Investigating the shared genetic architecture between breast and ovarian cancers.

High heritability and strong correlation have been observed in breast and ovarian cancers. However, their shared genetic architecture remained unclear. Linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (ρ-HESS) were applied to estimate heritability and genetic correlations. Bivariate causal mixture model (MiXeR) was used to qualify the polygenic overlap. Then, stratified-LDSC (S-LDSC) was used to identify tissue and cell type specificity. Meanwhile, the adaptive association test called MTaSPUsSet was performed to identify potential pleiotropic genes. The Single Nucleotide Polymorphisms (SNP) heritability was 13% for breast cancer and 5% for ovarian cancer. There was a significant genetic correlation between breast and ovarian cancers (rg=0.21). Breast and ovarian cancers exhibited polygenic overlap, sharing 0.4 K out 2.8 K of causal variants. Tissue and cell type specificity displayed significant enrichment in female breast mammary, uterus, kidney tissues, and adipose cell. Moreover, the 74 potential pleiotropic genes were identified between breast and ovarian cancers, which were related to the regulation of cell cycle and cell death. We quantified the shared genetic architecture between breast and ovarian cancers and shed light on the biological basis of the co-morbidity. Ultimately, these findings facilitated the understanding of disease etiology.

Causal association of rheumatoid arthritis with frailty and the mediation role of inflammatory cytokines: A Mendelian randomization study.

BACKGROUND: Previous observational studies have suggested the association between rheumatoid arthritis (RA) and frailty. However, it remains obscure whether this association is causal. This study aims to investigate the causal association of RA with frailty and the mediation effect of inflammatory cytokines using Mendelian randomization (MR) design. METHODS: Summary-level data for RA (N = 58,284), frailty index (FI) (N = 175,226), Fried frailty score (FFS) (N = 386,565), and 41 inflammatory cytokines (N = 8,293) were obtained from recent genome-wide association studies. Univariable and multivariable MR analyses were conducted to investigate and verify the causal association of RA with frailty. The potential mediation effects of inflammatory cytokines were estimated using two-step MR. RESULTS: Univariable inverse variance weighted MR analysis suggested that genetically determined RA was associated with increased FI (beta=0.021; 95 % CI: 0.012, 0.03; p = 2.2 × 10-6) and FFS (beta=0.011; 95 %CI: 0.007, 0.015; p = 8.811 × 10-8). The consistent results were observed in multivariable MR analysis after adjustment for asthma, smoking, BMI, physical activity, telomere length, and depression. Mediation analysis showed evidence of an indirect effect of RA on FI through monokine induced by interferon-gamma (MIG) with a mediated proportion of 9.8 % (95 %CI: 4.76 %, 19.05 %), on FFS via MIG and stromal cell-derived factor-1 alpha with a mediated proportion of 9.6 % (95 %CI: 0 %, 18.18 %) and 8.44 % (95 %CI: 0 %, 18.18 %), respectively. CONCLUSION: This study provided credible evidence that genetically predicted RA was associated with a higher risk of frailty. Additionally, inflammatory cytokines were involved in the mechanism of RA-induced frailty.

Causal effects of sleep traits on metabolic syndrome and its components: a Mendelian randomization study.

PURPOSE: Previous observational studies have suggested an association between sleep disturbance and metabolic syndrome (MetS). However, it remains unclear whether this association is causal. This study aims to investigate the causal effects of sleep-related traits on MetS using Mendelian randomization (MR). METHODS: Single-nucleotide polymorphisms strongly associated with daytime napping, insomnia, chronotype, short sleep, and long sleep were selected as genetic instruments from the corresponding genome-wide association studies (GWAS). Summary-level data for MetS were obtained from two independent GWAS datasets. Univariable and multivariable MR analyses were conducted to investigate and verify the causal effects of sleep traits on MetS. RESULTS: The univariable MR analysis demonstrated that genetically predicted daytime napping and insomnia were associated with increased risk of MetS in both discovery dataset (OR daytime napping = 1.630, 95% CI 1.273, 2.086; OR insomnia = 1.155, 95% CI 1.108, 1.204) and replication dataset (OR daytime napping = 1.325, 95% CI 1.131, 1.551; OR insomnia = 1.072, 95% CI 1.046, 1.099). For components, daytime napping was positively associated with triglycerides (beta = 0.383, 95% CI 0.160, 0.607) and waist circumference (beta = 0.383, 95% CI 0.184, 0.583). Insomnia was positively associated with hypertension (OR = 1.101, 95% CI 1.042, 1.162) and waist circumference (beta = 0.067, 95% CI 0.031, 0.104). The multivariable MR analysis indicated that the adverse effect of daytime napping and insomnia on MetS persisted after adjusting for BMI, smoking, drinking, and another sleep trait. CONCLUSION: Our study supported daytime napping and insomnia were potential causal factors for MetS characterized by central obesity, hypertension, or elevated triglycerides.

Impact of weekday of esophageal cancer surgery on long-term oncological outcomes.

BACKGROUND: Studies about the influence of weekday of esophagectomy on survival are limited and show conflicting results. This study aimed to explore whether weekday of esophagectomy affects patient's survival outcomes. METHODS: Patients who underwent esophagectomy in a grade-A tertiary hospital from January 2015 to December 2016 were enrolled. The primary outcome was 5-year overall survival (OS). The secondary outcomes were 5-year disease-free survival (DFS) and days of hospitalization. The impact of weekday surgery on 5-year OS and DFS were evaluated with Cox regression, and impact on days of hospitalization was assessed using logistic regression. Propensity score matching (PSM) analysis was used to balance the confounding factors. RESULTS: A total of 1478 patients were included. The 5-year OS and DFS were 63.77% and 59.26% respectively. Multivariate analyses adjusted for covariables indicated that weekday was not significantly associated with OS (P = 0.076), nor days of hospitalization (P = 0.824), but it appeared to be associated with DFS (P = 0.044). Additionally, PSM analysis showed no significant effect of weekday on the 5-year OS, nor DFS and days of hospitalization. CONCLUSION: In patients diagnosed with squamous esophageal cancer, the survival outcome of patients was not influenced by weekday.

Associations between physical activity and all-cause and cardiovascular mortality in adults with type 2 diabetes mellitus: A prospective cohort study from NHANES 2007-2018.

AIMS: To investigate the dose-response association between physical activity and all-cause and cardiovascular mortality in adults with type 2 diabetes mellitus and the effects of replacing sedentary behavior with physical activity. METHODS: 4808 adults with type 2 diabetes mellitus were included in NHANES 2007-2018. Cox proportional hazards models were used to calculate hazard ratios and 95% confidence intervals. Isotemporal substitution analyses were further to determine the possible benefit of replacing sedentary time. RESULTS: During a median follow-up of 6.58 years, 902 deaths occurred, including 290 deaths from cardiovascular disease. Compared with the inactive group, the low-active and high-active groups were associated with declined risks of all-cause mortality [HRs (95% CIs) 0.64 (0.50, 0.83); 0.60 (0.50, 0.73), respectively] and cardiovascular mortality [0.50 (0.29, 0.88); 0.54 (0.39, 0.76)), respectively]. Dose-response analysis showed a significant U-shaped curve between physical activity and all-cause and cardiovascular mortality. Replacing 30 min/day of sedentary time with physical activity was substantially linked to a reduced risk of 8-32% mortality. CONCLUSION: A high level of PA of 40.52 and 31.66 MET-h/week was respectively related to the lowest risk of all-cause and cardiovascular mortality. Replacing sedentary time with physical activity could benefit the type 2 diabetes mellitus population.

Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on T-cell marker genes to predict prognosis and immunotherapy response in bladder cancer.

BACKGROUND: T cells have been proven to play important roles in anti-tumor and tumor microenvironment shaping, while these roles have not been explained in bladder cancer (BLCA). METHODS: Single-cell RNA-sequencing (scRNA-seq) data were downloaded from the gene expression omnibus (GEO) database to screen T-cell marker genes. Bulk RNA-sequencing data and clinical information from BLCA patients were downloaded from the cancer genome atlas (TCGA) database to develop a prognosis signature. We analyzed the association of different risk groups with survival analysis, gene set enrichment analysis (GSEA), tumor mutational burden (TMB), and immunotherapy response. RESULTS: Based on 192 T-cell marker genes identified by scRNA-seq analysis, we constructed a prognostic signature containing 7 genes in the training cohort, which was further validated in the testing cohort and GEO cohort. The areas under the receiver operating characteristic curve at 1-, 3-, and 5 years were 0.734, 0.742 and 0.726 in the training cohort, 0.697, 0.671 and 0.670 in the testing cohort, 0.702, 0.665 and 0.629 in the GEO cohort, respectively. In addition, we constructed a nomogram based on clinical factors and the risk score of the signature. The low-risk group exhibited higher immune-related pathways, immune cell infiltration and TMB levels. Importantly, immunophenotype score and immunotherapy cohort (IMvigor210) analyses showed that the low-risk group had better immunotherapy response and prognosis. CONCLUSIONS: Our study reveals a novel prognostic signature based on T-cell marker genes, which provides a new target and theoretical support for BLCA patients.

Left compared with right thoracic approach thoracotomy in esophageal cancer: a retrospective cohort study.

BACKGROUND: Esophagectomy is regarded as one of the optimal treatments for resectable esophageal cancer. However, the impact of surgical approach on the long-term prognosis of esophageal cancer remains controversial. This study attempted to compare the long-term survival outcomes of patients receiving left and right thoracic esophagectomy for esophageal cancer. METHODS: A total of 985 patients underwent esophagectomy (including 453 left and 532 right thoracic approach) for esophageal cancer in Henan Cancer Hospital from January 2015 to December 2016 were enrolled. Their 5 year overall survival (OS) and disease-free survival (DFS) were retrospectively collected. Cox regression was performed to compare OS and DFS in patients who underwent left and right thoracic esophagectomy. Propensity score matching (PSM) analysis was used to balance confounding factors. RESULTS: The 5 year OS rates were 60.21% in the left and 51.60% in the right thoracic esophagectomy, respectively (P = 0.67). The 5 year DFS rates were 56.73% in the left and 47.93% and in the right thoracic esophagectomy, respectively (P = 0.36). Cox regression analysis showed there was no significant difference in long-term survival between patients with left and right surgical access (OS: HR = 0.95, 95% CI 0.77-1.18; DFS: HR = 0.91, 95% CI 0.74-1.12). In the cohort of patients obtained by PSM, Cox regression analysis yielded the similar results. CONCLUSION: For patients with resectable esophageal cancer, the surgical treatment through left thoracic approach can achieve the same long-term survival outcomes as the right thoracic approach.

An ultrastable 2D covalent organic framework coating for headspace solid-phase microextraction of organochlorine pesticides in environmental water.

Herein, a quinoline-linked ultrastable 2D covalent organic framework (COF-CN) coated fiber was successfully prepared and used for highly-sensitive headspace solid-phase microextraction (HS-SPME) of organochlorine pesticides (OCPs) in environmental water. The extraction efficiency of the COF-CN coating for all 14 OCPs was higher than that of four commercial SPME fiber coatings and most of the published works, with enrichment factors ranging from 540 to 5065. In combination with gas chromatography-tandem mass spectrometry (GC-MS/MS), a wide linear range (0.05-200 ng/L), low detection limits (LODs, 0.0010-13.54 ng/L) and satisfactory reproducibility and repeatability were obtained under optimal conditions. Compared with the published works, the LODs of the developed technique were improved 2-5.9 times, and the enrichment factors (EFs) of the developed method were enhanced at least 2 times. The COF-CN coated fiber can be easily recycled and reused at least 70 times without any washing step. The adsorption mechanism was first characterized by density functional theory calculations and X-ray photoelectron spectroscopy analysis. Besides, the established method was successfully applied to the analysis of the distribution of trace OCPs in real water samples from Henan Province. All these results proved the promising application of the developed HS-SPME-GC-MS/MS method for organic pollutants analysis in water samples.

Identification of exosomes-related lncRNAs in clear cell renal cell carcinoma based on Bayesian spike-and-slab lasso approach.

Exosomes-related long non-coding RNAs (lncRNAs) have been reported to play significant roles in clear cell renal cell carcinoma (ccRCC). However, there is little known about the relationship between exosomes-related lncRNAs and ccRCC. This study aimed to select optimal prognostic model based on exosomes-related lncRNAs to provide a methodological reference for high-dimensional data. Based on the Cancer Genome Atlas (TCGA) database of 515 ccRCC patients, two risk score models were generated underlying Bayesian spike-and-slab lasso and lasso regression. The optimal model was determined by calculating the area of time-dependent receiver-operating characteristic (ROC) curves in the TCGA and ArrayExpress databases. The immune patterns and sensitivity of immunotherapy between the high and low groups were further explored. Initially, we constructed two risk score models containing 11 and 7 exosomes-related lncRNAs according to Bayesian spike-and-slab lasso and lasso regression respectively. ROC curves revealed that the model constructed by Bayesian spike-and-slab lasso regression was more reliable in predicting survival at 1, 3, and 5 years, yielding an area under the curves (AUCs) of 0.796, 0.732, and 0.742, respectively. Kaplan-Meier (K-M) curves presented that prognosis was poorer in the high-risk score group (P < 0.001). Additionally, the high-risk score group patients were enriched in immune-activating phenotypes and more sensitive to immunotherapy. The exosomes-related lncRNAs model constructed with Bayesian spike-and-slab lasso regression has higher predictive power for ccRCC patients' prognosis, which provides methodological reference for the analysis of high-dimensional data in bioinformatics and guides the tailored treatment of ccRCC patients.

Prognostic Model for Clear-cell Renal Cell Carcinoma Based on Natural Killer Cell-related Genes.

BACKGROUND: Natural killer (NK) cells are a key factor affecting progression and immune surveillance of clear-cell renal cell carcinoma (ccRCC). This study sought to construct a natural killer cell-related prognostic signature (NKRPS) to predict the outcome of ccRCC patients and to furnish guidance for finding appropriate treatment strategies. METHODS: From the TCGA and ArrayExpress databases, transcriptomic profiles and relevant clinical information of ccRCC patients were downloaded for the TCGA cohort (n = 515) and the E-MTAB-1980 cohort (n = 101). With the univariate Cox analysis and LASSO-Cox regression algorithm, a NKRPS was built to evaluate patients' prognosis. Receiver operating characteristic (ROC) curves and calibration curves were drawn to estimate the predictive power of the prognostic model. Then, tumor microenvironment (TME), tumor mutational burden (TMB), sensitization to immune checkpoint inhibitors (ICIs) therapy and targeted drug treatment were analyzed in ccRCC patients. RESULTS: Nine genes (BID, CCL7, CSF2, IL23A, KNSTRN, RHBDD3, PIK3R3, RNF19B and VAV3) were identified to construct a NKRPS. High-risk group displayed undesirable survival compared to low-risk group (P < .05). Moreover, the area under the curve (AUC) of ROC at 1-, 3- and 5-year were 0.766, 0.755, and 0.757, respectively. High-risk group was characterized by superior immune infiltration, higher TMB, and higher expression of 5 ICI-related genes. Additionally, this model enabled to predict the sensitivity of patients to chemotherapy drugs. CONCLUSION: NKRPS had a strong predictive power on prognosis of ccRCC patients, which may facilitate individualized treatment and medical decision making.

Genetically predicted blood pressure, antihypertensive drugs and risk of heart failure: a Mendelian randomization study.

BACKGROUND: Elevated blood pressure (BP) was associated with higher risk of heart failure, but the relationship between BP-lowering via antihypertensive drugs and diminution of heart failure was inconclusive. This study aimed to estimate the causal association of BP with heart failure, and explore the effects of BP-lowering through different antihypertensive drug classes on heart failure risk using Mendelian randomization analysis with genetic variants as instrument variables. METHODS: Genetic variants associated with BP were derived from UK Biobank ( n  = 317 754) and the genome-wide association study (GWAS) meta-analysis of UK Biobank and International Consortium of Blood Pressure ( n  = 757 601). Heart failure summary association data were contributed by HERMES Consortium (47 309 heart failure cases and 930 014 controls). Inverse variance weighted (IVW) was performed to estimate causality between exposure and outcome, and weighted median was utilized as sensitivity analysis, and Mendelian randomization-Egger regression was used to identify pleiotropy of instrument variables. Multivariable Mendelian randomization (MVMR) was applied to control for the confounders. RESULTS: Genetically predicted SBP and DBP were associated with heart failure [SBP: odds ratio (OR) = 1.355, 95% confidence interval (CI) 1.201-1.529; DBP: OR = 1.348, 95% CI 1.213-1.498] in UK Biobank. Likewise, in the GWAS meta-analysis of UK Biobank and International Consortium of Blood Pressure, the causal associations were observed between SBP, DBP and heart failure (SBP: OR = 1.237, 95% CI 1.188-1.289; DBP: OR = 1.337, 95% CI 1.245-1.437). Genetically determined ß-blockers and calcium channel blockers (CCBs) were associated with lower risk of heart failure (ß-blockers: OR = 0.617, 95% CI 0.453-0.839; CCBs: OR = 0.730, 95% CI 0.625-0.851). No association was found between angiotensin receptor blockers (ARBs) and heart failure (OR = 1.593, 95% CI 0.647-3.924). When adjusted for smoking, alcohol, physical activity, fruit and vegetable intake, the results were stable. CONCLUSION: Our study indicates causal associations between SBP, DBP, and heart failure, and suggests the preventive effects of heart failure by BP-lowering using ß-blockers and CCBs.

Identification of the shared genetic architecture underlying seven autoimmune diseases with GWAS summary statistics.

Background: The common clinical symptoms and immunopathological mechanisms have been observed among multiple autoimmune diseases (ADs), but the shared genetic etiology remains unclear. Methods: GWAS summary statistics of seven ADs were downloaded from Open Targets Genetics and Dryad. Linkage disequilibrium score regression (LDSC) was applied to estimate overall genetic correlations, bivariate causal mixture model (MiXeR) was used to qualify the polygenic overlap, and stratified-LDSC partitioned heritability to reveal tissue and cell type specific enrichments. Ultimately, we conducted a novel adaptive association test called MTaSPUsSet for identifying pleiotropic genes. Results: The high heritability of seven ADs ranged from 0.1228 to 0.5972, and strong genetic correlations among certain phenotypes varied between 0.185 and 0.721. There was substantial polygenic overlap, with the number of shared SNPs approximately 0.03K to 0.21K. The specificity of SNP heritability was enriched in the immune/hematopoietic related tissue and cells. Furthermore, we identified 32 pleiotropic genes associated with seven ADs, 23 genes were considered as novel genes. These genes were involved in several cell regulation pathways and immunologic signatures. Conclusion: We comprehensively explored the shared genetic architecture across seven ADs. The findings progress the exploration of common molecular mechanisms and biological processes involved, and facilitate understanding of disease etiology.

Trends and influence factors in the prevalence, intervention, and control of metabolic syndrome among US adults, 1999-2018.

AIM: We aimed to describe the trends in the prevalence, intervention, and control of metabolic syndrome (MetS) among US adults through 1999-2018. Additionally, the influence factors of MetS and its control were further explored. METHODS: We included participants older than 20 using the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 (n = 22,114). The rate of prevalence, intervention, and control of MetS were caculated by survey weights. Joinpoint regression and survey-weighted generalized linear models were used to analyze trends and influence factors, respectively. RESULTS: The prevalence of MetS increased from 28.23 to 37.09% during 1999-2018 (P for trend < 0.05). The former smoker (OR = 1.20, 95%CI: 1.07, 1.36) and current smoker (OR = 1.27, 95%CI: 1.11, 1.45) increased the prevalence of MetS. While vigorous activity (OR = 0.53, 95%CI: 0.47, 0.61) decreased it. Among MetS components, the prevalence of elevated blood-glucose (from 21.18 to 34.68%) and obesity (from 44.81 to 59.06%) raised (P for trend < 0.05), with an uptrend in the use of antidiabetic (from 9.87 to 28.63%) and a downtrend of vigorous activity (from 23.79 to 16.53%) (P for trend < 0.05). Decreased trends were observed in the control of Hb1Ac (< 7%) (from 87.13 to 84.06%) and BMI (<25 kg/m2) (from 11.36 to 7.49%). Among MetS underwent antidiabetic, 45-64 years old and male decreased the control of Hb1Ac (< 7%). The control of BMI (<25 kg/m2) among individuals with physical activity was reduced mainly in the population of younger (aged 20-44 years old), male, non-Hispanic black, middle income and smoker (former and current). CONCLUSIONS: The prevalence of MetS increased significantly through 1999-2018. Elevated blood glucose and obesity were the main causes of MetS burden. Quitting smoking and increasing physical activity may decrease the prevalence of MetS. In the control of blood-glucose and obesity, we should screen out the focus population to modify treatment and improve lifestyle.

Mining of immunological and prognostic-related biomarker for cervical cancer based on immune cell signatures.

Background: Immunotherapy has changed the therapeutic landscape of cervical cancer (CC), but has durable anti-tumor activity only in a subset of patients. This study aims to comprehensively analyze the tumor immune microenvironment (TIME) of CC and to mine biomarkers related to immunotherapy and prognosis. Methods: The Cancer Genome Atlas (TCGA) data was utilized to identify heterogeneous immune subtypes based on survival-related immune cell signatures (ICSs). ICSs prognostic model was constructed by Cox regression analyses, and immunohistochemistry was conducted to verify the gene with the largest weight coefficient in the model. Meanwhile, the tumor immune infiltration landscape was comprehensively characterized by ESTIMATE, CIBERSORT and MCPcounter algorithms. In addition, we also analyzed the differences in immunotherapy-related biomarkers between high and low-risk groups. IMvigor210 and two gynecologic tumor cohorts were used to validate the reliability and scalability of the Risk score. Results: A total of 291 TCGA-CC samples were divided into two ICSs clusters with significant differences in immune infiltration landscape and prognosis. ICSs prognostic model was constructed based on eight immune-related genes (IRGs), which showed higher overall survival (OS) rate in the low-risk group (P< 0.001). In the total population, time-dependent receiver operating characteristic (ROC) curves displayed area under the curve (AUC) of 0.870, 0.785 and 0.774 at 1-, 3- and 5-years. Immunohistochemical results showed that the expression of the oncogene (FKBP10) was negatively correlated with the degree of differentiation and positively correlated with tumor stage, while the expression of tumor suppressor genes (S1PR4) was the opposite. In addition, the low-risk group had more favorable immune activation phenotype and higher enrichment of immunotherapy-related biomarkers. The Imvigor210 and two gynecologic tumor cohorts validated a better survival advantage and immune efficacy in the low-risk group. Conclusion: This study comprehensively assessed the TIME of CC and constructed an ICSs prognostic model, which provides an effective tool for predicting patient's prognosis and accurate immunotherapy.

Association between Dietary Total Antioxidant Capacity of Antioxidant Vitamins and the Risk of Stroke among US Adults.

The intake of antioxidant vitamins can scavenge free radicals and reduce oxidative stress, which may be beneficial for stroke. However, the relationship between total antioxidant capacity (TAC) of antioxidant vitamins and stroke is controversial. This study aims to investigate the association between dietary TAC and the risk of stroke in US adults. This study included participants over 20 years old from the 2001-2018 National Health and Nutrition Examination Survey (NHANES). Data from two 24 h dietary recalls were used to estimate the usual intake of antioxidant vitamins. TAC was calculated by the vitamin C equivalent antioxidant capacity reference values of individual antioxidant vitamins. Survey-weighted generalized linear models were performed to evaluate the relationship between TAC and the risk of stroke. A restricted cubic spline regression model was used to investigate the dose-response association. A total of 37,045 participants was involved, of whom 1391 suffered a stroke. Compared with the first tertile, the participants in the second tertile of TAC showed a lower risk of stroke (OR = 0.788, 95% CI: 0.662, 0.936) after adjusting for potential risk factors. The dose-response analysis showed a gradual increase in the risk of stroke as TAC decreases. Subgroups analyses indicated that this association was primarily in the population of those aged over 60 years old, who were female, consumed alcohol, were a former smoker and inactive. The sensitivity analysis presented consistent results. These results suggest that deficiency of dietary TAC was associated with an increased risk of stroke, particularly in populations with underlying oxidative stress injury.

Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysis.

Immune genes play an important role in the development and progression of acute myeloid leukemia (AML). However, the role of immune genes in the prognosis and microenvironment of AML remains unclear. In this study, we analyzed 151 AML patients in the TCGA database for relevant immune cell infiltration. AML patients were divided into high and low immune cell infiltration clusters based on ssGSEA results. Immune-related pathways, AML pathways and glucose metabolism pathways were enriched in the high immune cell infiltration cluster. Then we screened the differential immune genes between the two immune cell infiltration clusters. Nine prognostic immune genes were finally identified in the train set by LASSO-Cox regression. We constructed a model in the train set based on the nine prognostic immune genes and validated the predictive capability in the test set. The areas under the ROC curve of the train set and the test set for ROC at 1, 3, 5 years were 0.807, 0.813, 0.815, and 0.731, 0.745, 0.830, respectively. The areas under ROC curve of external validation set in 1, 3, and 5 years were 0.564, 0.619, and 0.614, respectively. People with high risk scores accompanied by high TMB had been detected with the worst prognosis. Single-cell sequencing analysis revealed the expression of prognostic genes in AML cell subsets and pseudo-time analysis described the differentiation trajectory of cell subsets. In conclusion, our results reveal the characteristics of immune microenvironment and cell subsets of AML, while it still needs to be confirmed in larger samples studies. The prognosis model constructed with nine key immune genes can provide a new method to assess the prognosis of AML patients.

Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on T-cell marker genes to predict prognosis and therapeutic response in lung squamous cell carcinoma.

Cancer immunotherapy is an increasingly successful strategy for treating patients with advanced or conventionally drug-resistant cancers. T cells have been proved to play important roles in anti-tumor and tumor microenvironment shaping, while these roles have not been explained in lung squamous cell carcinoma (LUSC). In this study, we first performed a comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data from the gene expression omnibus (GEO) database to identify 72 T-cell marker genes. Subsequently, we constructed a 5-gene prognostic signature in the training cohort based on the T-cell marker genes from the cancer genome atlas (TCGA) database, which was further validated in the testing cohort and GEO cohort. The areas under the receiver operating characteristic curve at 1-, 3-, and 5-years were 0.614, 0.713 and 0.702 in the training cohort, 0.669, 0.603 and 0.645 in the testing cohort, 0.661, 0.628 and 0.590 in the GEO cohort, respectively. Furthermore, we created a highly reliable nomogram to facilitate clinical application. Gene set enrichment analysis showed that immune-related pathways were mainly enriched in the high-risk group. Tumor immune microenvironment indicated that high-risk group exhibited higher immune score, stromal score, and immune cell infiltration levels. Moreover, genes of the immune checkpoints and human leukocyte antigen family were all overexpressed in high-risk group. Drug sensitivity revealed that low-risk group was sensitive to 8 chemotherapeutic drugs and high-risk group to 4 chemotherapeutic drugs. In short, our study reveals a novel prognostic signature based on T-cell marker genes, which provides a new target and theoretical support for LUSC patients.

Identification of a Prognostic Model Based on Immune Cell Signatures in Clear Cell Renal Cell Carcinoma.

Background: Accumulating evidence substantiated that the immune cells were intricately intertwined with the prognosis and therapy of clear cell renal cell carcinoma (ccRCC). We aimed to construct an immune cell signatures (ICS) score model to predict the prognosis of ccRCC patients and furnish guidance for finding appropriate treatment strategies. Methods: Based on The Cancer Genome Atlas (TCGA) database, the normalized enrichment score (NES) of 184 ICSf was calculated using single-sample gene set enrichment analysis (ssGSEA). An ICS score model was generated in light of univariate Cox regression and Least absolute shrinkage and selection operator (Lasso)-Cox regression, which was independently validated in ArrayExpress database. In addition, we appraised the predictive power of the model via Kaplan-Meier (K-M) curves and time-dependent receiver operating characteristic (ROC) curves. Eventually, immune infiltration, genomic alterations and immunotherapy were analyzed between high and low ICS score groups. Results: Initially, we screened 11 ICS with prognostic impact based on 515 ccRCC patients. K-M curves presented that the high ICS score group experienced a poorer prognosis (P < 0.001). In parallel, ROC curves revealed a satisfactory reliability of model to predict individual survival at 1, 3, and 5 years, with area under the curves (AUCs) of 0.744, 0.713, and 0.742, respectively. In addition, we revealed that the high ICS score group was characterized by increased infiltration of immune cells, strengthened BAP1 mutation frequency, and enhanced expression of immune checkpoint genes. Conclusion: The ICS score model has higher predictive power for patients' prognosis and can instruct ccRCC patients in seeking suitable treatment.

Comprehensive Analysis of N6-Methyladenosine-Related Long Noncoding RNA Prognosis of Acute Myeloid Leukemia and Immune Cell Infiltration.

N6-Methyladenosine-related long noncoding RNAs play an essential role in many cancers' development. However, the relationship between m6A-related lncRNAs and acute myelogenous leukemia (AML) prognosis remains unclear. We systematically analyzed the association of m6A-related lncRNAs with the prognosis and tumor immune microenvironment (TME) features using the therapeutically applicable research to generate effective treatment (TARGET) database. We screened 315 lncRNAs associated with AML prognosis and identified nine key lncRNAs associated with m6A by the LASSO Cox analysis. A model was established based on these nine lncRNAs and the predictive power was explored in The Cancer Genome Atlas (TCGA) database. The areas under the ROC curve of TARGET and TCGA databases for ROC at 1, 3, and 5 years are 0.701, 0.704, and 0.696, and 0.587, 0.639, and 0.685, respectively. The nomogram and decision curve analysis (DCA) showed that the risk score was more accurate than other clinical indicators in evaluating patients' prognoses. The clusters with a better prognosis enrich the AML pathways and immune-related pathways. We also found a close correlation between prognostic m6A-related lncRNAs and tumor immune cell infiltration. LAG3 expression at the immune checkpoint was lower in the worse prognostic cluster. In conclusion, m6A-related lncRNAs partly affected AML prognosis by remodeling the TME and affecting the anticarcinogenic ability of immune checkpoints, especially LAG3 inhibitors. The prognostic model constructed with nine key m6A-related lncRNAs can provide a method to assess the prognosis of AML patients in both adults and children.