scholarly journals Significance of PTEN Mutational Status Associated Gene Signature in the Progression and Prognosis of Endometrial Carcinoma

Author(s):  
Qing Hu ◽  
Jun Wang ◽  
Lina Ge ◽  
Ying Wu

Abstract BackgroundPTEN mutation had been reported to be involved in the development and prognosis of endometrial carcinoma (EC). However, a prognostic genes signature associated with PTEN mutational status has not been developed. In this study, we aim to conduct a PTEN mutation associated prognostic genes signature for EC.MethodsWe obtained the simple nucleotide variation and transcriptome profiling data from The Cancer Genome Atlas database as training data. Lasso Cox regression algorithm was used to establish PTEN mutation associated prognostic genes signature. The overall survival rate of the high-risk and low-risk groups was determined by Kaplan-Meier (K-M) method. The accuracy of risk score prediction was tested by ROC curve.ResultsK-M curves revealed that the EC patients with PTEN mutation have favorable survival outcome. Differential expression analysis between the EC patients with PTEN mutation and PTEN wild identified 224 differential expression genes (DEGs). Eighty-four DEGs with prognostic value was fitted into least absolute shrinkage and selection operator (LASSO)–Cox analysis and a seven PTEN mutation associated prognostic genes signature with robust prognostic ability was constructed, which was successfully validated in the other two datasets from cBioPortal database as well as 60 clinical specimens. Furthermore, the PTEN mutation associated prognostic genes signature had been proved to be an independent prognostic predictor for EC. Remarkably, the EC patients in high-risk group were characterized with higher stages and grades as well as lower tumor mutation burden of EC, with poor survival outcome. Collectively, the PTEN mutation associated prognostic genes signature was a favorable prognostic biomarker for EC.ConclusionIn summary, we conducted and validated a prognostic predictor for EC associated with PTEN mutational status, which may be used as favorable prognostic biomarkers and therapeutic targets for EC.

2021 ◽  
Author(s):  
Wancheng Zhao ◽  
Fangfang Bi ◽  
Xue Pan

Abstract Background:TP53 mutations are associated with poor outcome for patients with endometrial carcinoma (EC). However, to date, there have been no studies focused on the construction of TP53 mutational status-associated signature in EC. In this study, we aim to conduct a TP53 mutation associated prognostic genes signature for EC.Methods: Hence, we explored the mutational landscape of TP53 in patients with EC based on the simple nucleotide variation data downloaded from The Cancer Genome Atlas (TCGA) database. Differential expression analysis and least absolute shrinkage and selection operator (LASSO)–Cox analysis was used to establish TP53 mutation associated prognostic genes signature. The overall survival rate between the high-risk and low-risk groups was compared by Kaplan-Meier (K-M) method. Results: We found that the TP53 mutation was associated with poor outcome, older age, lower BMI, and higher grade and stage of EC in patients. A TP53 mutational status-associated signature was established based on transcriptome profiling data. Moreover, the patients in TCGA database were categorized into high- and low-risk groups. Kaplan–Meier (K-M) analysis indicated that the patients in the high-risk group have poor survival outcome. Furthermore, receiver operating characteristic (ROC) curves confirmed the robust prognostic prediction efficiency of the TP53 mutational status-associated signature. Finally, the prognostic ability was successfully verified in the other two datasets from cBioPortal database as well as in 60 clinical specimens.Conclusion: In summary, our research constructed a powerful TP53 mutational status-associated signature that could be a potential novel prognostic biomarker and therapeutic target for EC.


2021 ◽  
Vol 20 ◽  
pp. 153303382110049
Author(s):  
Bei Li ◽  
Long Fang ◽  
Baolong Wang ◽  
Zengkun Yang ◽  
Tingbao Zhao

Osteosarcoma often occurs in children and adolescents and causes poor prognosis. The role of RNA-binding proteins (RBPs) in malignant tumors has been elucidated in recent years. Our study aims to identify key RBPs in osteosarcoma that could be prognostic factors and treatment targets. GSE33382 dataset was downloaded from Gene Expression Omnibus (GEO) database. RBPs extraction and differential expression analysis was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to explore the biological function of differential expression RBPs. Moreover, we constructed Protein-protein interaction (PPI) network and obtained key modules. Key RBPs were identified by univariate Cox regression analysis and multiple stepwise Cox regression analysis combined with the clinical information from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Risk score model was generated and validated by GSE16091 dataset. A total of 38 differential expression RBPs was identified. Go and KEGG results indicated these RBPs were significantly involved in ribosome biogenesis and mRNA surveillance pathway. COX regression analysis showed DDX24, DDX21, WARS and IGF2BP2 could be prognostic factors in osteosarcoma. Spearman’s correlation analysis suggested that WARS might be important in osteosarcoma immune infiltration. In conclusion, DDX24, DDX21, WARS and IGF2BP2 might play key role in osteosarcoma, which could be therapuetic targets for osteosarcoma treatment.


Author(s):  
Yongmei Wang ◽  
Guimin Zhang ◽  
Ruixian Wang

Background: This study aims to explore the prognostic values of CT83 and CT83-related genes in lung adenocarcinoma (LUAD). Methods: We downloaded the mRNA profiles of 513 LUAD patients (RNA sequencing data) and 246 NSCLC patients (Affymetrix Human Genome U133 Plus 2.0 Array) from TCGA and GEO databases. According to the median expression of CT83, the TCGA samples were divided into high and low expression groups, and differential expression analysis between them was performed. Functional enrichment analysis of differential expression genes (DEGs) was conducted. Univariate Cox regression analysis and LASSO Cox regression analysis were performed to screen the optimal prognostic DEGs. Then we established the prognostic model. A Nomogram model was constructed to predict the overall survival (OS) probability of LUAD patients. Results: CT83 expression was significantly correlated to the prognosis of LUAD patients. A total of 59 DEGs were identified, and a predictive model was constructed based on six optimal CT83-related DEGs, including CPS1, RHOV, TNNT1, FAM83A, IGF2BP1, and GRIN2A, could effectively predict the prognosis of LUAD patients. The nomogram could reliably predict the OS of LUAD patients. Moreover, the six important immune checkpoints (CTLA4, PD1, IDO1, TDO2, LAG3, and TIGIT) were closely correlated with the Risk Score, which was also differentially expressed between the LUAD samples with high and low-Risk Scores, suggesting that the poor prognosis of LUAD patients with high-Risk Score might be due to the immunosuppressive microenvironments. Conclusion: A prognostic model based on six optimal CT83 related genes could effectively predict the prognosis of LUAD patients.


2021 ◽  
Author(s):  
Rui Feng ◽  
Jian Li ◽  
Weiling Xuan ◽  
Hanbo Liu ◽  
Dexin Cheng ◽  
...  

Abstract Background Hepatocellular carcinoma (HCC) is a prevalent primary liver cancer and the main cause of cancer mortality. Its high complexity and dismal prognosis bring dramatic difficulty to treatment. Due to the disclosed dual functions of autophagy in cancer development, understanding autophagy-related genes devotes into seeking novel biomarkers for HCC. Methods Differential expression of genes in normal and tumor groups was analyzed to acquire autophagy-related genes in HCC. GO and KEGG pathway analyses were conducted on these genes. Genes were then screened by univariate regression analysis. The screened genes were subjected to multivariate Cox regression analysis to build a prognostic model. The model was validated by ICGC validation set. Results Altogether, 42 autophagy-related differential genes were screened by differential expression analysis. Enrichment analysis showed that they were mainly enriched in pathways including regulation of autophagy and cell apoptosis. Genes were screened by univariate analysis and multivariate Cox regression analysis to build a prognostic model. The model was constituted by 6 feature genes: EIF2S1, BIRC5, SQSTM1, ATG7, HDAC1, FKBP1A. Validation confirmed the accuracy and independence of this model in predicting HCC patient’s prognosis. Conclusion A total of 6 feature genes were identified to build a prognostic risk model. This model is conducive to investigating interplay between autophagy-related genes and HCC prognosis.


1999 ◽  
Vol 17 (5) ◽  
pp. 1382-1382 ◽  
Author(s):  
Helga B. Salvesen ◽  
Ole Erik Iversen ◽  
Lars A. Akslen

PURPOSE: For endometrial carcinoma patients, there is a need for improved identification of high-risk groups that may benefit from postoperative adjuvant therapy. We therefore studied the prognostic impact of markers for cell proliferation, cell-cycle regulation, and angiogenesis among endometrial carcinoma patients in a population-based setting. PATIENTS AND METHODS: All patients diagnosed with endometrial carcinoma between 1981 and 1985 in Hordaland County, Norway, were studied. The median follow-up for the survivors was 11.5 years (range, 8 to 15 years), with no patient lost because of insufficient follow-up information. Paraffin-embedded tumor tissue, available in 96% of the cases (n = 142), was studied immunohistochemically for microvessel density (MVD) and expression of Ki-67, p53, and p21 proteins. We used the hot spot method for calculation of MVD, and expression of Ki-67 and p21 protein, because this approach may increase the probability of detecting small aggressive clones of possible prognostic relevance. The importance of these tumor markers was investigated in univariate survival analyses and Cox regression analysis. RESULTS: The majority of traditional clinicopathologic variables was significantly associated with the tumor biomarkers. Age, International Federation of Gynecology and Obstetrics (FIGO) stage, histologic type, histologic grade, MVD, as well as Ki-67, p53, and p21 protein expression, all significantly influenced survival in univariate analyses (P ≤ .05). In the Cox regression analysis, age, FIGO stage, MVD, Ki-67 expression, and p53 expression were the only variables with independent prognostic impact (P ≤ .05), whereas histologic type, histologic grade, and p21 expression had no independent influence. A group of high-risk patients with more than one unfavorable marker was identified. CONCLUSION: In addition to age and FIGO stage, MVD, Ki-67, and p53 protein expression showed an independent prognostic impact. Thus, information derived from routine histologic specimens identified a subgroup of high-risk endometrial carcinoma patients in this population-based study.


2021 ◽  
Vol 104 (1) ◽  
pp. 003685042110065
Author(s):  
Jing Wan ◽  
Peigen Chen ◽  
Yu Zhang ◽  
Jie Ding ◽  
Yuebo Yang ◽  
...  

Endometrial carcinoma (EC) is the fourth most common cancer in women. Some long non-coding RNAs (lncRNAs) are regarded as potential prognostic biomarkers or targets for treatment of many types of cancers. We aim to screen prognostic-related lncRNAs and build a possible lncRNA signature which can effectively predict the survival of patients with EC. We obtained lncRNA expression profiling from the TCGA database. The patients were classified into training set and verification set. By performing Univariate Cox regression model, Robust likelihood-based survival analysis, and Cox proportional hazards model, we developed a risk score with the Cox co-efficient of individual lncRNAs in the training set. The optimum cut-off point was selected by ROC analysis. Patients were effectively divided into high-risk group and low-risk group according to the risk score. The OS of the low-risk patients was significantly prolonged compared with that of the high-risk group. At last, we validated this 11-lncRNA signature in the verification set and the complete set. We identified an 11-lncRNA expression signature with high stability and feasibility, which can predict the survival of patients with EC. These findings provide new potential biomarkers to improve the accuracy of prognosis prediction of EC.


Author(s):  
Yin Sun ◽  
Juan Zhou ◽  
Yongjie Wang ◽  
Lin Zeng ◽  
Chao Liang ◽  
...  

Osteosarcoma (OSA) is the most common primary malignant bone tumor. More than 40% of patients with OSA have poor prognoses. We aimed to discover a biomarker for patient stratification and therapeutic targets for these high-risk patients. Using Single Sample Gene Set Enrichment Analysis (ssGSEA) and univariate Cox analysis, six hallmarks were identified as significant prognostic factors for overall survival (OS). Three were selected to construct a multivariate Cox model. Then, WGCNA, univariate Cox regression, Kaplan-Meier (KM) survival analyses, and multivariate Cox analyses were combined to filter promising candidates and establish a seven-gene signature to predict OS, whose prognostic value was validated internally and externally. Subsequently, Differential Expression Analysis was conducted between high- and low-risk patients, and the Robust Rank Aggregation algorithm was used to determine the robust DEGs. Metascape was used to perform pathway and process enrichment analyses as well as construct protein-protein interaction (PPI) networks. Finally, RPS28 was identified as an independent risk factor by using univariate and multivariate Cox regression, which was preliminarily validated as a promising therapeutic target by using RNA interference. In conclusion, we might contribute to optimizing risk stratification and an excellent therapeutic target for high-risk patients with OSA.


2021 ◽  
Vol 12 ◽  
Author(s):  
Denggang Fu ◽  
Biyu Zhang ◽  
Shiyong Wu ◽  
Yinghua Zhang ◽  
Jingwu Xie ◽  
...  

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies that has an unfavorable outcome and a high rate of relapse. Autophagy plays a vital role in the development of and therapeutic responses to leukemia. This study identifies a potential autophagy-related signature to monitor the prognoses of patients of AML. Transcriptomic profiles of AML patients (GSE37642) with the relevant clinical information were downloaded from Gene Expression Omnibus (GEO) as the training set while TCGA-AML and GSE12417 were used as validation cohorts. Univariate regression analyses and multivariate stepwise Cox regression analysis were respectively applied to identify the autophagy-related signature. The univariate Cox regression analysis identified 32 autophagy-related genes (ARGs) that were significantly associated with the overall survival (OS) of the patients, and were mainly rich in signaling pathways for autophagy, p53, AMPK, and TNF. A prognostic signature that comprised eight ARGs (BAG3, CALCOCO2, CAMKK2, CANX, DAPK1, P4HB, TSC2, and ULK1) and had good predictive capacity was established by LASSO–Cox stepwise regression analysis. High-risk patients were found to have significantly shorter OS than patients in low-risk group. The signature can be used as an independent prognostic predictor after adjusting for clinicopathological parameters, and was validated on two external AML sets. Differentially expressed genes analyzed in two groups were involved in inflammatory and immune signaling pathways. An analysis of tumor-infiltrating immune cells confirmed that high-risk patients had a strong immunosuppressive microenvironment. Potential druggable OS-related ARGs were then investigated through protein–drug interactions. This study provides a systematic analysis of ARGs and develops an OS-related prognostic predictor for AML patients. Further work is needed to verify its clinical utility and identify the underlying molecular mechanisms in AML.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 20-21
Author(s):  
Rhonda E. Ries ◽  
Timothy Junius Triche ◽  
Jenny L. Smith ◽  
Amanda R. Leonti ◽  
Todd A. Alonzo ◽  
...  

Monosomy 7 (mono7) alterations in acute myeloid leukemia (AML) are associated with poor outcome and disease progression. Through advancements in multi-omic approaches, more specific treatment strategies may be available for high-risk cohorts. Here we describe pediatric cases of AML with mono7, co-occurring fusions, associated outcome, and potential therapeutic treatments. Of the 2200 patients treated in 3 consecutive Children's Oncology Group protocols (AAML03P1, AAML0531, and AAML1031), 45 patients (2%) had karyotypic evidence of mono7 with full complement of clinical data for analysis. RNA sequencing was available for 37 and whole genome sequencing (WGS) for 8 cases. Fusions were identified using TransAbyss, STARfusion, and Cicero algorithms, while structural variants were analyzed by CREST in the WGS samples. Differential expression comparing mono7 AML (N=28) vs. other AML (N=1064) was performed and epigenetic profiling was evaluated using Illumina's EPIC array (N=1025, N=79 normal bone marrow controls). Of the 45 patients with mono7, 22 had additional karyotypic alterations including copy number variants in 7 and translocations in 15 (6 had confirmatory evidence by RNA seq). RNA seq also identified 9 additional cryptic fusions. In total, the cohort contains 5 cases (11.1%) with KMT2A fusions, 3 (6.7%) with CBF fusions, 7 (15.7%) with 3q26 alterations, and 7 (15%) with copy number alterations (Fig. 1A). In 14 patients (31%), mono7 was the sole karyotypic alteration. In 28 patients with ribo-depleted RNA seq data, cryptic fusions involving the ALK gene were identified in 4 patients (14.3%) with ALK fused to either SPTBN1 (n=3) or RANBP2 (n=1) genes. Cryptic ALK fusions were not detected in the 1064 cases of other AML (p=1.5x10-37), suggesting a unique association between ALK fusions and mono7 and potential genomic cooperation. A differential expression analysis compared patients with mono7 (N=28) to all other AML (N=1064). This analysis identified 1547 dysregulated genes. Of these, MECOM (MDS1/EVI1 COMplex) was identified as the top upregulated gene (logFC 7.24; p=4.4x10-74) with a median expression 5.45 TPM (range 0-89.2 TPM) in patients with mono7 vs. 0.013 TPM in other AML patients. Evaluation of outcome based on MECOM expression demonstrated that patients with high MECOM expression (greater than median) had a 3-yearOS of 22%±20% compared to that of 68%±20% with low MECOM expression, (p=0.026, Fig. 1B) All patients with 3q26 variants had elevated MECOM expression (n=7). In addition, 11 patients without 3q26 alterations/MECOM fusions had MECOM overexpression. Given lack of underlying genomic etiology, we sought to determine whether epigenetic factors might mediate MECOM expression. A panel of 6 CpGs was sufficient to distinguish hematopoietic stem cells (HSCs) from granulocyte-monocyte progenitors (GMPs). HSC-like hypermethylation of these CpGs was strongly associated with high MECOM expression. Further, there was high correlation between total MECOM expression and the methylation status of a CpG island proximal to the short EVI1 transcript variant of MECOM (Spearman's rho = -0.51, p < 0.001, Fig. 1C), suggesting a regulatory underpinning for permissive expression of EVI1. The stem-like epigenetic signature and concordant high MECOM expression of poor-prognosis mono7 AML are consistent with a "stemness" signature and portend poor survival (Fig. 1D). Stemness mRNA signatures have been implicated in high-risk pediatric AML (Smith JL, ASH 2017) and the epigenetic signatures of these genes further corroborate cell of origin as an independently prognostic factor even within high-risk AML. Focused interrogation of the MECOM locus thru integration of the RNA Seq and WGS identified allele specific MECOM expression, adding additional potential mechanism of modulation to MECOM expression. Structural variant analysis confirmed no other CNVs on chromosome 3, indicating cis dysregulation of MECOM. Here, by interrogation of the genome, phenome, transcriptome, and epigenome of mono7 AML a substantial phenotypic and prognostic heterogeneity exists defining a cohort of patients, regulated by genomic and epigenomic alterations. Further, discovery of cryptic ALK fusions in mono7 present a target for ALK inhibitors (FDA approved for non-small cell lung cancer) in this high-risk population. Disclosures No relevant conflicts of interest to declare.


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