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2022 ◽  
Vol 12 ◽  
Author(s):  
Hang Ji ◽  
Hongtao Zhao ◽  
Jiaqi Jin ◽  
Zhihui Liu ◽  
Xin Gao ◽  
...  

Effective treatment of glioblastoma (GBM) remains an open challenge. Given the critical role of the immune microenvironment in the progression of cancers, we aimed to develop an immune-related gene (IRG) signature for predicting prognosis and improving the current treatment paradigm of GBM. Multi-omics data were collected, and various bioinformatics methods, as well as machine learning algorithms, were employed to construct and validate the IRG-based signature and to explore the characteristics of the immune microenvironment of GBM. A five-gene signature (ARPC1B, FCGR2B, NCF2, PLAUR, and S100A11) was identified based on the expression of IRGs, and an effective prognostic risk model was developed. The IRG-based risk model had superior time-dependent prognostic performance compared to well-studied molecular pathology markers. Besides, we found prominent inflamed features in the microenvironment of the high-risk group, including neutrophil infiltration, immune checkpoint expression, and activation of the adaptive immune response, which may be associated with increased hypoxia, epidermal growth factor receptor (EGFR) wild type, and necrosis. Notably, the IRG-based risk model had the potential to predict the effectiveness of radiotherapy. Together, our study offers insights into the immune microenvironment of GBM and provides useful information for clinical management of this desperate disease.


2022 ◽  
Vol 12 ◽  
Author(s):  
Jinhui Liu ◽  
Guoliang Cui ◽  
Shuning Shen ◽  
Feng Gao ◽  
Hongjun Zhu ◽  
...  

BackgroundsEpithelial–mesenchymal transition (EMT) is a sequential process where tumor cells develop from the epithelial state to the mesenchymal state. EMT contributes to various tumor functions including initiation, propagating potential, and resistance to therapy, thus affecting the survival time of patients. The aim of this research is to set up an EMT-related prognostic signature for endometrial cancer (EC).MethodsEMT-related gene (ERG) expression and clinical data were acquired from The Cancer Genome Atlas (TCGA). The entire set was randomly divided into two sets, one for contributing the risk model (risk score) and the other for validating. Univariate and multivariate Cox proportional hazards regression analyses were applied to the training set to select the prognostic ERGs. The expression of 10 ERGs was confirmed by qRT-PCR in clinical samples. Then, we developed a nomogram predicting 1-/3-/5-year survival possibility combining the risk score and clinical factors. The entire set was stratified into the high- and low-risk groups, which was used to analyze the immune infiltrating, tumorigenesis pathways, and response to drugs.ResultsA total of 220 genes were screened out from 1,316 ERGs for their differential expression in tumor versus normal. Next, 10 genes were found to be associated with overall survival (OS) in EC, and the expression was validated by qRT-PCR using clinical samples, so we constructed a 10-ERG-based risk score to distinguish high-/low-risk patients and a nomogram to predict survival rate. The calibration plots proved the predictive value of our model. Gene Set Enrichment Analysis (GSEA) discovered that in the low-risk group, immune-related pathways were enriched; in the high-risk group, tumorigenesis pathways were enriched. The low-risk group showed more immune activities, higher tumor mutational burden (TMB), and higher CTAL4/PD1 expression, which was in line with a better response to immune checkpoint inhibitors. Nevertheless, response to chemotherapeutic drugs turned out better in the high-risk group. The high-risk group had higher N6-methyladenosine (m6A) RNA expression, microsatellite instability level, and stemness indices.ConclusionWe constructed the ERG-related signature model to predict the prognosis of EC patients. What is more, it might offer a reference for predicting individualized response to immune checkpoint inhibitors and chemotherapeutic drugs.


2022 ◽  
Vol 15 (1) ◽  
pp. 49
Author(s):  
Hay V. Duong ◽  
Thanh C. Nguyen ◽  
Xuan T. Nguyen ◽  
Minh Q. Nguyen ◽  
Phuoc H. Nguyen ◽  
...  

The presence of pesticide residues was investigated in the organic rice production model in An Giang province, Vietnam. A total number of sixteen pesticide residues was been recorded during the investigation. Based on their contamination rate, they are classified as follows. The high-risk group includes tricyclazole (80%). The medium-risk group includes chlorpyrifos (47%), isoprothiolane (47%), difenoconazole (40%), propiconazole (40%), hexaconazole (40%), chlorfenapyr (33%), azoxystrobin (20%), and cypermethrin (20%). The low-risk group includes metalaxyl & metalaxyl-M, paclobutazol, niclosamide, chlorfenson, fipronil, fipronil-desulfinyl, and fenoxanil, which were detected with a contamination rate of 7%. There were seven insecticides, seven fungicides, one snail killer, and one growth regulator.


2022 ◽  
Author(s):  
Yujian Xu ◽  
Youbai Chen ◽  
Zehao Niu ◽  
Zheng Yang ◽  
Jiahua Xing ◽  
...  

Abstract Ferroptosis-related lncRNAs are promising biomarkers for predicting the prognosis of many cancers. However, a ferroptosis-related signature to predict the prognosis of cutaneous melanoma (CM) has not been identified. The purpose of our study was to construct a ferroptosis-related lncRNA signature to predict prognosis and immunotherapy efficacy in CM. Ferroptosis-related differentially expressed genes (FDEGs) and lncRNAs (FDELs) were identified using TCGA, GTEx, and FerrDb datasets. We performed Cox and LASSO regressions to identify key FDELs, and constructed a risk score to stratify patients into high- and low-risk groups. A nomogram was developed for clinical use. We performed gene set enrichment analyses (GSEA) to identify significantly enriched pathways. Differences in the tumor microenvironment (TME) between the 2 groups were assessed using 7 algorithms. To predict the efficacy of immune checkpoint inhibitors (ICI), we analyzed the association between PD1 and CTLA4 expression and the risk score. Finally, differences in Tumor Mutational Burden (TMB) and molecular drugs Sensitivity between the 2 groups were performed. Here, we identified 5 lncRNAs (AATBC, AC145423.2, LINC01871, AC125807.2, and AC245041.1) to construct the risk score. The AUC of the lncRNA signature was 0.743 in the training cohort and was validated in the testing and entire cohorts. Kaplan-Meier analyses revealed that the high-risk group had poorer prognosis. Multivariate Cox regression showed that the lncRNA signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The 1-, 3-, and 5-year survival probabilities for CM patients were 92.7%, 57.2%, and 40.2% with an AUC of 0.804, indicating a good accuracy and reliability of the nomogram. GSEA showed that the high-risk group had lower ferroptosis and immune response. TME analyses confirmed that the high-risk group had lower immune cell infiltration (e.g., CD8+ T cells, CD4+ memory-activated T cells, and M1 macrophages) and lower immune functions (e.g., immune checkpoint activation). Low-risk patients whose disease expressed PD1 or CTLA4 were likely to respond better to ICIs. The analysis demonstrated that the TMB had significantly difference between low- and high- risk groups. Chemotherapy drugs, such as sorafenib, Imatinib, ABT.888 (Veliparib), Docetaxel, and Paclitaxel showed Significant differences in the estimated IC50 between the two risk groups. Overall, our novel ferroptosis-related lncRNA signature was able to accurately predict the prognosis and ICI outcomes of CM patients. These ferroptosis-related lncRNAs might be potential biomarkers and therapeutic targets for CM.


2022 ◽  
Vol 2022 ◽  
pp. 1-17
Author(s):  
Cao-Jie Chen ◽  
Hiroki Kajita ◽  
Noriko Aramaki-Hattori ◽  
Shigeki Sakai ◽  
Kazuo Kishi

Cutaneous melanoma refers to a common skin tumor that is dangerous to health with a great risk of metastasis. Previous researches reported that autophagy is associated with the progression of cutaneous melanoma. Nevertheless, the role played by genes with a relation to autophagy (ARG) in the prediction of the course of metastatic cutaneous melanoma is still largely unknown. We observed that thirteen ARGs showed relations to overall survival (OS) in the Cox regression investigation based on a single variate. We developed 2-gene signature, which stratified metastatic cutaneous melanoma cases to groups at great and small risks. Cases suffering from metastatic cutaneous melanoma in the group at great risks had power OS compared with cases at small risks. The risk score, T phase, N phase, and age were proved to be individual factors in terms of the prediction of OS. Besides, the risk scores identified by the two ARGs were significantly correlated with metastatic cutaneous melanoma. Receiver operating characteristic (ROC) curve analysis demonstrated accurate predicting performance exhibited by the 2-gene signature. We also found that the immunization and stromal scores achieved by the group based on large risks were higher compared with those achieved by the group based on small risks. The metastatic cutaneous melanoma cases achieving the score based on small risks acquired greater expression of immune checkpoint molecules as compared with the high-risk group. In conclusion, the 2-ARG gene signature indicated a novel prognostic indicator for prognosis prediction of metastatic cutaneous melanoma, which served as an important tool for guiding the clinical treatment of cutaneous melanoma.


2022 ◽  
Author(s):  
Piao Shen ◽  
Yuzhen Zheng ◽  
Siyu Zhu ◽  
Xingping Yang ◽  
Jian Tan ◽  
...  

Abstract Background: Primary pulmonary sarcoma (PPS) accounts for less than 1.1% of all pulmonary tumors. Few data outcomes are reported. This study aims to clarify the predictive value of clinicopathologic features on the overall survival (OS) of PPS patients.Methods: Patients with primary pulmonary sarcoma (PPS) were collected from the Surveillance, Epidemiology, and End Results (SEER) database (from 2000 to 2015) and divided randomly into training and validation cohorts at a ratio of 1:1. Univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) were implemented to identify prognostic factors related to overall survival of primary pulmonary sarcoma patients. Then, we performed multivariate Cox regression to establish a prognostic factors signature. The Kaplan- Meier (K-M) survival curves and time-dependent receiver operating characteristic (ROC) curves were plotted to estimate the prognostic power of the signature. In addition, multivariate Cox regression screened out independent prognostic factors and constructed a nomogram. Results: PPS patients with training group were divided into low- and high-risk group based on risk score, and high-risk group had a shorter survival time. The validation group got the same result. (P<0.001). On multivariate analysis of the training cohort, independent factors for survival were marriage, age, sex, grade, operation, metastasis and tumor size, which were all selected into the nomogram. The calibration curve and ROC plots for probability of 3-year and 5-year survival were in accord with prediction by nomogram and actual observation. And the C-index of the nomogram for predicting survival was 0.77 (95% CI, 0.74 to 0.80, P<0.05), which was statistically significant. Conclusion: We constructed a risk prognosis model based on PPS patients from SEER database. In addition, the construction of nomogram provides one more idea for clinical treatment.


2022 ◽  
Vol 2022 ◽  
pp. 1-27
Author(s):  
Wen Lv ◽  
Qi Yao

Background. Hepatocellular carcinoma (HCC) is one of the most heterogeneous malignant tumors that have been discovered so far, which makes the prognostic prediction difficult. The hypoxia, angiogenesis, and immunity-related genes (HAIRGs) are closely related to the development of liver cancer. However, the prognostic and treatment effect of hypoxia, angiogenesis, and immunity-related genes in HCC continues to be further clarified. Methods. The gene expression quantification data and clinical information in patients with liver cancer were downloaded from the TCGA database, and HAIRG signature was built by using the least absolute shrinkage and selection operator (LASSO) technique. Patient from the ICGC database validated the model. Then, tumor immune dysfunction and exclusion (TIDE) algorithm was applied to estimate the clinical response to immunotherapy and the sensitivity of drugs was evaluated by the half-maximal inhibitory concentration (IC50). Result. The HAIRGs were identified between the HCC patients and normal patients in the TCGA database. In univariate Cox regression analysis, seventeen differentially expressed genes (DEGs) were associated with overall survival (OS). An eight HAIRG signature model was constructed and was used to divide the patients into two groups according to the median value of the risk score base on the TCGA dataset. Patients in the high-risk group had a significant reduction in OS compared to those in the low-risk group ( P < 0.001 in the TCGA, P < 0.001 in the ICGC). For TCGA and ICGC databases of univariate Cox regression analyses, the risk score was used as an independent predictor of OS ( HR > 1 , P < 0.001 ). Functional analysis showed that the relevant immune pathways and immune responses were enriched, cellular component analysis showed that the immunoglobulin complex and other related substances were enriched, and immune status existed a difference in the high- and low-risk groups. Then, the tumor immune dysfunction and exclusion (TIDE) algorithm presented differences in immune response in the high- and low-risk groups ( P < 0.05 ), and based on drug sensitivity prediction, patients in the high-risk group were more sensitive to cisplatin compared to those in the low-risk group in both the TCGA and ICGC cohorts ( P < 0.05 ). Conclusions. HAIRG signature can be utilized for prognostic prediction in HCC, while it can be considered a prediction model for clinical evaluation of immunotherapy response and chemotherapy sensitivity in HCC.


Author(s):  
Jihui Chen ◽  
Yu Yang ◽  
Huimin Yao ◽  
Shuhong Bu ◽  
Lixia Li ◽  
...  

ObjectiveCarbapenem-resistant Klebsiella pneumoniae (CRKP) infections are associated with poor patient outcomes. We aimed to analyze the clinical information of adult patients with CRKP infection in order to establish a nomogram for mortality risk as well as to determine the treatment effectiveness of different antimicrobial regimens.MethodsAdult patients diagnosed with CRKP infection in a tertiary hospital in Shanghai between September 2019 and March 2021 were included. The clinical characteristics and clinical outcomes of these patients were analyzed.ResultsA total of 199 cases of CRKP infection were examined. Five factors, namely age ≥65 years, respiratory failure, Sequential Organ Failure Assessment score, serum procalcitonin ≥5 ng/mL, and appropriate treatments in 3 days, were found to be associated with 30-day mortality. Upon incorporating these factors, the nomogram achieved good concordance indexes of 0.85 (95% confidence interval [CI]: 0.80–0.90) and well-fitted calibration curves. Receiver-operating characteristic curves for 7-, 15-, and 30-day survival had areas under the curve of 0.90, 0.87, and 0.88, respectively. Three-drug combination therapy was observed to be associated with lower mortality in the high-risk group (adjusted hazard ratio = 0.24, 95% CI: 0.06–0.99) but not in the low-risk group. Ceftazidime–avibactam, fosfomycin, and amikacin were effective against infections caused by CRKP. Tigecycline improved the treatment efficiency in 7 days, but a trend toward increased mortality was seen (HR, 1.69; 95% CI: 0.98–2.94; P = 0.061).ConclusionThe antimicrobial regimen efficacy data and the predictive nomogram established in this study can help clinicians in identifying high-risk adult patients with CRKP infection, improving the therapeutic effect, and reducing mortality.


2022 ◽  
Author(s):  
Sarah E Jackson ◽  
Hazel Cheeseman ◽  
Deborah Arnott ◽  
Robbie Titmarsh ◽  
Jamie Brown

Objectives: To analyse associations between living in social housing and smoking in England and evaluate progress toward reducing disparities in smoking prevalence among residents of social housing compared with other housing types. Design: Nationally-representative, cross-sectional survey between January 2015 and February 2020. Setting: England. Participants: 105,562 adults (≥16y). Primary and secondary outcome measures: Linear and logistic regression were used to analyse associations between living in social housing (vs. other housing types) and smoking status, cigarettes per day, time to first cigarette, exposure to smoking by others, motivation to stop smoking, quit attempts, and use of cessation support. Analyses adjusted for sex, age, social grade, region, and survey year. Results: Adults living in social housing had twice the odds of being a smoker (ORadj=2.17, 95%CI 2.08-2.27), and the decline in smoking prevalence between 2015 and 2020 was less pronounced in this high-risk group (-7%; ORadj=0.98, 95%CI 0.96-1.01) than among adults living in other housing types (-24%; ORadj=0.95, 95%CI 0.94-0.96; housing tenure*survey year interaction p=0.020). Smokers living in social housing were more addicted than those in other housing (smoking within 30 minutes of waking: ORadj=1.50, 95%CI 1.39-1.61), but were no less motivated to stop smoking (ORadj=1.06, 95%CI 0.96-1.17) and had higher odds of having made a serious attempt to quit in the past year (ORadj=1.16, 95%CI 1.07-1.25). Among smokers who had tried to quit, those living in social housing had higher odds of using evidence-based cessation support (ORadj=1.22, 95%CI 1.07-1.39) but lower odds of remaining abstinent (ORadj=0.63, 95%CI 0.52-0.76). Conclusions: There remain stark inequalities in smoking and quitting behaviour by housing tenure in England, with declines in prevalence stalling between 2015 and 2020 despite progress in the rest of the population. In the absence of targeted interventions to boost quitting among social housing residents, inequalities in health are likely to worsen.


2022 ◽  
Vol 2022 ◽  
pp. 1-17
Author(s):  
Lei Zhang ◽  
Dahai Hu ◽  
Shuchen Huangfu ◽  
Jiaxin Zhou ◽  
Wei Wang ◽  
...  

The genomic variant features (mutations, deletions, structural variants, etc.) within gastric cancer impact its evolution and immunogenicity. The tumor has developed several coping strategies to respond to these changes by DNA repair and replication (DRR). However, the intrinsic relationship between the associated DRR-related genes and gastric cancer progression remained unknown. This study selected DRR-related genes with tumor mutation burden based on the TCGA (The Cancer Genome Atlas) database of gastric cancer transcriptome and mutation data. The prognosis model of seven genes (LAMA2, CREB3L3, SELP, ABCC9, CYP1B1, CDH2, and GAMT) was constructed by a univariate and LASSO regression analysis and divided into high-risk and low-risk groups with the median risk score. Survival analysis showed that overall survival (OS) was lower in the high-risk group than that in the low-risk group. Moreover, patients with gastric cancer in the high-risk group have worse survival in different subgroups, including age, gender, histological grade, and TNM stage. The nomogram that included risk scores for DRR-related genes could accurately foresee OS of patients with gastric cancer. Interestingly, the tumor mutation burden score was higher in the low-risk group than that in the high-risk group, and the risk score for DRR-related genes was negatively correlated with tumor mutation burden in gastric cancer. Next, we further combined the risk score and tumor mutation burden to evaluate the prognosis of gastric cancer patients. The low-risk cohort had a better prognosis than the high-risk cohort in the high tumor mutation burden subgroup. The number of mutation types in the high-risk group was lower than that in the low-risk group. In the immune microenvironment of gastric cancer, more naïve B cells, memory resting CD4+ T cells, Treg cells, monocytes cells, and resting mast cells were infiltrated in the high-risk group. At last, PD-L1 and IAP expressions were negatively correlated with the risk scores; patients with gastric cancer in the low-risk group showed better immunotherapy outcomes than those in the high-risk group. Overall, the DRR-related gene signature based on tumor mutation burden is a novel biomarker for prognostic and immunotherapy response in patients with gastric cancer.


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