Integrative analysis of single-cell and bulk RNA sequencing unveils a machine learning-based pan-cancer major histocompatibility complex-related signature for predicting immunotherapy efficacy.

Major histocompatibility complex (MHC) could serve as a potential biomarker for tumor immunotherapy, however, it is not yet known whether MHC could distinguish potential beneficiaries. Single-cell RNA sequencing datasets derived from patients with immunotherapy were collected to elucidate the association between MHC and immunotherapy response. A novel MHCsig was developed and validated using large-scale pan-cancer data, including The Cancer Genome Atlas and immunotherapy cohorts. The therapeutic value of MHCsig was further explored using 17 CRISPR/Cas9 datasets. MHC-related genes were associated with drug resistance and MHCsig was significantly and positively associated with immunotherapy response and total mutational burden. Remarkably, MHCsig significantly enriched 6% top-ranked genes, which were potential therapeutic targets. Moreover, we generated Hub-MHCsig, which was associated with survival and disease-special survival of pan-cancer, especially low-grade glioma. This result was also confirmed in cell lines and in our own clinical cohort. Later low-grade glioma-related Hub-MHCsig was established and the regulatory network was constructed. We provided conclusive clinical evidence regarding the association between MHCsig and immunotherapy response. We developed MHCsig, which could effectively predict the benefits of immunotherapy for multiple tumors. Further exploration of MHCsig revealed some potential therapeutic targets and regulatory networks.

Diagnosis of Alzheimer's disease by joining dual attention CNN and MLP based on structural MRIs, clinical and genetic data.

Alzheimer's disease (AD) is an irreversible central nervous degenerative disease, while mild cognitive impairment (MCI) is a precursor state of AD. Accurate early diagnosis of AD is conducive to the prevention and early intervention treatment of AD. Although some computational methods have been developed for AD diagnosis, most employ only neuroimaging, ignoring other data (e.g., genetic, clinical) that may have potential disease information. In addition, the results of some methods lack interpretability. In this work, we proposed a novel method (called DANMLP) of joining dual attention convolutional neural network (CNN) and multilayer perceptron (MLP) for computer-aided AD diagnosis by integrating multi-modality data of the structural magnetic resonance imaging (sMRI), clinical data (i.e., demographics, neuropsychology), and APOE genetic data. Our DANMLP consists of four primary components: (1) the Patch-CNN for extracting the image characteristics from each local patch, (2) the position self-attention block for capturing the dependencies between features within a patch, (3) the channel self-attention block for capturing dependencies of inter-patch features, (4) two MLP networks for extracting the clinical features and outputting the AD classification results, respectively. Compared with other state-of-the-art methods in the 5CV test, DANMLP achieves 93% and 82.4% classification accuracy for the AD vs. MCI and MCI vs. NC tasks on the ADNI database, which is 0.2%∼15.2% and 3.4%∼26.8% higher than that of other five methods, respectively. The individualized visualization of focal areas can also help clinicians in the early diagnosis of AD. These results indicate that DANMLP can be effectively used for diagnosing AD and MCI patients.

A novel cross-layer dual encoding-shared decoding network framework with spatial self-attention mechanism for hippocampus segmentation.

Accurate segmentation of the hippocampus from the brain magnetic resonance images (MRIs) is a crucial task in the neuroimaging research, since its structural integrity is strongly related to several neurodegenerative disorders, such as Alzheimer's disease (AD). Automatic segmentation of the hippocampus structures is challenging due to the small volume, complex shape, low contrast and discontinuous boundaries of hippocampus. Although some methods have been developed for the hippocampus segmentation, most of them paid too much attention to the hippocampus shape and volume instead of considering the spatial information. Additionally, the extracted features are independent of each other, ignoring the correlation between the global and local information. In view of this, here we proposed a novel cross-layer dual Encoding-Shared Decoding network framework with Spatial self-Attention mechanism (called ESDSA) for hippocampus segmentation in human brains. Considering that the hippocampus is a relatively small part in MRI, we introduced the spatial self-attention mechanism in ESDSA to capture the spatial information of hippocampus for improving the segmentation accuracy. We also designed a cross-layer dual encoding-shared decoding network to effectively extract the global information of MRIs and the spatial information of hippocampus. The spatial features of hippocampus and the features extracted from the MRIs were combined to realize the hippocampus segmentation. Results on the baseline T1-weighted structural MRI data show that the performance of our ESDSA is superior to other state-of-the-art methods, and the dice similarity coefficient of ESDSA achieves 89.37%. In addition, the dice similarity coefficient of the Spatial Self-Attention mechanism (SSA) strategy and the dual Encoding-Shared Decoding (ESD) strategy is 9.47%, 5.35% higher than that of the baseline U-net, respectively, indicating that the strategies of SSA and ESD can effectively enhance the segmentation accuracy of human brain hippocampus.

Identification of potential LncRNAs as papillary thyroid carcinoma biomarkers based on integrated bioinformatics analysis using TCGA and RNA sequencing data.

The roles and mechanisms of long non-coding RNAs (lncRNAs) in papillary thyroid cancer (PTC) remain elusive. We obtained RNA sequencing (RNA-seq) data of surgical PTC specimens from patients with thyroid cancer (THCA; n = 20) and identified differentially expressed genes (DEGs) between cancer and cancer-adjacent tissue samples. We identified 2309 DEGs (1372 significantly upregulated and 937 significantly downregulated). We performed Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment, and protein-protein interaction network analyses and screened for hub lncRNAs. Using the same methods, we analyzed the RNA-seq data from THCA dataset in The Cancer Genome Atlas (TCGA) database to identify differentially expressed lncRNAs. We identified 15 key differentially expressed lncRNAs and pathways that were closely related to PTC. Subsequently, by intersecting the differentially expressed lncRNAs with hub lncRNAs, we identified LINC02407 as the key lncRNA. Assessment of the associated clinical characteristics and prognostic correlations revealed a close correlation between LINC02407 expression and N stage of patients. Furthermore, receiver operating characteristic curve analysis showed that LINC02407 could better distinguish between cancerous and cancer-adjacent tissues in THCA patients. In conclusion, our findings suggest that LINC02407 is a potential biomarker for PTC diagnosis and the prediction of lymph node metastasis.

Detection of BRAF V600E in Fine-Needle Aspiration Samples of Thyroid Nodules by Droplet Digital PCR.

Background: BRAF exon 15 p.V600E (BRAF V600E) mutation has been established as an important molecular marker for papillary thyroid carcinoma diagnosis by ultrasound-guided fine-needle aspiration biopsy (FNAB). Sanger sequencing is the gold standard for detecting BRAF V600E mutations but fails to identify low-frequency mutations. However, droplet digital PCR (ddPCR) is a popular new method for detecting low-frequency mutations. Here, we compare the efficiency of droplet digital PCR (ddPCR) and Sanger sequencing for detection of the BRAF V600E mutation in thyroid fine-needle aspiration (FNA) samples. Methods: Thyroid fine-needle aspiration samples from 278 patients with 310 thyroid nodules were collected. Sanger sequencing and ddPCR were conducted to detect the BRAF V600E mutation. Results: The BRAF V600E mutation was found in 94 nodules (30.32%) by ddPCR and 40 nodules (12.90%) by Sanger sequencing in 310 FNA samples. A total of 119 nodules were confirmed PTC by postsurgical pathology. Among which the BRAF mutation was found in 80 (67.23%) nodules by ddPCR and 31 (26.05%) by Sanger sequencing. All nodules carrying the mutation detected by Sanger sequencing (SS+) were verified by ddPCR (ddPCR+). Also, all nodules with no mutation detected by ddPCR were interpreted as wild-type by Sanger sequencing (SS-). In addition. Almost all SS+/ddPCR + nodules (95.00%; 38/40) and SS-/ddPCR + nodules (100.00%; 54/54) displayed a BRAF mutation rate of >5% and <15%, respectively, indicating easy misdetection by Sanger sequencing when the mutation rate is between 5 and 15%. Conclusion: ddPCR has higher sensitivity than Sanger sequencing and we propose ddPCR as a supplement to Sanger sequencing in molecular testing of BRAF using FNAB samples.

Mammalian Target of Rapamycin as the Therapeutic Target of Vascular Proliferative Diseases: Past, Present, and Future.

ABSTRACT: The abnormal proliferation of vascular smooth muscle cells (VSMCs) is a key pathological characteristic of vascular proliferative diseases. Mammalian target of rapamycin (mTOR) is an evolutionarily conserved serine/threonine kinase that plays an important role in regulating cell growth, motility, proliferation, and survival, as well as gene expression in response to hypoxia, growth factors, and nutrients. Increasing evidence shows that mTOR also regulates VSMC proliferation in vascular proliferative diseases and that mTOR inhibitors, such as rapamycin, effectively restrain VSMC proliferation. However, the molecular mechanisms linking mTOR to vascular proliferative diseases remain elusive. In our review, we summarize the key roles of the mTOR and the recent discoveries in vascular proliferative diseases, focusing on the therapeutic potential of mTOR inhibitors to target the mTOR signaling pathway for the treatment of vascular proliferative diseases. In this study, we discuss mTOR inhibitors as promising candidates to prevent VSMC-associated vascular proliferative diseases.

Upregulation of GBP1 in thyroid primordium is required for developmental thyroid morphogenesis.

PURPOSE: Congenital hypothyroidism (CH) is a common congenital endocrine disorder in humans. CH-related diseases such as athyreosis, thyroid ectopy, and hypoplasia are primarily caused by dysgenic thyroid development. However, the underlying molecular mechanisms remain unknown. METHODS: To identify novel CH candidate genes, 192 CH patients were enrolled, and target sequencing of 21 known CH-related genes was performed. The remaining 98 CH patients carrying no known genes were subjected to exome sequencing (ES). The functions of the identified variants were confirmed using thyroid epithelial cells in vitro and in zebrafish model organisms in vivo. RESULTS: Four pathogenic GBP1 variations from three patients were identified. In zebrafish embryos, gbp1 knockdown caused defective thyroid primordium morphogenesis and hypothyroidism. The thyroid cells were stuck together and failed to dissociate from each other to form individual follicles in gbp1-deficient embryos. Furthermore, defects were restored with wild-type human GBP1 (hGBP1) messenger RNA (mRNA) except for mutated hGBP1 (p.H150Y, p.L187P) overexpression. GBP1 promoted ß-catenin translocation into the cytosol and suppressed the formation of cellular adhesion complexes. Suppression of cell-cell adhesion restored the thyroid primordium growth defect observed in gbp1-deficient zebrafish embryos. CONCLUSION: This study provides further understanding regarding thyroid development and shows that defective cellular remodeling could cause congenital hypothyroidism.

A five-gene panel refines differential diagnosis of thyroid nodules.

BACKGROUND: Molecular testing for oncogenic mutations in fine-needle aspiration has showed high predictive value in identifying malignant lesions from thyroid nodules with indeterminate cytology. METHODS: To figure out an efficient and economical gene panel for most medical institutions in China, we designed a five-gene panel including BRAF/NRAS/KRAS/HRAS/TERT genes and conducted a retrospective study to evaluate the role of this five-gene diagnostic panel in differential diagnosis of thyroid nodules. RESULTS: A total of 665 patients with 695 thyroid nodules were investigated in the current study. The fine-needle aspiration biopsy and surgically separated thyroid tissue specimens were harvested to test BRAF, TERT, NRAS, KRAS, and HRAS mutations. We identified 261 mutations in 665 patients, including 177 V600E mutations in BRAF. Three hundred and sixty-nine patients who underwent thyroid surgery after completion of the initial clinical and cytological evaluation were enrolled in the final analysis. The diagnostic sensitivity, specificity, and accuracy of the combination of FNAB cytology and five-gene detection were 74.7%, 93.8%, and 84.8%, respectively. BRAF V600E and five-gene panel could recognize 46.4% and 53.6% of papillary thyroid carcinoma in the patients with cytologically indeterminate nodules. CONCLUSION: The five-gene panel can effectively improve the sensitivity, negative predictive value, and accuracy of fine-needle aspiration biopsy cytology, especially in the patients with cytologically indeterminate nodules.

Microglia-associated neuroinflammation is a potential therapeutic target for ischemic stroke.

Microglia-associated neuroinflammation plays an important role in the pathophysiology of ischemic stroke. Microglial activation and polarization, and the inflammatory response mediated by these cells play important roles in the development, progression and outcome of brain injury after ischemic stroke. Currently, there is no effective strategy for treating ischemic stroke in clinical practice. Therefore, it is clinically important to study the role and regulation of microglia in stroke. In this review, we discuss the involvement of microglia in the neuroinflammatory process in ischemic stroke, with the aim of providing a better understanding of the relationship between ischemic stroke and microglia.

Comparisons and Combined Application of Two-Dimensional and Three-Dimensional Real-time Shear Wave Elastography in Diagnosis of Thyroid Nodules.

Purpose Two-dimensional and three-dimensional real-time shear wave elastography (2D+3D SWE) represents a new technology for the quantification of tissue elasticity. This study investigated whether they could be performed to differentiate between benign and malignant thyroid nodules. Methods Conventional B-mode ultrasound, 2D and 3D SWE were performed in 96 patients with 97 thyroid nodules with pathology results. Results All the elastography values of 2D&3D SWE in malignant thyroid nodules were higher than those in benign nodules. These two elastography methods alone could not improve diagnostic value comparing to B-mode ultrasound significantly. However, B-mode US + 2D SWE (TI-RADS ≥ 4c or S-Emean ≥ 23.75 kPa, suspicious), B-mode US + 3D SWE (TI-RADS ≥ 4c or 3D-T-Emean ≥ 20.75 kPa, suspicious), B-mode US + 2D + 3D SWE (TI-RADS ≥ 4c or S-Emean ≥ 23.75 kPa or 3D-T-Emean ≥ 20.75 kPa, suspicious) had higher sensitivity and accuracy values than those of 3 methods alone but lower specificity values. Among them, B-mode ultrasound + 2D SWE had the highest sensitivity, NPV, accuracy and Youden's index (0.881, 0.788, 0.804 and 0.57). Conclusions 2D SWE or 3D SWE alone could not improve the diagnostic value of differentiating malignant from benign thyroid nodules comparing to conventional B-mode ultrasound. But combination methods could improve the diagnostic value, especially B-mode US + 2D SWE.

Preliminary study of diffusion kurtosis imaging in thyroid nodules and its histopathologic correlation.

OBJECTIVES: To evaluate the utility of diffusion kurtosis imaging (DKI) of patients with thyroid nodules and to assess the probable correlation with histopathological factors. METHODS: The study included 58 consecutive patients with thyroid nodules who underwent magnetic resonance imaging (MRI) examination, including DKI and diffusion-weighted imaging (DWI). Histopathological analysis of paraffin sections included cell density and immunohistochemical analysis of Ki-67 and vascular endothelial growth factor (VEGF). Statistical analyses were performed using Student's t-test, receiver operating characteristic (ROC) curves and Spearman's correlation. RESULTS: The diffusion parameters, cell density and immunohistochemistry analysis between malignant and benign lesions showed significant differences. The largest area under the ROC curve was acquired for the D value (AUC = 0.797). The highest sensitivity was shown with the use of K (threshold = 0.832, sensitivity = 0.917). The Ki-67 expression generally stayed low. A moderate correlation was found between ADC, D and cell density (r = -0.536, P = 0.000; r = -0.570, P = 0.000) and ADC, D and VEGF expression (r = -0.451, P = 0.000; r = -0.522, P = 0.000). CONCLUSION: The DKI-derived parameters D and K demonstrated an advantage compared to conventional DWI for thyroid lesion diagnosis. While the histopathological study indicated that the D value correlated better with extracellular change than the ADC value, the K value probably changed relative to the intracellular structure. KEY POINTS: • DWI and DKI parameters can identify PTC from benign thyroid nodules. • Correlations were found between diffusion parameters and histopathological analysis. • DKI obtains better diagnostic accuracy than conventional DWI.

National prevalence of coronary heart disease and its relationship with human development index: A systematic review.

BACKGROUND: Coronary heart disease has become a major health concern over the past several decades. Several reviews have assessed the effects of socioeconomic status on the coronary heart disease epidemic in communities and countries, but only a few reviews have been performed at a global level. This study was to explore the relationship between the prevalence of coronary heart disease and socioeconomic development worldwide using the Human Development Index. DESIGN: Systematic review. METHODS: The data in this study were collected from the MEDLINE database. Cross-sectional studies reporting the prevalence of coronary heart disease until November 2014 were collected. The Human Development Index was sourced from the United Nations Development Programme Database and was used to measure the socioeconomic achievements of countries. Each country was classified as a developing or developed country based on its level of development according to the Human Development Index value. RESULTS: Based on the data analysis on the global level, coronary heart disease prevalence had no association with the national Human Development Index (rho = 0.07). However, there was a positive association between coronary heart disease prevalence and the national Human Development Index in developing countries, although a negative association existed in developed countries (rho = 0.47 and -0.34, respectively). In addition, the past decades have witnessed a growing coronary heart disease epidemic in developing countries, with reverse trends observed in developed countries (P = 0.021 and 0.002, respectively). CONCLUSIONS: With the development of socioeconomic status, as measured by the Human Development Index, the prevalence of coronary heart disease is growing in developing countries, while declining in developed countries. Future research needs to pay more attention to the reasonable allocation of medical resources and control of coronary heart disease risk factors.

Prevalence of Nonalcoholic Fatty Liver Disease and Economy.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is a growing health issue around the world. AIM: This study is to investigate whether adult prevalence of NAFLD correlates with national economic status. METHODS: Literature search on PubMed database was conducted to identify eligible records fully published before September 2014. Gross national income (GNI) per capita was chosen to evaluate national economic status. Pearson coefficient, linear regression, and unpaired t test were performed in the statistical analyses. RESULTS: Twenty-one population-based surveys (seven in East Asia, five in South Asia, three in Middle East, and six in Europe) were included. The pooled prevalence of NAFLD was 24.24%, and the global prevalence was positively correlated with GNI per capita (r = 0.4782, P = 0.0283). Europe witnessed a higher prevalence (28.04%) than Middle East (12.95%, P = 0.0092) and East Asia (19.24%, P = 0.0083). Male presented a higher prevalence than female (P = 0.019), especially in Europe (P = 0.0132) and in Caucasians (P = 0.0383). Furthermore, male prevalence and rural prevalence individually were correlated with economic status (r = 0.5725, P = 0.0257 and r = 0.7389, P = 0.0060). Lastly, the urban (23.93%) witnessed a higher prevalence than the rural or the urban + rural (12.65%, P = 0.0141) in the countries of GNI per capita <$10,000. CONCLUSIONS: This study suggested that countries with higher economic status tend to present a higher prevalence of NAFLD. It is believed to provide a distinctive epidemiologic perspective to global situation of NAFLD.

Prevalence of fatty liver disease and the economy in China: A systematic review.

AIM: To investigate the relationship between the economy and the adult prevalence of fatty liver disease (FLD) in mainland China. METHODS: Literature searches on the PubMed and Chinese National Knowledge Infrastructure databases were performed to identify eligible studies published before July 2014. Records were limited to cross-sectional surveys or baseline surveys of longitudinal studies that reported the adult prevalence of FLD and recruited subjects from the general population or community. The gross domestic product (GDP) per capita was chosen to assess the economic status. Multiple linear regression and Loess regression were chosen to fit the data and calculate the 95%CIs. Fitting and overfitting of the models were considered in choosing the appropriate models. RESULTS: There were 27 population-based surveys from 26 articles included in this study. The pooled mean prevalence of FLD in China was 16.73% (95%CI: 13.92%-19.53%). The prevalence of FLD was correlated with the GDP per capita and survey years in the country (adjusted R (2) = 0.8736, P GDP per capita = 0.00426, P years = 0.0000394), as well as in coastal areas (R (2) = 0.9196, P GDP per capita = 0.00241, P years = 0.00281). Furthermore, males [19.28% (95%CI: 15.68%-22.88%)] presented a higher prevalence than females [14.1% (95%CI: 11.42%-16.61%), P = 0.0071], especially in coastal areas [21.82 (95%CI: 17.94%-25.71%) vs 17.01% (95%CI: 14.30%-19.89%), P = 0.0157]. Finally, the prevalence was predicted to reach 20.21% in 2020, increasing at a rate of 0.594% per year. CONCLUSION: This study reveals a correlation between the economy and the prevalence of FLD in mainland China.

Systematic Review with Meta-Analysis: Alcohol Consumption and Risk of Colorectal Serrated Polyp.

BACKGROUND: Alcohol intake is closely related to colorectal cancer, which remains inconsistent with studies on the relation between alcohol consumption and risk of colorectal serrated polyp (SP) which was proven to have potential of developing into malignant serrated neoplasm. AIM: A meta-analysis investigating the association between alcohol intake and colorectal SP with the dose-response of alcohol intake was conducted. METHODS: The literature search was performed on PubMed to identify pertinent articles presenting results for at least three categories of alcohol consumption dated up to October 2014. Summarized relative risks (RRs) with 95 % confidence intervals (CIs) were estimated using random or fixed effects models based on statistical heterogeneity. RESULTS: A total of ten observational studies were identified in this meta-analysis. All drinkers were associated with 24 % increased risk of colorectal SP compared with non-/occasional drinkers. In particular, the light alcohol intake was not related to an increased risk of colorectal SP (RR 1.05, 95 % CI 0.93-1.18), whereas the RRs were 1.19 (95 % CI 1.02-1.40) for moderate alcohol intake and 1.60 (95 % CI 1.35-1.91) for heavy alcohol intake. The risks were consistent in further dose-response analysis. Meanwhile, subgroup analyses demonstrated that patients in America had more increased risk of SP with respect to those in Europe and Asia. In terms of subtype of colorectal SP, alcohol consumption had a greater influence on SSA than HP. CONCLUSIONS: This is the first meta-analysis that demonstrated the relationship between moderate and heavy alcohol consumption and increasing risks of colorectal SP.

[Detection of lymph node of rabbit thyroid by real-time fluorescence imaging].

OBJECTIVE: To detect the lymph nodes (LN) of rabbit thyroid by fluorescence imaging and to provide experimental evidence for its clinical application. METHODS: Each of 50 lateral thyroid lobes of 25 rabbits was injected with 0.02 ml of indocyanine green (ICG), and 0.02 ml methylene followed. ICG fluorescence was detected using photodynamic eye (PDE). The methylene staining in LN was also observed. The onset time of ICG staining in LN was measured. RESULTS: The detection rate of fluorescence imaging and blue dye imaging were respectively 86.0% (43/50) and 66.0% (33/50), with a significant difference (P = 0.034), and the accuracy were respectively 85.5% (53/62) and 70.7% (41/58). The onset time (x(-) ± s) of ICG staining in LN was (118.3 ± 16.1) s. CONCLUSIONS: Fluorescence imaging showed satisfied detection rate and accuracy. The detection rate of LN by fluorescence imaging was higher than that by blue dye imaging. Fluorescence imaging could be an alternative method for the detection of LN of thyroid in future clinical practice.