High Risk Group
Recently Published Documents





2021 ◽  
Vol 11 ◽  
Hui Li ◽  
Linyan Chen ◽  
Hao Zeng ◽  
Qimeng Liao ◽  
Jianrui Ji ◽  

BackgroundColon adenocarcinoma (COAD) is one of the most common malignant tumors in the world. The histopathological features are crucial for the diagnosis, prognosis, and therapy of COAD.MethodsWe downloaded 719 whole-slide histopathological images from TCIA, and 459 corresponding HTSeq-counts mRNA expression and clinical data were obtained from TCGA. Histopathological image features were extracted by CellProfiler. Prognostic image features were selected by the least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) algorithms. The co-expression gene module correlated with prognostic image features was identified by weighted gene co-expression network analysis (WGCNA). Random forest was employed to construct an integrative prognostic model and calculate the histopathological-genomic prognosis factor (HGPF).ResultsThere were five prognostic image features and one co-expression gene module involved in the model construction. The time-dependent receiver operating curve showed that the prognostic model had a significant prognostic value. Patients were divided into high-risk group and low-risk group based on the HGPF. Kaplan-Meier analysis indicated that the overall survival of the low-risk group was significantly better than the high-risk group.ConclusionsThese results suggested that the histopathological image features had a certain ability to predict the survival of COAD patients. The integrative prognostic model based on the histopathological images and genomic features could further improve the prognosis prediction in COAD, which may assist the clinical decision in the future.

2021 ◽  
Ye Tian ◽  
Yanan Zhang ◽  
Jing Dong ◽  
Lin Li

Abstract Background: Pytoproptosis has been verified to participate in various malignancies. However, studies on pyroptosis-related lncRNAs in breast cancer and its effects on tumor immune micro-environment are still limited. Consequently, it was aimed in this study to construct a pyroptosis-related lncRNAs signature for prognostic prediction and explore the effect of the pyroptosis-related LncRNAs on tumor immune microenvironment through LncRNA-miRNA-mRNA regulatory network. Methods: The pyroptosis-related differentially expressed genes (DEGs) were discovered using differential expression analysis. The differentially expressed LncRNAs (DELncRNAs) associated with DEGs were discovered using correlation analysis. The function of DEGs was analyed using GO and KEGG analyses. The LncRNAs signature used as the prognostic model of breast cancer was constructed using univariate and multivariate Cox analysis, and the effectiveness was verified by K-M analysis and ROC curve. The risk score calculated using the prognostic model was proved as an independent factor by univariate Cox analysis, multivariate Cox analysis and PCA analysis, and used to predict patient prognosis through nomogram. The pathyways enriched in High risk group and Low risk group were analyzed by GSEA. The differences in immune cell distribution (B cell memory, T cell CD4+, T cell CD8+ among others) were analyzed using ssGSEA. The immune function (type I/II IFN response among others), immune checkpoint (ADORA2A among others) and m6A-related protein expression (FTO among others) of High risk group and Low risk group were compared. The regulatory network of pyroptosis-related LncRNA-miRNA-mRNA was constructed and the core network was extracted. The functions of the target genes of miRNA associated with DELncRNAs were explored using GO and KEGG analysis. Results: A 9 LncRNAs signature (LMNTD2-AS1, AL589765.4, AC079298.3, U62317.3, LINC02446, AL645608.7, HSD11B1-AS1, AC009119.1, AC087239.1) was constructed as the prognostic model of breast cancer. Significant differences were discovered in immune cell distribution, immune function, immune checkpointand m6A-related protein expression between High risk group and Low risk group. The regulatory network of LncRNA-miRNA-mRNA was constructed and found to participate in the crosstalk among apoptosis, pyroptosis and necroptosis of breast cancer. Conclusions: The 9 lncRNAs signature was valuable for predicting breast cancer prognosis, and the pyroptosis-related lncRNAs influenced tumor immune microenvironment of breast cancer through the LncRNA-miRNA-mRNA regulatory network.

2021 ◽  
Vol 11 ◽  
Liye Wang ◽  
Rongzhen Luo ◽  
Qianyi Lu ◽  
Kuikui Jiang ◽  
Ruoxi Hong ◽  

IntroductionHR+/HER2− breast cancer (BC) has a much lower pathological complete response (pCR) rate to neoadjuvant chemotherapy (NAC). Therefore, to better stratify the relapse risk for HR+/HER2− non-pCR populations, it is essential to accurate identification new prognostic markers.Materials and MethodsThe study retrospectively analyzed 105 stage II–III patients who were diagnosed with HR+/HER2− BC and received NAC followed by breast and axilla surgery between 2013 and 2019 in Sun Yat-Sen University Cancer Center. The Miller–Payne (MP) grading system was used to evaluate pathological responses to NAC. The 70-gene signature was used to classify the prognosis signatures.ResultsAmong the 105 patients, the study demonstrated that larger tumor size and lower progesterone receptor level at baseline and larger tumor size postoperative were statistically significantly associated with worse disease-free survival (DFS) (p = 0.004, p = 0.021, and p = 0.001, respectively). Among 54 patients who underwent the 70-gene assays, 26 (48.1%) had a low-risk signature; 28 (51.9%) patients had a high-risk signature. Patients with poor response (MP grades 1–2) were more likely to with a high-risk 70-gene signature than those with good response (MP grades 4–5). The final analysis showed that DFS was longer in the low-risk group than in the high-risk group [52.4 vs. 36.1 months of the median DFS, hazard ratio (HR) for recurrence, 0.29; 95% confidence interval (CI), 0.10–0.80; p = 0.018]. DFS was longer in the good response (MP grades 3–4) group than in the poor response (MP grades 1–2) group (94.7% vs. 60% of the patients free from recurrence; HR, 0.16; 95% CI, 0.05–0.47; p = 0.037). When stratified by MP grades combined with the 70-gene signature, subgroup analyses showed the good-response low-risk group with the best DFS, whereas the poor-response high-risk group showed the worst DFS (p = 0.048). Due to the short median follow-up time of 34.5 months (5.9–75.1 months), MP grades and the 70-gene signature did not show significant prognostic value for overall survival.ConclusionThe study showed that analysis of MP grades combined with the 70-gene signature with residual NAC-resistant breast samples has a significant correlation with DFS.

2021 ◽  
Vol 8 ◽  
Haige Zheng ◽  
Huixian Liu ◽  
Yumin Lu ◽  
Hengguo Li

Background: Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous tumor with a high incidence and poor prognosis. Therefore, effective predictive models are needed to evaluate patient outcomes and optimize treatment.Methods: Robust Rank Aggregation (RRA) method was used to identify highly robust differentially-expressed genes (DEGs) between HNSCC and normal tissue in 9 GEO and TCGA datasets. Univariate Cox regression analysis and Lasso Cox regression analysis were performed to identify DEGs related to the Overall survival (OS) and to construct a prognostic gene signature (HNSCCSig). External validation was performed using GSE65858 dataset. Moreover, comprehensive bioinformatics analyses were used to identify the association between HNSCCSig and tumor immune environment.Results: A total of 257 reliable DEGs were identified by differentially analysis result of TCGA and GSE65858 datasets. The HNSCCSig including 7 mRNAs (SLURP1, SCARA5, CLDN10, MYH11, CXCL13, HLF, and ITGA3) were developed and validated to identify high-risk group who had a worse OS than low-risk group in TCGA and GSE65858 datasets. Cox regression analysis showed that the HNSCCSig could independently predict OS in both the TCGA and the GSE65858 datasets. Further research demonstrated that the infiltration bundance of CD8 + T cells, B cells, neutrophils, and NK cells were significantly lower in the high-risk group. A nomogram was also constructed by combining the HNSCCSig and clinical characters.Conclusion: We established and validated the HNSCCSig consisting of SLURP1, SCARA5, CLDN10, MYH11, CXCL13, HLF, and ITGA3. A nomogram combining HNSCCSig and some clinical parameters was constructed to identify high-risk HNSCC-patients with poor prognosis.

2021 ◽  
Vol 21 (1) ◽  
Noémi Meisznerné Kuklek ◽  
Máté Cséplő ◽  
Eszter Pozsonyi ◽  
Henriette Pusztafalvi

Abstract Background People with disadvantages are a high-risk group of unemployment or underemployment. Disadvantages include disability, under-education, or being a member of a minority, etc. Effective labor market programs could be a key in raising employment and quality of life among this high-risk group of society. The TOP 6.8.2.-15-NA1 project is one of the main Hungarian labor market programs. The project’s primary aims are increasing the employability of disadvantaged unemployed and supporting the efficiency of job-seeking. Methods Our goal was to analyze the effects and methodology of the TOP 6.8.2.-15-NA1 project in Hungary. The sample of our study contains participants of the project (n = 300), based in Zala County, Hungary. Results After 28 days, 53.3% of participants had a job. At the 180th day status, the rate of employed people was 47.3%. We could identify low-educated participants and older participants as higher-risk groups of long-term unemployment. Conclusions We emphasize the role of these services (job-seeking clubs, organization of job fairs, and mentorship) in the long-term individual success of participants. Improving the employment rate for people with disadvantages is a critical factor for enhancing the quality of life for individuals with disadvantages.

2021 ◽  
Shaopei Ye ◽  
Wenbin Tang ◽  
Ke Huang

Abstract Background: Autophagy is a biological process to eliminate dysfunctional organelles, aggregates or even long-lived proteins. . Nevertheless, the potential function and prognostic values of autophagy in Wilms Tumor (WT) are complex and remain to be clarifed. Therefore, we proposed to systematically examine the roles of autophagy-associated genes (ARGs) in WT.Methods: Here, we obtained differentially expressed autophagy-related genes (ARGs) between healthy and Wilms tumor from Therapeutically Applicable Research To Generate Effective Treatments(TARGET) and The Cancer Genome Atlas (TCGA) database. The functionalities of the differentially expressed ARGs were analyzed using Gene Ontology. Then univariate COX regression analysis and multivariate COX regression analysis were performed to acquire nine autophagy genes related to WT patients’ survival. According to the risk score, the patients were divided into high-risk and low-risk groups. The Kaplan-Meier curve demonstrated that patients with a high-risk score tend to have a poor prognosis.Results: Eighteen DEARGs were identifed, and nine ARGs were fnally utilized to establish the FAGs based signature in the TCGA cohort. we found that patients in the high-risk group were associated with mutations in TP53. We further conducted CIBERSORT analysis, and found that the infiltration of Macrophage M1 was increased in the high-risk group. Finally, the expression levels of crucial ARGs were verifed by the experiment, which were consistent with our bioinformatics analysis.Conclusions: we emphasized the clinical significance of autophagy in WT, established a prediction system based on autophagy, and identified a promising therapeutic target of autophagy for WT.

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11911
Lei Liu ◽  
Huayu He ◽  
Yue Peng ◽  
Zhenlin Yang ◽  
Shugeng Gao

Background The prognosis of patients for lung adenocarcinoma (LUAD) is known to vary widely; the 5-year overall survival rate is just 63% even for the pathological IA stage. Thus, in order to identify high-risk patients and facilitate clinical decision making, it is vital that we identify new prognostic markers that can be used alongside TNM staging to facilitate risk stratification. Methods We used mRNA expression from The Cancer Genome Atlas (TCGA) cohort to identify a prognostic gene signature and combined this with clinical data to develop a predictive model for the prognosis of patients for lung adenocarcinoma. Kaplan-Meier curves, Lasso regression, and Cox regression, were used to identify specific prognostic genes. The model was assessed via the area under the receiver operating characteristic curve (AUC-ROC) and validated in an independent dataset (GSE50081) from the Gene Expression Omnibus (GEO). Results Our analyses identified a four-gene prognostic signature (CENPH, MYLIP, PITX3, and TRAF3IP3) that was associated with the overall survival of patients with T1-4N0-2M0 in the TCGA dataset. Multivariate regression suggested that the total risk score for the four genes represented an independent prognostic factor for the TCGA and GEO cohorts; the hazard ratio (HR) (high risk group vs low risk group) were 2.34 (p < 0.001) and 2.10 (p = 0.017). Immune infiltration estimations, as determined by an online tool (TIMER2.0) showed that CD4+ T cells were in relative abundance in the high risk group compared to the low risk group in both of the two cohorts (both p < 0.001). We established a composite prognostic model for predicting OS, combined with risk-grouping and clinical factors. The AUCs for 1-, 3-, 5- year OS in the training set were 0.750, 0.737, and 0.719; and were 0.645, 0.766, and 0.725 in the validation set. The calibration curves showed a good match between the predicted probabilities and the actual probabilities. Conclusions We identified a four-gene predictive signature which represents an independent prognostic factor and can be used to identify high-risk patients from different TNM stages of LUAD. A new prognostic model that combines a prognostic gene signature with clinical features exhibited better discriminatory ability for OS than traditional TNM staging.

Motoko Kosugi

As of June 2021, there have been more than 13,000 deaths in Japan due to the COVID-19 pandemic. Data from the Ministry of Health, Labor, and Welfare show that the mortality rate of COVID-19 greatly varies by age. In this study, using data from a questionnaire survey, an investigation was carried out to find differences in anxiety and risk perception, attitudes toward risk, and the frequency of implementation of countermeasures to infection among age groups that are prone to a greater risk of mortality, as well as the main factors that determine the frequency of implementation. Older people, who form a high-risk group, have a stronger tendency for anxiety and cautious attitudes toward COVID-19, and they more frequently implement preventive behaviors. The results of multiple regression analysis showed that the frequency of implementation of behaviors is determined not only by anxiety, cautious attitude, risk of aggravation to oneself, and perceived effectiveness of behaviors but also by regret, altruism, and conformity. In addition, almost no age-based gap was found between the determinants, suggesting that the motivation to take infection preventive behaviors is the same regardless of age.

2021 ◽  
Tian Lan ◽  
Die Wu ◽  
Wei Quan ◽  
Donghu Yu ◽  
Sheng Li ◽  

Abstract Background: Glioma is a fatal brain tumor characterized by invasive nature, rapidly proliferation and tumor recurrence. Despite aggressive surgical resection followed by concurrent radiotherapy and chemotherapy, the overall survival (OS) of Glioma patients remains poor. Ferroptosis is a unique modality to regulate programmed cell death and associated with multiple steps of tumorigenesis of a variety of tumors.Methods: In this study, ferroptosis-related genes model was identified by differential analysis and Cox regression analysis. GO, KEGG and GSVA analysis were used to detect the potential biological functions and signaling pathway. The infiltration of immune cells was quantified by Cibersort.Results: The patients’ samples are stratified into two risk groups based on 4-gene signature. High-risk group has poorer overall survival. The results of functional analysis indicated that the extracellular matrix-related biologic functions and pathways were enriched in high-risk group, and that the infiltration of immunocytes is different in two groups.Conclusion: In summary, a novel ferroptosis-related gene signature can be used for prognostic prediction in glioma. The filtered genes related to ferroptosis in clinical could be a potential extra method to assess glioma patients’ prognosis and therapeutic.

2021 ◽  
Joanne L Doherty ◽  
Adam C Cunningham ◽  
Samuel JRA Chawner ◽  
Hayley M Moss ◽  
Diana C Dima ◽  

Background While genetic risk factors for psychiatric and neurodevelopmental disorders have been identified, the neurobiological route from genetic risk to neuropsychiatric outcome remains unclear. 22q11.2 deletion syndrome (22q11.2DS) is a copy number variant (CNV) syndrome associated with high rates of neurodevelopmental and psychiatric disorders including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD) and schizophrenia. Alterations in neural integration and cortical connectivity have been linked to the spectrum of neuropsychiatric disorders seen in 22q11.2DS and may be a mechanism by which the CNV acts to increase risk. Despite this, few studies have investigated electrophysiological connectivity in this high-risk group. Studying children with 22q11.2DS provides a unique paradigm to identify brain markers of neurodevelopmental impairment and to relate these to underlying biology. Methods Magnetoencephalography (MEG) was used to investigate resting-state cortical oscillatory patterns in 34 children with 22q11.2DS and 25 controls aged 10-17 years old. Oscillatory activity and functional connectivity across six frequency bands were compared between groups. Regression analyses were used to explore the relationships between these measures, IQ and neurodevelopmental symptoms. Results Children with 22q11.2DS had atypical oscillatory activity and functional connectivity across multiple frequency bands (delta, beta and gamma bands). In the 22q11.2DS group, low frequency (alpha band) activity was negatively associated with cognitive ability and positively associated with ASD and ADHD symptoms. Frontal high frequency (gamma band) activity and connectivity were positively associated with ASD and ADHD symptoms, while posterior gamma activity was negatively associated with ASD symptoms. Conclusions These findings highlight that haploinsufficiency at the 22q11.2 locus alters both local and long-range cortical circuitry, which could be a mechanism underlying neurodevelopmental vulnerability in this high risk group.

Sign in / Sign up

Export Citation Format

Share Document