scholarly journals USP19 and RPL23 as Candidate Prognostic Markers for Advanced-Stage High-Grade Serous Ovarian Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 3976
Author(s):  
Haeyoun Kang ◽  
Min Chul Choi ◽  
Sewha Kim ◽  
Ju-Yeon Jeong ◽  
Ah-Young Kwon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Ovarian Cancer ◽  
Ovarian Carcinoma ◽  
Prognostic Markers ◽  
The Cancer Genome Atlas ◽  
Immune Gene ◽  
Mrna Levels ◽  
High Grade ◽  
Advanced Stage ◽  
Serous Ovarian Carcinoma

Ovarian cancer is one of the leading causes of deaths among patients with gynecological malignancies worldwide. In order to identify prognostic markers for ovarian cancer, we performed RNA-sequencing and analyzed the transcriptome data from 51 patients who received conventional therapies for high-grade serous ovarian carcinoma (HGSC). Patients with early-stage (I or II) HGSC exhibited higher immune gene expression than patients with advanced stage (III or IV) HGSC. In order to predict the prognosis of patients with HGSC, we created machine learning-based models and identified USP19 and RPL23 as candidate prognostic markers. Specifically, patients with lower USP19 mRNA levels and those with higher RPL23 mRNA levels had worse prognoses. This model was then used to analyze the data of patients with HGSC hosted on The Cancer Genome Atlas; this analysis validated the prognostic abilities of these two genes with respect to patient survival. Taken together, the transcriptome profiles of USP19 and RPL23 determined using a machine-learning model could serve as prognostic markers for patients with HGSC receiving conventional therapy.

Prognostic significance of differential expression of angiogenic genes in women with invasive high-grade serous ovarian carcinoma.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 5509-5509 ◽  
Author(s):  
Sharareh Siamakpour-Reihani ◽  
Kouros Owzar ◽  
Chen Jiang ◽  
Taylor Turner ◽  
Andrew Berchuck ◽  
...  
Keyword(s):  
Ovarian Carcinoma ◽  
Prognostic Significance ◽  
Genetic Alterations ◽  
The Cancer Genome Atlas ◽  
P Value ◽  
Mrna Levels ◽  
High Grade ◽  
Q Value ◽  
Serous Ovarian Carcinoma ◽  
Angiogenic Genes

5509 Background: High-grade serous ovarian carcinoma (HGSC) is an aggressive type of epithelial ovarian cancer associated with numerous genetic alterations and poor survival. Our objective was to identify novel angiogenic biomarkers that are associated with tumor angiogenesis and clinical outcome in women with HGSC. Methods: Between 1988 and 2001, 51 snap frozen samples from women with advanced HGSC were obtained. RNA was extracted and analyzed by the Affymetrix GeneChip U133A array. A panel of 285 probe sets (features) linked to 145 genes involved in angiogenesis were screened. Microvessel density (MVD) counts, surrogates of angiogenesis, were determined using CD31 and CD105, markers of proliferating endothelial cells. The association between mRNA expression levels and overall survival (OS) were assessed using a rank score statistic. The effect size was estimated parametrically as a hazard ratio (HR) under a proportional hazards model. We accounted for multiple testing within the false-discovery rate (FDR) framework using the Storey q-value method. The associations between expression level and OS for the implicated genes were further assessed in a published HGSC cohort from the “The Cancer Genome Atlas” (TCGA) database. Results: A panel of 43 features linked to 31 angiogenic genes were significantly associated with long term OS (FDR q-value (q) < 0.05). In the TCGA cohort, four genes exhibited some level of significance and concordant direction of effect as assessed by HRs: AKT1 (q = 0.018, HR = 0.44; TCGA unadjusted p-value (p) <0.011, HR = 0.81), and CD44 (q < 0.003, HR = 0.48; TCGA p < 0.054, HR = 0.89) were associated with better survival; while EPHB2 (q < 0.009, HR = 8.12; TCGA p < 0.051, HR = 1.23) and ERBB2(q < 0.019, HR = 2.86, TCGA p < 0.055, HR = 1.19) were associated with worse survival. After adjusting for multiple comparisons, CD105-MVD and CD31-MVD were not significantly associated with angiogenic gene expression. Conclusions: Our data demonstrated that mRNA levels of 31 angiogenic genes were associated with OS in advanced HGSC. Among these 4 were externally confirmed using TCGA data. Further evaluation is warranted to verify our preliminary findings.

GATA3 and stemness of high-grade serous ovarian carcinoma: novel hope for the deadliest type of ovarian cancer

Human Cell ◽  
2020 ◽  
Vol 33 (3) ◽  
pp. 904-906 ◽  
Author(s):  
Amr Ahmed El-Arabey ◽  
Mohnad Abdalla ◽  
Adel Rashad Abd-Allah
Keyword(s):  
Ovarian Cancer ◽  
Ovarian Carcinoma ◽  
High Grade ◽  
Serous Ovarian Carcinoma

scholarly journals Mechanisms of Chromosomal Instability in High-grade Serous Ovarian Carcinoma

2019 ◽  
Author(s):  
N. Tamura ◽  
N. Shaikh ◽  
D. Muliaditan ◽  
J. McGuinness ◽  
D. Moralli ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Ovarian Carcinoma ◽  
Single Molecule ◽  
Chromosomal Instability ◽  
Poor Prognosis ◽  
Spindle Assembly Checkpoint ◽  
Western World ◽  
Cancer Type ◽  
High Grade ◽  
Serous Ovarian Carcinoma

AbstractChromosomal instability (CIN), the continual gain and loss of chromosomes or parts of chromosomes, occurs in the majority of cancers and confers poor prognosis. Mechanisms driving CIN remain unknown in most cancer types due to a scarcity of functional studies. High-grade serous ovarian carcinoma (HGSC), the most common subtype of ovarian cancer, is the major cause of death due to gynaecological malignancy in the Western world with chemotherapy resistance developing in almost all patients. HGSC exhibits high rates of chromosome aberrations and knowledge of causative mechanisms is likely to represent an important step towards combating the poor prognosis of this disease. However, very little is known about the nature of chromosomal instability exhibited by this cancer type in particular due to a historical lack of appropriate cell line models. Here we perform the first in-depth functional characterisation of mechanisms driving CIN in HGSC by analysing eight cell lines that accurately recapitulate HGSC genetics as defined by recent studies. We show, using a range of established functional CIN assays combined with live cell imaging and single molecule DNA fibre analysis, that multiple mechanisms co-exist to drive CIN in HGSC. These include supernumerary centrosomes, elevated microtubule dynamics and DNA replication stress. By contrast, the spindle assembly checkpoint was intact. These findings are relevant for developing therapeutic approaches to manipulating CIN in ovarian cancer, and suggests that such approaches may need to be multimodal to combat multiple co-existing CIN drivers.

scholarly journals The metabolic stress-activated checkpoint LKB1-MARK3 axis acts as a tumor suppressor in high-grade serous ovarian carcinoma

2022 ◽  
Vol 5 (1) ◽  
Author(s):  
Hidenori Machino ◽  
Syuzo Kaneko ◽  
Masaaki Komatsu ◽  
Noriko Ikawa ◽  
Ken Asada ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Ovarian Carcinoma ◽  
Cell Cycle Progression ◽  
Target Genes ◽  
Metabolic Stress ◽  
Ovarian Cancer Cells ◽  
Hippo Signaling ◽  
High Grade ◽  
Gynecological Malignancy ◽  
Serous Ovarian Carcinoma

AbstractHigh-grade serous ovarian carcinoma (HGSOC) is the most aggressive gynecological malignancy, resulting in approximately 70% of ovarian cancer deaths. However, it is still unclear how genetic dysregulations and biological processes generate the malignant subtype of HGSOC. Here we show that expression levels of microtubule affinity-regulating kinase 3 (MARK3) are downregulated in HGSOC, and that its downregulation significantly correlates with poor prognosis in HGSOC patients. MARK3 overexpression suppresses cell proliferation and angiogenesis of ovarian cancer cells. The LKB1-MARK3 axis is activated by metabolic stress, which leads to the phosphorylation of CDC25B and CDC25C, followed by induction of G2/M phase arrest. RNA-seq and ATAC-seq analyses indicate that MARK3 attenuates cell cycle progression and angiogenesis partly through downregulation of AP-1 and Hippo signaling target genes. The synthetic lethal therapy using metabolic stress inducers may be a promising therapeutic choice to treat the LKB1-MARK3 axis-dysregulated HGSOCs.

scholarly journals Ovarian Cancer Metastasis to the Larynx: A Case Report and Review of the Literature

2020 ◽  
Vol 2020 ◽  
pp. 1-4
Author(s):  
Chad Purcell ◽  
Ayham Al Afif ◽  
Martin Bullock ◽  
Martin Corsten
Keyword(s):  
Ovarian Cancer ◽  
Ovarian Carcinoma ◽  
World Literature ◽  
Cancer Metastasis ◽  
High Grade ◽  
Review Of The Literature ◽  
Serous Ovarian Carcinoma ◽  
The World ◽  
History Of ◽  
Progressive Dysphagia

Laryngeal secondary malignancies are rare, and most spread locoregionally from hypopharyngeal or thyroid primaries. Metastasis of ovarian carcinoma to the larynx is extremely rare. A 65-year-old woman with a history of high grade serous ovarian carcinoma was undergoing carboplatin chemotherapy for recurrence. She presented with progressive dysphagia and hoarseness; a computer tomography (CT) scan demonstrated bilateral necrotic lymphadenopathy and hypopharyngeal fullness. A hypopharyngeal mass was confirmed on examination, and operative biopsy identified it as high-grade serous ovarian. To our knowledge, this report describes the second immunohistochemically proven metastatic ovarian cancer detected in the larynx in the world literature.

scholarly journals The MEK1/2 Pathway as a Therapeutic Target in High-Grade Serous Ovarian Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1369
Author(s):  
Mikhail S. Chesnokov ◽  
Imran Khan ◽  
Yeonjung Park ◽  
Jessica Ezell ◽  
Geeta Mehta ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Tumor Growth ◽  
Ovarian Carcinoma ◽  
Cell Lines ◽  
Tumor Growth Rate ◽  
High Recurrence Rate ◽  
High Grade ◽  
Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) is the deadliest of gynecological cancers due to its high recurrence rate and acquired chemoresistance. RAS/MEK/ERK pathway activation is linked to cell proliferation and therapeutic resistance, but the role of MEK1/2-ERK1/2 pathway in HGSOC is poorly investigated. We evaluated MEK1/2 pathway activity in clinical HGSOC samples and ovarian cancer cell lines using immunohistochemistry, immunoblotting, and RT-qPCR. HGSOC cell lines were used to assess immediate and lasting effects of MEK1/2 inhibition with trametinib in vitro. Trametinib effect on tumor growth in vivo was investigated using mouse xenografts. MEK1/2 pathway is hyperactivated in HGSOC and is further stimulated by cisplatin treatment. Trametinib treatment causes cell cycle arrest in G1/0-phase and reduces tumor growth rate in vivo but does not induce cell death or reduce fraction of CD133+ stem-like cells, while increasing expression of stemness-associated genes instead. Transient trametinib treatment causes long-term increase in a subpopulation of cells with high aldehyde dehydrogenase (ALDH)1 activity that can survive and grow in non-adherent conditions. We conclude that MEK1/2 inhibition may be a promising approach to suppress ovarian cancer growth as a maintenance therapy. Promotion of stem-like properties upon MEK1/2 inhibition suggests a possible mechanism of resistance, so a combination with CSC-targeting drugs should be considered.

scholarly journals The role of distinct BRD4 isoforms and their contribution to high-grade serous ovarian carcinoma pathogenesis

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Ana Luiza Drumond-Bock ◽  
Magdalena Bieniasz
Keyword(s):  
Ovarian Cancer ◽  
Ovarian Carcinoma ◽  
Transcriptional Control ◽  
Epithelial Mesenchymal Transition ◽  
Genetic Alterations ◽  
High Grade ◽  
Mesenchymal Transition ◽  
Serous Ovarian Carcinoma ◽  
Ovarian Cancer Cell Lines ◽  
Patient Prognosis

AbstractHigh-grade serous ovarian carcinoma (HGSOC) is the most aggressive type of ovarian cancer, often diagnosed at advanced stages. Molecularly, HGSOC shows high degree of genomic instability associated with large number of genetic alterations. BRD4 is the 4th most amplified gene in HGSOC, which correlates with poor patients’ prognosis. BRD4 is constitutively expressed and generates two proteins, BRD4 long (BRD4-L) and BRD4 short (BRD4-S). Both isoforms contain bromodomains that bind to lysine-acetylated histones. Amongst other functions, BRD4 participates in chromatin organization, acetylation of histones, transcriptional control and DNA damage repair. In cancer patients with amplified BRD4, the increased activity of BRD4 is associated with higher expression of oncogenes, such as MYC, NOTCH3 and NRG1. BRD4-driven oncogenes promote increased tumor cells proliferation, genetic instability, epithelial-mesenchymal transition, metastasis and chemoresistance. Ablation of BRD4 activity can be successfully achieved with bromodomain inhibitors (BETi) and degraders, and it has been applied in pre-clinical and clinical settings. Inhibition of BRD4 function has an effective anti-cancer effect, reducing tumor growth whether ablated by single agents or in combination with other drugs. When combined with standard chemotherapy, BETi are capable of sensitizing highly resistant ovarian cancer cell lines to platinum drugs. Despite the evidence that BRD4 amplification in ovarian cancer contributes to poor patient prognosis, little is known about the specific mechanisms by which BRD4 drives tumor progression. In addition, newly emerging data revealed that BRD4 isoforms exhibit contradicting functions in cancer. Therefore, it is paramount to expand studies elucidating distinct roles of BRD4-L and BRD4-S in HGSOC, which has important implications on development of therapeutic approaches targeting BRD4.

scholarly journals Development of Machine Learning Models to Predict Platinum Sensitivity of High-Grade Serous Ovarian Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1875
Author(s):  
Suhyun Hwangbo ◽  
Se Ik Kim ◽  
Ju-Hyun Kim ◽  
Kyung Jin Eoh ◽  
Chanhee Lee ◽  
...  
Keyword(s):  
Machine Learning ◽  
Ovarian Carcinoma ◽  
Model Performance ◽  
Ca 125 ◽  
Lymph Node Status ◽  
High Grade ◽  
Learning Models ◽  
Platinum Sensitivity ◽  
Serous Ovarian Carcinoma ◽  
Machine Learning Models

To support the implementation of individualized disease management, we aimed to develop machine learning models predicting platinum sensitivity in patients with high-grade serous ovarian carcinoma (HGSOC). We reviewed the medical records of 1002 eligible patients. Patients’ clinicopathologic characteristics, surgical findings, details of chemotherapy, treatment response, and survival outcomes were collected. Using the stepwise selection method, based on the area under the receiver operating characteristic curve (AUC) values, six variables associated with platinum sensitivity were selected: age, initial serum CA-125 levels, neoadjuvant chemotherapy, pelvic lymph node status, involvement of pelvic tissue other than the uterus and tubes, and involvement of the small bowel and mesentery. Based on these variables, predictive models were constructed using four machine learning algorithms, logistic regression (LR), random forest, support vector machine, and deep neural network; the model performance was evaluated with the five-fold cross-validation method. The LR-based model performed best at identifying platinum-resistant cases with an AUC of 0.741. Adding the FIGO stage and residual tumor size after debulking surgery did not improve model performance. Based on the six-variable LR model, we also developed a web-based nomogram. The presented models may be useful in clinical practice and research.

scholarly journals Overexpression of ICAM-1 Predicts Poor Survival in High-Grade Serous Ovarian Carcinoma: A Study Based on TCGA and GEO Databases and Tissue Microarray

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Shasha Wang ◽  
Can Yin ◽  
Ying Zhang ◽  
Lu Zhang ◽  
Lin Tao ◽  
...  
Keyword(s):  
Overall Survival ◽  
Ovarian Carcinoma ◽  
Mrna Expression ◽  
Adhesion Molecule ◽  
Poor Prognosis ◽  
Prognostic Biomarker ◽  
The Cancer Genome Atlas ◽  
High Grade ◽  
Poor Survival ◽  
Serous Ovarian Carcinoma

Intercellular cell adhesion molecule-1 (ICAM-1), an important adhesion molecule in the immunoglobulin superfamily, is expressed on many cell types. Recent studies have identified ICAM-1 as a potential oncogene that promotes the development of epithelial ovarian cancer (EOC); it was also found to be associated with poor survival. However, the clinical significance of its expression in high-grade serous ovarian carcinoma (HGSOC) is unclear. Thus, this study aimed to investigate the significance of ICAM-1 expression in HGSOC. Data on ICAM1 expression and mutations in serous ovarian carcinoma (SOC) were obtained from the Cancer Genome Atlas (TCGA), and ICAM1 mRNA expression data in HGSOC were obtained from the Gene Expression Omnibus (GEO) database. ICAM-1 expression was evaluated by immunohistochemistry in HGSOC and normal fallopian tube tissues microarray. In TCGA data, amplification/mutation of ICAM1 was identified in 12% of serous ovarian carcinoma samples, and overexpression of ICAM1 mRNA predicted reduced overall survival in SOC. From TCGA and GEO data, SOC patients with ICAM1 mRNA overexpression treated with chemotherapeutic drugs that contained taxol or taxol and platin together had significantly reduced progression-free survival. According to GEO data, ICAM1 mRNA expression was found significantly higher in HGSOC than in control samples. In our study, ICAM-1 overexpression was observed in 63.1% (65/103) of HGSOCs. As a prognostic biomarker, overexpression of ICAM-1 predicted reduced recurrence-free and overall survival and is an independent risk factor for poor prognosis. These findings suggest that overexpression of ICAM-I is an independent indicator of poor prognosis for HGSOC and that it can serve as an effective clinical prognostic biomarker for this disease.

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