Tumor-derived apoptotic extracellular vesicle-mediated intercellular communication promotes metastasis and stemness of lung adenocarcinoma.

Apoptosis has long been recognized as a significant mechanism for inhibiting tumor formation, and a plethora of stimuli can induce apoptosis during the progression and treatment of tumors. Moreover, tumor-derived apoptotic extracellular vesicles (apoEVs) are inevitably phagocytosed by live tumor cells, promoting tumor heterogeneity. Understanding the mechanism by which apoEVs regulate tumor cells is imperative for enhancing our knowledge of tumor metastasis and recurrence. Herein, we conducted a series of in vivo and in vitro experiments, and we report that tumor-derived apoEVs promoted lung adenocarcinoma (LUAD) metastasis, self-renewal and chemoresistance. Mechanistically, we demonstrated that apoEVs facilitated tumor metastasis and stemness by initiating the epithelial-mesenchymal transition program and upregulating the transcription of the stem cell factor SOX2. In addition, we found that ALDH1A1, which was transported by apoEVs, activated the NF-κB signaling pathway by increasing aldehyde dehydrogenase enzyme activity in recipient tumor cells. Furthermore, targeting apoEVs-ALDH1A1 significantly abrogated these effects. Collectively, our findings elucidate a novel mechanism of apoEV-dependent intercellular communication between apoptotic tumor cells and live tumor cells that promotes the formation of cancer stem cell-like populations, and these findings reveal that apoEVs-ALDH1A1 may be a potential therapeutic target and biomarker for LUAD metastasis and recurrence.

SERPINB5 is a prognostic biomarker and promotes proliferation, metastasis and epithelial-mesenchymal transition (EMT) in lung adenocarcinoma.

BACKGROUND: Serine protease inhibitors clade B serpins (SERPINBs) are the largest subclass of protease inhibitors, once thought of as a tumor suppressor gene family. However, some SERPINBs exhibit functions unrelated to the inhibition of catalytic activity. METHODS: The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Gene Set Cancer Analysis (GSCA), and cBioPortal databases were utilized to investigate SERPINBs expression, prognostic correlation, and genomic variation in 33 cancer types. We also conducted a comprehensive transcriptome analysis in multiple lung adenocarcinoma (LUAD) cohorts to reveal the molecular mechanism of SERPINB5 in LUAD. Then, qPCR and immunohistochemistry were used to verify the expression and prognostic value of SERPINB5 in LUAD patients. Furthermore, knockdown and overexpression of SERPINB5 in LUAD cell lines were performed to evaluate cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT). RESULTS: The expression of SERPINB5 was upregulated and demethylated in LUAD, and its abnormally high expression was significantly correlated with poor overall survival (OS). In addition, the expression of SERPINB5 was analyzed to determine its prognostic value in LUAD and confirmed that SERPINB5 was an independent predictor of LUAD in TCGA and GEO cohorts and qPCR validation with 106 clinical samples. At last, A knockdown of SERPINB5 in LUAD cells reduced proliferation, migration, and EMT. Proliferation, migration, and invasion are promoted by the overexpression of SERPINB5. CONCLUSION: Therefore, SERPINB5 has shown potential as a prognostic biomarker for LUAD, and it may become a potential therapeutic target for lung adenocarcinoma.

The independent prognostic effect of marital status on non-small cell lung cancer patients: a population-based study.

Background: Previous studies had demonstrated that marital status was an independent prognostic factor in multiple cancers. However, the impact of marital status on non-small cell lung cancer (NSCLC) patients was still highly controversial. Method: All NSCLC patients diagnosed between 2010-2016 were selected from the Surveillance, Epidemiology and End Results (SEER) database. To control the confounding effect of related clinicopathological characteristics, propensity score matching (PSM) was conducted between married and unmarried groups. In addition, independent prognostic clinicopathological factors were evaluated via Cox proportional hazard regression. Moreover, nomograms were established based on the clinicopathological characteristics, and the predictive accuracy was assessed by calibration curves. Furthermore, decision curve analysis (DCA) was used to determine the clinical benefits. Results: In total, 58,424 NSCLC patients were enrolled according to the selection criteria. After PSM, 20,148 patients were selected into each group for further analysis. The married group consistently demonstrated significantly better OS and CSS compared to unmarried group [OS median survival (95% CI): 25 (24-26) vs. 22 (21-23) months, p < 0.001; CSS median survival (95% CI): 31 (30-32) vs. 27 (26-28) months, p < 0.001]. Moreover, single patients were associated with the worst OS [median survival (95% CI): 20 (19-22) months] and CSS [median survival (95%CI): 24 (23-25) months] among unmarried subgroups. Besides, unmarried patients had a significantly worse prognosis compared to married patients in both univariate and multivariate Cox proportional hazard regressions. Furthermore, married group was associated with better survival in most subgroups. To predict the 1-, 3- and 5-year OS and CSS probabilities, nomograms were established based on age, race, sex, gender, marital status, histology, grade, TNM stage. The C-index for OS and CSS were 0.759 and 0.779. And the calibration curves showed significant agreement between predictive risk and the observed probability. DCA indicated nomograms had consistently better predict performance. Conclusion: This study demonstrated that unmarried NSCLC patients were associated with significantly worse OS and CSS compared to married NSCLC patients. Therefore, unmarried patients need not only closer surveillance, but also more social and family support, which may improve patients' adherence and compliance, and eventually improve the survival.

Intrinsic Immunogenic Tumor Cell Death Subtypes Delineate Prognosis and Responsiveness to Immunotherapy in Lung Adenocarcinoma.

Recent studies have highlighted the combination of activation of host immunogenic cell death (ICD) and tumor-directed cytotoxic strategies. However, overall multiomic analysis of the intrinsic ICD property in lung adenocarcinoma (LUAD) has not been performed. Therefore, the aim of this study was to develop an ICD-based risk scoring system to predict overall survival (OS) and immunotherapeutic efficacy in patients. In our study, both weighted gene co-expression network analysis (WGCNA) and LASSO-Cox analysis were utilized to identify ICDrisk subtypes (ICDrisk). Moreover, we identify genomic alterations and differences in biological processes, analyze the immune microenvironment, and predict the response to immunotherapy in patients with pan-cancer. Importantly, immunogenicity subgroup typing was performed based on the immune score (IS) and microenvironmental tumor neoantigens (meTNAs). Our results demonstrate that ICDrisk subtypes were identified based on 16 genes. Furthermore, high ICDrisk was proved to be a poor prognostic factor in LUAD patients and indicated poor efficacy of immune checkpoint inhibitor (ICI) treatment in patients with pan-cancer. The two ICDrisk subtypes displayed distinct clinicopathologic features, tumor-infiltrating immune cell patterns, and biological processes. The ISlowmeTNAhigh subtype showed low intratumoral heterogeneity (ITH) and immune-activated phenotypes and correlated with better survival than the other subtypes within the high ICDrisk group. This study suggests effective biomarkers for the prediction of OS in LUAD patients and immunotherapeutic response across Pan-cancer and contributes to enhancing our understanding of intrinsic immunogenic tumor cell death.

Identification of A novel anoikis-related genes-based signature for non-small cell lung cancer.

The prognostic value of anoikis in NSCLC and its mechanism in tumorigenesis and progress have not been fully elucidated. This study aimed to reveal the correlation between anoikis-related genes (ARGs) and tumor prognosis, to reveal molecular and immune features, and to evaluate the anticancer drug sensitivity and the efficacy of immunotherapy of NSCLC. ARGs were selected from both the GeneCards and Harmonizome databases and then were intersected with the Cancer Genome Atlas (TCGA) database by differential expression analysis, followed by functional analysis of the target ARGs. An ARGs-based prognostic signature was constructed using LASSO (least absolute shrinkage and selection operator) Cox regression analysis; Kaplan-Meier analysis, univariant and multivariant Cox analysis were used to validate the value of this model in NSCLC prognosis. Differential analyses on molecular and immune landscapes were applied in the model. Anticancer drug sensitivity and efficacy in immune-checkpoint inhibitors (ICI) therapy were analyzed. A total of 509 ARGs and 168 differentially expressed ARGs in NSCLC were generated. Functional analysis revealed enrichment in extracolonic apoptotic signaling pathway, collagen-containing ECM, and integrin binding, and indicated an association with the PI3K-Akt signaling pathway. Subsequently, a 14-genes signature was generated. The high-risk group had a worse prognosis, with higherM0 and M2 macrophage infiltration, and fewer CD8 T-cells and T follicular helper (TFH) cells. The high-risk group had higher expression of immune checkpoint genes, HLA-I genes, and higher TIDE scores than the low-risk group, leading to less benefit of ICI therapy. Additionally, an Immunohistochemical staining comparison revealed that FADD was highly expressed in tumor tissue, compared to normal tissue, consistent with the previous results.

Ten-year trends of the clinicopathological characteristics, surgical treatments and survival outcomes of operable lung cancer patients in monocenter: a retrospective cohort study.

Background: Lung cancer is one of the cancers with the highest morbidity and mortality. During the last decade, the trends of clinical characteristics, surgical treatments and survival of lung cancer patients in China have remained unclear. Methods: All lung cancer patients operated on from 2011 to 2020 were identified in a prospectively maintained database of Sun Yat-sen University Cancer Center. Results: A total of 7,800 lung cancer patients were included in this study. Within the past 10 years, the average age at diagnosis of the patients remained stable, the proportion of asymptomatic, female and nonsmoking patients increased, and the average tumor size decreased from 3.766 to 2.300 cm. In addition, the proportion of early stage and adenocarcinoma increased, while that of squamous cell carcinoma decreased. Among the patients, the proportion of patients having video-assisted thoracic surgery increased. More than 80% of the patients underwent lobectomy and systematic nodal dissection over the 10 years. Additionally, both the average postoperative length of stay and 1-, 3-, and 6-month postoperative mortality decreased. Moreover, the 1-, 3-, and 5-year overall survival (OS) rates of all the operable patients increased from 89.8, 73.9, and 63.8% to 99.6, 90.7, and 80.8%, respectively. The 5-year OS rates of the patients with stage I, II, and III lung cancer were 87.6, 79.9, and 59.9%, respectively, which were higher than those in other published data. Conclusion: There were significant changes in the clinicopathological characteristics, surgical treatments and survival outcomes of the patients with operable lung cancer from 2011 to 2020.

A tumor microenvironment gene set-Based prognostic signature for non-small-cell lung cancer.

Background: The tumor microenvironment (TME) is involved in the development and progression of lung carcinomas. A deeper understanding of TME landscape would offer insight into prognostic biomarkers and potential therapeutic targets investigation. To this end, we aimed to identify the TME components of lung cancer and develop a prognostic signature to predict overall survival (OS). Methods: Expression data was retrieved from The Cancer Genome Atlas (TCGA) database and differentially expressed TME-related genes were calculated between tumor and normal tissues. Then nonnegative matrix factorization (NMF) clustering was used to identify two distinct subtypes. Results: Our analysis yielded a gene panel consisting of seven TME-related genes as candidate signature set. With this panel, our model showed that the high-risk group experienced a shorter survival time. This model was further validated by an independent cohort with data from Gene Expression Omnibus (GEO) database (GSE50081 and GSE13213). Additionally, we integrated the clinical factors and risk score to construct a nomogram for predicting prognosis. Our data suggested less immune cells infiltration but more fibroblasts were found in tumor tissues derived from patients at high-risk and those patients exhibited a worse immunotherapy response. Conclusion: The signature set proposed in this work could be an effective model for estimating OS in lung cancer patients. Hopefully analysis of the TME could have the potential to provide novel diagnostic, prognostic and therapeutic opportunities.

Novel Risk Prediction Model to Determine Adverse Heart Failure Outcomes in Arrhythmogenic Right Ventricular Cardiomyopathy.

Background Patients with arrhythmogenic right ventricular cardiomyopathy are at risk for life-threatening ventricular tachyarrhythmias, but progressive heart failure (HF) may occur in later stages of disease. This study aimed to characterize potential risk predictors and develop a model for individualized assessment of adverse HF outcomes in arrhythmogenic right ventricular cardiomyopathy. Methods and Results Longitudinal and observational cohorts with 290 patients with arrhythmogenic right ventricular cardiomyopathy from the Fuwai Hospital in Beijing, China, and 99 patients from the University Heart Center in Zurich, Switzerland, with follow-up data were studied. The primary end point of the study was heart transplantation or death attributable to HF. The model was developed by Cox regression analysis for predicting risk and was internally validated. During 4.92±3.03 years of follow-up, 48 patients reached the primary end point. The determinants of the risk prediction model were left ventricular ejection fraction, serum creatinine levels, moderate-to-severe tricuspid regurgitation, and atrial fibrillation. Implantable cardioverter-defibrillators did not reduce the occurrence of adverse HF outcomes. Conclusions A novel risk prediction model for arrhythmogenic right ventricular cardiomyopathy has been developed using 2 large and well-established cohorts, incorporating common clinical parameters such as left ventricular ejection fraction, serum creatinine levels, tricuspid regurgitation, and atrial fibrillation, which can identify patients who are at risk for terminal HF events, and may guide physicians to assess individualized HF risk and to optimize management strategies.

Mutation-Derived Long Noncoding RNA Signature Predicts Survival in Lung Adenocarcinoma.

Background: Genomic instability is one of the representative features of cancer evolution. Recent research has revealed that long noncoding RNAs (lncRNAs) play a critical role in maintaining genomic instability. Our work proposed a gene signature (GILncSig) based on genomic instability-derived lncRNAs to probe the possibility of lncRNA signatures as an index of genomic instability, providing a potential new approach to identify genomic instability-related cancer biomarkers. Methods: Lung adenocarcinoma (LUAD) gene expression data from an RNA-seq FPKM dataset, somatic mutation information and relevant clinical materials were downloaded from The Cancer Genome Atlas (TCGA). A prognostic model consisting of genomic instability-related lncRNAs was constructed, termed GILncSig, to calculate the risk score. We validated GILncSig using data from the Gene Expression Omnibus (GEO) database. In this study, we used R software for data analysis. Results: Through univariate and multivariate Cox regression analyses, five genomic instability-associated lncRNAs (LINC01671, LINC01116, LINC01214, lncRNA PTCSC3, and LINC02555) were identified. We constructed a lncRNA signature (GILncSig) related to genomic instability. LUAD patients were classified into two risk groups by GILncSig. The results showed that the survival rate of LUAD patients in the low-risk group was higher than that of those in the high-risk group. Then, we verified GILncSig in the GEO database. GILncSig was associated with the genomic mutation rate of LUAD. We also used GILncSig to divide TP53 mutant-type patients and TP53 wild-type patients into two groups and performed prognostic analysis. The results suggested that compared with TP53 mutation status, GILncSig may have better prognostic significance. Conclusions: By combining the lncRNA expression profiles associated with somatic mutations and the corresponding clinical characteristics of LUAD, a lncRNA signature (GILncSig) related to genomic instability was established.

Analysis of the tumor immune environment identifies an immune gene set-based prognostic signature in non-small cell lung cancer.

BACKGROUND: The tumor immune environment plays a critical role in lung cancer initiation and prognosis. Therefore, understanding how the tumor immune environment impacts the overall survival (OS) of patients with advanced lung cancer post immunotherapy is of great importance. In this article, we aimed to identify the immune components of lung cancer and develop an immune prognostic signature to predict OS. METHODS: Differentially expressed immune-related genes were calculated between tumor and normal tissues using expression data from The Cancer Genome Atlas (TCGA) database. Then univariate Cox regression analysis was conducted to select prognosis-related genes and the prognostic risk model was constructed by multivariate Cox regression analysis. Patient risk scores were calculated, and a clinical correlation analysis was performed within the risk model. In addition, immune cell infiltration patterns were identified to find the immune cell subtypes related to prognosis. RESULTS: A gene model consisting of 12 immune-related genes was used as our signature. The model showed that the high-risk group experienced a shorter survival time, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.733. High-risk immune genes, such as S100 calcium binding protein A16 (S100A16) and angiopoietin-like 4 (ANGPTL4), were associated with more malignant clinical manifestations. Further, we discovered that extensive infiltration of B cells, dendritic cells, and mast cells indicated a favorable prognosis. CONCLUSIONS: The signature developed in this paper could be an effective model for estimating OS in lung cancer patients, and the immune cell infiltration analysis of the tumor immune microenvironment could shed light on more effective treatment in clinical practice.

Role of Senescence and Aging in SARS-CoV-2 Infection and COVID-19 Disease.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global pandemic associated with substantial morbidity and mortality worldwide, with particular risk for severe disease and mortality in the elderly population. SARS-CoV-2 infection is driven by a pathological hyperinflammatory response which results in a dysregulated immune response. Current advancements in aging research indicates that aging pathways have fundamental roles in dictating healthspan in addition to lifespan. Our review discusses the aging immune system and highlights that senescence and aging together, play a central role in COVID-19 pathogenesis. In our review, we primarily focus on the immune system response to SARS-CoV-2 infection, the interconnection between severe COVID-19, immunosenescence, aging, vaccination, and the emerging problem of Long-COVID. We hope to highlight the importance of identifying specific senescent endotypes (or "sendotypes"), which can used as determinants of COVID-19 severity and mortality. Indeed, identified sendotypes could be therapeutically exploited for therapeutic intervention. We highlight that senolytics, which eliminate senescent cells, can target aging-associated pathways and therefore are proving attractive as potential therapeutic options to alleviate symptoms, prevent severe infection, and reduce mortality burden in COVID-19 and thus ultimately enhance healthspan.

The Independent Prognostic Effect of Lymph Node Dissection on Patients With Stage IA NSCLC With Different T Stages.

Background: Currently, the extent of lymph node evaluation necessary for patients with early-stage non-small-cell lung cancer (NSCLC) remains controversial according to the latest ESMO and NCCN guidelines. In this study, we aimed to evaluate the survival effect of different numbers of lymph nodes examined (LNE) and regions of lymph nodes removed (LNR) in patients with stage IA NSCLC. Method: All patients with stage IA NSCLC undergoing lobectomy or bilobectomy were selected from the surveillance, epidemiology, and end results (SEER) database. The number of LNE and LNR were stratified into 4 groups (0, 1-2, 3-8, and ≥9 lymph nodes) and 3 groups (0, 1-3, and ≥4 regions) respectively. Additionally, the survival curves of overall survival (OS) and cancer-specific survival (CSS) were plotted and compared with the Kaplan-Meier method and log-rank test. Independent prognostic clinicopathological factors were evaluated via Cox proportional hazard regression and subgroup analysis. Results: Totally, 12,490 patients with stage IA NSCLC were enrolled in our study. Patients with ≥9 LNE and ≥4 LNR in both the T1b and T1c stages consistently demonstrated the significantly best OS and CSS outcomes. In the multivariate analysis, patients with ≥9 LNE consistently had a significantly better CSS [hazards ration (HR) (95% CI):0.539 (0.438-0.663)], and those with ≥4 LNR consistently had a significantly better OS [HR (95% CI):0.678 (0.476-0.966)]. Furthermore, ≥9 LNE and ≥4 LNR were associated with better survival in most subgroups. Conclusion: This study demonstrated that ≥9 LNE and ≥4 LNR are highly recommended for stage IA2 and stage IA3 patients but optional for stage IA1 patients.

Resolving the intertwining of inflammation and fibrosis in human heart failure at single-cell level.

Inflammation and fibrosis are intertwined mechanisms fundamentally involved in heart failure. Detailed deciphering gene expression perturbations and cell-cell interactions of leukocytes and non-myocytes is required to understand cell-type-specific pathology in the failing human myocardium. To this end, we performed single-cell RNA sequencing and single T cell receptor sequencing of 200,615 cells in both human dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) hearts. We sampled both lesion and mild-lesion tissues from each heart to sequentially capture cellular and molecular alterations to different extents of cardiac fibrosis. By which, left (lesion) and right ventricle (mild-lesion) for DCM hearts were harvest while infarcted (lesion) and non-infarcted area (mild-lesion) were dissected from ICM hearts. A novel transcription factor AEBP1 was identified as a crucial cardiac fibrosis regulator in ACTA2+ myofibroblasts. Within fibrotic myocardium, an infiltration of a considerable number of leukocytes was witnessed, especially cytotoxic and exhausted CD8+ T cells and pro-inflammatory CD4+ T cells. Furthermore, a subset of tissue-resident macrophage, CXCL8hiCCR2+HLA-DRhi macrophage was particularly identified in severely fibrotic area, which interacted with activated endothelial cell via DARC, that potentially facilitate leukocyte recruitment and infiltration in human heart failure.

The role of senescence in the pathogenesis of atrial fibrillation: A target process for health improvement and drug development.

Cellular senescence is a state of growth arrest that occurs after cells encounter various stresses. Senescence contributes to tumour suppression, embryonic development, and wound healing. It impacts on the pathology of various diseases by secreting inflammatory chemokines, immune modulators and other bioactive factors. These secretory biosignatures ultimately cause inflammation, tissue fibrosis, immunosenescence and many ageing-related diseases such as atrial fibrillation (AF). Because the molecular mechanisms underpinning AF development remain unclear, current treatments are suboptimal and have serious side effects. In this review, we summarize recent results describing the role of senescence in AF. We propose that senescence factors induce AF and have a causative role. Hence, targeting senescence and its secretory phenotype may attenuate AF.

Development and validation of a prediction model for lung adenocarcinoma based on RNA-binding protein.

BACKGROUND: RNA-binding proteins (RBPs) have been found to participate in the development and progression of cancer. This present study aimed to construct a RBP-based prognostic prediction model for lung adenocarcinoma (LUAD). METHODS: RNA sequencing data and corresponding clinical information were acquired from The Cancer Genome Atlas (TCGA) and served as a training set. The prediction model was validated using the dataset in Gene Expression Omnibus (GEO) databases. Univariate and multivariate Cox regression analyses were conducted to identify the RBPs associated with survival. R software (http://www.r-project.org) was used for analysis in this study. RESULTS: Nine hub prognostic RBPs (CIRBP, DARS2, DDX24, GAPDH, LARP6, SNRPE, WDR3, ZC3H12C, ZC3H12D) were identified by univariate Cox regression analysis and multivariate Cox regression analysis. Using a risk score based on the nine-hub RBP model, we separated the LUAD patients into a low-risk group and a high-risk group. The outcomes revealed that patients in the high-risk group had poorer survival than those in the low-risk group. This signature was validated in the GEO database. Further study revealed that the risk score can be an independent prognostic biomarker for LUAD. A nomogram based on the nine hub RBPs was built to quantitatively predict the prognosis of LUAD patients. CONCLUSIONS: Our nine-gene signature model could be used as a marker to predict the prognosis of LUAD and has potential for use in treatment individualization.

Single-cell reconstruction of the adult human heart during heart failure and recovery reveals the cellular landscape underlying cardiac function.

Owing to the prevalence and high mortality rates of cardiac diseases, a more detailed characterization of the human heart is necessary; however, this has been largely impeded by the cellular diversity of cardiac tissue and limited access to samples. Here, we show transcriptome profiling of 21,422 single cells-including cardiomyocytes (CMs) and non-CMs (NCMs)-from normal, failed and partially recovered (left ventricular assist device treatment) adult human hearts. Comparative analysis of atrial and ventricular cells revealed pronounced inter- and intracompartmental CM heterogeneity as well as compartment-specific utilization of NCM cell types as major cell-communication hubs. Systematic analysis of cellular compositions and cell-cell interaction networks showed that CM contractility and metabolism are the most prominent aspects that are correlated with changes in heart function. We also uncovered active engagement of NCMs in regulating the behaviour of CMs, exemplified by ACKR1+-endothelial cells, injection of which preserved cardiac function after injury. Beyond serving as a rich resource, our study provides insights into cell-type-targeted intervention of heart diseases.

The homozygous variant c.245G > A/p.G82D in PNPLA2 is associated with arrhythmogenic cardiomyopathy phenotypic manifestations.

Arrhythmogenic cardiomyopathy (ACM) is a familial cardiomyopathy featured by fibrofatty replacement of cardiomyocytes. Responsible genetic factors are not discernible in approximately one-third of ACM probands. To investigate this further, we performed whole genome sequencing in 14 mutation-negative ACM probands who underwent cardiac transplantation, and we identified one ACM proband with a rare homozygous missense variant in PNPLA2 (c.245G > A, p.G82D), a rate-limiting enzyme that hydrolyzes triglycerides into fatty acids and diacylglycerol. Bioinformatic analysis suggested that this missense variant may lead to loss of function and therefore impair lipid catabolism. Genetic screening in this proband's family also inferred that the homozygous variant cosegregated with disease. To validate the pathogenicity of this variant and confirm its association with ACM, we established a knockin mouse model carrying the orthologous human homozygous PNPLA2 variant. Interestingly, mice with the homozygous variant presented with arrhythmias and significant cardiac dysfunction at 12 weeks, whereas heterozygous mice were not affected. Moreover, those homozygous mice suffered sudden death and/or heart failure by the age of 14 weeks. Pathological examination showed that extensive lipogenesis in cardiomyocytes and cardiac fibrosis were prominent in the myocardium. Herein, our data demonstrated that the homozygous missense variant PNPLA2 (c.245G > A, p.G82D) associated with a recessive form of ACM.

Outcome and Pathological Characteristics of Primary Malignant Cardiac Tumors.

The literature on malignant cardiac tumors is relatively limited because they are rare, especially among the Chinese population. We analyzed 14 patients diagnosed with malignant cardiac tumors in Fuwai Hospital and present the results of surgical treatments on the tumors. The mean age at tumor diagnosis was 47 years in a male-dominated cohort. There was a high frequency of pericardial effusion and coronary artery involvement in our group. We compared the survival times of patients who received different treatments and found that surgery improved prognosis of tumors, especially for patients who underwent orthotopic heart transplantation.

Recessive variants in plakophilin-2 contributes to early-onset arrhythmogenic cardiomyopathy with severe heart failure.

AIMS: Plakophilin-2 (PKP2) is the most prevalent mutant gene causing arrhythmogenic cardiomyopathy (ACM) and PKP2 carriers are prone to develop ventricular arrhythmic events. The objective of this study is to use integrated analysis of whole genome sequencing (WGS) and transcriptome sequencing (RNAseq) to identify deep intronic and/or coding variants that cause aberrant splicing events in ACM patients, and hence, to test the hypothesis that recessive variants in PKP2 may lead to early-onset ACM with severe heart failure. METHODS AND RESULTS: We performed WGS and RNAseq in 27 heart transplanted ACM patients. By integrated analysis of WGS/RNAseq, we discovered that two patients with PKP2 variants were affected in recessive pattern. One patient had aberrant splicing arising from two intronic variants that led to exon skipping and exon retention. We screened three additional recessive PKP2 variants in 47 non-heart transplanted ACM patients. We compared the clinical characteristics of recessive PKP2 (n = 5) and heterozygous PKP2 carriers (n = 18), and found that recessive PKP2 variant carriers all had early-onset ACM with left ventricular dysfunction. We examined truncating PKP2 variants in explanted hearts and confirmed that truncated PKP2 was not translated. Moreover, the morphology of intercalated disc in recessive PKP2 variants carriers was similar to normal heart suggesting little intercalated disc remodelling. CONCLUSION: By using combined implementation of WGS RNAseq, we were able to demonstrate that recessive variants in PKP2 may contribute to early-onset ACM with severe heart failure. These findings may play a role in risk stratification of ACM based on genetic testing in clinical practice.