BRCA1 and MAD2 Are Coexpressed and Are Prognostic Indicators in Tubo-ovarian High-Grade Serous Carcinoma

Biomarkers in high grade serous ovarian cancer

High-grade serous ovarian cancer (HGSC) is the most common subtype of ovarian cancer. HGSC patients typically present with advanced disease, which is often resistant to chemotherapy and recurs despite initial responses to therapy, resulting in the poor prognosis associated with this disease. There is a need to utilise biomarkers to manage the various aspects of HGSC patient care. In this review we discuss the current state of biomarkers in HGSC, focusing on the various available immunohistochemical (IHC) and blood-based biomarkers, which have been examined for their diagnostic, prognostic and theranostic potential in HGSC. These include various routine clinical IHC biomarkers such as p53, WT1, keratins, PAX8, Ki67 and p16 and clinical blood-borne markers and algorithms such as CA125, HE4, ROMA, RMI, ROCA, and others. We also discuss various components of the liquid biopsy as well as a number of novel IHC biomarkers and non-routine blood-borne biomarkers, which have been examined in various ovarian cancer studies. We also discuss the future of ovarian cancer biomarker research and highlight some of the challenges currently facing the field.

Identification of MAD2L1 and BUB1B as Potential Biomarkers Associated with Progression and Prognosis of Ovarian Cancer

Ovarian cancer develops insidiously and is frequently diagnosed at advanced stages. Screening for ovarian cancer is an effective strategy for reducing mortality. This study aimed to investigate the molecular mechanisms underlying the development of ovarian cancer and identify novel tumor biomarkers for the diagnosis and prognosis of ovarian cancer. Three databases containing gene expression profiles specific to serous ovarian cancer (GSE18520, GSE12470, and GSE26712) were acquired. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were analyzed for the differentially expressed gene (DEGs). The protein-protein interaction (PPI) network was constructed using the STRING database. The pivotal genes in the PPI network were screened using the Cytoscape software. Survival curve analysis was performed using a Kaplan-Meier Plotter. The cancer genome atlas and Gene Expression Omnibus databases were used to find the relationship between Hub gene and serous ovarian cancer. PCR and immunohistochemistry were used to detect the expression of Hub gene in serous ovarian cancer tissues and cells. Downstream pathways of the candidate tumor marker genes were predicted using Gene Set Enrichment Analysis. In this study, 252 DEGs were screened for pathway enrichment. 20 Hub genes were identified. Survival analysis suggested that Aurka, Bub1b, Cenpf, Cks1b, Kif20a, Mad2l1, Racgap1, and Ube2c were associated with the survival of patients with serous ovarian cancer. MAD2L1 and BUB1B levels were significantly different in serous ovarian cancer at different stages. Finally, Mad2l1 was found to play a role in the cell cycle, oocyte meiosis, and ubiquitin-mediated proteolysis. Meanwhile, Bub1b may play a role in the cell cycle, ubiquitin-mediated proteolysis, and spliceosome processes. Mad2l1 and Bub1b could be used as markers to predict ovarian carcinogenesis and prognosis, providing candidate targets for the diagnosis and treatment of serous ovarian cancer.

Establishing the role of BRCA1 in the diagnosis, prognosis and immune infiltrates of breast invasive cancer by bioinformatics analysis and experimental validation

BACKGROUND

Breast cancer susceptibility gene 1 (BRCA1) is a well-known gene that acts a vital role in suppressing the growth of tumors. Previous studies have primarily focused on the genetic mutations of BRCA1 and its association with hereditary breast invasive carcinoma (BRCA). However, little research has been done to investigate the relationship between BRCA1 and immune infiltrates and prognosis in BRCA.

METHODS

We obtained the expression profiles and clinical information of patients with BRCA from the Cancer Genome Atlas (TCGA) database. The levels of the BRCA1 gene between BRCA tissues and normal breast tissues were compared through the Wilcoxon rank-sum test. Additionally, we performed WB and RT-qPCR techniques to detect the expression of BRCA1. We conducted functional enrichment analyses. Furthermore, we assessed immune cell infiltration using a single-sample gene set enrichment analysis. The methylation status of the BRCA1 gene was analyzed using the UALCAN and MethSurv databases. The Cox regression analysis and (KM) Kaplan-Meier method were employed to determine the prognostic value of BRCA1. In order to provide a practical tool for predicting the overall survival rates at different time points, we also constructed a nomogram.

RESULTS

Our analysis revealed that the expression of BRCA1 was significantly higher in BRCA tissues compared to normal tissues. Furthermore, this increased level of BRCA1 was found to be associated with specific BRCA subtypes, including T2, stage II, ER positive, ect. Importantly, the overexpression of BRCA1 was shown to be a negative prognostic marker for the overall survival rates of BRCA patients. Moreover, low methylation status of the BRCA1 gene was related to a poorer prognosis. Furthermore, our results indicated that high levels of BRCA1 are related to a decrease in level of killer immune cells, such as natural killer (NK) cells, macrophages, CD8+ T cells, and plasma-like dendritic cells (pDCs) within the tumor microenvironment.

CONCLUSIONS

Our study is the first to provide evidence indicating that the presence of BRCA1 can serve as a reliable marker for both diagnosing and determining the prognosis of BRCA. Moreover, BRCA1 acts as a crucial indicator of the cancer's potential to infiltrate and invade the immune system, which has important implications for developing targeted therapies in BRCA.

P53 and TLR4 expression are prognostic markers informing progression free survival of advanced stage high grade serous ovarian cancer

OBJECTIVE

New prognostic biomarkers, and bio-signatures, are urgently needed to facilitate a precision medicine-based approach to more effectively treat patients with high-grade serous ovarian cancer (HGSC). In this study, we analysed the expression patterns of a series of candidate protein biomarkers.

METHODS

The panel of markers which included MyD88, TLR4, MAD2, PR, OR, WT1, p53, p16, CD10 and Ki67 was assessed using immunohistochemistry in a tissue microarray (TMA) cohort of n = 80 patients, composed of stage 3-4 HGSCs. Each marker was analysed for their potential to predict both overall survival (OS) and progression-free survival (PFS).

RESULTS

TLR4 and p53 were found to be individually predictive of poorer PFS (Log Rank, p = 0.017, p = 0.030 respectively). Cox regression analysis also identified high p53 and TLR4 expression as prognostic factors for reduced PFS (p53; HR=1.785, CI=1.036-3.074, p = 0.037 and TLR4; HR=2.175, CI=1.112-4.253, p = 0.023). Multivariate forward conditional Cox regression analysis, examining all markers, identified a combined signature composed of p53 and TLR4 as prognostic for reduced PFS (p = 0.023).

CONCLUSION

Combined p53 and TLR4 marker assessment may help to aid treatment stratification for patients diagnosed with advanced-stage HGSC.

Mitotic checkpoint defects: en route to cancer and drug resistance

Loss of mitosis regulation is a common feature of malignant cells that leads to aberrant cell division with inaccurate chromosome segregation. The mitotic checkpoint is responsible for faithful transmission of genetic material to the progeny. Defects in this checkpoint, such as mutations and changes in gene expression, lead to abnormal chromosome content or aneuploidy that may facilitate cancer development. Furthermore, a defective checkpoint response is indicated in the development of drug resistance to microtubule poisons that are used in treatment of various blood and solid cancers for several decades. Mitotic slippage and senescence are important cell fates that occur even with an active mitotic checkpoint and are held responsible for the resistance. However, contradictory findings in both the scenarios of carcinogenesis and drug resistance have aroused questions on whether mitotic checkpoint defects are truly responsible for these dismal outcomes. Here, we discuss the possible contribution of the faulty checkpoint signaling in cancer development and drug resistance, followed by the latest research on this pathway for better outcomes in cancer treatment.

The role of the MAD2-TLR4-MyD88 axis in paclitaxel resistance in ovarian cancer

Despite the use of front-line anticancer drugs such as paclitaxel for ovarian cancer treatment, mortality rates have remained almost unchanged for the past three decades and the majority of patients will develop recurrent chemoresistant disease which remains largely untreatable. Overcoming chemoresistance or preventing its onset in the first instance remains one of the major challenges for ovarian cancer research. In this study, we demonstrate a key link between senescence and inflammation and how this complex network involving the biomarkers MAD2, TLR4 and MyD88 drives paclitaxel resistance in ovarian cancer. This was investigated using siRNA knockdown of MAD2, TLR4 and MyD88 in two ovarian cancer cell lines, A2780 and SKOV-3 cells and overexpression of MyD88 in A2780 cells. Interestingly, siRNA knockdown of MAD2 led to a significant increase in TLR4 gene expression, this was coupled with the development of a highly paclitaxel-resistant cell phenotype. Additionally, siRNA knockdown of MAD2 or TLR4 in the serous ovarian cell model OVCAR-3 resulted in a significant increase in TLR4 or MAD2 expression respectively. Microarray analysis of SKOV-3 cells following knockdown of TLR4 or MAD2 highlighted a number of significantly altered biological processes including EMT, complement, coagulation, proliferation and survival, ECM remodelling, olfactory receptor signalling, ErbB signalling, DNA packaging, Insulin-like growth factor signalling, ion transport and alteration of components of the cytoskeleton. Cross comparison of the microarray data sets identified 7 overlapping genes including MMP13, ACTBL2, AMTN, PLXDC2, LYZL1, CCBE1 and CKS2. These results demonstrate an important link between these biomarkers, which to our knowledge has never before been shown in ovarian cancer. In the future, we hope that triaging patients into alterative treatment groups based on the expression of these three biomarkers or therapeutic targeting of the mechanisms they are involved in will lead to improvements in patient outcome and prevent the development of chemoresistance.

DNA damage response and repair in ovarian cancer: Potential targets for therapeutic strategies

Ovarian cancer is among the most lethal gynecologic malignancies with a poor survival prognosis. The current therapeutic strategies involve surgery and chemotherapy. Research is now focused on novel agents especially those targeting DNA damage response (DDR) pathways. Understanding the DDR process in ovarian cancer necessitates having a detailed knowledge on a series of signaling mediators at the cellular and molecular levels. The complexity of the DDR process in ovarian cancer and how this process works in metastatic conditions is comprehensively reviewed. For evaluating the efficacy of therapeutic agents targeting DNA damage in ovarian cancer, we will discuss the components of this system including DDR sensors, DDR transducers, DDR mediators, and DDR effectors. The constituent pathways include DNA repair machinery, cell cycle checkpoints, and apoptotic pathways. We also will assess the potential of active mediators involved in the DDR process such as therapeutic and prognostic candidates that may facilitate future studies.