ArticleScientific reports2019
Prognostic classification of endometrial cancer using a molecular approach based on a twelve-gene NGS panel.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- A Novel Self-Competitive Fishing Primer qPCR Approach for Efficient POLE Mutation Detection in Endometrial Cancer Molecular Classification.Current issues in molecular biology · 2026Article
- Comparative evaluation of HTG and TempO Seq targeted transcriptome profiling methods.Scientific reports · 2026Article
- Review
- Computational image and molecular analysis reveal unique prognostic features of immune architecture in African Versus European American women with endometrial cancer.NPJ precision oncology · 2025Article
- Molecular Classification of Endometrial Cancers Using an Integrative DNA Sequencing Panel.Journal of surgical oncology · 2025Article
- Research progress of artificial intelligence in the early screening, diagnosis, precise treatment and prognosis prediction of three central gynecological malignancies.Frontiers in oncology · 2025Review
- Review
- Runt-related transcription factors in human carcinogenesis: a friend or foe?Journal of cancer research and clinical oncology · 2023Review
- Tumor-Infiltrating CD8-Positive T-Cells Associated with MMR and p53 Protein Expression Can Stratify Endometrial Carcinoma for Prognosis.Diagnostics (Basel, Switzerland) · 2023Article
- The Role of Biomarkers in Guiding Clinical Decision-Making in Oncology.Journal of the advanced practitioner in oncology · 2023Review
- Novel next generation sequencing panel method for the multiple detection and identification of foodborne pathogens in agricultural wastewater.Frontiers in microbiology · 2023Article
- Outcomes of fertility preservation treatments in patients with endometrial cancer with different molecular classifications based on an NGS panel.Frontiers in oncology · 2023Article
- Clinical evaluation of a droplet digital PCR assay for detectingJournal of gynecologic oncology · 2022Article
- The Diminishment of Novel Endometrial Carcinoma-Derived Stem-like Cells by Targeting Mitochondrial Bioenergetics and MYC.International journal of molecular sciences · 2022Article
- Prognosis Stratification Tools in Early-Stage Endometrial Cancer: Could We Improve Their Accuracy?Cancers · 2022Article
- A comprehensive next generation sequencing tissue assay for Asian-prevalent cancers-Analytical validation and performance evaluation with clinical samples.Frontiers in molecular biosciences · 2022Article
- Components ofJournal of oncology · 2022Article
- Machine learning random forest for predicting oncosomatic variant NGS analysis.Scientific reports · 2021Article
- The MCM3AP-AS1/miR-126/VEGF axis regulates cancer cell invasion and migration in endometrioid carcinoma.World journal of surgical oncology · 2021Article
- A Narrative Review of the Role of Diet and Lifestyle Factors in the Development and Prevention of Endometrial Cancer.Cancers · 2021Review
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8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Endometrial Cancer (EC) is one of the most common malignancies in women in developed countries. Molecular characterization of different biotypes may improve clinical management of EC. The Cancer Genome Atlas (TCGA) project has revealed four prognostic EC subgroups: POLE, MSI; Copy Number Low (CNL) and Copy Number High (CNH). The goal of this study was to develop a method to classify tumors in any of the four EC prognostic groups using affordable molecular techniques. Ninety-six Formalin-Fixed Paraffin-embedded (FFPE) samples were sequenced following a NGS TruSeq Custom Amplicon low input (Illumina) protocol interrogating a multi-gene panel. MSI analysis was performed by fragment analysis using eight specific microsatellite markers. A Random Forest classification algorithm (RFA), considering NGS results, was developed to stratify EC patients into different prognostic groups. Our approach correctly classifies the EC patients into the four TCGA prognostic biotypes. The RFA assigned the samples to the CNH and CNL groups with an accuracy of 0.9753 (p < 0.001). The prognostic value of these groups was prospectively reproduced on our series both for Disease-Free Survival (p = 0.004) and Overall Survival (p = 0.030).Hence, with the molecular approach herein described, a precise and suitable tool that mimics the prognostic EC subtypes has been solved and validated. Procedure that might be introduced into routine diagnostic practices.
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