CLARIFY: cell-cell interaction and gene regulatory network refinement from spatially resolved transcriptomics.

MOTIVATION: Gene regulatory networks (GRNs) in a cell provide the tight feedback needed to synchronize cell actions. However, genes in a cell also take input from, and provide signals to other neighboring cells. These cell-cell interactions (CCIs) and the GRNs deeply influence each other. Many computational methods have been developed for GRN inference in cells. More recently, methods were proposed to infer CCIs using single cell gene expression data with or without cell spatial location information. However, in reality, the two processes do not exist in isolation and are subject to spatial constraints. Despite this rationale, no methods currently exist to infer GRNs and CCIs using the same model. RESULTS: We propose CLARIFY, a tool that takes GRNs as input, uses them and spatially resolved gene expression data to infer CCIs, while simultaneously outputting refined cell-specific GRNs. CLARIFY uses a novel multi-level graph autoencoder, which mimics cellular networks at a higher level and cell-specific GRNs at a deeper level. We applied CLARIFY to two real spatial transcriptomic datasets, one using seqFISH and the other using MERFISH, and also tested on simulated datasets from scMultiSim. We compared the quality of predicted GRNs and CCIs with state-of-the-art baseline methods that inferred either only GRNs or only CCIs. The results show that CLARIFY consistently outperforms the baseline in terms of commonly used evaluation metrics. Our results point to the importance of co-inference of CCIs and GRNs and to the use of layered graph neural networks as an inference tool for biological networks. AVAILABILITY AND IMPLEMENTATION: The source code and data is available at https://github.com/MihirBafna/CLARIFY.

TedSim: temporal dynamics simulation of single-cell RNA sequencing data and cell division history.

Recently, lineage tracing technology using CRISPR/Cas9 genome editing has enabled simultaneous readouts of gene expressions and lineage barcodes, which allows for the reconstruction of the cell division tree and makes it possible to reconstruct ancestral cell types and trace the origin of each cell type. Meanwhile, trajectory inference methods are widely used to infer cell trajectories and pseudotime in a dynamic process using gene expression data of present-day cells. Here, we present TedSim (single-cell temporal dynamics simulator), which simulates the cell division events from the root cell to present-day cells, simultaneously generating two data modalities for each single cell: the lineage barcode and gene expression data. TedSim is a framework that connects the two problems: lineage tracing and trajectory inference. Using TedSim, we conducted analysis to show that (i) TedSim generates realistic gene expression and barcode data, as well as realistic relationships between these two data modalities; (ii) trajectory inference methods can recover the underlying cell state transition mechanism with balanced cell type compositions; and (iii) integrating gene expression and barcode data can provide more insights into the temporal dynamics in cell differentiation compared to using only one type of data, but better integration methods need to be developed.

The effect of dietary carbohydrate and calorie restriction on weight and metabolic health in overweight/obese individuals: a multi-center randomized controlled trial.

BACKGROUND: Both low-carbohydrate (LC) and calorie-restricted (CR) diets have been shown to have metabolic benefits. However, the two regimens have yet to be thoroughly compared. We conducted a 12-week randomized trial to compare the effects of these diets separately and in combination on both weight loss and metabolic risk factors in overweight/obese individuals. METHODS: A total of 302 participants were randomized to LC diet (n = 76), CR diet (n = 75), LC + CR diet (n = 76), or normal control (NC) diet (n = 75) using a computer-based random number generator. The primary outcome was the change in body mass index (BMI). The secondary outcomes included body weight, waist circumference, waist-to-hip ratio, body fat, and metabolic risk factors. All participants attended health education sessions during the trial. RESULTS: A total of 298 participants were analyzed. BMI change over 12 weeks was - 0.6 (95% CI, - 0.8 to - 0.3) kg/m2 in NC, - 1.3 (95% CI, - 1.5 to - 1.1) kg/m2 in CR, - 2.3 (95% CI, - 2.6 to - 2.1) kg/m2 in LC, and - 2.9 (95% CI, - 3.2 to - 2.6) kg/m2 in LC + CR. LC + CR diet was more effective than LC or CR diet alone at reducing BMI (P = 0.001 and P < 0.001, respectively). Furthermore, compared with the CR diet, the LC + CR diet and LC diet further reduced body weight, waist circumference, and body fat. Serum triglycerides were significantly reduced in the LC + CR diet group compared with the LC or CR diet alone. Plasma glucose, homeostasis model assessment of insulin resistance, and cholesterol concentrations (total, LDL, and HDL) did not change significantly between the groups during the 12-week intervention. CONCLUSIONS: The reduction of carbohydrate intake without restricting caloric intake is more potent to achieve weight loss over 12 weeks when compared to a calorie-restricted diet in overweight/obese adults. The combination of restricting carbohydrate and total calorie intake may augment the beneficial effects of reducing BMI, body weight, and metabolic risk factors among overweight/obese individuals. TRIAL REGISTRATION: The study was approved by the institutional review board of Zhujiang Hospital of Southern Medical University and registered at the China Clinical Trial Registration Center (registration number: ChiCTR1800015156).

The association of FGF-21 with the risk of newly diagnosed type-2 diabetes mellitus: a cross-sectional study in Southern China.

BACKGROUND: This study investigated the relationship between fibroblast growth factor 21 (FGF-21) and newly diagnosed type-2 diabetes mellitus (T2DM). METHODS: In this cross-sectional study, FGF-21 and T2DM risk were analyzed using restricted cubic splines with univariate or multivariate logistic regression analysis. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated via logistic regression analysis. Cluster and subgroup analyses were conducted to evaluate the associations between FGF-21 and diabetes in different subpopulations. Nomograms and ROC curves were used to explore the clinical utility of FGF-21 in the diabetes assessment model. RESULTS: High levels of FGF-21 were significantly associated with a high risk of T2DM after adjusting for confounding factors in both the total population and subpopulations (P for trend < 0.001). In the total population, the ORs of diabetes with increasing FGF-21 quartiles were 1.00 (reference), 1.24 (95% CI 0.56-2.80; quartile 2), 2.47 (95% CI 1.18-5.33; quartile 3), and 3.24 (95% CI 1.53-7.14; quartile 4) in Model 4 (P < 0.001), and the trend was consistent in different subpopulations. In addition, compared with the model constructed with conventional noninvasive indicators, the AUC of the model constructed by adding FGF-21 was increased from 0.668 (95% CI: 0.602-0.733) to 0.715 (95% CI: 0.654-0.777), indicating that FGF-21 could significantly improve the risk-assessment efficiency of type-2 diabetes. CONCLUSION: This study demonstrated that a high level of circulating FGF-21 was positively correlated with diabetes, and levels of FGF-21 could be an important biomarker for the assessment of diabetes risk.

The relationship between the CUN-BAE body fatness index and incident diabetes: a longitudinal retrospective study.

BACKGROUND: The Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) index has been recommended as an ideal indicator of body fat and exhibited significant correlation with cardiometabolic risk factors. However, whether the CUN-BAE index correlates with incident diabetes in Asian populations is unknown. Therefore, this longitudinal study was designed to evaluate the association between baseline CUN-BAE index and type 2 diabetes mellitus (T2DM). METHODS: This retrospective longitudinal study involved 15,464 participants of 18-79 years of age in the NAGALA (NAfld in the Gifu Area Longitudinal Analysis) study over the period of 2004-2015. Cox proportional hazards regression was performed to test the relationship between the baseline CUN-BAE index and diabetes incidence. Further stratification analysis was conducted to ensure that the results were robust. The diagnostic utility of the CUN-BAE index was tested by the receiver operating characteristic (ROC) curve. RESULTS: Over the course of an average follow-up of 5.4 years, 373 (2.41%) participants developed diabetes. A higher diabetes incidence was associated with higher CUN-BAE quartiles (P for trend< 0.001). Each 1 unit increase in CUN-BAE index was associated with a 1.08-fold and 1.14-fold increased risk of diabetes after adjustment for confounders in males and females, respectively (both P < 0.001). Stratification analysis demonstrated a consistent positive correlation between baseline CUN-BAE and diabetes incidence. Moreover, based on ROC analysis, CUN-BAE exhibited a better capacity for diabetes prediction than both body mass index (BMI) and waist circumference (WC) in both sexes. CONCLUSIONS: The baseline CUN-BAE level was independently related to the incidence of diabetes. Increased adiposity determined by CUN-BAE could be used as a strong nonlaboratory predictor of incident diabetes in clinical practice.

Maximum likelihood reconstruction of ancestral networks by integer linear programming.

MOTIVATION: The study of the evolutionary history of biological networks enables deep functional understanding of various bio-molecular processes. Network growth models, such as the Duplication-Mutation with Complementarity (DMC) model, provide a principled approach to characterizing the evolution of protein-protein interactions (PPIs) based on duplication and divergence. Current methods for model-based ancestral network reconstruction primarily use greedy heuristics and yield sub-optimal solutions. RESULTS: We present a new Integer Linear Programming (ILP) solution for maximum likelihood reconstruction of ancestral PPI networks using the DMC model. We prove the correctness of our solution that is designed to find the optimal solution. It can also use efficient heuristics from general-purpose ILP solvers to obtain multiple optimal and near-optimal solutions that may be useful in many applications. Experiments on synthetic data show that our ILP obtains solutions with higher likelihood than those from previous methods, and is robust to noise and model mismatch. We evaluate our algorithm on two real PPI networks, with proteins from the families of bZIP transcription factors and the Commander complex. On both the networks, solutions from our ILP have higher likelihood and are in better agreement with independent biological evidence from other studies. AVAILABILITY AND IMPLEMENTATION: A Python implementation is available at https://bitbucket.org/cdal/network-reconstruction. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CD4+ and CD8+ cytotoxic T lymphocytes may induce mesenchymal cell apoptosis in IgG4-related disease.

BACKGROUND: IgG4-related disease (IgG4-RD) is an immune-mediated fibrotic disorder that has been linked to CD4+ cytotoxic T lymphocytes (CD4+CTLs). The effector phenotype of CD4+CTLs and the relevance of both CD8+ cytotoxic T lymphocytes (CD8+CTLs) and apoptotic cell death remain undefined in IgG4-RD. OBJECTIVE: We sought to define CD4+CTL heterogeneity, characterize the CD8+CTL response in the blood and in lesions, and determine whether enhanced apoptosis may contribute to the pathogenesis of IgG4-RD. METHODS: Blood analyses were undertaken using flow cytometry, cell sorting, transcriptomic analyses at the population and single-cell levels, and next-generation sequencing for the TCR repertoire. Tissues were interrogated using multicolor immunofluorescence. Results were correlated with clinical data. RESULTS: We establish that among circulating CD4+CTLs in IgG4-RD, CD27loCD28loCD57hi cells are the dominant effector subset, exhibit marked clonal expansion, and differentially express genes relevant to cytotoxicity, activation, and enhanced metabolism. We also observed prominent infiltration of granzyme A-expressing CD8+CTLs in disease tissues and clonal expansion in the blood of effector/memory CD8+ T cells with an activated and cytotoxic phenotype. Tissue studies revealed an abundance of cells undergoing apoptotic cell death disproportionately involving nonimmune, nonendothelial cells of mesenchymal origin. Apoptotic cells showed significant upregulation of HLA-DR. CONCLUSIONS: CD4+CTLs and CD8+CTLs may induce apoptotic cell death in tissues of patients with IgG4-RD with preferential targeting of nonendothelial, nonimmune cells of mesenchymal origin.

Serum macrophage inhibitory cytokine-1 as a clinical marker for non-small cell lung cancer.

The aim of this study was to investigate the value of serum macrophage inhibitory factor-1 (MIC-1) level in patients with non-small cell lung cancer (NSCLC). Serum samples from 296 patients with NSCLC and 240 healthy controls were collected. The levels of serum MIC-1 were determined by ELISA. The serum MIC-1 levels in NSCLC patients were higher than that of the controls (P <.001). Univariate and multivariate Cox regression analysis showed that serum MIC-1 was an independent prognostic indicator of OS and PFS. Serum MIC-1 is a valuable biomarker for the diagnosis and prognosis of NSCLC.

Serum pleiotrophin as a diagnostic and prognostic marker for small cell lung cancer.

Pleiotrophin (PTN) is involved in tumour progression, angiogenesis and metastasis. The purpose of this study was to investigate the expression level of PTN in the serum of patients with small cell lung cancer (SCLC) and to explore the clinical significance of PTN. Serum samples from 128 patients with SCLC, 120 healthy volunteers (HV) and 60 patients with benign lung disease (BLD) were collected. The levels of serum PTN were determined with ELISA and its correlation with the clinical data was examined. The serum PTN levels in SCLC patients were significantly higher than that in BLD patients (P < 0.05) or HV (P < 0.05). With a cutoff value of 258.18 ng/mL, the sensitivity and specificity of PTN to SCLC patients and BLD patients, SCLC patients and HV were 79.2% and 91.7%, 86.7% and 95.8% respectively. An area under the curve for all stages of SCLC resulting from PTN, which was significantly better than the other tumour markers tested including progastrin-releasing peptide and neuron-specific enolase. High serum PTN levels appear to correlate with poor survival in patients with SCLC. These results suggest that PTN levels in the serum could be a new effective biomarker for the diagnosis and prognosis of SCLC.

Topotecan alleviates ventilator-induced lung injury via NF-κB pathway inhibition.

OBJECTIVE: We investigated the effect of topotecan on injury and inflammation in a model of ventilator-inducedlunginjury (VILI). METHODS: Acute lung injury (ALI) was induced in mice by high-tidal volume ventilation, and the mice were then treated with topotecan or PBS. Lung tissue and bronchoalveolar lavage fluid were collected to assess pulmonary vascular leaks, inflammation, and cell apoptosis. RESULTS: Compared to PBS treatment, topotecan significantly decreased the ALI score, myeloperoxidase (MPO) content, total protein concentration, and presence of inflammatory cells and inflammatory cytokines in bronchoalveolar lavage fluid. Topotecan also reduced caspase-3 activation and type Ⅱ alveolar epithelial cell apoptosis. Moreover, topotecan inhibited NF-κB expression and activation in the VILI model. CONCLUSION: Topotecan alleviates acute lung injury in the model of VILI through the inhibition of the NF-κB pathway.

Structured Background Modeling for Hyperspectral Anomaly Detection.

Background modeling has been proven to be a promising method of hyperspectral anomaly detection. However, due to the cluttered imaging scene, modeling the background of an hyperspectral image (HSI) is often challenging. To mitigate this problem, we propose a novel structured background modeling-based hyperspectral anomaly detection method, which clearly improves the detection accuracy through exploiting the block-diagonal structure of the background. Specifically, to conveniently model the multi-mode characteristics of background, we divide the full-band patches in an HSI into different background clusters according to their spatial-spectral features. A spatial-spectral background dictionary is then learned for each cluster with a principal component analysis (PCA) learning scheme. When being represented onto those dictionaries, the background often exhibits a block-diagonal structure, while the anomalous target shows a sparse structure. In light of such an observation, we develop a low-rank representation based anomaly detection framework that can appropriately separate the sparse anomaly from the block-diagonal background. To optimize this framework effectively, we adopt the standard alternating direction method of multipliers (ADMM) algorithm. With extensive experiments on both synthetic and real-world datasets, the proposed method achieves an obvious improvement in detection accuracy, compared with several state-of-the-art hyperspectral anomaly detection methods.

Accounting for technical noise in single-cell RNA-seq experiments.

Single-cell RNA-seq can yield valuable insights about the variability within a population of seemingly homogeneous cells. We developed a quantitative statistical method to distinguish true biological variability from the high levels of technical noise in single-cell experiments. Our approach quantifies the statistical significance of observed cell-to-cell variability in expression strength on a gene-by-gene basis. We validate our approach using two independent data sets from Arabidopsis thaliana and Mus musculus.

Prognostic values of B7-H4 in non-small cell lung cancer.

OBJECTIVE: The aim of this study was to explore the prognostic value of serum soluble B7-H4 (sB7-H4) levels in patients with non-small cell lung cancer (NSCLC). METHODS: Serum specimens from 316 NSCLC patients and 240 healthy controls were collected. The concentrations of sB7-H4 were measured by ELISA. RESULTS: The levels of sB7-H4 in NSCLC patients were significantly higher than that of the controls (P<0.01). Multivariate survival analysis indicated that sB7-H4 was an independent prognostic indicator of overall survival and progression-free survival (P<0.01). CONCLUSIONS: Measurement of serum sB7-H4 might be a useful prognostic biomarker for NSCLC.

[Analysis of clinical phenotype and ACAT1 gene mutation in a family affected with beta-ketothiolase deficiency].

OBJECTIVE: To investigate the clinical phenotype and ACAT1 gene mutation in a family affected with beta-ketothiolase deficiency (BKTD). METHODS: Clinical features and laboratory test data were collected. The probands were monozygotic twin brothers. Genomic DNA was isolated from peripheral blood leukocytes obtained from the probands and their family members. Molecular genetic testing of the ACAT1 gene was carried out. RESULTS: The probands have presented with fever, vomiting and severe ketoacidosis. By arterial blood gas testing, pH was determined to be 7.164, bicarbonate was 4.0 mmol/L, and urine ketone was ++++. Urinary organic acid gas chromatography-mass spectrometry analysis showed excessive excretion of 3-hydroxybutyric acid, 2-methyl-3-hydroxybutyric acid and tiglylglycine. Increased 3-hydroxybutyrylcarnitine (C4-OH), tiglylcarnitine(C5:1) and 3-hydroxyisovalerylcarnitine (C5-OH) levels. The clinical phenotype of proband's parents were both normal, but an elder sister turned out to be an affected patient. Genetic analysis has identified two heterozygous mutations [c.622C>T(p.R208X) and c.653C>T (p.S218F)] in the proband, which were respectively detected in the mother and father. The c.653C>T (p.S218F) mutation was not found among the 100 healthy controls and has not been included in the Human Gene Mutation Database(HGMD). CONCLUSION: The primary clinical manifestations of BKTD is ketoacidosis. Urine organic acid and blood acylcarnitine analyses play an important role in the diagnosis of the disease. The compound heterozygous of ACAT1 gene mutations probably underlie the BKTD in our patient.

[Analysis of L2HGDH gene mutation in a patient with 2-hydroxyglutaric aciduria].

OBJECTIVE: To explore pathogenic mutation in a family affected with 2-hydroxyglutaric aciduria. METHODS: Exons of 3 candidate genes, including L2HGDH, D2HGDH and SLC25A1, were amplified with polymerase chain reaction and subjected to direct sequencing. RESULTS: DNA sequencing has found that the proband and his affected younger brother have both carried a heterozygous mutation c.845G>A (p.R282Q) in the exon 7 of the L2HGDH gene. The same mutation was not detected in the his sister who was healthy. Pedigree analysis has confirmed that the above mutation was inherited from the mother. No mutation was detected in exons and flanking sequences of the D2HGDH and SLC25A1 genes. CONCLUSION: Mutation of the L2HGDH gene probably underlies the 2-hydroxyglutaric aciduria in this family.

Prognostic value of soluble H7-B4 in pleural effusion associated with lung cancer.

B7-H4, a member of the inhibitory B7 family, can restrain T cell proliferation, activation, and cytokine secretion and may be involved in immune evasion in cancer patients. This study aimed to evaluate the diagnostic and prognostic value of pleural effusion levels of soluble B7-H4 (sB7-H4) in lung cancer patients with malignant pleural effusion (MPE). Pleural effusion samples were collected from 98 lung cancer patients with malignant effusion and from 60 patients with nonmalignant pleural effusion. Pleural effusion concentrations of sB7-H4 were measured using sandwich enzyme-linked immunosorbent assay. Malignant effusion exhibited higher sB7-H4 levels than those in nonmalignant effusion (P < 0.01). Lung cancer patients with pleural effusion sB7-H4 levels below 35.8 ng/ml had a longer overall survival than those with higher levels (P < 0.05). By multivariate analysis, pleural effusion sB7-H4 was an independent prognostic factor in patients with MPE. In conclusion, measurement of sB7-H4 might be a useful diagnostic and prognostic value for MPE patients.

Clinical significance and biological roles of TRIM24 in human bladder carcinoma.

Tripartite motif-containing 24 (TRIM24), also known as transcription intermediary factor 1-alpha (TIF1α), is a chromatin-associated protein which as been has been implicated in carcinogenesis. However, its expression profile and biological roles in human bladder carcinoma has not been investigated. In this study, we examined its expression in 95 bladder cancer specimens. We found that TRIM24 expression was upregulated in 39 of 95 (41.1 %) specimens compared with normal control. TRIM24 overexpression was associated with local invasion and advanced grade of bladder cancer. In addition, we transfected TRIM24 plasmid into BIU-87 cell line and TRIM24 siRNA into 5637 cell line. Colony formation, CCK-8, and transwell assay were used to assess its biological roles in bladder cancer cells. The result showed that TRIM24 could facilitate cancer cell growth and invading ability. Western blot analysis demonstrated that TRIM24 upregulated cyclin D1, cyclin E, p-IκBα, and p-AKT expression, suggesting TRIM24 activates NF-κB and AKT pathways. In addition, NF-κB inhibitor reversed the effect of TRIM24 on cyclin D1. In conclusion, TRIM24 is overexpressed in human bladder cancer and facilitates bladder cancer growth and invasion, possibly through NF-κB and AKT signaling pathways.

Involvement of miR-143 in cisplatin resistance of gastric cancer cells via targeting IGF1R and BCL2.

We investigated the possible role of miR-143 in the development of cisplatin resistance in human gastric cancer cell line. miR-143 was detected by quantitative real-time PCR. Cisplatin resistance changes of cells was tested via MTT assay. Target genes of miR-143 were verified by dual-luciferase activity assay. Immunohistochemistry, immunofluorescence staining, Western blot, cell proliferation, and clonogenic and apoptosis assay were used to elucidate the mechanism of miR-143 in cisplatin resistance formation. miR-143 was downregulated in gastric cancer tissues and cell lines. It was also downregulated in cisplatin-resistant gastric cancer cell line SGC7901/cisplatin (DDP), which was concurrent with the upregulation of IGF1R and BCL2, compared with the parental SGC7901 cell line, respectively. Overexpressed miR-143 sensitized SGC7901/DDP cells to cisplatin. The luciferase activity suggested that IGF1R and BCL2 were both target genes of miR-143. Enforced miR-143 reduced its target proteins, inhibited SGC7901/DDP cells proliferation, and sensitized SGC7901/DDP cells to DDP-induced apoptosis. Our findings suggested that hsa-miR-143 could modulate cisplatin resistance of human gastric cancer cell line at least in part by targeting IGF1R and BCL2.

Glycaemic control and its associated factors in Chinese adults with type 1 diabetes mellitus.

BACKGROUND: Glycaemic control is a great challenge in the management of type 1 diabetes mellitus (T1DM). There is limited data concerning glycaemic control among adults with T1DM. We used data from the Guangdong T1DM Translational Medicine Study to evaluate glycaemic control and its associated factors in Chinese adults with T1DM. METHODS: This cross-sectional analysis included 827 participants who were 18 years of age or older and had been living with T1DM for at least 1 year. Participants with HbA1c levels <7% were compared against those with HbA1c levels ≥ 7%. A multivariate logistic regression model was used to examine factors associated with glycaemic control. RESULTS: Among the 827 participants, the mean age was 34.2 ± 12.1 years and the median (interquartile range) duration of diabetes was 6.1 (3.4, 10.4) years. The median HbA1c level was 8.5% (7.5%, 10.2%). Only one-fifth of participants had HbA1c levels <7%. Insufficient glycaemic control (HbA1c ≥ 7%) was strongly associated with infrequent self-monitoring of blood glucose (OR = 1.21, 95% CI 1.14 ~ 1.29, p = 0.000), high insulin dose (OR = 1.27, 95% CI 1.07 ~ 1.52, p = 0.006), smoking (OR = 3.11, 95% CI 1.44 ~ 6.72, p = 0.004), low-frequency clinical visits (OR = 2.74, 95% CI 1.47 ~ 5.10, p = 0.001), the presence of diabetic autoantibodies (OR = 1.63, 95% CI 1.07 ~ 2.48, p = 0.022) and low fasting C-peptide (FCP) levels (OR = 1.21, 95% CI 1.01 ~ 1.46, p = 0.049) after adjustment for age at disease onset, education level, household income and diet control. CONCLUSIONS: Most adult patients with T1DM did not achieve the HbA1c target. Identifying determinants for glycaemic control provides us valuable information to improve glycaemic control in these patients. Copyright © 2015 John Wiley & Sons, Ltd.

Evaluation of serum and pleural levels of soluble B7-H4 in lung cancer patients with pleural effusion.

OBJECTIVE: To evaluate the diagnostic value of sB7-H4 and CEA in both serum and pleural effusion of lung cancer patients. METHODS: Levels of sB7-H4 and CEA in 90 patients with malignant pleural effusion due to lung cancer and 58 patients with benign pleural effusion were measured by ELISA. RESULTS: The sB7-H4 and CEA levels in pleural effusion, serum and their ratio (F/S) were higher in lung cancer group than that in benign group (p < 0.01). The diagnostic efficiency of sB7-H4 combined CEA was superior to either sB7-H4 or CEA. CONCLUSIONS: Measurement of sB7-H4 and CEA might be useful diagnostic value for malignant effusion.