prognosis evaluation
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2021 ◽  
Author(s):  
Yu‐Chen Han ◽  
Min Gao ◽  
Ming‐Ming Pan ◽  
Bin Wang ◽  
Hong Liu ◽  
...  

Author(s):  
D. A. Teplyuk ◽  
M. Ch. Semenistaya ◽  
S. M. Sorokoletov ◽  
L. B. Lazebnik ◽  
Ch. S. Pavlov

Nonalcoholic fatty liver disease (NAFLD) is a disease which etiology is related to various metabolic, ethnic, genetic and even ecologic factors. Complexity of etiology and multiply pathogenesis ways, leading eventually to the lipid droplets appearance in hepatocytes, infl ammation process and parenchyma fi brosis in liver, and also frequent cardiometabolic comorbidities, together make diffi cult risks stratifi cation and prognosis evaluation in NAFLD patients. Another matter is a question of NAFLD therapy, since unifi ed pharmacotherapy approaches are not yet adopted worldwide, and lifestyle modifi cation being accepted as an eff ective therapeutic approach, is not followed by patients in real world setting. Current review is dedicated to the consideration of NAFLD diagnostics, its risk of progression and existing therapeutical capabilities.


2021 ◽  
Vol 11 ◽  
Author(s):  
Qinfeng Zhou ◽  
Lianfang Liu ◽  
Jing Zhou ◽  
Yuanyuan Chen ◽  
Dacheng Xie ◽  
...  

The long non-coding RNA metastasis-associated lung adenocarcinoma transcript-1 (MALAT1) was initially found to be overexpressed in early non-small cell lung cancer (NSCLC). Accumulating studies have shown that MALAT1 is overexpressed in the tissue or serum of NSCLC and plays a key role in its occurrence and development. In addition, the expression level of MALAT1 is significantly related to the tumor size, stage, metastasis, and distant invasion of NSCLC. Therefore, MALAT1 could be used as a biomarker for the early diagnosis, severity assessment, or prognosis evaluation of NSCLC patients. This review describes the basic properties and biological functions of MALAT1, focuses on the specific molecular mechanism of MALAT1 as a microRNA sponge in the occurrence and development of NSCLC in recent years, and emphasizes the application and potential prospect of MALAT1 in molecular biological markers and targeted therapy of NSCLC.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ni Yang ◽  
Kuo Liu ◽  
Mengxuan Yang ◽  
Xiang Gao

Noncoding RNAs have been shown with powerful ability in post-transcriptional regulation, enabling intertwined RNA crosstalk and global molecular interaction in a large amount of dysfunctional conditions including cancer. Competing endogenous RNAs (ceRNAs) are those competitively binding with shared microRNAs (miRNAs), freeing their counterparts from miRNA-induced degradation, thus actively influencing and connecting with each other. Constantly updated analytical approaches boost outstanding advancement achieved in this burgeoning hotspot in multilayered intracellular communication, providing new insights into pathogenesis and clinical treatment. Here, we summarize the mechanisms and correlated factors under this RNA interplay and deregulated transcription profile in neoplasm and tumor progression, underscoring the great significance of ceRNAs for diagnostic values, monitoring biomarkers, and prognosis evaluation in cancer.


2021 ◽  
Vol Volume 13 ◽  
pp. 7841-7850
Author(s):  
Lei Yang ◽  
Hong-Fang Sun ◽  
Lin-Qing Guo ◽  
Hai-Bing Cao

2021 ◽  
Author(s):  
Jiasheng Xu ◽  
Kaili Liao ◽  
Chengfeng Wu ◽  
Qijun Yang ◽  
Hongping Wan ◽  
...  

Abstract Background: To classify colon cancer and predict the prognosis of patients with multiple characteristics of the genome.Methods: We used the mRNA expression profile data and mutation maf files of colon cancer patients in the TCGA database to calculate the TMB value of patients. Combined with CNV, MSI, and corresponding clinical information, the patients were clustered by the "K-means" method to identify different molecular subtypes of colon cancer. Comparing the differences of prognosis, and immune cell infiltration, and other indicators among patients in each subgroup, we used COX and lasso regression analysis to screen out the prognosis difference genes among subgroups and construct the prognosis prediction model. We used the external data set to verify the model, and carried out the hierarchical analysis of the model to compare the immune infiltration of patients in the high and low-risk groups. And detected the expression differences of core genes in tumor tissues of patients with different clinical stages by qPCR and immunohistochemistry.Results: We successfully calculated the TMB value and divided the patients into three subgroups. The prognosis of the second subgroup was significantly different from the other two groups. The mmunoinfiltration analysis showed that the expression of NK.cells.resting increased in cluster1 and cluster 3, and the expression of T.cells.CD4.memory.resting increased in cluster3. By analyzing the differences among subgroups, we screened out eight core genes related to prognoses, such as HYAL1, SPINK4, EREG, and successfully constructed a patient prognosis evaluation model. The test results of the external data set shows that the model can accurately predict the prognosis of patients; Compared with risk factors such as TNM stage and age, the risk score of the model has higher evaluation efficiency. The experimental results confirmed that the differential expression of eight core genes was basically consistent with the model evaluation results.Conclusion: Colon cancer patients were further divided into three subtypes by using genomic multi-features, and eight-core genes related to prognosis were screened out and the prognosis evaluation model was successfully constructed. With external data and experiments, it verified that the model had good evaluation efficiency.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Rui-kun Zhang ◽  
Jia-lin Liu

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and invasive malignant tumors in the world. The change in DNA methylation is a key event in HCC. Methods Methylation datasets for HCC and 17 other types of cancer were downloaded from The Cancer Genome Atlas (TCGA). The CpG sites with large differences in methylation between tumor tissues and paracancerous tissues were identified. We used the HCC methylation dataset downloaded from the TCGA as the training set and removed the overlapping sites among all cancer datasets to ensure that only CpG sites specific to HCC remained. Logistic regression analysis was performed to select specific biomarkers that can be used to diagnose HCC, and two datasets—GSE157341 and GSE54503—downloaded from GEO as validation sets were used to validate our model. We also used a Cox regression model to select CpG sites related to patient prognosis. Results We identified 6 HCC-specific methylated CpG sites as biomarkers for HCC diagnosis. In the training set, the area under the receiver operating characteristic (ROC) curve (AUC) for the model containing all these sites was 0.971. The AUCs were 0.8802 and 0.9711 for the two validation sets from the GEO database. In addition, 3 other CpG sites were analyzed and used to create a risk scoring model for patient prognosis and survival prediction. Conclusions Through the analysis of HCC methylation datasets from the TCGA and Gene Expression Omnibus (GEO) databases, potential biomarkers for HCC diagnosis and prognosis evaluation were ascertained.


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Min Li ◽  
Jing Li ◽  
Kaichuan Chen ◽  
Jia Wang ◽  
Minjie Sheng ◽  
...  

Background. To evaluate the correlations between the inflammatory factors in the aqueous humor and hyperreflective foci (HRF) in patients with intractable macular edema treated with antivascular endothelial growth factor (anti-VEGF). Methods. This study included 17 patients with intractable macular edema (ME) treated with anti-VEGF agents. Inflammatory factors in the aqueous humor were measured by the Cytometric Beads Array before injection, and the numbers of HRF pre- and post-anti-VEGF treatment were counted from four different directions (90 degrees, 45 degrees, 180 degrees, and 135 degrees) in the SD-OCT images, respectively, before treatment and one month after treatment. The correlations between inflammatory factors and the numbers of HRF were assessed. Results. The numbers of HRF were reduced significantly after anti-VEGF treatment. The change in the HRFs at the 90-degree location was significantly positively correlated with IL-8 and VCAM-1. The change of all HRFs was significantly positively correlated with IL-8. The HRFs before the treatment also had a positive correlation with IL-8 and VCAM-1. Conclusion. After anti-VEGF treatment, the numbers of HRF in intractable ME declined greatly. The higher the levels of IL-8 and VCAM-1 before treatment, the more significant the reduction of HRF after anti-VEGF treatment, which indicated that HRF could be an effective noninvasive imaging indicator for evaluating the effect of anti-VEGF on intractable macular edema. The OCT images at the 90-degree location could better show the inflammatory reaction of patients and also had better clinical significance for the prognosis evaluation of ME associated with inflammation.


2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Lei Chen ◽  
Limin Wei

Abstract Background and Aims Recently, more and more attention has been paid to the predictive value of neutrophil to lymphocyte ratio (NLR) in various diseases. As a novel marker for inflammatory response, NLR has been proved to be useful for the diagnosis and prognosis evaluation of inflammatory diseases such as tumor, diabetes, atherosclerosis and other disease. It is well known that inflammatory response plays an important role in the occurrence and development of AKI. Previous studies have shown that NLR has a great value in the diagnosis of AKI, but its value in the prognosis evaluation in AKI patients, especially in critical ill patients with AKI, remains unclear. This study aimed at investigating the predictive value of neutrophil-lymphocyte ratio (NLR) on the risk of 90-day mortality in critically ill patients with acute kidney injury (AKI), so as to provide a simple, feasible, and valuable tool for the prognosis assessment of such patients. Method The data of 802 critically ill patients with AKI admitted to the intensive care unit of the First Affiliated Hospital of Xi'an Jiaotong University from January 2015 to December 2019 were retrospectively analyzed. According to the initial NLR level at admission, they were divided into a low NLR group (NLR≤9) and a high NLR group (NLR>9). Differences in comorbidities, the initial Sequential Organ Failure Assessment (SOFA) score, white blood cell (WBC), neutrophil percentage (Neu%), hemoglobin (Hb), platelet (PLT), lactic acid (Lac), pH, blood glucose (Glu), creatine kinase (CK), and all-cause mortality at 90-day were compared between groups. Binary Logistic regression model was used to analyze the risk factors for 90-day mortality in critically ill patients with AKI, and the receiver operating characteristic (ROC) curve was computed to evaluate the predictive value of NLR for the risk of 90-day mortality in such patients. Results There were no statistically significant differences in age, sex, and Glu between the two groups. The SOFA score, WBC, Hb, Plt, Lac, CK, SC, BUN and NEU%of patients in the high NLR group were higher than those in the low NLR group, while the BMI and pH value was lower in the high NLR group than that in the low NLR group. The 90-day mortality rate was significantly higher in the high NLR group than that in the low NLR group (36.2% vs 16%, P < 0.001). Binary Logistic regression showed that NLR was an independent risk factor for 90-day mortality in critically ill patients with AKI (OR=2.402, 95% CI:1.633-3.533,ï¼°<0.001), even after adjusting for age, gender, BMI, comorbidities, SOFA score, and AKI stages. The area under the ROC curve (AUC) of NLR predicting 90-day mortality was 0.613 with a highest prognostic cut-off point of 8. The sensitivity was 65.77%, and the specificity was 54.78%. Conclusion NLR has a predictive value on risk of the 90-day mortality in critically ill patients with AKI. As a simple and easily available clinical indicator, NLR could be applied as a valuable tool in guiding the initial treatment of such patients.


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