, we developed an eight-mRNA model that could classify OC patients into the high- and low-risk group with significantly different overall survival. We explored the regulatory mechanism of eight-mRNAs in the signature by searching the published article, the majority of which were reported to be associated with tumorigenesis and tumor proliferation. DEFB1 is commonly considered as a single copy gene that encodes beta-defensin 1 (BD-1), a member of the host defense peptide group. In human cancers, BD-1 is proposed to inhibit cell growth and promote apoptosis, acting as a tumor suppressor[21, 22]. Zhang et.al found that forkhead box G1 (FOXG1) and miR-422a negatively regulated each other, forming a double-negative feedback loop to modulate the development and metastasis of hepatocellular carcinoma. KRTCAP3 was reported to be overexpressed in gastric cancer and human keratinocytes[23, 24] while KLHL14 participated in the development and metastasis of endometrial cancer. Besides, KLHL14 was also found to mutate in primary central nervous system lymphoma (PCNSL), playing a role in CNS development. Kyle et al proposed that SYNE4, as an outer nuclear membrane protein, could induce kinesin-mediated cell polarization. The mutation of SYNE4 mediated the distinct disease phenotypes, acting as disease-causing behavior. However, contrary to our observation, CXCR4 is observed to highly expressed in high-grade serous epithelial ovarian cancer which positively related to tumor dissemination and metastasis while CCDC80 is down-regulated in papillary thyroid carcinomas and considered as a tumor suppressor role[29, 30]. Treating with CXCR4 antagonists significantly inhibits tumor pro-invasive phenotype and knockdown of CCDC80 is susceptible to developed thyroid adenoma and ovarian cancer [31, 32]. Note that the role of TMC4 in ovarian cancer pathogenesis has not been studied. This may offer a new direction for TMC4 in ovarian cancer research. More recently, the prognostic value of mRNA-related signature has been reported in several studies[33, 34]. However, current traditional clinical risk factors and clinical models have limited success in predicting OC patients’ outcomes due to the molecular heterogeneity and false-positive rate. Our LASSO regression model results with independent validation suggested that the combination of eight mRNA has good robustness and reproducibility in predicting prognosis for OC patients independent from traditional clinical risk factors, with the area under the ROC curve (AUC) marked 0.815, significantly higher than tumor stage, grade, and patients’ age.
To investigate the biological function of various types of immune cells regarding ovarian cancer, we explored the relative gene of each immune cell type and found that macrophage part expressed expressively higher in high-risk group in both training and testing cohort, pointing out the oncogenic-role of macrophages in ovarian cancer development. Macrophage, as a type of immune-related cells, has already been considered to be closely associated with the malignant biological behavior of various cancers. M2 macrophage-like tumor-associated macrophages (TAMs) secreted EGF and then activated EGFR on tumor cells, further upregulating VEGF/VEGF-R signaling in surrounding tumor cells to finally mediate ovarian cancer cell proliferation and migration. The exosomal miR-223 derived from macrophages under hypoxia condition reduced PTEN expression and led to increased PI3K/AKT signal activation, consequently mediated the drug resistance of EOC cells. Hence, the potential therapeutic tools targeting macrophages may provide new perspective into ovarian cancer treatment.
There are some highlights of our study. First of all, from the RRA integrated approach, we jointly explored six ovarian cancer datasets in GEO databases and TCGA OC patients’ data matrix, finding some interesting niche factors and unique modules that were not seen earlier. Second, this study discovered a multitude of differentially expressed genes and hub genes between ovarian cancer and normal tissues, as well as the mutation condition of these genes. This information summarizes the genetic-level changes during the pathophysiological process of ovarian cancer and provides possible target molecules for further research. Third, the prognostic model in our study can effectively predict OC patients’ outcomes, which provide a new method to help gynecologists evaluate patients’ prognosis in clinical practices.
However, some aspects of our study required improvement. First, our research was completely based on public data analysis, additional experimental studies are needed to explore the detailed molecular mechanism regarding DEGs and pathways, as well as the eight-mRNA prognostic model. Second, candidate drugs targeting hub genes and immune-related cells are needed to explore and clinical trials are also needed to verify whether the hub genes can be targeted to truly exert therapeutic effects and whether the prognostic model effectively predicts patients’ outcomes for OC. That said, with the ever-increasing accessibility and volume of genomic data from clinical patients and the continued development of technologies and algorithms, the bioinformatic analysis will further promote the progress of accurate diagnoses and personalized treatment in ovarian cancer.