Annotation of cell types (ACT): a convenient web server for cell type annotation.

BACKGROUND: The advancement of single-cell sequencing has progressed our ability to solve biological questions. Cell type annotation is of vital importance to this process, allowing for the analysis and interpretation of enormous single-cell datasets. At present, however, manual cell annotation which is the predominant approach remains limited by both speed and the requirement of expert knowledge. METHODS: To address these challenges, we constructed a hierarchically organized marker map through manually curating over 26,000 cell marker entries from about 7000 publications. We then developed WISE, a weighted and integrated gene set enrichment method, to integrate the prevalence of canonical markers and ordered differentially expressed genes of specific cell types in the marker map. Benchmarking analysis suggested that our method outperformed state-of-the-art methods. RESULTS: By integrating the marker map and WISE, we developed a user-friendly and convenient web server, ACT ( http://xteam.xbio.top/ACT/ or http://biocc.hrbmu.edu.cn/ACT/ ), which only takes a simple list of upregulated genes as input and provides interactive hierarchy maps, together with well-designed charts and statistical information, to accelerate the assignment of cell identities and made the results comparable to expert manual annotation. Besides, a pan-tissue marker map was constructed to assist in cell assignments in less-studied tissues. Applying ACT to three case studies showed that all cell clusters were quickly and accurately annotated, and multi-level and more refined cell types were identified. CONCLUSIONS: We developed a knowledge-based resource and a corresponding method, together with an intuitive graphical web interface, for cell type annotation. We believe that ACT, emerging as a powerful tool for cell type annotation, would be widely used in single-cell research and considerably accelerate the process of cell type identification.

Application of Model-Building Based on Arterial Ultrasound Imaging Evaluation to Predict CHD Risk.

Objective: Atherosclerotic is a chronic systemic disease that may occur in multiple vascular beds, including the carotid arteries, renal arteries, lower limb arteries, and cerebral vessels. Coronary atherosclerosis shares similar risk factors, pathogenesis, and pathophysiological basis with the atherosclerotic lesions of arteries at these sites. Arterial ultrasound assessment data were used to explore the correlation of atherosclerotic disease with CHD lesions and their severity and the number of lesion branches, as well as to evaluate its value in predicting CHD risk, in combination with traditional risk factors. Methods: A total of 363 inpatients with suspected CHD in the Department of Cardiology of the First Hospital of Harbin Medical University from November 2017 to June 2021 were selected. Patient clinical data, blood biochemical examination results, and ultrasound examination of neck vessels, abdominal arteries, and limb arteries were collected to obtain atherosclerosis assessment data. We then compared the differences between the CHD group and the control group, analyzed their correlation with CHD lesions and severity and the number of lesion branches, and evaluated the correlation with the coronary Gensini score. After adjustment for traditional risk factors, logistic regression was applied to analyze the relationship between arterial ultrasound assessment data and the risk of CHD. In addition, ROC plots were drawn to evaluate the risk of arterial ultrasound assessment data, combined with traditional risk factors, to predict CHD. Results: With regard to abnormal blood biochemical index values, differences in lipids, HDL-C, FIB, CK-MB, hs-cTnI, BNP, and GGT were found between the CHD group and the control group. Carotid plaque count, abdominal aortic flow velocity, inferior mesenteric artery flow velocity, classification of the number of stenotic branches of abdominal aortic branch arteries, lower-extremity-artery plaque count, degree of lower-extremity-artery stenosis, and lower-extremity-artery AS were risk factors for arterial ultrasound assessment data of CHD. Carotid plaque count, carotid artery AS, inferior mesenteric artery flow velocity, abdominal aortic flow velocity, abdominal aortic plaque count, abdominal aortic branch artery stenosis branch classification, lower-extremity-artery plaque count, lower-extremity-artery stenosis branch classification, degree of lower-extremity-artery stenosis, and lower-extremity-artery AS, combined with traditional risk factors, were mostly more effective than traditional risk factor models in predicting CHD, its severity, and the number of branch lesions; moreover, the predictive value was higher. Specifically, carotid plaque count, carotid AS, lower-extremity-artery AS, the degree of stenosis of lower-extremity arteries, and abdominal aortic branch artery stenosis branch classification can be used as predictor variables for CHD risk. Among these variables, the carotid plaque count can be used as an independent predictor of CHD. Conclusion: The incidence of arterial intima-media thickening (IMT), plaques, and stenosis can provide a reference for understanding the pattern of systemic atherogenesis and the distribution of atherosclerosis.

Revealing the functions of clonal driver gene mutations in patients based on evolutionary dependencies.

The clonal mutations in driver genes enable cells to gradually acquire growth advantage in tumor development. Therefore, revealing the functions of clonal driver gene mutations is important. Here, we proposed the method FCMP that considered evolutionary dependencies to analyze the functions of clonal driver gene mutations in a single patient. Applying our method to five cancer types from The Cancer Genome Atlas, we identified specific functions and common functions of clonal driver gene mutations. We found that the clonal driver gene mutations in the same patient played multiple functions. We also found that clonal mutations in the same driver gene performed different functions in different patients. These findings suggested that the clonal driver gene mutations showed strong tumor heterogeneity. In the pan-cancer analysis, the immune-related functions for clonal driver gene mutations were shared by multiple cancer types. In addition, clonal mutations in some driver genes predicted the survival of patients in cancers.

Effect of nitrogen supply on stay-green sorghum in differing post-flowering water regimes.

MAIN CONCLUSION: The expression of stay-green (SG) characteristic in sorghum under water stress was related to N supply. SG genotype performed better than a non-stay-green (NSG) genotype at medium and high N levels. The differences in physiological parameters between SG and NSG genotypes were not significant at low N level and severe water stress. Grain sorghum [Sorghum bicolor (L.) Moench] with stay-green (SG) trait has the potential to produce more biomass and use soil water and nitrogen (N) more efficiently under post-flowering water stress. Previous studies were mostly conducted without N deficiency and more information is needed for interactions among soil N availability, SG genotype, and post-flowering water stress. In this study, the differences in leaf growth and senescence, shoot and root biomass, evapotranspiration (ET), water use efficiency (WUE), leaf photosynthetic responses, and nitrogen use efficiency (NUE) between a SG genotype (BTx642) and a non-stay-green (NSG) genotype (Tx7000) were examined. The two genotypes were grown at three N levels (Low, LN; Medium, MN; High, HN) and under three post-flowering water regimes (No water deficit, ND; Moderate water deficit, MD; Severe water deficit, SD). The genotypic difference was generally significant while it frequently interacted with N levels and water regimes. At medium and high N levels, SG genotype consistently had greater green leaf area, slower senescence rate, more shoot biomass and root biomass, and greater WUE and NUE than the NSG genotype under post-flowering drought. However, differences in several variables (e.g., leaf senescence, ET, WUE and NUE) between genotypes were not significant under SD at LN. At HN and MN, photosynthetic function of SG genotype was better maintained under drought. At LN, SG genotype maintained greater green leaf area but had lower photosynthetic activity than the NSG genotype. Nonetheless, adequate N supply is important for SG genotype under drought and greater root biomass may contribute to greater NUE in SG genotype.

Zeaxanthin promotes browning by enhancing mitochondrial biogenesis through the PKA pathway in 3T3-L1 adipocytes.

Obesity is closely associated with maintaining mitochondrial homeostasis, and mitochondrial dysfunction can lead to systemic lipid metabolism disorders. Zeaxanthin (ZEA) is a kind of carotenoid with potent antioxidant activity and has been reported to promote mitochondrial biogenesis. Nevertheless, the molecular mechanism has not been explained. In this study, we first discovered that ZEA stimulated 3T3-L1 adipocyte browning by increasing the expression of specific markers (Cd137, Tbx1, Sirt1, Cidea, Ucp1, Tmem26, and Cited1), thereby reducing lipid accumulation. Besides, ZEA promoted mitochondrial biogenesis by increasing the expression of PRDM16, UCP1, NRF2, PGC-1α, and SIRT1. Moreover, the uncoupled oxygen consumption rate (OCR) of protons leaked in 3T3-L1 adipocytes was rapidly increased by ZEA treatment, which improved mitochondrial respiration and energy metabolism. Furthermore, we found that ZEA promotes browning by enhancing mitochondrial biogenesis partly through the protein kinase A (PKA) pathway. This study provided new insight into the promotion of browning and mitochondrial biogenesis by ZEA, suggesting that ZEA probably has potential therapeutic effects on obesity.

IDH clonal heterogeneity segregates a subgroup of non-1p/19q codeleted gliomas with unfavourable clinical outcome.

AIMS: Diffuse gliomas (DGs) are classified into three major molecular subgroups following the revised World Health Organisation (WHO) classification criteria based on their IDH mutation and 1p/19q codeletion status. However, substantial biological heterogeneity and differences in the clinical course are apparent within each subgroup, which remain to be resolved. We sought to assess the clonal status of somatic mutations and explore whether additional molecular subgroups exist within DG. METHODS: A computational framework that integrates the variant allele frequency, local copy number and tumour purity was used to infer the clonality of somatic mutations in 876 DGs from The Cancer Genome Atlas (TCGA). We performed an unsupervised cluster analysis to identify molecular subgroups and characterised their clinical and biological significance. RESULTS: DGs showed widespread genetic intratumoural heterogeneity (ITH), with nearly all driver genes harbouring subclonal mutations, even for known glioma initiating event IDH1 (17.1%). Gliomas with subclonal IDH mutation and without 1p/19q codeletion showed shorter overall and disease-specific survival, higher ITH and exhibited differences in genomic patterns, transcript levels and proliferative potential, when compared with IDH clonal mutation and no 1p/19q codeletion gliomas. We defined a refined stratification system based on the current WHO glioma molecular classification, which showed close correlations with patients' clinical outcomes. CONCLUSIONS: For the first time, we integrated the clonal status of somatic mutations into cancer genomic classification and highlighted the necessity of considering IDH clonal architectures in glioma precision stratification.

Revealing the subtyping of non-small cell lung cancer based on genomic evolutionary patterns by multi-region sequencing.

Accurately classifying patients with non-small cell lung cancer (NSCLC) from the perspective of tumor evolution has not been systematically studied to date. Here, we reconstructed phylogenetic relationships of somatic mutations in 100 early NSCLC patients (327 lesions) through reanalyzing the TRACERx data. Based on the genomic evolutionary patterns presented on the phylogenetic trees, we grouped NSCLC patients into three evolutionary subtypes. The phylogenetic trees among three subtypes exhibited distinct branching structures, with one subtype representing branched evolution and another reflecting the early accumulation of genomic variation. However, in the evolutionary pattern of the third subtype, some mutations experienced selective sweeps and were gradually replaced by multiple newly formed subclonal populations. The subtype patients with poor prognosis had higher intra-tumor heterogeneity and subclonal diversity. We combined genomic heterogeneity with clinical phenotypes analysis and found that subclonal expansion results in the progression and deterioration of the tumor. The molecular mechanisms of subtype-specific Early Driver Feature (EDF) genes differed across the evolutionary subtypes, reflecting the characteristics of the subtype itself. In summary, our study provided new insights on the stratification of NSCLC patients based on genomic evolution that can be valuable for us to understand the development of pulmonary tumor profoundly.

Identifying bifurcated paths with differential function impact in glioblastomas evolution.

The evolutionary dynamics of human cancers has been investigated popularly and several bifurcated paths in cancer evolutionary trajectories are revealed to be with differential outcomes and phenotypes. However, whether such bifurcated paths exist in glioblastoma (GBM) remains unclear. In 385 GBM samples, through determining the clonal status of cancer driver events and inferring their temporal order, we constructed a temporal map of evolutionary trajectories at the patient population level. By investigating the differential impact on clinical outcome, we identified four key bifurcated paths, namely, "chromosome 10 copy number loss (ie, 10 loss) → chromosome 19 copy number gain (ie, 19 gain): 10 loss → 13q loss"; "10 loss → 19 gain: 10 loss → 15q loss"; "10 loss → 19 gain: 10 loss → 6q loss" and "10 loss → 19 gain: 10 loss → 16q loss". They formed a core multibranches path, with 10 loss being regarded as the common earliest event followed by 19 gain and four other departure events (13q loss, 15q loss, 6q loss and 16q loss), which may account for their difference in genome instability and patient survival time. Compared to "10 loss → 19 gain", the patients with "10 loss → 13q loss" had higher telomerase activity. Notably, there were obvious discrepancies in immune activity and immune cell infiltration level between patients with "10 loss → 13q/16q loss" and "10 loss → 19 gain", highlighting the bifurcated paths' effect on tumor immune microenvironment. In summary, our study identifies four key bifurcated paths in GBM for the first time, suggesting the feasibility of patient stratification and prognosis prediction based on key bifurcated paths.

Clonal tumor mutations in homologous recombination genes predict favorable clinical outcome in ovarian cancer treated with platinum-based chemotherapy.

OBJECTIVE: Platinum-based chemotherapy remains the first-line treatment for ovarian carcinoma by inducing DNA damage. The therapeutic impact of clonal and subclonal somatic mutations in DNA damage repair (DDR) pathways remains unexplored. METHODS: We performed an integrated analysis to infer the clonality of somatic deleterious mutations in 385 ovarian carcinomas treated with platinum-based chemotherapy. The Kaplan-Meier method was performed for visualization and the differences between survival curves were calculated by log-rank test. Proportional hazards models were used to estimate relative hazards for platinum-free interval (PFI), progression-free survival (PFS) and overall survival (OS). RESULTS: We found that somatic deleterious mutations in DDR pathways exhibited widespread clonal heterogeneity, and that patients with DDR clonal mutations exhibited a "hypermutator phenotype". Clonal somatic mutations in homologous recombination repair (HRR) pathway were significantly associated with better OS (HR = 0.19 (95% CI, 0.06-0.59), P = 0.0044) and PFS (HR = 0.20 (95% CI, 0.08-0.49), P = 0.0005) than HRR wild-type, while HRR subclonal mutations were not associated with prognosis. Moreover, HRR clonal mutations were associated with significantly higher chemotherapy sensitive rate (P = 0.0027) and longer PFI (HR = 0.20 (95% CI, 0.08-0.49), P = 0.0005) than HRR wild-type, while HRR subclonal mutations were not. We validated our findings using an independent cohort of 93 ovarian cancer patients that received platinum-based chemotherapy. CONCLUSIONS: HRR clonal mutations, but not subclonal mutations, were associated with improved survival, chemotherapy response, and genome instability compared with HRR wild-type.

Identification of Dysregulated Competitive Endogenous RNA Networks Driven by Copy Number Variations in Malignant Gliomas.

Gliomas represent 80% of malignant brain tumors. Because of the high heterogeneity, the oncogenic mechanisms in gliomas are still unclear. In this study, we developed a new approach to identify dysregulated competitive endogenous RNA (ceRNA) interactions driven by copy number variation (CNV) in both lower-grade glioma (LGG) and glioblastoma multiforme (GBM). By analyzing genome and transcriptome data from The Cancer Genome Atlas (TCGA), we first found out the protein coding genes and long non-coding RNAs (lncRNAs) significantly affected by CNVs and further determined CNV-driven dysregulated ceRNA interactions by a customized pipeline. We obtained 13,776 CNV-driven dysregulated ceRNA pairs (including 3,954 mRNAs and 306 lncRNAs) in LGG and 262 pairs (including 221 mRNAs and 11 lncRNAs) in GBM, respectively. Our results showed that most of the ceRNA interactions were weakened by CNVs in both LGG and GBM, and many CNV-driven genes shared the same ceRNAs in the dysregulated ceRNA networks. Functional analysis indicated that the CNV-driven ceRNA network involved in some important mechanisms of tumorigenesis, such as cell cycle, p53 signaling pathway and TGF-beta signaling pathway. Further investigation of the ceRNA pairs in the communities from the dysregulated ceRNA network revealed more detailed biological functions related to the oncogenesis of malignant gliomas. Moreover, by exploring the association of CNV-driven ceRNAs with prognosis and histological subtype, we found that the copy number status of MTAP, KLHL9, and ELAVL2 related to the overall survival in LGG and showed high correlation with histological subtype. In conclusion, this study provided new insight into the molecular mechanisms and clinical biomarkers in gliomas.