scholarly journals Identification of a six-gene signature with prognostic value for patients with endometrial carcinoma

2018 ◽  
Vol 7 (11) ◽  
pp. 5632-5642 ◽  
Author(s):  
Yizi Wang ◽  
Fang Ren ◽  
Peng Chen ◽  
Shuang Liu ◽  
Zixuan Song ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Prognostic Value ◽  
Gene Signature

scholarly journals Identification of the prognostic value of a 2-gene signature of the WNT gene family in UCEC using bioinformatics and real-world data

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuexin Hu ◽  
Mingjun Zheng ◽  
Dandan Zhang ◽  
Rui Gou ◽  
Ouxuan Liu ◽  
...  
Keyword(s):  
Gene Family ◽  
Endometrial Carcinoma ◽  
Clinical Features ◽  
Risk Score ◽  
Real World ◽  
Prognostic Value ◽  
Gene Signature ◽  
Real World Data ◽  
Uterine Corpus ◽  
World Data

Abstract Background The WNT gene family plays an important role in the occurrence and development of malignant tumors, but its involvement has not been systematically analyzed in uterine corpus endometrial carcinoma (UCEC). This study aimed to evaluate the prognostic value of the WNT gene family in UCEC. Methods Pan-cancer transcriptome data of the UCSC Xena database and Genotype-Tissue Expression (GTEx) normal tissue data were downloaded to analyze the expression and prognosis of 19 WNT family genes in UCEC. A cohort from The Cancer Genome Atlas-Uterine Corpus Endometrial Carcinoma (TCGA-UCEC) was used to analyze the expression of the WNT gene family in different immune subtypes and clinical subgroups. The STRING database was used to analyze the interaction of the WNT gene family and its biological function. Univariate Cox regression analysis and Lasso cox analysis were used to identify the genes associated with significant prognosis and to construct multi signature prognosis model. An immunohistochemical assay was used to verify the predictive ability of the model. Risk score and the related clinical features were used to construct a nomogram. Results The expression levels of WNT2, WNT3, WNT3A, WNT5A, WNT7A, and WNT10A were significantly different among different immune subtypes and correlated with TP53 mutation. According to the WNT family genes related to the prognosis of UCEC, UCEC was classified into two subtypes (C1, C2). The prognosis of subtype C1 was significantly better than that of subtype C2. A 2-gene signature (WNT2 and WNT10A) was constructed and the two significantly prognostic groups can be divided based on median Risk score. These results were verified using real-world data, and the nomogram constructed using clinical features and Risk score had good prognostic ability. Conclusions The 2-gene signature including WNT2 and WNT10A can be used to predict the prognosis of patients with UCEC, which is important for clinical decision-making and individualized therapy for patients with UCEC.

scholarly journals Identification of an immune gene signature with prognostic value for patients with uterine corpus endometrial carcinoma

2020 ◽  
Author(s):  
Cankun Zhou ◽  
Chaomei Li ◽  
Fangli Yan ◽  
Yuhua Zheng
Keyword(s):  
Regression Analysis ◽  
Endometrial Carcinoma ◽  
Prognostic Value ◽  
Prognostic Model ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Signature ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Immune Genes

Abstract Background: Uterine corpus endometrial carcinoma (UCEC) is a very common gynecological malignancy with a poor prognosis in the late stage. Therefore, the purpose of this study was to determine an immune-related gene signature that predicts the patients’ OS for UCEC. Methods: Based on TCGA, ImmPort, and Cistrome databases, the differential immune genes were screened and the TFs regulatory network was constructed. Functional enrichment and pathway analysis of differential immune genes were carried out. Prognostic value of 410 immune genes was analyzed by Cox regression analysis, a prognostic model was constructed, ROC curves were used to verify the accuracy of the model, and independent prognostic analysis was performed. Finally, the immune cell content was obtained by TIMER, and the correlation with the immune gene expression was evaluated by univariate Cox regression analysis. Results: It was found that the immune cell microenvironment and PI3K-Akt, MARK signaling pathways were involved in the development of UCEC. Based on the established prognostic model, ten-gene prognosis signature (PDIA3, LTA, PSMC4, TNF, SBDS, HDGF, HTR3E, NR3C1, PGR, CBLC) for UCEC prognostic prediction were finally identified, and our study has shown that risk-score can be a powerful prognostic factor for UCEC, independent of other clinical factors. The levels of B cells and neutrophils may be significantly correlated with the patient's risk score. Conclusions: Our studies showed that the ten-gene prognosis signature had important clinical value for the prognosis of UCEC, which was helpful for individualized treatment and provided a new target for tumor immunotherapy.

Prognostic value of peritoneal cytology in endometrial carcinoma

1990 ◽  
Vol 33 (1) ◽  
pp. 87-87
Author(s):  
R.N. Grimshaw ◽  
W.C. Tupper ◽  
R.C. Fraser ◽  
M.G. Tompkins ◽  
J.F. Jeffrey
Keyword(s):  
Endometrial Carcinoma ◽  
Prognostic Value ◽  
Peritoneal Cytology

Prognostic value of myometrial invasion and TCGA groups of endometrial carcinoma

2021 ◽  
Author(s):  
Antonio Raffone ◽  
Antonio Travaglino ◽  
Diego Raimondo ◽  
Daniele Neola ◽  
Federica Renzulli ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Prognostic Value ◽  
Myometrial Invasion

Prognostic Value of DNA Ploidy and S-Phase Fraction in Stage I Endometrial Carcinoma

1995 ◽  
Vol 58 (2) ◽  
pp. 149-156 ◽  
Author(s):  
Jacobus Pfisterer ◽  
Friedrich Kommoss ◽  
Willi Sauerbrei ◽  
Ina Rendl ◽  
Marion Kiechle ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Prognostic Value ◽  
Dna Ploidy ◽  
S Phase ◽  
Stage I ◽  
Phase Fraction

Prospective Multicenter Validation Confirms the Prognostic Superiority of the Endometrial Carcinoma Prognostic Index in International Federation of Gynecology and Obstetrics Stage 1 and 2 Endometrial Carcinoma

2003 ◽  
Vol 21 (22) ◽  
pp. 4214-4221 ◽  
Author(s):  
Jan P.A. Baak ◽  
Wim Snijders ◽  
Bianca van Diermen ◽  
Paul J. van Diest ◽  
Fred W. Diepenhorst ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Prognostic Value ◽  
Dna Ploidy ◽  
Prognostic Index ◽  
Prognostic Indicator ◽  
International Federation ◽  
Kaplan Meier ◽  
Gynecology And Obstetrics ◽  
Stage 1 ◽  
Endometrial Carcinomas

Purpose: To validate the prognostic value of the endometrial carcinoma prognostic index (ECPI; combined myometrium invasion, flow cytometric DNA ploidy, and morphometric mean shortest nuclear axis [MSNA]) versus classic prognosticators. Patients and Methods: Prospective multicenter ECPI analysis was conducted in 463 endometrial carcinomas with a median of 6.5 years (range, 1 to 10 years) follow-up, review of pathology features, and univariate (Kaplan-Meier) and multivariate (Cox) analyses. Results: Initial routine and review diagnoses varied considerably (invasion depth, 11%; type, 20%; grade, 34%; vessel invasion, 72%); the review diagnoses were stronger prognostically. In International Federation of Gynecology and Obstetrics stage 1 (after histopathologic examination; pFIGO-1; n = 372; 38 deaths occurred as a result of disease [10.2%]), DNA ploidy was prognostic in hysterectomies (P < .00001) but not in curettages (P = .06). ECPI was a stronger prognostic indicator than other features. ECPI, MSNA, and DNA ploidy were also prognostic in pFIGO-1B and -1C subgroups. Multivariate analysis in pFIGO-1 showed that uterine MSNA ≤ versus > 7.93 μm (hazard ratio [HR], 3.4) and grade (as 1 + 2 v 3; HR, 2.6) added to the ECPI (HR, 32), but only in patients with an unfavorable ECPI of > 0.87. Adjuvant radiotherapy was not an independent prognostic factor in any of the subgroups. In pFIGO-2 (n = 46), ECPI, DNA-ploidy, and age (≤ 64, > 64 years) were significant. In FIGO-3 (n = 31) and FIGO-4 (n = 14), none of the classic or other features analyzed was of prognostic value, which explains why in previous studies using different mixtures of FIGO stages, DNA ploidy prognostic results varied. Conclusion: In endometrial carcinoma, DNA-ploidy is prognostic in hysterectomy and not in curettage samples. The ECPI is prognostically much stronger than the classic features widely used for therapy triage in pFIGO-1 and -2.

scholarly journals The Landscape of Glycosyltransferase Gene Signature for Overall Survival Prediction in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Qiang Cai ◽  
Shizhe Yu ◽  
Jian Zhao ◽  
Duo Ma ◽  
Long Jiang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Risk Score ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Groups ◽  
Gene Signature ◽  
Low Risk ◽  
Regression Analyses ◽  
Risk Patients

Abstract Background: Hepatocellular carcinoma (HCC) is heterogeneous disease occurring in the background of chronic liver diseases. The role of glycosyltransferase (GT) genes have recently been the focus of research associating with the development of tumors. However, the prognostic value of GT genes in HCC remains not elucidated. This study aimed to demonstrate the GT genes related to the prognosis of HCC through bioinformatics analysis.Methods: The GT genes signatures were identified from the training set of The Cancer Genome Atlas (TCGA) dataset using univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Then, we analyzed the prognostic value of GT genes signatures related to the overall survival (OS) of HCC patients. A prognostic model was constructed, and the risk score of each patient was calculated as formula, which divided HCC patients into high- and low-risk groups. Kaplan-Meier (K-M) and Receiver operating characteristic (ROC) curves were used to assess the OS of HCC patients. The prognostic value of GT genes signatures was further investigated in the validation set of TCGA database. Univariate and multivariate Cox regression analyses were performed to demonstrate the independent factors on OS. Finally, we utilized the gene set enrichment analysis (GSEA) to annotate the function of these genes between the two risk categories. Results: In this study, we identified and validated 4 GT genes as the prognostic signatures. The K-M analysis showed that the survival rate of the high-risk patients was significantly lower than that of the low-risk patients. The risk score calculated with 4 gene signatures could predict OS for 3-, 5-, and 7-year in patients with HCC, revealing the prognostic ability of these gene signature. In addition, Multivariate Cox regression analyses indicated that the risk score was an independent prognostic factor for HCC. Functional analysis further revealed that immune-related pathways were enriched, and immune status in HCC were different between the two risk groups.Conclusion: In conclusion, a novel GT genes signature can be used for prognostic prediction in HCC. Thus, targeting GT genes may be a therapeutic alternative for HCC.

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