Current state of biomarkers in ovarian cancer prognosis

FBXO28 promotes cell proliferation, migration and invasion via upregulation of the TGF-beta1/SMAD2/3 signaling pathway in ovarian cancer

BACKGROUND

Ovarian cancer is one of the most common gynecological malignancies due to the lack of early symptoms, early diagnosis and limited screening. Therefore, it is necessary to understand the molecular mechanism underlying the occurrence and progression of ovarian cancer and to identify a basic biomarker for the early diagnosis and clinical treatment of ovarian cancer.

METHODS

The association between FBXO28 and ovarian cancer prognosis was analyzed using Kaplan‒Meier survival analysis. The difference in FBXO28 mRNA expression between normal ovarian tissues and ovarian tumor tissues was obtained from The Cancer Genome Atlas (TCGA), and Genotype-Tissue Expression (GTEx) cohorts. The expression levels of the FBXO28 protein in ovarian cancer tissues and normal ovarian tissues were measured via immunohistochemical staining. Western blotting was used to determine the level of FBXO28 expression in ovarian cancer cells. The CCK-8, the colony formation, Transwell migration and invasion assays were performed to evaluate cell proliferation and motility.

RESULTS

We found that a higher expression level of FBXO28 was associated with poor prognosis in ovarian cancer patients. Analysis of the TCGA and GTEx cohorts showed that the FBXO28 mRNA level was lower in normal ovarian tissue samples than in ovarian cancer tissue samples. Compared with that in normal ovarian tissues or cell lines, the expression of FBXO28 was greater in ovarian tumor tissues or tumor cells. The upregulation of FBXO28 promoted the viability, proliferation, migration and invasion of ovarian cancer cells. Finally, we demonstrated that FBXO28 activated the TGF-beta1/Smad2/3 signaling pathway in ovarian cancer.

CONCLUSIONS

In conclusion, FBXO28 enhanced oncogenic function via upregulation of the TGF-beta1/Smad2/3 signaling pathway in ovarian cancer.

VGLL3 expression is associated with macrophage infiltration and predicts poor prognosis in epithelial ovarian cancer

Background/objective

High-grade serous ovarian carcinoma (HGSOC) is the most common histologic type of epithelial ovarian cancer (EOC). Due to its poor survival outcomes, it is essential to identify novel biomarkers and therapeutic targets. The hippo pathway is crucial in various cancers, including gynaecological cancers. Herein, we examined the expression of the key genes of the hippo pathway and their relationship with clinicopathological significance, immune cells infiltration and the prognosis of HGSOC.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data were curated to analyse the mRNA expression as well as the clinicopathological association and correlation with immune cell infiltration in HGSOC. The protein levels of significant genes in the HGSOC tissue were analysed using Tissue Microarray (TMA)-based immunohistochemistry. Finally, DEGs pathway analysis was performed to find the signalling pathways associated with VGLL3.

Results

VGLL3 mRNA expression was significantly correlated with both advanced tumor stage and poor overall survival (OS) (p=0.046 and p=0.003, respectively). The result of IHC analysis also supported the association of VGLL3 protein with poor OS. Further, VGLL3 expression was significantly associated with tumor infiltrating macrophages. VGLL3 expression and macrophages infiltration were both found to be independent prognostic factors (p=0.003 and p=0.024, respectively) for HGSOC. VGLL3 was associated with four known and three novel cancer-related signalling pathways, thus implying that VGLL3 is involved in the deregulation of many genes and pathways.

Conclusion

Our study revealed that VGLL3 may play a distinct role in clinical outcomes and immune cell infiltration in patients with HGSOC and that it could potentially be a prognostic marker of EOC.

tRNA-derived small RNA 3'U-tRFValCAC promotes tumour migration and early progression in ovarian cancer

INTRODUCTION

Despite recent advances in epithelial ovarian cancer (EOC) management, the highly heterogenous histological/molecular tumour background and patients' treatment response obstructs personalised prognosis and therapeutics. Herein, we have studied the role and clinical utility of the novel subclass of tRNA-derived small RNA fragments emerging via 3'-trailer processing of pre-tRNAs (3'U-tRFs) in EOC.

METHODS

SK-OV-3 and OVCAR-3 cells were used for in vitro study. Following transfection, cell growth and migration were assessed by CCK8 and wound healing assays, respectively. 3'U-tRFs levels were assessed by reverse transcription quantitative PCR (RT-qPCR), following 3'-end RNA polyadenylation. A screening (OVCAD, n = 100) and institutionally independent validation (TU Munich, n = 103) cohorts were employed for survival analysis using disease progression and patients' death as clinical end-points. Bootstrap analysis was performed for internal validation, and decision curve analysis was used to evaluate clinical benefit on disease prognosis.

RESULTS

Following primary clinical assessment, target prediction and gene ontology analyses, the 3'U-tRF^ValCAC (derived from pre-tRNA^ValCAC) was highlighted to regulate cell proliferation and adhesion, and to correlate with inferior patients' outcome. 3'U-tRF^ValCAC transfection of SK-OV-3 and OVCAR-3 cells resulted in significantly increased cell growth and migration, in a dose-dependent manner. Elevated tumour 3'U-tRF^ValCAC levels were associated with significantly higher risk for early progression and worse survival following first-line platinum-based chemotherapy, independently of patients' clinicopathological data, chemotherapy response, and residual tumour. Interestingly, 3'U-tRF^ValCAC-fitted multivariate models improved risk stratification and provided superior clinical net benefit in prediction of treatment outcome compared to disease established markers.

CONCLUSIONS

3'U-tRF^ValCAC promotes tumour cell growth and migration and supports modern risk stratification and prognosis in EOC.

Highly Charged Ru(II) Polypyridyl Complexes as Photosensitizer Agents in Photodynamic Therapy of Epithelial Ovarian Cancer Cells

Ovarian cancer recurrence is frequent and associated with chemoresistance, leading to extremely poor prognosis. Herein, we explored the potential anti-cancer effect of a series of highly charged Ru(II)-polypyridyl complexes as photosensitizers in photodynamic therapy (PDT), which were able to efficiently sensitize the formation of singlet oxygen upon irradiation (Ru12+ and Ru22+) and to produce reactive oxygen species (ROS) in their corresponding dinuclear metal complexes with the Fenton active Cu(II) ion/s ([CuRu1]4+ and [Cu2Ru2]6+). Their cytotoxic and anti-tumor effects were evaluated on human ovarian cancer A2780 cells both in the absence or presence of photoirradiation, respectively. All the compounds tested were well tolerated under dark conditions, whereas they switched to exert anti-tumor activity following photoirradiation. The specific effect was mediated by the onset of programed cell death, but only in the case of Ru12+ and Ru22+ was preceded by the loss of mitochondrial membrane potential soon after photoactivation and ROS production, thus supporting the occurrence of apoptosis via type II photochemical reactions. Thus, Ru(II)-polypyridyl-based photosensitizers represent challenging tools to be further investigated in the identification of new therapeutic approaches to overcome the innate chemoresistance to platinum derivatives of some ovarian epithelial cancers and to find innovative drugs for recurrent ovarian cancer.

Identification and validation of a gene-based signature reveals SLC25A10 as a novel prognostic indicator for patients with ovarian cancer

Background

Ovarian cancer is a common gynecological cancer with poor prognosis and poses a serious threat to woman life and health. In this study, we aimed to establish a prognostic signature for the risk assessment of ovarian cancer.

Methods

The Cancer Genome Atlas (TCGA) dataset was used as the training set and the International Cancer Genome Consortium (ICGC) dataset was set as an independent external validation. A multi-stage screening strategy was used to determine the prognostic features of ovarian cancer with R software. The relationship between the prognosis of ovarian cancer and the expression level of SLC25A10 was selected for further analysis.

Results

A total of 16 prognosis-associated genes were screened to construct the risk score signature. Survival analysis showed that patients in the high-risk score group had a poor prognosis compared to the low-risk group. Accuracy of this prognostic signature was confirmed by the receiver operating characteristic (ROC) curve and decision curve analysis (DCA), and validated with ICGC cohort. This signature was identified as an independent factor for predicting overall survival (OS). Nomogram constructed by multiple clinical parameters showed excellent performance for OS prediction. Finally, it’s found that patients with low expression of SLC25A10 generally had poor survival and higher resistance to most chemotherapeutic drugs.

Conclusions

In sum, we developed a 16-gene prognostic signature, which could serve as a promising tool for the prognostic prediction of ovarian cancer, and the expression level of SLC25A10 was tightly associated with OS of the patients.

Anhuienoside C inhibits human ovarian cancer cell growth by inducing apoptosis, suppression of cell migration and invasion, and targeting PI3K/AKT/mTOR signaling pathway

The present study was initiated to examine the anticancer effects of Anhuienoside C (AC) against ovarian cancer and postulates the possible molecular mechanism of its action. 3-[4,5-Dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide assay was implemented for determination of the effects of AC on cell viability of the ovarian cancer OVACAR-3 cell line. To study cellular morphology, phase contrast microscopy was performed. Apoptosis was examined via acridine orange/ethidium bromide used staining assays. Flow cytometry was used to check the different phases of the cell cycle. Cell migration and invasion assays were performed via transwell chamber assay. The effects of AC on expression of phosphoinositide 3-kinases (PI3K), protein kinase B (AKT), and mammalian target of rapamycin (mTOR) protein in ovarian cell were assessed using western blotting assay. The results indicated that the cell proliferation rate lowered in AC-treated OVACAR-3 cells as compared to the untreated controls in a dose-dependent manner. Cell morphology changed substantially by the exposure to AC and remained dose dependent. These morphological changes were indicative of apoptotic cell death. Apoptosis analysis showed dose-dependent increase of apoptosis. The cell migration and invasion of OVACAR-3 cells was reduced to a minimum by AC in a dose-dependent manner. Finally, western blotting assay showed blocking of PI3K/AKT/mTOR signaling pathway with increasing AC doses. Taking all together, AC is a potential ovarian cancer inhibitor. It induces its anti-ovarian cancer effects via induction of apoptosis, delaying cell migration and invasion, and blocking PI3K/AKT/mTOR signaling pathway.

Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients

Background

Ovarian cancer (OV) is deemed the most lethal gynecological cancer in women. The aim of this study was to construct an effective gene prognostic model for predicting overall survival (OS) in patients with OV.

Methods

The expression profiles of glycolysis‐related genes (GRGs) and clinical data of patients with OV were extracted from The Cancer Genome Atlas (TCGA) database. Univariate, multivariate, and least absolute shrinkage and selection operator Cox regression analyses were conducted, and a prognostic signature based on GRGs was constructed. The predictive ability of the signature was analyzed using training and test sets.

Results

A gene risk signature based on nine GRGs (ISG20, CITED2, PYGB, IRS2, ANGPTL4, TGFBI, LHX9, PC, and DDIT4) was identified to predict the survival outcome of patients with OV. The signature showed a good prognostic ability for OV, particularly high‐grade OV, in the TCGA dataset, with areas under the curve (AUC) of 0.709 and 0.762 for 3‐ and 5‐year survival, respectively. Similar results were found in the test sets, and the AUCs of 3‐, 5‐year OS were 0.714 and 0.772 in the combined test set. And our signature was an independent prognostic factor. Moreover, a nomogram combining the prediction model and clinical factors was developed.

Conclusion

Our study established a nine‐GRG risk model and nomogram to better predict OS in patients with OV. The risk model represents a promising and independent prognostic predictor for patients with OV. Moreover, our study on GRGs could offer guidance for the elucidation of underlying mechanisms in future studies.

LncRNA RP11-499E18.1 Inhibits Proliferation, Migration, and Epithelial-Mesenchymal Transition Process of Ovarian Cancer Cells by Dissociating PAK2-SOX2 Interaction

Background: Ovarian cancer (OC)is a deadly gynecological malignancy worldwide. It is urgent to identify diagnostic biomarkers of OC to disclose the underlying mechanism. Methods and Materials: Bioinformatics analysis was used to identify target genes. Gene expression was detected and altered by qRT-PCR and cell transfection, respectively. The interaction between RP11-499E18.1 and PAK2, as well as that between PAK2 and SOX2, was determined using RNA pulldown, RNA immunoprecipitation (RIP), and co-immunoprecipitation (co-IP) assay, respectively. Localizations of RP11-499E18.1, PAK2, and SOX2 were respectively determined employing immunohistochemical (IHC), IF, and FISH. The regulatory effects of RP11-499E18.1, PAK2, and SOX2 on OC cell proliferation, migration, colony formation, epithelial-mesenchymal transition (EMT)-related factor expression, and SOX2 nuclear translocation were determined. Finally, the effects of RP11-499E18.1 and PAK2 expression on the tumor growth in nude mice were determined. Results: RP11-499E18.1, PAK2, and SOX2 were selected in our study. RP11-499E18.1 was downregulated, while PAK2 and SOX2 was upregulated in OC tissues and cells. RP11-499E18.1 coexists in the nucleus and cytoplasm of OC cells. There is an interaction between RP11-499E18.1 and PAK2, as well as PAK2 and SOX2 in OC cells. Alteration of RP11-499E18.1 and PAK2 expression both had no influence on PAK2 and SOX2 levels, but PAK2 upregulation notably augmented p-SOX2 level. RP11-499E18.1 overexpression suppressed OC cell proliferation, migration, and colony formation, as well as SOX2 nuclear translocation. Besides, it inhibited tumor growth in nude mice. However, these effects were notably reversed by PAK2 upregulation and eventually offset by SOX2 knockdown. Additionally, RP11-499E18.1 overexpression reduced PAK2-SOX2 interaction and SOX phosphorylation, and increased the binding of RP11-499E18.1 by PAK2. Conclusion: These lines of evidence demonstrated that RP11-499E18.1 might play its tumor suppressor roles in OC via regulation of the RP11-499E18.1-PAK2-SOX2 axis. This research indicated that RP11-499E18.1 might be used as a diagnostic biomarker for OC in the future.

Roles of lncRNA MAGI2-AS3 in human cancers

Long noncoding RNAs (lncRNAs) are noncoding RNAs more than 200 nucleotides in length. A growing number of reports indicate that lncRNAs play a key role in multiple cancers by serving as oncogenes or tumor suppressor genes. MAGI2 antisense RNA 3 (MAGI2-AS3) is ubiquitously expressed in human cancers, and the level of MAGI2-AS3 expression is associated with the progression and prognosis of cancers. Moreover, dysregulation of MAGI2-AS3 has been found to regulate cancer cell proliferation, cell death, invasion and metastasis and treatment resistance by serving as a competing endogenous RNA (ceRNA), epigenomic regulator, and transcriptional regulator. Moreover, increasing evidence shows that MAGI2-AS3 may be a potential biomarker for cancer prognosis and a potential target for cancer therapy. In this review, we summarize current research on the functions, mechanisms and clinical significance of the lncRNA MAGI2-AS3 in cancer development.

Current update on malignant epithelial ovarian tumors

Epithelial ovarian cancer (EOC) represents the most frequently occurring gynecological malignancy, accounting for more than 70% of ovarian cancer deaths. Preoperative imaging plays an important role in assessing the extent of disease and guides the next step in surgical decision-making and operative planning. In this article, we will review the multimodality imaging features of various subtypes of EOC. We will also discuss the role of imaging in the staging, management, and surveillance of EOC.

High FOXA1 immunohistochemical expression level associates with mucinous histology, favorable clinico-pathological prognostic parameters and survival advantage in epithelial ovarian cancer

Background

Forkhead box (FOX) A1 is a potential therapeutic biomarker that has been investigated in various human cancers. Limited data exist about FOXA1 biologic role in epithelial ovarian cancer (EOC).

Aim

This study assessed FOXA1 immunohistochemical (IHC) expression and evaluated its association with clinico-pathological parameters in EOC including overall and disease-free survivals (OS, DFS) and patient’s outcome.

Methods

Patient’s socio-epidemiologic, clinical, radiological, laboratory, surgical, and follow-up data were collected. After histopathologic typing, grading and staging, FOXA1 IHC expression was scored in 98 EOC specimens. Clinico-pathological associations were investigated in high-and low-FOXA1 expression groups using appropriate statistical methods. Kaplan-Meier method was used for survival analysis.

Results

FOXA1 tumor cell nuclear staining was detected in 63.3% of EOC with weak, moderate and strong scores (28.6%, 12.2% and 22.5% respectively). Comparing high- and low-expression groups (34.7% and 65.3% respectively), high FOXA1 was associated with larger tumors, low mean serum CA-125, tumor histopathology (mucinous and low-grade serous), type I EOC, limited tumor’s anatomical extent, absence of nodal or distant metastases and omental nodules, earlier FIGO stages, non-recurrent tumors and survival advantage with longer and OS and DFS (all p ≤ 0.05). Independent predictors of high FOXA1 expression included: omental nodules, tumor’s anatomical extent and tumor’s size (p ≤ 0.001, = 0.046 and = 0.023 respectively).

Conclusion

FOXA1 is frequently expressed in EOC notably mucinous and low-grade serous carcinomas in association with favorable prognostic clinico-pathological parameters and longer OS and DFS. It likely has a suppressor function in EOC and could be recommended as a prognostic and therapeutic biomarker.

Low Expression of Circular RNA hsa_circ_0078607 Predicts Poor Prognosis in High-Grade Serous Ovarian Cancer

Objective

Recent studies have shown that circRNAs participate in ovarian cancer progression and act as potential biomarkers for ovarian cancer diagnosis and prognosis. In the present study, we aimed to investigate the expression pattern and prognostic significance of circ_0078607 in high-grade serous ovarian cancer (HGSOC).

Methods

The expression of circ_0078607 was detected by quantitative real-time polymerase chain reaction (qRT-PCR) in 49 cases of HGSOC. Clinical data of patients with HGSOC were retrospectively collected, and those patients were divided according to their expression of circ_0078607. Correlation between circ_0078607 and clinical features as well as the prognosis in patients with HGSOC was analyzed. t-test and chi-square test were used to compare continuous and categorical variables. The Cox hazard regression model was used to assess prognostic factors. Both progression-free survival (PFS) and overall survival (OS) curves were generated by Kaplan-Meier method.

Results

The expression of circ_0078607 was significantly downregulated in ovarian cancer tissues compared with adjacent non-cancerous tissues. Besides, patients with low circ_0078607 expression exhibited parameters associated with poor prognosis, including advanced FIGO stage and higher serum CA125 level. Kaplan-Meier survival curve analysis showed that patients with low circ_0078607 expression had shorter PFS and OS. Cox regression analysis showed that low expression of circ_0078607 was a predictor for poor PFS and OS in HGSOC patients.

Conclusion

Low expression of circ_0078607 might be an adverse prognostic indicator for HGSOC.

KCNH3 Predicts Poor Prognosis and Promotes Progression in Ovarian Cancer

Background

Ovarian cancer (OC) is one of the most common causes of cancer-related death among women; accordingly, new biomarkers of OC are urgently needed. Potassium voltage-gated channel sub-family H member 3 (KCNH3) is a voltage-gated potassium channel member involved in cognitive function and diabetes. Here, we aimed to elucidate the role and potential molecular mechanisms of KCNH3 in OC.

Materials and Methods

KCNH3 expression levels in OC tissues were analyzed using TCGA data and confirmed by RT-qPCR and immunohistochemistry in OC tissues. The cell counting kit-8 was used to assess cell proliferation in OC cells in which KCNH3 was knocked-down with small interference RNA (siRNA). Wound-healing and transwell invasion assays were used to assess migratory and invasive abilities, respectively. Cell cycle distribution and apoptosis were determined using a flow cytometer. Gene set enrichment analysis and Western blot were used to investigate the potential pathways of KCNH3 in OC development.

Results

TCGA data and RT-qPCR results from patients with OC revealed high KCNH3 expression in OC tissues compared to normal ovarian tissues. Survival analysis in patients with OC suggested that high KCNH3 expression might be an independent predictor for poor overall survival and disease-free survival. In vitro studies showed that KCNH3 silencing in OC cells could inhibit cell proliferation and migration ability, and induce apoptosis and G2/M phase arrest. Furthermore, Western blot results showed that KCNH3 silencing might induce downregulation of RPA1 and RPA2 expression level in both SKOV3 and COC1 cells.

Conclusion

KCNH3 plays an important role in cancer progression in patients with OC. Further investigation might reveal KCNH3 as a potential biomarker for prognosis or diagnosis in OC.

A prognosis-predictive nomogram of ovarian cancer with two immune-related genes: CDC20B and PNPLA5

Ovarian carcinoma (OV) is one of the most lethal gynecological malignancies globally, and the overall 5-year survival rate of OV was 47% in 2018 according to American data. To increase the survival rate of patients with OV, many researchers have sought to identify biomarkers that act as both prognosis-predictive markers and therapy targets. However, most of these have not been suitable for clinical application. The present study aimed at constructing a predictive prognostic nomogram of OV using the genes identified by combining The Cancer Genome Atlas (TCGA) dataset for OV with the immune score calculated by the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Firstly, the algorithm was used to calculate the immune score of patients with OV in the TCGA-OV dataset. Secondly, differentially expressed genes (DEGs) between low and high immune score tissues were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was performed to predict the functions of these DEGs. Thirdly, univariate, multivariate and Lasso Cox's regression analyses were carried out step by step, and six prognosis-related DEGs were identified. Then, Kaplan-Myer survival curves were generated for these genes and validated by comparing their expression levels to further narrow the range of DEGs and to calculate the risk score. Two genes were identified, cell division cycle 20B and patatin-like phospholipase domain containing 5, which were both shown to have higher expression levels in OV tissues and to be significantly associated with the prognosis of OV. Next, a nomogram was created using these two genes and age, and using the receiver operating characteristic (ROC) curve and calibration curve, the effectiveness of the nomogram was validated. Finally, an external validation was conducted for this nomogram. The ROC showed that the areas under the curve (AUCs) of the 3- and 5-year overall survival predictions for the nomogram were 0.678 and 0.62, respectively. Moreover, the ROC of the external validation model showed that the AUCs of the 3- and 5-year were 0.699 and 0.643, respectively, demonstrating the effectiveness of the generated nomogram. In conclusion, the present study has identified two immune-related genes as biomarkers that reliably predict overall survival in OV. These biomarkers might also be potential molecular targets of immune therapy to treat patients with OV.

Circulating and Tissue microRNAs as Biomarkers for Ovarian Cancer Prognosis

Ovarian cancer (OC) is one of the most common cancers globally with a high rate of cancer- associated mortality. OC may be classified into epithelial cell neoplasms, germ cell neoplasms and stromal cell neoplasms. The five-year survival in the early and advanced stages of disease is approximately 90% and 15%, respectively. microRNAs are short, single-stranded, non-coding ribonucleic acid (RNA). miRNAs play critical roles in post transcriptionally regulations of gene expression. miRNAs are found in different tissues and body fluids. In carcinogenesis the expression of miRNAs are altered. Recent studies have revealed that there is a relationship between alteration of miRNAs expression and the prognosis of patients with OC. The aim of this review was to summarize the findings of recent studies that have investigated the expression of circulating and tissue miRNAs as novel biomarkers in the prognosis of OC.

MAGI2-AS3 suppresses MYC signaling to inhibit cell proliferation and migration in ovarian cancer through targeting miR-525-5p/MXD1 axis

Ovarian cancer (OV) is one of the most lethal gynecological malignance in females, and usually diagnosed at advanced stages. Long noncoding RNAs (lncRNAs) exhibit their crucial functions in modulatory mechanisms of cancers. Substantive studies have proven the anti-tumor role of MAGI2-AS3 in multiple cancers, but the physiological functions of MAGI2-AS3 in OV need more detailed explanations. The current study corroborated that overexpression of MAGI2-AS3 executed inhibitory activity in OV via hindering cell proliferation, cell cycle, migration as well as invasion while promoted apoptosis. Moreover MAGI2-AS3 bound with miR-525-5p and negatively regulated the expression of miR-525-5p. Further studies testified that MXD1 was a downstream target of miR-525-5p and the competing relationship between MAGI2-AS3 and MXD1 were confirmed by RNA pull down. Based on the combination between MAX and MYC, we analyzed the effects of MAGI2-AS3 on MXD1 and MYC, unveiling the competing relationship between MXD1 and MYC for binding to MAX. Finally, we constructed rescue assays to certify that MAGI2-AS3 suppressed the course of OV via enhancing MXD1 expression. In summary, MAGI2-AS3 repressed the progression of OV by targeting miR-525-5p/MXD1 axis, offering a novel insight into understanding OV at the molecular level.

LINC-PINT suppresses tumour cell proliferation, migration and invasion through targeting miR-374a-5p in ovarian cancer

LncRNA LINC-PINT acts as an important regulator in the development of many cancers. The current study aimed to explore the role of LINC-PINT in the progression of ovarian cancer (OC). LINC-PINT expression level in different FIGO stages of OC and its adjacent tissues, normal HOSE and OC cell lines (A2780, SKOV3, OVCAR3 and HO-8910) was determined by qRT-PCR. Survival analysis on LINC-PINT and OC patients was conducted by Kaplan-Meier. CCK-8, flow cytometry, wound-healing, Transwell assays and western blot were performed to detect the effects of LINC-PINT on proliferation, apoptosis, migration, invasion and EMT process in OC cells. Target gene of LINC-PINT was predicted by Starbase and verified by dual-luciferase reporter assay. The expression of miR-374a-5p in normal and OC tissues, LINC-PINT- or siLINC-PINT-modified OC cells was determined. Moreover, rescue assay was carried out to confirm whether LINC-PINT contributes to the development of OC cells through targeting miR-374a-5p. Low expression of LINC-PINT was observed in OC tissues and cells, noticeably, LINC-PINT expression was even lower in OC tissues with higher FIGO stage. Increased LINC-PINT expression significantly inhibited cell proliferation, promoted apoptosis and suppressed migration, invasion and EMT process, while silencing of LINC-PINT caused the opposite results. Moreover, LINC-PINT sponged miR-374a-5p and overexpressed miR-374a-5p attenuated the effect of up-regulated LINC-PINT on cell viability, migration, invasion and apoptosis. LINC-PINT acts as a tumour suppressor, as it could inhibit cell proliferation, migration, invasion and EMT process, and promote cell apoptosis through down-regulating miR-374a-5p. SIGNIFICANCE OF THE STUDY: Ovarian cancer (OC), which is a frequently diagnosed tumour in female reproductive organs, has a high incidence rate behind cervical cancer and endometrial cancer. LncRNA LINC-PINT acts as an important regulator in the development of many cancers. The current study aimed to explore the role of LINC-PINT in the progression of ovarian cancer (OC) and found that LINC-PINT inhibited cell proliferation, migration invasion and EMT process of OC cell via regulating miR-374a-5p; it might be a potential target for OC treatment.

Downregulated Long Noncoding RNA DGCR5 Acts as a New Promising Biomarker for the Diagnosis and Prognosis of Ovarian Cancer

Emerging evidence have indicated that dysregulated long noncoding ribonucleic acids act as a novel diagnostic and therapeutic target in the progression of ovarian cancer. Long noncoding RNA DiGeorge syndrome critical region gene 5 has been reported to participate in some types of human cancer progresses, but its clinical roles in ovarian cancer had been rarely reported. This study aimed to explore the expression, clinicopathological features, diagnostic, and prognostic values of DiGeorge syndrome critical region gene 5 in ovarian cancer. The total levels of DiGeorge syndrome critical region gene 5 transcript variant 1 (NR_002733.2) and 2 (NR_045121.1) in patients with ovarian cancer were determined by quantitative reverse transcription polymerase chain reaction. The correlation of DiGeorge syndrome critical region gene 5 expression with clinicopathological factors was statistically analyzed by χ² test. Overall survival analysis was carried out with the Kaplan–Meier curves with the log-rank test. Univariate and multivariate Cox regression analyses were performed to identify the prognostic significance of DiGeorge syndrome critical region gene 5 expression. Receiver operating characteristic curves were constructed to estimate the diagnostic and prognostic usefulness of DiGeorge syndrome critical region gene 5 in ovarian cancer. Results showed that relative DiGeorge syndrome critical region gene 5 expression was reduced by 36.81% and 65.79% in ovarian cancer tissues of patients and Gene Expression Omnibus DataSets (GSE119056) in contrast to normal tissues, respectively. Patients with lymph node metastasis and distant metastasis exhibited lower levels of DiGeorge syndrome critical region gene 5 in contrast to those patients with non-lymph node metastasis and non-distant metastasis, respectively. Low expression of DiGeorge syndrome critical region gene 5 was significantly associated with large tumor size, more lymph node metastasis, present distant metastasis, advanced clinical stage, and short overall survival in patients with ovarian cancer. Low expression of DiGeorge syndrome critical region gene 5 was an independent unfavorable prognostic factor for overall survival in patients with ovarian cancer. Receiver operating characteristics curves for prognosis yielded significant area under curves for lymph node metastasis, clinical stage, and overall survival. In conclusion, our study demonstrated that downregulated DiGeorge syndrome critical region gene 5 may be a new promising biomarker for predicting clinical progression and prognosis in patients with ovarian cancer.

Overcoming Resistance to Platinum-Based Drugs in Ovarian Cancer by Salinomycin and Its Derivatives-An In Vitro Study

Polyether ionophore salinomycin (SAL) and its semi-synthetic derivatives are recognized as very promising anticancer drug candidates due to their activity against various types of cancer cells, including multidrug-resistant populations. Ovarian cancer is the deadliest among gynecologic malignancies, which is connected with the development of chemoresistant forms of the disease in over 70% of patients after initial treatment regimen. Thus, we decided to examine the anticancer properties of SAL and selected SAL derivatives against a series of drug-sensitive (A2780, SK-OV-3) and derived drug-resistant (A2780 CDDP, SK-OV-3 CDDP) ovarian cancer cell lines. Although SAL analogs showed less promising IC₅₀ values than SAL, they were identified as the antitumor agents that significantly overcome the resistance to platinum-based drugs in ovarian cancer, more potent than unmodified SAL and commonly used anticancer drugs—5-fluorouracil, gemcitabine, and cisplatin. Moreover, when compared with SAL used alone, our experiments proved for the first time increased selectivity of SAL-based dual therapy with 5-fluorouracil or gemcitabine, especially towards A2780 cell line. Looking closer at the results, SAL acted synergistically with 5-fluorouracil towards the drug-resistant A2780 cell line. Our results suggest that combinations of SAL with other antineoplastics may become a new therapeutic option for patients with ovarian cancer.

Biologic Mechanisms Linked to Prognosis in Ovarian Cancer that May Be Affected by Aging

The increase of both life expectancy of the Western industrialized population and cancer incidence with aging is expected to result in a rapid expansion of the elderly cancer population, including patients with epithelial ovarian cancer (EOC). Although the survival of patients with EOC has generally improved over the past three decades, this progress has yet to provide benefits for elderly patients. Compared with young age, advanced age has been reported as an adverse prognostic factor influencing EOC. However, contradicting results have been obtained, and the mechanisms underlying this observation are poorly defined. Few papers have been published on the underlying biological mechanisms that might explain this prognosis trend. We provide an extensive review of mechanisms that have been linked to EOC prognosis and/or aging in the published literature and might underlie this relationship in humans.

Low BCL7A expression predicts poor prognosis in ovarian cancer

Background and objective

Ovarian cancer is a common gynaecological cancer with a poor prognosis that poses a serious threat to human life and health. It is essential to explore the possible prognostic biomarkers of ovarian cancer. As an important tumour suppressor gene, BCL7A actively participates in the growth of tumours. We aimed to study the prognostic role of BCL7A in ovarian cancer.

Results

Through data mining of RNAseq data from the Cancer Genome Atlas database (TCGA), we explored the clinical relevance of BCL7A mRNA expression. As a result, we found that BCL7A is expressed at low levels in ovarian cancer tissues and is correlated with survival status. Survival analysis showed that, compared with those who had higher levels of BCL7A expression, patients with ovarian cancer and low levels of BCL7A generally had shorter overall/relapse-free survival times. Cox regression models showed that low BCL7A expression could be used as an independent prognostication factor for ovarian cancer patients.

Conclusions

Low BCL7A expression is an independent risk factor for poor prognosis in ovarian cancer patients.

Increased STAT1 Expression in High Grade Serous Ovarian Cancer Is Associated With a Better Outcome

OBJECTIVE

Recently it has been demonstrated that constitutively activated signal transducer and activator of transcription 1 (STAT1) gene expression may act as a biomarker of ovarian cancer chemotherapy response. In this study, our objective was to validate the use of STAT1 immunohistochemistry as a prognostic biomarker for disease outcome using a cohort derived from Latin America.

METHODS

We evaluated a cohort of Brazilian high-grade serous ovarian cancer, comprising 65 patients with outcome data covering more than 5 years to determine the prognostic and predictive value of STAT1 expression levels. High-grade serous ovarian cancer tumors were used to construct a tissue microarray. Exploratory analyses were conducted on clinical, histopathological, and STAT1 expression data that included descriptive statistics and Pearson correlative analyses. Survival curves for disease-free survival and overall survival were obtained by the Kaplan-Meier method, and the significance of homogeneity between the classes was assessed by log-rank statistics (Mantel-Cox).

RESULTS

High expression of STAT1 in tumors was significantly associated with improved disease-free survival (P = 0.0256) and overall survival (P = 0.0193). Proportional hazards regression analysis showed STAT1 expression had an independent effect on both disease-free survival (P = 0.0358) and overall survival (P = 0.0469).

CONCLUSIONS

These findings from a Brazilian cohort of patients with ovarian cancer reinforce the association of high STAT1 expression with better response to chemotherapy, providing additional validation of this protein as both a prognostic and predictive biomarker. Collectively, these results together with other recently published studies increase the feasibility of using the STAT1 pathway for the development of novel immunomodulator drugs that could enhance response to treatment.

Developing a Prognostic Gene Panel of Epithelial Ovarian Cancer Patients by a Machine Learning Model

Epithelial ovarian cancer patients usually relapse after primary management. We utilized the support vector machine algorithm to develop a model for the chemo-response using the Cancer Cell Line Encyclopedia (CCLE) and validated the model in The Cancer Genome Atlas (TCGA) and the GSE9891 dataset. Finally, we evaluated the feasibility of the model using ovarian cancer patients from our institute. The 10-gene predictive model demonstrated that the high response group had a longer recurrence-free survival (RFS) (log-rank test, p = 0.015 for TCGA, p = 0.013 for GSE9891 and p = 0.039 for NTUH) and overall survival (OS) (log-rank test, p = 0.002 for TCGA and p = 0.016 for NTUH). In a multivariate Cox hazard regression model, the predictive model (HR: 0.644, 95% CI: 0.436⁻0.952, p = 0.027) and residual tumor size < 1 cm (HR: 0.312, 95% CI: 0.170⁻0.573, p < 0.001) were significant factors for recurrence. The predictive model (HR: 0.511, 95% CI: 0.334⁻0.783, p = 0.002) and residual tumor size < 1 cm (HR: 0.252, 95% CI: 0.128⁻0.496, p < 0.001) were still significant factors for death. In conclusion, the patients of high response group stratified by the model had good response and favourable prognosis, whereas for the patients of medium to low response groups, introduction of other drugs or clinical trials might be beneficial.

Ovarian Cancer Prognostic Prediction Model Using RNA Sequencing Data

Ovarian cancer is one of the leading causes of cancer-related deaths in gynecologic malignancies. Over 70 % of ovarian cancer cases are high-grade serous ovarian cancers (HGSC) and have high death rates due to their resistance to chemotherapy. Despite advances in surgical and pharmaceutical therapies, overall survival rates are not good and accurate prediction of prognosis is not easy because of the highly heterogeneous nature of ovarian cancer. To improve patient's prognosis through proper treatment, we present a prognostic prediction model by integrating the high dimensional RNA sequencing data with their clinical data through the following steps: (1) gene filtration, (2) pre-screening, (3) gene marker selection (4) integrated study of selected gene markers and prediction model building. These steps of the prognostic prediction model can be applied to other types of cancer besides ovarian cancer.

Integrin Subunit beta 8 (ITGB8) Upregulation Is an Independent Predictor of Unfavorable Survival of High-Grade Serous Ovarian Carcinoma Patients

Background

ITGB8 encodes a β subunit of integrin (integrin β8), which is upregulated in some types of cancer. In the current study, we examined the expression profile of ITGB8 in serous ovarian cancer (SOVC) and investigated its potential as an independent prognostic indicator for overall survival (OS) and recurrence-free survival (RFS) in high-grade SOVC.

Material/Methods

A secondary study was conducted based on genomic and survival data in large online databases, including the Gene Expression Omnibus (GEO), the Human Protein Atlas (HPA), and the Cancer Genome Atlas-Ovarian cancer (TCGA-OV). Kaplan-Meier curves were generated to evaluate the association between ITGB8 expression and OS/RFS. Univariate and multivariate analysis were performed with the Cox regression model.

Results

ITGB8 was significantly upregulated in ovarian cancer tissues compared to that in normal ovary tissues. High-grade SOVC patients with high ITGB8 expression had significantly shorter OS and RFS compared to their low-expression counterparts. Increased ITGB8 expression might be an independent prognostic indicator of unfavorable OS (HR: 1.424, 95%CI: 1.228–1.653, p<0.001) and RFS (HR: 2.167, 95%CI: 1.507–3.114, p<0.001) in high-grade SOVC. DNA amplification was frequent (149/509, 29.3%) in high-grade SOVC patients and was associated with increased ITGB8 expression compared to the copy-neutral cases.

Conclusions

ITGB8 expression might be a valuable prognostic biomarker in high-grade SOVC, the expression of which might be regulated by its DNA copy numbers.

Early identification of recurrence in ovarian cancer: a comparison between the ovarian cancer metastasis index and CA-125 levels

Ovarian cancer (OC) is the second most common gynecologic malignancy. A clinical observational study was performed to investigate whether indicators that assess the risk of metastasis can identify recurrence earlier in OC patients. By successfully recruiting 41 patients with OC who underwent chemotherapy, we compared cancer antigen-125 (CA-125) and the ovarian cancer metastasis index (OCMI), which was previously developed by us in the clinic for this purpose. Our results showed that patients and their families generally took a sensible attitude toward disease progression and were willing to accept a new way to gain knowledge about the disease. Herein, the new way was the possibility of monitoring recurrence by introducing the OCMI into the clinic. Fifteen patients experienced recurrence during chemotherapy, implying treatment failure. For 53% of these patients, an abnormally high OCMI suggested a strong tendency toward metastasis at least one chemotherapy cycle prior to the pathological examination confirming recurrence. In comparison, the early recognition rate of recurrence using CA-125 levels was merely 13%. Furthermore, we found that the mean values of the OCMI no longer declined after the fourth chemotherapy cycle, implying that excessive chemotherapy brings no benefit to OC patients. In conclusion, our findings provide a novel and feasible approach to monitor the effectiveness of chemotherapy in the treatment of OC by assessing the potential risk of metastasis.

Indirubin suppresses ovarian cancer cell viabilities through the STAT3 signaling pathway

Background

Indirubin is the active component of Danggui Longhui Wan, a traditional Chinese medicine formulation. Due to its anti-inflammation and anti-tumor effects, indirubin has been widely used for the treatment of inflammation, cancer, and other chronic disease. Herein, we aimed to investigate the role and mechanism of indirubin in human ovarian cancer cell proliferation.

Materials and methods

The cell viability was determined by Cell Counting Kit-8 and colony formation assays by treatment with different dosages of indirubin over 72 hours. Apoptosis was examined by flow cytometry with fluorescein isothiocyanate Annexin V Apoptosis Detection Kit. Western blot assay was finally applied to analyze the expression of cancer-related STAT3 pathway and its downstream proteins.

Results

Indirubin was found to significantly inhibit cell viability and induce apoptosis in 2 human ovarian cancer cell lines. Mechanistic studies revealed that indirubin treatment led to reduced levels of phosphorylated-STAT3, thus repressing the downstream pro-survival proteins and elevating pro-apoptosis ones.

Conclusion

Our study provided the evidence for anti-survival activity of indirubin by inhibiting cell viability and inducing apoptosis in human ovarian cancer cells, which involved impaired STAT3 signaling pathway. Our findings further support indirubin as a potential drug candidate against human ovarian cancer.

Preoperative platelet-lymphocyte ratio is an independent prognostic factor in ampullary carcinoma following pancreaticoduodenectomy

The objective of the present study was to evaluate whether preoperative platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) could predict the prognosis for curative resected ampullary carcinoma. A total of 94 patients were retrospectively included over a 6-year period in which consecutive cases underwent pancreaticoduodenectomy for ampullary malignancy. Preoperative blood results were available in the 94 cases of resected ampullary carcinoma. Preoperative PLR and NLR cut-off values of 226.8 and 2.58 were determined to represent the optimal cut-off values in the cases for survival analysis. PLR remained a significant independent predictor of survival in multivariate analysis (Cox, P<0.001) in addition to tumor differentiation (P<0.001), nodal status (P<0.001) and stage (P<0.001). While NLR failed to serve as a prognostic factor in univariate (P=0.0637) and multivariate (P=0.164) survival analysis. Furthermore, the nodal involvement rate was higher in high PLR group (74.2 vs. 19.05%, P<0.001). Preoperative PLR and NLR merit further evaluation as a prognostic index in curative resected ampullary carcinoma. Additionally, it is a candidate predictor for the lymph node metastasis.

Establishment of a SVM classifier to predict recurrence of ovarian cancer

Gene expression data using retrieved ovarian cancer (OC) samples were used to identify genes of interest and a support vector machine (SVM) classifier was subsequently established to predict the recurrence of OC. Three datasets (GSE17260, GSE44104 and GSE51088) investigating OC gene expression were downloaded from the Gene Expression Omnibus. Differentially expressed genes (DEGs) in samples from patients with non-recurrent and recurrent OC were revealed via a homogeneity test and quality control analysis. A protein-protein interaction (PPI) network was subsequently established for the DEGs using data from Biological General Repository for Interaction Datasets, Human Protein Reference Database and Database of Interacting Proteins. Degrees of interaction and betweenness centrality (BC) scores were calculated for each node in the PPI network. The top 100 genes ranked by BC scores were selected to identify feature genes via recursive feature elimination using the GSE17260 dataset. Following this, a SVM classifier was constructed and further validated using the GSE44104 and GSE51088 datasets and independent gene expression data obtained from the Cancer Genome Atlas (TCGA). A total of 639 DEGs were identified from the three gene expression datasets, and a PPI network including 249 nodes and 354 edges was constructed. A SVM classifier consisting of 39 feature genes (including cullin 3, mouse double minute 2 homolog, aurora kinase A, WW domain containing oxidoreducatase, large tumor suppressor kinase 2, sirtuin 6, staphylococcal nuclease and tudor domain containing 1, leucine rich repeats and immunoglobulin like domains 1 and aurora kinase 1 interacting protein 1) was subsequently constructed. The prediction accuracies of the SVM classifier for GSE17260, GSE44104 and GSE51088 datasets as well as data downloaded from TCGA were revealed to be 92.7, 93.3, 96.6 and 90.4%, respectively. Furthermore, the results of the present study revealed that patients with predicted non-recurrent OC survived significantly longer compared with the patients with predicted recurrent OC (P=6.598×10⁻⁶). A SVM classifier consisting of 39 feature genes was established for predicting the recurrence and prognosis of OC. Therefore, the results of the present study suggested that the 39 feature genes may serve important roles in the development of OC and may represent therapeutic biomarkers of OC.

Effect of combined inhibition of p110 alpha PI3K isoform and STAT3 pathway in ovarian cancer platinum-based resistance

Background

Ovarian cancer is associated with poor prognostic outcome due to late diagnosis and to intrinsic and acquired resistance to platinum-based chemotherapy in a large number of patients. This chemoresistance is acquired through the peritoneal and ascites microenvironment by several released factors, such as IL-6,. Preclinical studies have implicated the activation of PI3K pathway in chemoresistance, showing it to extend tumor cell survival and modulate multidrug resistance. We aimed to evaluate the implication of the p110 alpha PI3K subunit in ovarian cancer chemoresistance acquisition, and to evaluate whether the STAT3 pathway can mediate resistance to PI3K inhibitors through secretion of IL6.

Results

Human ovarian adenocarcinoma IGROV-1 and JHOC-5 cells cultured in ascites showed an increase in carboplatinum-based resistance. Level of chemoresistance was associated to IL6 concentration in ascites. Activation of PI3K/Akt, STAT and MAPK pathways was observed after IGROV-1 incubation with ascites and treatment with carboplatin. Neither IGROV-1 nor JHOC-5 cells exposed to ascites treated with additional IL-6 directed antibody showed any reversion of the chemoresistance.

Conclusion

IL6-related resistance was not abolished by the selective inhibition of PI3K alpha subunit coupled with the anti-IL6-receptor antibody tocilizumab. This dual inhibition requires further exploration in other ovarian cancer models such as clear cell carcinoma.

Increased DHRS12 expression independently predicts poor survival in patients with high-grade serous ovarian cancer

AIM

To explore the expression profile of some DHRS genes in high-grade serous ovarian cancer (SOVC) and to study their prognostic values.

PATIENTS & METHODS

A retrospective bioinformatic analysis was performed using data in the Gene Expression Omnibus, the Human Protein Atlas and the Cancer Genome Atlas-Ovarian Cancer.

RESULTS

Increased DHRS12 expression was an independent indicator of poor overall survival (hazard ratio [HR]: 1.265, 95% CI: 1.075-1.488; p = 0.005) and recurrence-free survival (RFS; HR: 2.242, 95%CI: 1.464-3.432; p < 0.001) in patients with high-grade SOVC. DNA deletion was associated with decreased DHRS12 expression, as well as the best overall survival and RFS among the three copy number alteration groups.

CONCLUSION

DHRS12 might serve as a valuable prognostic biomarker in high-grade SOVC.

miR-423-5p serves as a diagnostic indicator and inhibits the proliferation and invasion of ovarian cancer

MicroRNA (miR)-423-5p is a potential target for the diagnosis and therapy of heart failure and cancer. The present study aimed to investigate the expression and role of miR-423-5p in ovarian cancer. miR-423-5p expression in ovarian tissues and plasma collected from ovarian cancer patients and healthy volunteers was analyzed by polymerase chain reaction analysis. In addition, a cell proliferation assay, clonogenic assay and Matrigel-based assay were performed to evaluate the role of miR-423-5p in ovarian cancer cells. The results demonstrated that miR-423-5p was downregulated in ovarian cancer tissues and plasma from ovarian cancer patients, compared with healthy individuals. Of note, miR-423-5p expression in ovarian tissues and plasma was demonstrated to be inversely correlated with ovarian cancer progression. Transfection with miR-423-5p efficiently increased miR-423-5p expression in A2780-s and A2780-cp cells, which had low miR-423-5p expression. Ectopic overexpression of miR-423-5p reduced cell proliferation, colony formation and invasion of ovarian cancer cells. In conclusion, the present study indicated that miR-423-5p may serve as a diagnostic indicator and functions as a tumor suppressor in ovarian cancer.

Three-Dimensional Cellular Arrangement in Epithelial Ovarian Cancer Cell Lines TOV-21G and SKOV-3 is Associated with Apoptosis-Related miRNA Expression Modulation

Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy, and the lack of chemoresistance biomarkers contributes to the poor prognosis. Cancer stem cells (CSC) have been investigated in EOC to understand its relationship with chemoresistance and recurrence. In this context, in vitro cultivation-models are important tools for CSC studies. MicroRNAs (miRNAs) play key roles in cancer, CSC regulation and apoptosis. Thus, this study aims to evaluate the tumorsphere model as CSC-enrichment method in EOC studies and investigate apoptosis-related miRNAs in tumorspheres-derived EOC cell lines. TOV-21G and SKOV-3 were cultured in monolayer and tumorspheres. Genetic profiles of cell lines were obtained using COSMIC database. CD24/CD44/CD146/CD177 and ALDH1 markers were evaluated in cell lines and tumorspheres-derived by flow cytometry. Eleven miRNAs were selected by in silico analysis for qPCR analysis. According to COSMIC, TOV-21G and SKOV-3 have eight and nine cancer-related mutations, respectively. TOV-21G showed a CD44^+/high/CD24^-/low/CD117^-/low/CD146^-/low/ALDH1^low profile in both culture models; thus, no significant difference between cultivation models was identified. SKOV-3 showed a CD44^+/high/CD24^+/high/ CD117^-/low/CD146^-/low/ALDH1^low profile in both culture models, although the tumorsphere model showed a significant increase in CD24^+/high subpopulation (ovarian CSC-like). Among eleven miRNAs, we observed differences in miRNA expression between culture models. MiR-26a was overexpressed in TOV-21G tumorspheres, albeit downregulated in SKOV-3 tumorspheres. MiR-125b-5p, miR-17-5p and miR-221 was downregulated in tumorsphere model in both cell lines. Given that tumorsphere-derived SKOV-3 had a higher ratio of CD24^+/high cells, we suggest that miR-26a, miR-125b-5p, miR-17-5p and miR-221 downregulation could be related to poor EOC prognosis.

Panel of seven long noncoding RNA as a candidate prognostic biomarker for ovarian cancer

Ovarian cancer is one of the most common and lethal gynecological malignancies. The diagnosis of ovarian cancer is often at an advanced stage. Accumulated evidence suggests that long noncoding RNAs (lncRNAs) play important roles during ovarian tumorigenesis. In this study, using the lncRNA-mining approach, we analyzed lncRNA expression profiles of 493 ovarian cancer patients from Gene Expression Omnibus datasets, and identified a signature group of seven lncRNAs (BC037530, AK021924, AK094536, AK094536, BC062365, BC004123 and BC007937) associated with patient survival in the training dataset GSE9891. We also formulated a risk score model to divide patients into low-risk and high-risk groups based on the expression of these seven lncRNAs. We further validated the predictive power of our risk score model in two other datasets, GSE26193 and GSE63885. Our analysis showed that the seven-lncRNA signature can serve as an independent predictor apart from Federation of Gynecology and Obstetrics (FIGO) stage and patient age. Further investigation revealed the seven-lncRNA signature correlated with few critical signaling pathways involved in cancer. Combined, all these findings strongly support that the seven-lncRNA signature can serve as a strong prognosis biomarker.

A brief review of the management of platinum-resistant-platinum-refractory ovarian cancer

Ovarian cancer, which ranks fifth in cancer deaths among women, is the most lethal gynecologic malignancy. Epithelial ovarian cancer (EOC) is the most common histologic type, with the 5-year survival for all stages estimated at 45.6%. This rate increases to more than 70% in the minority of patients who are diagnosed at an early stage, but declines to 35% in the vast majority of patients diagnosed at advanced stage. Recurrent EOC is incurable. Platinum sensitivity (or lack thereof) is a major determinant of prognosis. The current standard treatment is primary surgery followed by platinum-based chemotherapy. In recurrent platinum-resistant/platinum-refractory EOC, sequential single-agent salvage chemotherapy is superior to multiagent chemotherapy. Multiagent regimens increase toxicity without clear benefit; however, no preferred sequence of single agents is recommended. The impact of targeted therapies and immunotherapies on progression-free survival and overall survival, which remains dismal, is under active investigation. Currently, clinical trials offer the best hope for the development of a new treatment paradigm in this recalcitrant disease.

Impact of the putative cancer stem cell markers and growth factor receptor expression on the sensitivity of ovarian cancer cells to treatment with various forms of small molecule tyrosine kinase inhibitors and cytotoxic drugs

Increased expression and activation of human epidermal growth factor receptor (EGFR) and HER-2 have been reported in numerous cancers. The aim of this study was to determine the sensitivity of a large panel of human ovarian cancer cell lines (OCCLs) to treatment with various forms of small molecule tyrosine kinase inhibitors (TKIs) and cytotoxic drugs. The aim was to see if there was any association between the protein expression of various biomarkers including three putative ovarian cancer stem cell (CSC) markers (CD24, CD44, CD117/c-Kit), P-glycoprotein (P-gp), and HER family members and response to treatment with these agents. The sensitivity of 10 ovarian tumour cell lines to the treatment with various forms of HER TKIs (gefitinib, erlotinib, lapatinib, sapitinib, afatinib, canertinib, neratinib), as well as other TKIs (dasatinib, imatinib, NVP-AEW541, crizotinib) and cytotoxic agents (paclitaxel, cisplatin and doxorubicin), as single agents or in combination, was determined by SRB assay. The effect on these agents on the cell cycle distribution, and downstream signaling molecules and tumour migration were determined using flow cytometry, western blotting, and the IncuCyte Clear View cell migration assay respectively. Of the HER inhibitors, the irreversible pan-TKIs (canertinib, neratinib and afatinib) were the most effective TKIs for inhibiting the growth of all ovarian cancer cells, and for blocking the phosphorylation of EGFR, HER-2, AKT and MAPK in SKOV3 cells. Interestingly, while the majority of cancer cells were highly sensitive to treatment with dasatinib, they were relatively resistant to treatment with imatinib (i.e., IC50 >10 µM). Of the cytotoxic agents, paclitaxel was the most effective for inhibiting the growth of OCCLs, and of various combinations of these drugs, only treatment with a combination of NVP-AEW541 and paclitaxel produced a synergistic or additive anti-proliferative effect in all three cell lines examined (i.e., SKOV3, Caov3, ES2). Finally, of the TKIs, only treatment with afatinib, neratinib and dasatinib were able to reduce the migration of HER-2 overexpressing SKOV3 cells. We did not find any significant association between the expression of putative ovarian CSC marker, HER family members, c-MET, ALK, and IGF-IR and the response to the irreversible HER TKIs. Our results support the need for further investigations of the therapeutic potential of these irreversible HER family blockers in ovarian cancer, and the therapeutic potential of dasatinib when used in combination with the inhibitors of the HER family members in ovarian cancer.