Gene Expression Subtyping Reveals Immune alterations:TCGA Database for Prognosis in Ovarian Serous Cystadenocarcinoma

Feng, Chao; Xu, Yan; Liu, Yuanyuan; Zhu, Lixia; Wang, Le; Cui, Xueying; Lü, Jingjing; Zhang, Yan; Zhou, Lina; Chen, Min-Bin; Zhang, Zhiqin; Li, Ping

doi:10.3389/fmolb.2021.619027

Cited by 6 publications

(3 citation statements)

References 66 publications

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“…To avoid excessive false positive and false negative results, up-regulated differentially expressed genes (DEGs) between 2 groups were identified with the criteria of P<0.05 and fold change (FC) >3/2, down-regulated DEGs between two groups were identified with the criteria of P<0.05 and FC <2/3 according to the previous criteria ( 18 - 21 ). The ClusterProfiler package was used to conduct the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses.…”

Section: Methodsmentioning

confidence: 99%

A centrosome-related gene signature for predicting the overall survival of uveal melanoma

Yu,

Guo,

et al. 2024

Transl Cancer Res

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Background Centrosome aberration (CA) plays a vital role in tumorigenesis and metastasis under pathophysiological conditions. The existence of CA was first reported in uveal melanoma (UVM) recently. Our study aimed to investigate the association of centrosome-related genes with UVM prognosis. Methods The Cancer Genome Atlas (TCGA)-UVM and Gene Expression Omnibus series (GSE) 22138 were included in the study. Least absolute shrinkage and selection operator (LASSO) and Cox regression were combined to screen out key genes and construct a centrosome-related gene signature. Kaplan-Meier (KM) survival curves were used to evaluate the survival differences between the 2 groups. Gene enrichment, immune infiltration, and mutation profile were used to explore the underlying mechanism. Results A centrosome-related gene signature was constructed: Risk score =−3.27071 × MAP6 − 5.03735 × CCDC40 − 2.68459 × PRKCD + 1.826349 × IGFBP4 + 11.66582 × RAB6C − 4.86899 × CCND3. The survival possibilities of the two groups were significantly different. The high-risk group showed cancer progression, inflammation, and immune restriction characteristics when compared with the low-risk group. BAP1 mutation was associated with high risk and SF3B1 mutation was associated with low risk according to the signature. Conclusions Our study first investigated the role of centrosome-related genes in UVM overall survival (OS). We then constructed a centrosome-related gene signature for UVM, which provides new insights into the role of CA in UVM and identifies novel centrosome-related biomarkers.

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Section: Methodsmentioning

confidence: 99%

A centrosome-related gene signature for predicting the overall survival of uveal melanoma

Yu,

Guo,

et al. 2024

Transl Cancer Res

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“…[ 9 , 10 ] One research reported that a better clinical prognosis model related to the immune microenvironment was established for OV. [ 11 ] Another study identified 10 immune microenvironment genes related to the prognosis of OV. [ 12 ] Besides, 2 lncRNA-related molecular subtypes which had significant different prognosis and immunological characteristics by analyzing OV cohort in The Cancer Genome Atlas (TCGA).…”

Section: Introductionmentioning

confidence: 99%

Identification of two immune subtypes and four hub immune-related genes in ovarian cancer through multiple analysis

Tang,

Zhang,

Tang

2023

Medicine

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Immune classification of ovarian cancer (OV) becomes more and more influential for its immunotherapy. However, current studies had few immune subtypes of OV. It is urgent to explore the immune subtypes and deeper hub immune-related genes (IRGs) of OV for follow-up treatment. A total number of 379 OV samples were obtained from UCSC online website. Single sample gene set enrichment analysis of 29 immune gene sets was used for identifying immune subtypes of OV and gene set variation analysis were used for exploring the hallmarks and Kyoto Encyclopedia of Genes and Genomes pathways of immune types. Two immunity subtypes (Immunity_H and Immunity_L) were identified by single sample gene set enrichment analysis. The OV patients in Immunity_H group had longer overall survival compared with those in Immunity_L group. The Immunity_H had higher stromal score, immune score and estimate score and the tumor purity had the adverse tendency. Besides, the gene set variation analysis enrichment results showed positive relationship between improved immunoreaction and pathways correlated to classical signaling pathway (PI3K/AKT/MTOR, P53, TNFA/NFkB signaling pathways) and immune responses (T/B cell receptor signaling pathways and primary immunodeficiency). Furthermore, 4 hub IRGs (CCR5, IL10RA, ITGAL and PTPRC) were jointly dug by weighted gene co-expression network construction and Cytoscape. Our team also explored the mutations of 4 hub IRGs and PTPRC showed nearly 7% amplification. Besides, 8 immune-checkpoint genes had higher expression in Immuity_H group compared with Immuity_L group, except CD276. The correlation between PD-1/PD-L1 and 4 hub IRGs were explored and gene set enrichment analysis were conducted to explore the underlying mechanisms of PTPRC in OV. Finally, western-blotting showed PTPRC could regulate immune checkpoint PD-L1 expression via JAK-STAT signaling pathway. In a word, 2 immune subtypes and 4 hub IRGs of OV were identified by multiple analysis.

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“…Despite their previous omission, these easily assessed factors profiling the distinct specificities of functional status and social support may be prognostic indicators. Currently used prognostic models for HGSOC mainly focus on biomarkers (12)(13)(14)(15), or clinical features with radiology (16,17). They reported the range of models' c-index of about 0.6-0.7.…”

Section: Introductionmentioning

confidence: 99%

Novel prognostic nomograms to assess survival in high-grade serous ovarian carcinoma after surgery and chemotherapy: a retrospective cohort study from SEER database

Wu¹,

Bao²,

Luo³

et al. 2022

Ann Transl Med

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Background: Despite high-grade serous ovarian carcinoma (HGSOC) being the most common epithelial ovarian cancer, it is a heterogenous group of tumors with several histological subtypes. The goal of our study was to develop specifical models to predict the survival of actively treated, HGSOC.Methods: This retrospective cohort study included patients with HGSOC who had undergone surgery and chemotherapy between the years of 2010 and 2016 using the Surveillance, Epidemiology, and End Results (SEER) database. A total of 3,788 cases were randomly divided into a training (n=2,591) and test set (n=1,197).Cox-LASSO algorithm and cross validation (based on lambda.1se) were used to identify survival factors in the training set. Nomograms were created and internally validated. We used Harrell's C-statistic to assess discrimination. The performance of each nomogram was evaluated using calibration plots. The clinical benefit of our models was evaluated using a decision curve analysis.Results: The significant prognostic factors were marital status, age, lymph node (LN) dissection, tumor size, residual disease, and the International Federation of Obstetrics and Gynecology (FIGO) stage, which were utilized to develop the nomogram for accurately predicting 3-and 5-year overall survival (OS). Among the above factors, except for marital status, the others were included in the model for cancer-specific survival (CSS). The C-indices for OS and CSS achieved 0.679 [95% confidence interval (CI): 0.660 to 0.699] and 0.678 (95% CI: 0.658 to 0.698), respectively, in the training set and 0.662 (95% CI: 0.633 to 0.690) and 0.680 (95% CI: 0.653 to 0.707), respectively, in the test set. The good consistency was illustrated using calibration plots. In comparison with models including only FIGO or the AJCC staging system, C-index in our study were increased by 4.5-7.0% for the development test and by 6.7-7.9% for the validation test. In addition, the nomograms had a bigger range of threshold probabilities in the DCA curves. The high-risk subgroup had significantly less favorable survival than the low-risk subgroup.Conclusions: The present study indicated that the low-cost nomograms could be used as a potential prognostic tool specially for predicting survival in patients with HGSOC. Given the relatively small C-index, we still need to build a more accurate model to predict survival of HGSOC.

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Gene Expression Subtyping Reveals Immune alterations:TCGA Database for Prognosis in Ovarian Serous Cystadenocarcinoma

Cited by 6 publications

References 66 publications

A centrosome-related gene signature for predicting the overall survival of uveal melanoma

A centrosome-related gene signature for predicting the overall survival of uveal melanoma

Identification of two immune subtypes and four hub immune-related genes in ovarian cancer through multiple analysis

Novel prognostic nomograms to assess survival in high-grade serous ovarian carcinoma after surgery and chemotherapy: a retrospective cohort study from SEER database

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