scholarly journals A radiogenomics application for prognostic profiling of endometrial cancer

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Erling A. Hoivik ◽  
Erlend Hodneland ◽  
Julie A. Dybvik ◽  
Kari S. Wagner-Larsen ◽  
Kristine E. Fasmer ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
High Risk ◽  
Treatment Strategies ◽  
Risk Groups ◽  
The Cancer Genome Atlas ◽  
Tumor Segmentation ◽  
Poor Survival ◽  
Cancer Genome Atlas ◽  
Automated Machine Learning ◽  
Magnetic Resonance Imaging Mri

AbstractPrognostication is critical for accurate diagnosis and tailored treatment in endometrial cancer (EC). We employed radiogenomics to integrate preoperative magnetic resonance imaging (MRI, n = 487 patients) with histologic-, transcriptomic- and molecular biomarkers (n = 550 patients) aiming to identify aggressive tumor features in a study including 866 EC patients. Whole-volume tumor radiomic profiling from manually (radiologists) segmented tumors (n = 138 patients) yielded clusters identifying patients with high-risk histological features and poor survival. Radiomic profiling by a fully automated machine learning (ML)-based tumor segmentation algorithm (n = 336 patients) reproduced the same radiomic prognostic groups. From these radiomic risk-groups, an 11-gene high-risk signature was defined, and its prognostic role was reproduced in orthologous validation cohorts (n = 554 patients) and aligned with The Cancer Genome Atlas (TCGA) molecular class with poor survival (copy-number-high/p53-altered). We conclude that MRI-based integrated radiogenomics profiling provides refined tumor characterization that may aid in prognostication and guide future treatment strategies in EC.

scholarly journals Identification of prognostic hypoxia-related genes signature on the tumor microenvironment in esophageal cancer

2021 ◽  
Vol 18 (6) ◽  
pp. 7743-7758
Author(s):  
Linlin Tan ◽  
◽  
Dingzhuo Cheng ◽  
Jianbo Wen ◽  
Kefeng Huang ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
High Risk ◽  
Immune Cells ◽  
Immune Cell ◽  
Risk Group ◽  
Roc Curves ◽  
Risk Groups ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas

<abstract> <sec><title>Background</title><p>Hypoxia is a crucial factor in the development of esophageal cancer. The relationship between hypoxia and immune status in the esophageal cancer microenvironment is becoming increasingly important in clinical practice. This study aims to clarify and investigate the possible connection between immunotherapy and hypoxia in esophageal cancer.</p> </sec> <sec><title>Methods</title><p>The Cancer Genome Atlas databases are used to find two types of esophageal cancer cases. Cox regressions analyses are used to screen genes for hypoxia-related traits. After that, the genetic signature is validated by survival analysis and the construction of ROC curves. GSEA is used to compare differences in enrichment in the two groups and is followed by the CIBERSORT tool to investigate a potentially relevant correlation between immune cells and gene signatures.</p> </sec> <sec><title>Results</title><p>We found that the esophageal adenocarcinoma hypoxia model contains 3 genes (PGK1, PGM1, SLC2A3), and the esophageal squamous cell carcinoma hypoxia model contains 2 genes (EGFR, ATF3). The findings demonstrated that the survival rate of patients in the high-risk group is lower than in the lower-risk group. Furthermore, we find that three kinds of immune cells (memory activated CD4+ T cells, activated mast cells, and M2 macrophages) have a marked infiltration in the tissues of patients in the high-risk group. Moreover, we find that PD-L1 and CD244 are highly expressed in high-risk groups.</p> </sec> <sec><title>Conclusions</title><p>Our data demonstrate that oxygen deprivation is correlated with prognosis and the incidence of immune cell infiltration in patients with both types of esophageal cancer, which provides an immunological perspective for the development of personalized therapy.</p> </sec> </abstract>

scholarly journals L1CAM is an independent predictor of poor survival in endometrial cancer — An analysis of The Cancer Genome Atlas (TCGA)

2016 ◽  
Vol 141 (2) ◽  
pp. 336-340 ◽  
Author(s):  
Thanh H. Dellinger ◽  
David D. Smith ◽  
Ching Ouyang ◽  
Charles D. Warden ◽  
John C. Williams ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Independent Predictor ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Poor Survival ◽  
Cancer Genome Atlas ◽  
Genome Atlas

PET Parameters are Useful in Predicting Endometrial Cancer Risk Classes and Prognosis

2020 ◽  
Author(s):  
Adnan Budak ◽  
Emrah Beyan ◽  
Abdurrahman Hamdi Inan ◽  
Ahkam Göksel Kanmaz ◽  
Onur Suleyman Aldemir ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
High Risk ◽  
Myometrial Invasion ◽  
Risk Groups ◽  
Total Sample ◽  
Tumor Stage ◽  
Low Risk ◽  
Tumor Diameter ◽  
Grade 3 ◽  
Fdg Pet Ct

Abstract Aim We investigate the role of preoperative PET parameters to determine risk classes and prognosis of endometrial cancer (EC). Methods We enrolled 81 patients with EC who underwent preoperative F-18 FDG PET/CT. PET parameters (SUVmax, SUVmean, MTV, TLG), grade, histology and size of the primary tumor, stage of the disease, the degree of myometrial invasion (MI), and the presence of lymphovascular invasion (LVI), cervical invasion (CI), distant metastasis (DM) and lymph node metastasis (LNM) were recorded. The relationship between PET parameters, clinicopathological risk factors and overall survival (OS) was evaluated. Results The present study included 81 patients with EC (mean age 60). Of the total sample, 21 patients were considered low risk (endometrioid histology, stage 1A, grade 1 or 2, tumor diameter < 4 cm, and LVI negative) and 60 were deemed high risk. All of the PET parameters were higher in the presence of a high-risk state, greater tumor size, deep MI, LVI and stage 1B-4B. MTV and TLG values were higher in the patients with non-endometrioid histology, CI, grade 3 and LNM. The optimum cut-off levels for differentiating between the high and low risk patients were: 11.1 for SUVmax (AUC = 0.757), 6 for SUVmean (AUC = 0.750), 6.6 for MTV(AUC = 0.838) and 56.2 for TLG(AUC = 0.835). MTV and TLG values were found as independent prognostic factors for OS, whereas SUVmax and SUVmean values were not predictive. Conclusions The PET parameters are useful in noninvasively differentiating between risk groups of EC. Furthermore, volumetric PET parameters can be predictive for OS of EC.

scholarly journals Identification of novel autophagy-related lncRNAs associated with a poor prognosis of colon adenocarcinoma through bioinformatics analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dejun Wu ◽  
Zhenhua Yin ◽  
Yisheng Ji ◽  
Lin Li ◽  
Yunxin Li ◽  
...  
Keyword(s):  
High Risk ◽  
Poor Prognosis ◽  
Notch Pathway ◽  
Colon Adenocarcinoma ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Future Research ◽  
Risk Patients ◽  
Cancer Genome Atlas ◽  
Immune Score

AbstractLncRNAs play a pivotal role in tumorigenesis and development. However, the potential involvement of lncRNAs in colon adenocarcinoma (COAD) needs to be further explored. All the data used in this study were obtained from The Cancer Genome Atlas database, and all analyses were conducted using R software. Basing on the seven prognosis-related lncRNAs finally selected, we developed a prognosis-predicting model with powerful effectiveness (training cohort, 1 year: AUC = 0.70, 95% Cl = 0.57–0.78; 3 years: AUC = 0.71, 95% Cl = 0.6–0.8; 5 years: AUC = 0.76, 95% Cl = 0.66–0.87; validation cohort, 1 year: AUC = 0.70, 95% Cl = 0.58–0.8; 3 years: AUC = 0.73, 95% Cl = 0.63–0.82; 5 years: AUC = 0.68, 95% Cl = 0.5–0.85). The VEGF and Notch pathway were analyzed through GSEA analysis, and low immune and stromal scores were found in high-risk patients (immune score, cor =  − 0.15, P < 0.001; stromal score, cor =  − 0.18, P < 0.001) , which may partially explain the poor prognosis of patients in the high-risk group. We screened lncRNAs that are significantly associated with the survival of patients with COAD and possibly participate in autophagy regulation. This study may provide direction for future research.

Prognosis-associated methylation subtypes in endometrial carcinoma patients and the role of magnetic nanoparticles in gene extraction

2021 ◽  
Vol 11 (8) ◽  
pp. 1288-1298
Author(s):  
Liang Wang ◽  
Fengxia Xue
Keyword(s):  
Endometrial Cancer ◽  
Magnetic Nanoparticles ◽  
Endometrial Carcinoma ◽  
High Throughput Sequencing ◽  
Risk Groups ◽  
Vital Role ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Tumor Subtypes

Endometrial cancer is one of the most common gynecological malignancies, and DNA methylation plays a vital role in its occurrence and development. In this study, we collected the relevant data on endometrial cancer from the Cancer Genome Atlas database and UCSC website. By screening and processing the data, we obtained 410 samples and 16,381 methylation sites. Endometrial carcinoma can be divided into seven molecular subtypes using consensus clustering method. Based on the analysis of the differences among subtypes, the methylation degree of different sites was obtained, and the prognosis model of methylation sites was established. Based on the median value of the train group, the train and test groups were divided into high and low-risk groups. The survival between the high and low-risk groups was different. It also showed that this model can predict the survival of patients, with better accuracy. In conclusion, the tumor subtypes based on methylation sites can provide a better guidance for treatment, relapse, and prognosis of endometrial cancer. In this study, magnetic nanoparticles can be used to extract genomic DNA and total RNA due to their paramagnetism and biocompatibility, then transcriptome high-throughput sequencing was performed. It may serve as potential cancer immune biomarker targets for developing future oncological treatments.

scholarly journals Development and validation of a 13-m6a related lncRNA prognostic signature for lung adenocarcinoma

2021 ◽  
Author(s):  
Pingfan Wu ◽  
Xiaowen Zhao ◽  
Ling Xue ◽  
Xiaojing Yang ◽  
Yuxiang Shi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Treatment Strategies ◽  
Risk Groups ◽  
Gene Expression Omnibus ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature ◽  
P53 Signaling ◽  
Selection Operator

Abstract Considerable evidence suggests that N6-methyladenosine (m6A) is involved in the regulation of long non-coding RNA (lncRNA), whichparticipates in the occurrence, development and prognosis of tumorscancerBut the relationship between m6A regulators-related lncRNA (mRlncRNA) and lung adenocarcinoma (LUAD) remains unclear. This study aims to determine a feature based on mRlncRNA for prognostic evaluation of LUAD patients. By integrating the gene expression data of LUAD and normal samples from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, the m6A gene and mRlncRNA with imbalanced expression were screened out. Then we used the least absolute shrinkage and selection operator (LASSO) to obtain the 13-lncRNA prognostic signature in the TCGA training cohort. Patients were divided into two risk groups based on the risk score of lncRNAs characteristics, and their overall survival (OS) was significantly different. The predictive power of this signature was verified in TCGA testing cohort and entire TCGA cohort. These landmark lncRNAs were involved in several biologiocal processes and pathways related to cell cycle, DNA replication, P53 signaling pathway and mismatch repair. Besides, the high-risk group was low-response to cisplatin, while high-response to mitomycin, docetaxel and immunotherapy. In conclusion, we identified a 13-mRlncRNA model associated with prognosis and treatment sensitivity in LUAD, which may provide clues about the influence of m6A on lncRNA in LUAD and promote the further improvement of LUAD individualized treatment strategies.

scholarly journals Racial differences in endometrial cancer molecular portraits in The Cancer Genome Atlas

Oncotarget ◽  
2018 ◽  
Vol 9 (24) ◽  
pp. 17093-17103 ◽  
Author(s):  
David S. Guttery ◽  
Kevin Blighe ◽  
Konstantinos Polymeros ◽  
R. Paul Symonds ◽  
Salvador Macip ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Racial Differences ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

TNFα signalling predicts poor prognosis of patients with endometrial cancer

2020 ◽  
Vol 41 (8) ◽  
pp. 1065-1073
Author(s):  
Verena Wieser ◽  
Samira Abdel Azim ◽  
Susanne Sprung ◽  
Katharina Knoll ◽  
Johanna Kögl ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Clinical Outcome ◽  
The Cancer Genome Atlas ◽  
Western World ◽  
Low Grade ◽  
Necrosis Factor Alpha ◽  
Cancer Genome Atlas ◽  
Factor Alpha ◽  
The Impact

Abstract Endometrial cancer (EC) is the most common gynaecologic tumour in the Western world. Previous studies have implicated an imbalance of oestrogens and progestogens in the development of most ECs, while the role of low-grade tissue inflammation remains largely unexplored. We investigated the impact of tumour necrosis factor alpha (TNFα), a central mediator of inflammation and spermatogenesis-associated protein 2 (SPATA2), a regulator of TNF receptor signalling, on clinical outcomes in EC. We evaluated TNFA and SPATA2 transcript levels in 239 EC patients and 25 non-malignant control tissues. Findings were validated in a cohort of 332 EC patients from The Cancer Genome Atlas (TCGA). Expression of TNFA and SPATA2 was increased in EC when compared with control tissues (P &lt; 0.001). TNFA expression correlated with SPATA2 expression in non-malignant (P = 0.003, rS = 0.568) and EC tissue (P = 0.005, rS = 0.179). High TNFA and SPATA2 expression were associated with poor recurrence-free survival (RFS; P = 0.049 and P = 0.018) and disease-specific (P = 0.034 and P = 0.002) survival. Increased SPATA2 expression was also associated with decreased overall survival (OS; P = 0.013). In multivariate analysis, both TNFA and SPATA2 were predictors of clinical outcome. The impact of SPATA2 on RFS and OS could be validated in the TCGA cohort. Our study demonstrates that ECs exhibit a TNF signature which predicts clinical outcome. These findings indicate that TNF signalling modulates the course of EC, which could be therapeutically utilized in the future.

scholarly journals Cyclin-Dependent Kinase and Antioxidant Gene Expression in Cancers with Poor Therapeutic Response

2020 ◽  
Vol 13 (2) ◽  
pp. 26
Author(s):  
George S. Scaria ◽  
Betsy T. Kren ◽  
Mark A. Klein
Keyword(s):  
Hepatocellular Carcinoma ◽  
Pancreatic Cancer ◽  
Antioxidant Defense ◽  
Treatment Strategies ◽  
The Cancer Genome Atlas ◽  
Cyclin Dependent Kinase ◽  
Critical Pathways ◽  
Cancer Genome Atlas ◽  
Antioxidant Gene Expression ◽  
Pan Cancer

Pancreatic cancer, hepatocellular carcinoma (HCC), and mesothelioma are treatment-refractory cancers, and patients afflicted with these cancers generally have a very poor prognosis. The genomics of these tumors were analyzed as part of The Cancer Genome Atlas (TCGA) project. However, these analyses are an overview and may miss pathway interactions that could be exploited for therapeutic targeting. In this study, the TCGA Pan-Cancer datasets were queried via cBioPortal for correlations among mRNA expression of key genes in the cell cycle and mitochondrial (mt) antioxidant defense pathways. Here we describe these correlations. The results support further evaluation to develop combination treatment strategies that target these two critical pathways in pancreatic cancer, hepatocellular carcinoma, and mesothelioma.

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