Association Between Long-Term Exposure to Ambient Air Pollution and the Risk of Mild Cognitive Impairment in a Chinese Urban Area: A Case-Control Study.

Background: As a prodromal stage of dementia, significant emphasis has been placed on the identification of modifiable risks of mild cognitive impairment (MCI). Research has indicated a correlation between exposure to air pollution and cognitive function in older adults. However, few studies have examined such an association among the MCI population inChina. Objective: We aimed to explore the association between air pollution exposure and MCI risk from the Hubei Memory and Aging Cohort Study. Methods: We measured four pollutants from 2015 to 2018, 3 years before the cognitive assessment of the participants. Logistic regression models were employed to calculate odds ratios (ORs) to assess the relationship between air pollutants and MCI risk. Results: Among 4,205 older participants, the adjusted ORs of MCI risk for the highest quartile of PM2.5, PM10, O3, and SO2 were 1.90 (1.39, 2.62), 1.77 (1.28, 2.47), 0.56 (0.42, 0.75), and 1.18 (0.87, 1.61) respectively, compared with the lowest quartile. Stratified analyses indicated that such associations were found in both males and females, but were more significant in older participants. Conclusions: Our findings are consistent with the growing evidence suggesting that air pollution increases the risk of mild cognitive decline, which has considerable guiding significance for early intervention of dementia in the older population. Further studies in other populations and broader geographical areas are warranted to validate these findings.

Associations among multidomain lifestyles, chronic diseases, and dementia in older adults: a cross-sectional analysis of a cohort study.

Background: Unhealthy lifestyles and chronic diseases are commonly seen and treatable factors in older adults and are both associated with dementia. However, the synergistic effect of the interaction of lifestyles and chronic diseases on dementia is unknown. Methods: We determined independent associations of multidomain lifestyles and chronic diseases (cerebrovascular disease, diabetes, and hypertension) with dementia and examined their synergistic impact on dementia among older adults. The data were drawn from the Hubei Memory and Aging Cohort Study. We created a summary score of six factors for multidomain lifestyles. Dementia was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders IV. Logistic regression and multiple correspondence analyses were used to explore the relationships among multidomain lifestyles, chronic diseases, and dementia. A sensitivity analysis was performed to minimize the interference of reverse causality and potential confounders. Results: Independent associations with dementia were found in unhealthy (OR = 1.90, 95% CI: 1.38-2.61) and intermediate healthy lifestyles (OR, 3.29, 2.32-4.68), hypertension (OR, 1.21, 1.01-1.46), diabetes (OR, 1.30, 1.04-1.63), and cerebrovascular disease (OR, 1.39, 1.12-1.72). Interactions of diabetes (p = 0.004), hypertension (p = 0.004), and lifestyles were significant, suggesting a combined impact on dementia. Sensitivity analysis supported the strong association among multidomain lifestyles, chronic diseases, and dementia prevalence. Conclusion: An unhealthy lifestyle was associated with a higher prevalence of dementia, regardless of whether the participants had chronic diseases; however, this association was stronger in individuals with chronic diseases. Multidomain lifestyles and chronic diseases may have an enhanced impact on dementia.

Hub genes, diagnostic model, and predicted drugs in systemic sclerosis by integrated bioinformatics analysis.

Background: Systemic sclerosis (scleroderma; SSc), a rare and heterogeneous connective tissue disease, remains unclear in terms of its underlying causative genes and effective therapeutic approaches. The purpose of the present study was to identify hub genes, diagnostic markers and explore potential small-molecule drugs of SSc. Methods: The cohorts of data used in this study were downloaded from the Gene Expression Complex (GEO) database. Integrated bioinformatic tools were utilized for exploration, including Weighted Gene Co-Expression Network Analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) regression, gene set enrichment analysis (GSEA), Connectivity Map (CMap) analysis, molecular docking, and pharmacokinetic/toxicity properties exploration. Results: Seven hub genes (THY1, SULF1, PRSS23, COL5A2, NNMT, SLCO2B1, and TIMP1) were obtained in the merged gene expression profiles of GSE45485 and GSE76885. GSEA results have shown that they are associated with autoimmune diseases, microorganism infections, inflammatory related pathways, immune responses, and fibrosis process. Among them, THY1 and SULF1 were identified as diagnostic markers and validated in skin samples from GSE32413, GSE95065, GSE58095 and GSE125362. Finally, ten small-molecule drugs with potential therapeutic effects were identified, mainly including phosphodiesterase (PDE) inhibitors (BRL-50481, dipyridamole), TGF-ß receptor inhibitor (SB-525334), and so on. Conclusion: This study provides new sights into a deeper understanding the molecular mechanisms in the pathogenesis of SSc. More importantly, the results may offer promising clues for further experimental studies and novel treatment strategies.

Prevalence and risk factors for subjective cognitive decline and the correlation with objective cognition among community-dwelling older adults in China: Results from the Hubei memory and aging cohort study.

INTRODUCTION: The prevalence and risk factors for subjective cognitive decline (SCD) and its correlation with objective cognition decline (OCD) among community-dwelling older adults is inconsistent. METHODS: Older adults underwent neuropsychological and clinical evaluations to reach a consensus on diagnoses. RESULTS: This study included 7486 adults without mild cognitive impairment and dementia (mean age: 71.35 years [standard deviation = 5.40]). The sex-, age-, and residence-adjusted SCD prevalence was 58.33% overall (95% confidence interval: 58.29% to 58.37%), with higher rates of 61.25% and 59.87% in rural and female subgroups, respectively. SCD global and OCD language, SCD memory and OCD global, SCD and OCD memory, and SCD and OCD language were negatively correlated in fully adjusted models. Seven health and lifestyle factors were associated with an increased risk for SCD. DISCUSSION: SCD affected 58.33% of older adults and may indicate concurrent OCD, which should prompt the initiation of preventative intervention for dementia. HIGHLIGHTS: SCD affects 58.33% of older adults in China. SCD may indicate concurrent objective cognitive decline. Difficulty finding words and memory impairments may indicate a risk for AD. The presence of SCD may prompt preventative treatment initiation of MCI or dementia. Social network factors may be initial targets for the early prevention of SCD.

GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels.

Cancer initiation and progression are likely caused by the dysregulation of biological pathways. Gene set analysis (GSA) could improve the signal-to-noise ratio and identify potential biological insights on the gene set level. However, platforms exploring cancer multi-omics data using GSA methods are lacking. In this study, we upgraded our GSCALite to GSCA (gene set cancer analysis, http://bioinfo.life.hust.edu.cn/GSCA) for cancer GSA at genomic, pharmacogenomic and immunogenomic levels. In this improved GSCA, we integrated expression, mutation, drug sensitivity and clinical data from four public data sources for 33 cancer types. We introduced useful features to GSCA, including associations between immune infiltration with gene expression and genomic variations, and associations between gene set expression/mutation and clinical outcomes. GSCA has four main functional modules for cancer GSA to explore, analyze and visualize expression, genomic variations, tumor immune infiltration, drug sensitivity and their associations with clinical outcomes. We used case studies of three gene sets: (i) seven cell cycle genes, (ii) tumor suppressor genes of PI3K pathway and (iii) oncogenes of PI3K pathway to prove the advantage of GSCA over single gene analysis. We found novel associations of gene set expression and mutation with clinical outcomes in different cancer types on gene set level, while on single gene analysis level, they are not significant associations. In conclusion, GSCA is a user-friendly web server and a useful resource for conducting hypothesis tests by using GSA methods at genomic, pharmacogenomic and immunogenomic levels.

A miR-9-5p/FOXO1/CPEB3 Feed-Forward Loop Drives the Progression of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide, but its regulatory mechanism remains unclear and potential clinical biomarkers are still lacking. Co-regulation of TFs and miRNAs in HCC and FFL module studies may help to identify more precise and critical driver modules in HCC development. Here, we performed a comprehensive gene expression and regulation analysis for HCC in vitro and in vivo. Transcription factor and miRNA co-regulatory networks for differentially expressed genes between tumors and adjacent tissues revealed the critical feed-forward loop (FFL) regulatory module miR-9-5p/FOXO1/CPEB3 in HCC. Gain- and loss-of-function studies demonstrated that miR-9-5p promotes HCC tumor proliferation, while FOXO1 and CPEB3 inhibit hepatocarcinoma growth. Furthermore, by luciferase reporter assay and ChIP-Seq data, CPEB3 was for the first time identified as a direct downstream target of FOXO1, negatively regulated by miR-9-5p. The miR-9-5p/FOXO1/CPEB3 FFL was associated with poor prognosis, and promoted cell growth and tumor progression of HCC in vitro and in vivo. Our study identified for the first time the existence of miR-9-5p/FOXO1/CPEB3 FFL and revealed its regulatory role in HCC progression, which may represent a new potential target for cancer therapy.

The Use of Lipoprotein-Associated Phospholipase A2 in a Chinese Population to Predict Cardiovascular Events.

Objective: To explore associations between lipoprotein-associated phospholipase A2 (Lp-PLA2) and the risk of cardiovascular events in a Chinese population, with a long-term follow-up. Methods: A random sample of 2,031 participants (73.6% males, mean age = 60.4 years) was derived from the Asymptomatic Polyvascular Abnormalities Community study (APAC) from 2010 to 2011. Serum Lp-PLA2 levels were determined by enzyme-linked immunosorbent assay (ELISA). The composite endpoint was a combination of first-ever stroke, myocardial infarction (MI) or all-cause death. Lp-PLA2 associations with outcomes were assessed using Cox models. Results: The median Lp-PLA2 level was 141.0 ng/mL. Over a median follow-up of 9.1 years, we identified 389 events (19.2%), including 137 stroke incidents, 43 MIs, and 244 all-cause deaths. Using multivariate Cox regression, when compared with the lowest Lp-PLA2 quartile, the hazard ratios with 95% confidence intervals for developing composite endpoints, stroke, major adverse cardiovascular events, and all-cause death were 1.77 (1.24-2.54), 1.92 (1.03-3.60), 1.69 (1.003-2.84), and 1.94 (1.18-3.18) in the highest quartile, respectively. Composite endpoints in 145 (28.6%) patients occurred in the highest quartile where Lp-PLA2 (159.0 ng/mL) was much lower than the American Association of Clinical Endocrinologists recommended cut-off point, 200 ng/mL. Conclusion: Higher Lp-PLA2 levels were associated with an increased risk of cardiovascular event/death in a middle-aged Chinese population. The Lp-PLA2 cut-off point may be lower in the Chinese population when predicting cardiovascular events.

CBX2 and EZH2 cooperatively promote the growth and metastasis of lung adenocarcinoma.

The disruption of epigenetic regulation is common in tumors; the abnormal expression of epigenetic factors leads to cancer occurrence and development. In this study, to investigate the potential function of histone methylation regulators in lung adenocarcinoma (LUAD), we performed differential expression analysis using RNA-seq data downloaded from The Cancer Genome Atlas (TCGA) database, and identified CBX2 and EZH2 as obviously upregulated histone methylation regulators. CBX2 knockdown significantly inhibited LUAD cell growth and metastasis in vitro and in vivo. The combined high expression of CBX2 and EZH2 was an indicator of poor prognosis in LUAD. The inhibition of both CBX2 and EZH2 exerted cooperative suppressive effects on the growth and metastasis of LUAD cells. Mechanistically, we revealed that CBX2 and EZH2 downregulated several PPAR signaling pathway genes and tumor suppressor genes through binding to their promoter cooperatively or separately. Furthermore, knockdown of CBX2 improved the therapeutic efficiency of EZH2 inhibitor on A549 cells. Our study reveals the cooperative oncogenic role of CBX2 and EZH2 in promoting LUAD progression, thereby providing potential targets for LUAD diagnosis and therapy.

The Hubei Memory and Aging Cohort Study: Study Design, Baseline Characteristics, and Prevalence of Cognitive Impairments.

BACKGROUND: Despite the improved access to health services in China, inadequate diagnosis and management of dementia are common issues, especially in rural regions. OBJECTIVE: The Hubei Memory & Aging Cohort Study was designed as a prospective study in Central China to determine the prevalence, incidence, and risk factors for dementia and mild cognitive impairment (MCI) among urban and rural older adults. METHODS: From 2018-2020, participants aged ≥65 years were screened, and data regarding their life behaviors, families, socio-economic status, physical and mental health, social and psychological factors, and cognition were collected. Diagnoses of MCI and dementia were made via consensus diagnosis using the Diagnostic and Statistical Manual of Mental Disorders fourth edition criteria. RESULTS: Of 8,221 individuals who completed their baseline clinical evaluation, 4,449 (54.1%) were women and 3,164 (38.4%) were from remote rural areas (average age: 71.96 years; mean education period: 7.58 years). At baseline, 25.98%(95%confidence interval [CI]: 24.99-26.96) and 7.24%(95%CI: 6.68-7.80) of the participants were diagnosed with MCI and dementia, respectively. Prevalence showed a strong relationship with age. The substantial disparities between rural and urban regions in MCI and dementia prevalence and multiple dementia-related risk factors were revealed. Especially for dementia, the prevalence rate in rural areas was 2.65 times higher than that in urban regions. CONCLUSION: Our results suggested that public health interventions are urgently needed to achieve equitable diagnosis and management for people living with dementia in the communities across urban and rural areas.

Population-attributable fractions of risk factors for all-cause dementia in China rural and urban areas: a cross-sectional study.

BACKGROUND: The prevalence of dementia in China, particularly in rural areas, is consistently increasing; however, research on population-attributable fractions (PAFs) of risk factors for dementia is scarce. METHODS: We conducted a cross-sectional survey, namely, the China Multicentre Dementia Survey (CMDS) in selected rural and urban areas from 2018 to 2020. We performed face-to-face interviews and neuropsychological and clinical assessments to reach a consensus on dementia diagnosis. Prevalence and weighted PAFs of eight modifiable risk factors (six classical: less childhood education, hearing impairment, depression, physical inactivity, diabetes, and social isolation, and two novels: olfactory decline and being unmarried) for all-cause dementia were estimated. RESULTS: Overall, CMDS included 17,589 respondents aged ≥ 65 years, 55.6% of whom were rural residents. The age- and sex-adjusted prevalence for all-cause dementia was 9.11% (95% CI 8.96-9.26), 5.19% (5.07-5.31), and 11.98% (11.8-12.15) in the whole, urban, and rural areas of China, respectively. Further, the overall weighted PAFs of the eight potentially modifiable risk factors were 53.72% (95% CI 52.73-54.71), 50.64% (49.4-51.89), and 56.54% (55.62-57.46) in the whole, urban, and rural areas of China, respectively. The eight risk factors' prevalence differed between rural and urban areas. Lower childhood education (PAF: 13.92%) and physical inactivity (16.99%) were primary risk factors in rural and urban areas, respectively. CONCLUSIONS: The substantial urban-rural disparities in the prevalence of dementia and its risk factors exist, suggesting the requirement of resident-specific dementia-prevention strategies.

Urban-Rural Disparities in the Association Between Body Mass Index and Cognitive Impairment in Older Adults: A Cross-Sectional Study in Central China.

BACKGROUND: Some studies have demonstrated an association between low and high body mass index (BMI) and an increased risk of dementia. However, only a few of these studies were performed in rural areas. OBJECTIVE: This cross-sectional study investigated the associations between BMI and cognitive impairment among community-dwelling older adults from rural and urban areas. METHODS: 8,221 older persons enrolled in the Hubei Memory & Ageing Cohort Study (HMACS) were recruited. Sociodemographic and lifestyle data, comorbidities, physical measurements, and clinical diagnoses of cognitive impairment were analyzed. Logistic regression was performed to assess the associations of BMI categories with cognitive impairment. A series of sensitivity analyses were conducted to test whether reverse causality could influence our results. RESULTS: Being underweight in the rural-dwelling participants increased the risk of cognitive impairment. Being overweight was a protective factor in rural-dwelling participants aged 65-69 years and 75-79 years, whereas being underweight was significantly associated with cognitive impairment (OR, 1.37; 95% CI: 1.03-1.83; p < 0.05). Sensitivity analyses support that underweight had an additive effect on the odds of cognitive impairment and was related to risk of dementia. Interaction test revealed that the differences between urban/rural in the relationship between BMI and cognitive impairment are statistically significant. CONCLUSION: Associations between BMI and cognitive impairment differ among urban/rural groups. Older people with low BMI living in rural China are at a higher risk for dementia than those living in urban areas.

A comprehensive survey for human transcription factors on expression, regulation, interaction, phenotype and cancer survival.

Transcription factors (TFs) act as key regulators in biological processes through controlling gene expression. Here, we conducted a systematic study for all human TFs on the expression, regulation, interaction, mutation, phenotype and cancer survival. We revealed that the average expression levels of TFs in normal tissues were lower than 50% expression of non-TFs, whereas TF expression was increased in cancers. TFs that are specifically expressed in an individual tissue or cancer may be potential marker genes. For instance, TGIF2LX/Y were preferentially expressed in testis and NEUROG1, PRDM14, SRY, ZNF705A and ZNF716 were specifically highly expressed in germ cell tumors. We found different distributions of target genes and TF co-regulations in different TF families. Some small TF families have huge protein interaction pairs, suggesting their central roles in transcriptional regulation. The bZIP family is a small family involving many signaling pathways. Survival analysis indicated that most TFs significantly affect survival of one or more cancers. Some survival-related TFs were also specifically highly expressed in the corresponding cancer types, which may be potential targets for cancer therapy. Finally, we identified 43 TFs whose mutations were closely correlated to survival, suggesting their cancer-driven roles. The systematic analysis of TFs provides useful clues for further investigation of TF regulatory mechanisms and the role of TFs in diseases.

Expression profile of immune checkpoint genes and their roles in predicting immunotherapy response.

Immune checkpoint genes (ICGs) play critical roles in circumventing self-reactivity and represent a novel target to develop treatments for cancers. However, a comprehensive analysis for the expression profile of ICGs at a pan-cancer level and their correlation with patient response to immune checkpoint blockade (ICB) based therapy is still lacking. In this study, we defined three expression patterns of ICGs using a comprehensive survey of RNA-seq data of tumor and immune cells from the functional annotation of the mammalian genome (FANTOM5) project. The correlation between the expression patterns of ICGs and patients survival and response to ICB therapy was investigated. The expression patterns of ICGs were robust across cancers, and upregulation of ICGs was positively correlated with high lymphocyte infiltration and good prognosis. Furthermore, we built a model (ICGe) to predict the response of patients to ICB therapy using five features of ICG expression. A validation scenario of six independent datasets containing data of 261 patients with CTLA-4 and PD-1 blockade immunotherapies demonstrated that ICGe achieved area under the curves of 0.64-0.82 and showed a robust performance and outperformed other mRNA-based predictors. In conclusion, this work revealed expression patterns of ICGs and underlying correlations between ICGs and response to ICB, which helps to understand the mechanisms of ICGs in ICB signal pathways and other anticancer treatments.

The expression and regulation of HOX genes and membrane proteins among different cytogenetic groups of acute myeloid leukemia.

BACKGROUND: The cytogenetic aberrations were considered as markers for diagnosis and prognosis in acute myeloid leukemia (AML), while the expression and regulation under different cytogenetic groups remain to be fully elucidated. METHODS: In this paper, for favorable, poor, and cytogenetically normal groups of AML patients, we performed comprehensive bioinformatics analyses including identifying differentially expressed genes (DEGs) and microRNAs (miRNAs) among them, functional enrichment and regulatory networks. RESULTS: We found that DEGs were enriched in membrane-related processes. Eleven genes and two miRNAs were significantly differentially expressed among these three AML groups. In survival analysis, membrane-related genes and several miRNAs were significant on prognostic outcome. Notably, six HOXA and three HOXB genes were significantly in low expression and high methylation in AML with favorable cytogenetics. Meanwhile, the miRNA-HOX gene co-regulatory networks revealed that HOXA5 was a hub node and regulated an AML oncogene SPARC. CONCLUSION: Our work may provide novel insights to the molecular characteristics and classification between AML with different cytogenetics.

A 6-Membrane Protein Gene score for prognostic prediction of cytogenetically normal acute myeloid leukemia in multiple cohorts.

Background: Cytogenetically normal acute myeloid leukemia (CN-AML) is a large proportion of AMLs with diverse prognostic outcomes. Identifying membrane protein genes as prognostic factors to stratify CN-AML patients will be critical to improve their outcomes. Purpose: This study aims to identify prognostic factors to stratify CN-AML patients to choose better treatments and improve their outcomes. Methods: CN-AML data were from TCGA cohort (n = 79) and four GEO datasets. We identified independent prognostic genes by Cox regression and Kaplan-Meier methods, and constructed linear regression model using LASSO algorithm. The prediction error curve was calculated using R package "pec". Results: Based on independent prognostic membrane genes, we constructed a regression model for CN-AML prognosis prediction: score = (0.0492 * CD52) - (0.0018 * CD96) + (0.0131 * EMP1) + (0.2058 * TSPAN2) + (0.0234 * STAB1) - (0.3658 * MBTPS1), which was named as MPG6 (6-Membrane Protein Gene) score. Tested in multiple CN-AML datasets, consistent results showed that CN-AML patients with high MPG6 score had poor survival, higher WBC count and shorter EFS. Comparing with other reported scoring models, the benchmark result of MPG6 achieved better association with survival in multiple cohorts. Moreover, by combining with other clinical indicators in CN-AML, MPG6 could improve the performance of survival prediction and serve as a robust prognostic factor. Conclusions: We identified the MPG6 score as a stable indicator with great potential for clinical application in risk stratification and outcome prediction in CN-AML.

Landscape of cancer diagnostic biomarkers from specifically expressed genes.

Although there has been great progress in cancer treatment, cancer remains a serious health threat to humans because of the lack of biomarkers for diagnosis, especially for early-stage diagnosis. In this study, we comprehensively surveyed the specifically expressed genes (SEGs) using the SEGtool based on the big data of gene expression from the The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) projects. In 15 solid tumors, we identified 233 cancer-specific SEGs (cSEGs), which were specifically expressed in only one cancer and showed great potential to be diagnostic biomarkers. Among them, three cSEGs (OGDH, MUDENG and ACO2) had a sample frequency >80% in kidney cancer, suggesting their high sensitivity. Furthermore, we identified 254 cSEGs as early-stage diagnostic biomarkers across 17 cancers. A two-gene combination strategy was applied to improve the sensitivity of diagnostic biomarkers, and hundreds of two-gene combinations were identified with high frequency. We also observed that 13 SEGs were targets of various drugs and nearly half of these drugs may be repurposed to treat cancers with SEGs as their targets. Several SEGs were regulated by specific transcription factors in the corresponding cancer, and 39 cSEGs were prognosis-related genes in 7 cancers. This work provides a survey of cancer biomarkers for diagnosis and early diagnosis and new insights to drug repurposing. These biomarkers may have great potential in cancer research and application.

Identification of STAB1 in Multiple Datasets as a Prognostic Factor for Cytogenetically Normal AML: Mechanism and Drug Indications.

Cytogenetically normal acute myeloid leukemia (CN-AML) presents with diverse outcomes in different patients and is categorized as an intermediate prognosis group. It is important to identify prognostic factors for CN-AML risk stratification. In this study, using the TCGA CN-AML dataset, we found that the scavenger receptor stabilin-1 (STAB1) is a prognostic factor for poor outcomes and validated it in three other independent CN-AML datasets. The high STAB1 expression (STAB1high) group had shorter event-free survival compared with the low STAB1 expression (STAB1low) group in both the TCGA dataset (n = 79; p = 0.0478) and GEO: GSE6891 dataset (n = 187; p = 0.0354). Differential expression analysis between the STAB1high and STAB1low groups revealed that upregulated genes in the STAB1high group were enriched in pathways related to cell adhesion and migration and immune responses. We confirmed that STAB1 suppression inhibits cell growth in KG1a and NB4 leukemia cells. Expression correlation analyses between STAB1 and cancer drug targets suggested that patients in the STAB1low group are more sensitive to the BCL2 inhibitor venetoclax, and we confirmed it in cell lines. In conclusion, we identified STAB1 as a prognostic factor for CN-AML in multiple datasets, explored its underlying mechanism, and provided potential therapeutic indications.

Transcriptome and Regulatory Network Analyses of CD19-CAR-T Immunotherapy for B-ALL.

Chimeric antigen receptor (CAR) T cell therapy has exhibited dramatic anti-tumor efficacy in clinical trials. In this study, we reported the transcriptome profiles of bone marrow cells in four B cell acute lymphoblastic leukemia (B-ALL) patients before and after CD19-specific CAR-T therapy. CD19-CAR-T therapy remarkably reduced the number of leukemia cells, and three patients achieved bone marrow remission (minimal residual disease negative). The efficacy of CD19-CAR-T therapy on B-ALL was positively correlated with the abundance of CAR and immune cell subpopulations, e.g., CD8+ T cells and natural killer (NK) cells, in the bone marrow. Additionally, CD19-CAR-T therapy mainly influenced the expression of genes linked to cell cycle and immune response pathways, including the NK cell mediated cytotoxicity and NOD-like receptor signaling pathways. The regulatory network analyses revealed that microRNAs (e.g., miR-148a-3p and miR-375), acting as oncogenes or tumor suppressors, could regulate the crosstalk between the genes encoding transcription factors (TFs; e.g., JUN and FOS) and histones (e.g., HIST1H4A and HIST2H4A) involved in CD19-CAR-T therapy. Furthermore, many long non-coding RNAs showed a high degree of co-expression with TFs or histones (e.g., FOS and HIST1H4B) and were associated with immune processes. These transcriptome analyses provided important clues for further understanding the gene expression and related mechanisms underlying the efficacy of CAR-T immunotherapy.

Genomic landscape and mutational impacts of recurrently mutated genes in cancers.

BACKGROUND: Cancer genes tend to be highly mutated under positive selection. Better understanding the recurrently mutated genes (RMGs) in cancer is critical for explicating the mechanisms of tumorigenesis and providing vital clues for therapy. Although some studies have investigated functional impacts of RMGs in specific cancer types, a comprehensive analysis of RMGs and their mutational impacts across cancers is still needed. METHODS: We obtained data from The Cancer Genome Atlas (TCGA) and calculated mutation rate of each gene in 31 cancer types. Functional analysis was performed to identify the important signaling pathways and enriched protein types of RMGs. In order to evaluate functional impacts of RMGs, differential expression, survival, and pairwise mutation patterns analyses were performed. RESULTS: Totally, we identified 897 RMGs and 624 of them were specifically mutant in only a single cancer type. Functional analysis demonstrated that these RMGs were enriched in hydrolases, cytoskeletal protein, and pathways like MAPK, cell cycle, PI3K-Akt, ECM receptor interaction, and energy metabolism. The differentially expressed genes potentially affected by the same common RMG showed a relatively low overlap across different cancer types. For the 19 Mucin (MUC) family genes, nine of them were RMGs and four of them (MUC17, MUC5B, MUC4, and MUC16) were common RMGs shared in 8 to 17 cancer types. The results showed that recurrent mutations in MUC genes were significantly associated with better survival prognosis. Only a small part of RMGs was differentially expressed due to their own mutations and most of them were downregulated. In addition, pairwise mutation pattern analysis revealed the high frequency of co-occurred mutations among RMGs in STAD. CONCLUSION: Through the functional analysis of RMGs, we found that six signaling pathways were disrupted in most cancer types and that energy metabolism was abnormal in tumors. The results also revealed a strong correlation between recurrently mutated genes from MUC family and human survival. In addition, gene expression and survival prognosis were associated with different mutation types of RMGs.