Discovery of a biomarker candidate for surgical stratification in high-grade serous ovarian cancer

Cunnea, Paula; Nixon, Katherine; Rinne, Natasha; Aboagye, Eric O.; Fotopoulou, Christina

doi:10.1038/s41416-020-01252-2

Cited by 14 publications

(10 citation statements)

References 33 publications

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“…Various findings have shown that ovarian cancer is associated with high mortality, and in most cases, it is diagnosed after the metastasis of cancer beyond the ovaries and often throughout the abdomen, which should be considered because early detection can lead to effective treatment and lower recurrence. [19][20][21] One of the limitations of this study was the small number of samples studied. During the 12 years of study, we tried to increase the sample as much as possible to a reasonable and measurable level.…”

Section: Discussionmentioning

confidence: 94%

Recurrence and 5-year survival rate in patients with borderline ovarian tumors and related factors in Kurdistan

2022

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The aim of this study was to investigate the recurrence rate and five-year survival in patients with borderline ovarian tumors and related factors. This retrospective cohort study was performed on 20 women diagnosed with a borderline ovarian tumor in Kurdistan province, Iran, between 2007 and 2019. Patients' records were reviewed and a researcher-made questionnaire was completed for each patient, which included demographic and clinical variables related to patient survival. The most common type of ovarian borderline tumor was the serous borderline ovarian tumor (75%). In fifty percent of the cases, cystectomy was used as th treatment. Recurrence was observed in three patients (15%), two of which were treated with cystectomy, and the other case was treated by TAH + BSO method (p = 0.64). There was no significant difference in terms of the type of surgery, history of infertility, history of taking contraceptive pills, age, age at diagnosis, and BMI between the two groups with and without recurrence (p > 0.05). The overall survival rate was 100% and none of the patients died at the end of follow-up. There was no relationship between any of the clinical and demographic variables with disease recurrence, and since all patients were alive after the end of the follow-up period. In summary, it was not possible to assess the relationship between patients' survival rate and studied variables.

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Section: Discussionmentioning

confidence: 94%

Recurrence and 5-year survival rate in patients with borderline ovarian tumors and related factors in Kurdistan

2022

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“…DPM1, one of the relevant genes, is a vital sensor molecule related to the regulation of cytosolic Ca 2+ levels in the maintenance of B-cell functions and a potential prognostic tumor marker of HCC ( Li et al, 2020b ). ALG5 was reported as a prognostic biomarker for early tumor progression in advanced high-grade serous ovarian cancer (HGSOC) ALG5 ( Lu et al, 2021 ). A previous study indicated that ALG9 was regulated by lncRNA MEG3 and participated in the drug resistance mechanism in acute myeloid leukemia ( Yu et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Expression of ALG3 in Hepatocellular Carcinoma and Its Clinical Implication

Zhao

Zheng

Huang

et al. 2022

Front. Mol. Biosci.

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Background: Recent studies have shown that alpha-1,3-mannosyltransferase (ALG3) promoted tumorigenesis and progression in multiple cancer types. Our study planned to explore the clinical implication and potential function of ALG3 in hepatocellular carcinoma.Materials and Methods: Data from public databases were used to analyze the ALG3 expression and its impact on the clinical significance of patients with HCC. The ALG3 expression was confirmed by qRT-PCR and Western blot. Immunohistochemistry was used to confirm the ALG3 expression and explore its clinical implication in HCC. KEGG, GO, and GSEA enrichment analyses were utilized to explore the biological pathways related to ALG3 in HCC. TIMER2.0 was applied to assess the association between ALG3 and immune infiltration. CCK8, MTT, and transwell assays were used to investigate the role of ALG3 downregulation in HCC cell lines.Results: qRT-PCR, WB, and IHC proved ALG3 was highly overexpressed in HCC tissues. The Kaplan–Meier analysis verified the overexpression of ALG3 was related to poor overall survival (p < 0.001). Multivariate cox regression analysis showed that the high ALG3 expression was an independent risk prognostic factor. GSEA and TIMER2.0 predicted that ALG3 participates in cell differentiation and cycle and correlates with immune cell infiltration. Transwell assay results showed that ALG3 silencing also impaired the invasion ability of HCC cells.Conclusion: ALG3 was overexpressed and considered a potential indicator of survival in HCC, and our findings provided a novel therapeutic target for HCC.

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“…One such technology is microarray sequencing, in which mRNA counts are used to describe gene expression. Such data, known as transcriptomics, are widely used in the biomedical domain and when analyzed alongside survival times have provided extraordinary opportunities for biomarker characterization and prognostic modeling ( Bøvelstad et al , 2007 ; Lightbody et al , 2019 ; Lloyd et al , 2015 ; Lu et al , 2021 ). However, profiling data are often high-dimensional, which introduces several statistical challenges including: (i) variable selection, (ii) effect estimation of the features, (iii) uncertainty quantification and (iv) scalable computation.…”

Section: Introductionmentioning

confidence: 99%

Variational Bayes for high-dimensional proportional hazards models with applications within gene expression

et al. 2022

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Motivation Few Bayesian methods for analyzing high-dimensional sparse survival data provide scalable variable selection, effect estimation and uncertainty quantification. Such methods often either sacrifice uncertainty quantification by computing maximum a posteriori estimates, or quantify the uncertainty at high (unscalable) computational expense. Results We bridge this gap and develop an interpretable and scalable Bayesian proportional hazards model for prediction and variable selection, referred to as SVB. Our method, based on a mean-field variational approximation, overcomes the high computational cost of MCMC whilst retaining useful features, providing a posterior distribution for the parameters and offering a natural mechanism for variable selection via posterior inclusion probabilities. The performance of our proposed method is assessed via extensive simulations and compared against other state-of-the-art Bayesian variable selection methods, demonstrating comparable or better performance. Finally, we demonstrate how the proposed method can be used for variable selection on two transcriptomic datasets with censored survival outcomes, and how the uncertainty quantification offered by our method can be used to provide an interpretable assessment of patient risk. Availability and implementation our method has been implemented as a freely available R package survival.svb (https://github.com/mkomod/survival.svb). Supplementary information Supplementary materials are available at Bioinformatics online.

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Discovery of a biomarker candidate for surgical stratification in high-grade serous ovarian cancer

Cited by 14 publications

References 33 publications

Recurrence and 5-year survival rate in patients with borderline ovarian tumors and related factors in Kurdistan

Recurrence and 5-year survival rate in patients with borderline ovarian tumors and related factors in Kurdistan

Expression of ALG3 in Hepatocellular Carcinoma and Its Clinical Implication

Variational Bayes for high-dimensional proportional hazards models with applications within gene expression

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