Modeling RNA-Binding Protein Specificity In Vivo by Precisely Registering Protein-RNA Crosslink Sites.

RNA-binding proteins (RBPs) regulate post-transcriptional gene expression by recognizing short and degenerate sequence motifs in their target transcripts, but precisely defining their binding specificity remains challenging. Crosslinking and immunoprecipitation (CLIP) allows for mapping of the exact protein-RNA crosslink sites, which frequently reside at specific positions in RBP motifs at single-nucleotide resolution. Here, we have developed a computational method, named mCross, to jointly model RBP binding specificity while precisely registering the crosslinking position in motif sites. We applied mCross to 112 RBPs using ENCODE eCLIP data and validated the reliability of the discovered motifs by genome-wide analysis of allelic binding sites. Our analyses revealed that the prototypical SR protein SRSF1 recognizes clusters of GGA half-sites in addition to its canonical GGAGGA motif. Therefore, SRSF1 regulates splicing of a much larger repertoire of transcripts than previously appreciated, including HNRNPD and HNRNPDL, which are involved in multivalent protein assemblies and phase separation.

The germ cell-specific RNA binding protein RBM46 is essential for spermatogonial differentiation in mice.

Control over gene expression is exerted, in multiple stages of spermatogenesis, at the post-transcriptional level by RNA binding proteins (RBPs). We identify here an essential role in mammalian spermatogenesis and male fertility for 'RNA binding protein 46' (RBM46). A highly evolutionarily conserved gene, Rbm46 is also essential for fertility in both flies and fish. We found Rbm46 expression was restricted to the mouse germline, detectable in males in the cytoplasm of premeiotic spermatogonia and meiotic spermatocytes. To define its requirement for spermatogenesis, we generated Rbm46 knockout (KO, Rbm46-/-) mice; although male Rbm46-/- mice were viable and appeared grossly normal, they were infertile. Testes from adult Rbm46-/- mice were small, with seminiferous tubules containing only Sertoli cells and few undifferentiated spermatogonia. Using genome-wide unbiased high throughput assays RNA-seq and 'enhanced crosslinking immunoprecipitation' coupled with RNA-seq (eCLIP-seq), we discovered RBM46 could bind, via a U-rich conserved consensus sequence, to a cohort of mRNAs encoding proteins required for completion of differentiation and subsequent meiotic initiation. In summary, our studies support an essential role for RBM46 in regulating target mRNAs during spermatogonia differentiation prior to the commitment to meiosis in mice.

Complexity and graded regulation of neuronal cell-type-specific alternative splicing revealed by single-cell RNA sequencing.

The enormous cellular diversity in the mammalian brain, which is highly prototypical and organized in a hierarchical manner, is dictated by cell-type-specific gene-regulatory programs at the molecular level. Although prevalent in the brain, the contribution of alternative splicing (AS) to the molecular diversity across neuronal cell types is just starting to emerge. Here, we systematically investigated AS regulation across over 100 transcriptomically defined neuronal types of the adult mouse cortex using deep single-cell RNA-sequencing data. We found distinct splicing programs between glutamatergic and GABAergic neurons and between subclasses within each neuronal class. These programs consist of overlapping sets of alternative exons showing differential splicing at multiple hierarchical levels. Using an integrative approach, our analysis suggests that RNA-binding proteins (RBPs) Celf1/2, Mbnl2, and Khdrbs3 are preferentially expressed and more active in glutamatergic neurons, while Elavl2 and Qk are preferentially expressed and more active in GABAergic neurons. Importantly, these and additional RBPs also contribute to differential splicing between neuronal subclasses at multiple hierarchical levels, and some RBPs contribute to splicing dynamics that do not conform to the hierarchical structure defined by the transcriptional profiles. Thus, our results suggest graded regulation of AS across neuronal cell types, which may provide a molecular mechanism to specify neuronal identity and function that are orthogonal to established classifications based on transcriptional regulation.

N-glycan fingerprint predicts alpha-fetoprotein negative hepatocellular carcinoma: A large-scale multicenter study.

Alpha-fetoprotein (AFP)-negative hepatocellular carcinoma (ANHCC) patients account for more than 30% of the whole entity of HCC patients and are easily misdiagnosed. This three-phase study was designed to find and validate new ANHCC N-glycan markers which identified from The Cancer Genome Atlas (TCGA) database and noninvasive detection. Differentially expressed genes (DEGs) of N-glycan biosynthesis and degradation related genes were screened from TCGA database. Serum N-glycan structure abundances were analyzed using N-glycan fingerprint (NGFP) technology. Totally 1340 participants including ANHCC, chronic liver diseases and healthy controls were enrolled after propensity score matching (PSM). The Lasso algorithm was used to select the most significant N-glycan structures abundances. Three machine learning models [random forest (RF), support vector machine (SVM) and logistic regression (LR)] were used to construct the diagnostic algorithms. All 13N-glycan structure abundances analyzed by NGFP demonstrated significant and was enrolled by Lasso. Among the three machine learning models, LR algorithm demonstrated the best diagnostic performance for identifying ANHCC in training cohort (LR: AUC: 0.842, 95%CI: 0.784-0.899; RF: AUC: 0.825, 95%CI: 0.766-0.885; SVM: AUC: 0.610, 95%CI: 0.527-0.684). This LR algorithm achieved a high diagnostic performance again in the independent validation (AUC: 0.860, 95%CI: 0.824-0.897). Furthermore, the LR algorithm could stratify ANHCC into two distinct subgroups with high or low risks of overall survival and recurrence in follow-up validation. In conclusion, the biomarker panel consisting of 13N-glycan structures abundances using the best-performing algorithm (LR) was defined and indicative as an effective tool for HCC prediction and prognosis estimate in AFP negative subjects.

Serum N-glycan fingerprint nomogram predicts liver fibrosis: a multicenter study.

OBJECTIVES: Liver cirrhosis (LC) is the end-stage of fibrosis in chronic liver diseases, non-invasive early detection of liver fibrosis (LF) is particularly essential for therapeutic decision. Aberrant glycosylation of glycoproteins has been demonstrated to be closely related to liver abnormalities. METHODS: This study was designed to enroll a total of 1,565 participants with LC/LF, chronic hepatitis virus (CHB) and healthy controls. Fibrosis was confirmed by liver biopsy. Using capillary electrophoresis N-glycan fingerprint (NGFP) analysis, we developed a nomogram algorithm (FIB-G) to discriminate LC from non-cirrhotic subjects. RESULTS: The FIB-G demonstrated good diagnostic performances in identifying LC with the area under the curve (AUC) 0.895 (95%CI: 0.857-0.915). Furthermore, the diagnostic efficiencies of FIB-G were superior to that of log (P2/P8), procollagen III N-terminal (PIIINP), type IV collage (IV-C), laminin (LN), hyaluronic acid (HA), aspartate transaminase to platelets ratio index (APRI), and FIB-4 when detecting significant fibrosis (S0-1 vs. S2-4, AUC: 0.787, 95%CI: 0.701-0.873), severe fibrosis (S0-2 vs. S3-4, AUC: 0.844, 95%CI: 0.763-0.924), and LC (S0-3 vs. S4, AUC: 0.773, 95%CI: 0.667-0.880). Besides, changes of FIB-G were associated well with the regression of fibrosis and liver function Child-Pugh classification. CONCLUSIONS: FIB-G is an accurate multivariant N-glycomic algorithm for LC prediction and fibrosis progression/regression monitoring. The high throughput feasible NGFP using only 2 µL of serum could help physicians make the more precise non-invasive staging of LF or cirrhosis and reduce the need for invasive liver biopsy.

Revealing heavy metal correlations with water quality and tracking its latent factors by canonical correlation analysis and structural equation modeling in Dongjianghu Lake.

Decreasing levels of water quality and elevated concentrations of heavy metals in freshwaters can pose global challenges for drinking water sources. Multivariate statistical techniques have been applied on data matrices of water quality and heavy metals for keen characterization of their spatio-temporal variations, exploration of latent factors, and identification of pollution sources. Non-metric multidimensional scaling (nMDS), canonical correlation analysis (CCA), and structural equation modeling (SEM) were employed to process data matrices of the water quality and heavy metals with 14 parameters measured at 13 sampling sites in Dongjianghu Lake in March, June, August, and December 2016. The sampling sites were grouped into three clusters using the nMDS, suggesting that the increasing order of the water quality levels was approximately midstream < downstream < upstream and lake. The CCA of 14 parameters proved that the Escherichia coli, CODMn, TP, TN, TEMP, DO, and pH were the latent factors to distinguish the sampling sites, suggesting that the natural disturbances further influenced the lake and upstream, while the anthropogenic activities further influenced the midstream and downstream. The CCA of the heavy metals exhibited that the CODMn, F-, and E. coli were the latent factors of the Cu, Zn, and As, while the DO and TEMP were the latent factors of the Cd. This indicated that the Cu, As, and Zn were mainly associated with the anthropogenic activities, while the Cd was predominantly relative to the natural conditions. The SEM of the water quality and heavy metals showed that the weights of CODMn (28.64%), NH3-N (14.96%), BOD5 (14.32%), TN (12.88%), and TP (10.18%) were higher than those of the pH (8.37%), DO (7.73%), TEMP (2.58%), and E. coli (0.34%). This indicated that the former exhibited strong influences on the heavy metals than the latter. Moreover, the CODMn and BOD5 were the key factors of the heavy metals, which should be attributed to the no-point sources, especially the exploitation mining and mill tailings. The water quality assessment by the nMDS, CCA, and SEM can determine the status, trend corresponding to its standards, and trace latent factors and identify possible pollution sources. The study could provide a guide for water quality evaluation and pollution control.

Improving Tumor-to-Background Contrast through Hydrophilic Tetrazines: The Construction of 18 F-Labeled PET Agents Targeting Nonsmall Cell Lung Carcinoma.

Bioorthogonal reactions have been widely used in the biomedical field. 18 F-TCO/Tetrazine ligation is the most reactive radiolabelled inverse electron demand Diels-Alder reaction, but its application had been limited due to modest contrast ratios of the resulting conjugates. Herein, we describe the use of hydrophilic tetrazines to improve tumor-to-background contrast of neurotensin receptor targeted PET agents. PET agents were constructed using a rapid Diels-Alder reaction of the radiolabeled trans-cyclooctene (18 F-sTCO) with neurotensin (NT) conjugates of a 3,6-diaryltetrazine, 3-methyl-6-aryltetrazine, and a derivative of 3,6-di(2-hydroxyethyl)tetrazine. Although cell binding assays demonstrated all agents have comparable binding affinity, the conjugate derived from 3,6-di(2-hydroxyethyl)tetrazine demonstrated the highest tumor to muscle contrast, followed by conjugates of the 3-methyl-6-aryltetrazine and 3,6-diaryltetrazine.

The diagnostic value of serum DSA-TRF in hepatocellular carcinoma.

TRF is a glycoprotein mainly secreted by hepatocytes, The aim of this study was to explore the diagnostic value of aberrant glycosylated serum transferrin (TRF) especially containing multi-antennary glycans in hepatocellular carcinoma (HCC).A total of 581 subjects including HCC patients, liver cirrhosis (LC) patients, chronic hepatitis (CHB) patients and healthy controls (HC) were recruited. All the subjects were randomly assigned to training group (n = 411) and validation group (n = 170). We firstly analyzed the serum protein N-glycome profiling of HCC, LC, and HC by DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE) technology. We established a lectin-antibody sandwich ELISA (Lectin-ELISA) method to detect multi-antennary glycans-contained TRF (DSA-TRF) in serum, in which Datura stramonium Agglutinin (DSA) was used for specific recognition. Levels of serum DSA-TRF and TRF were analyzed respectively. The diagnostic efficacies of DSA-TRF and TRF of differentiating HCC patients from CHB, LC patients and HC within the training group were evaluated using receiver operating characteristic (ROC) curve and tested in the validation group.The result found that in training group, serum TRF and DSA-TRF levels differed significantly between HCC (1.86 ± 0.50, g/L, 0.285 ± 0.06), CHB + LC (2.39 ± 0.74, g/L, 0.189 ± 0.07) and HC (1.92 ± 0.69, g/L, 0.249 ± 0.09) (HCC vs. CHB + LC, P < 0.001; HCC vs. HC, P < 0.001; CHB + LC vs. HC, P < 0.001). The area under the ROC curve (AUC) of DSA-TRF was significantly superior to AFP (0.880, 95%CI: 0.834-0.925 vs. 0.776, 95%CI: 0.725-0.827, P = 0.003) in differentiating HCC from CHB + LC. The AUC of diagnostic model GlycoTRF1 (0.981, 95%CI: 0.969-0.993) was higher than DSA-TRF and AFP alone (P<0.001) in differentiating HCC from CHB + LC, which was verified in validation group.The results indicated that the serum DSA-TRF might serve as a potential glycan biomarker for distinguishing HCC from CHB and LC.

Clinical and CT imaging features between the first nucleic acid-negative and first nucleic acid-positive COVID-19 patients. / 2019å† çŠ¶ç— æ¯’ç— é¦–æ¬¡æ ¸é ¸é˜´æ€§ä¸Žé¦–æ¬¡æ ¸é ¸é˜³æ€§æ‚£è€ ä¸´åºŠåŠCT影像学表现.

OBJECTIVES: To investigate the role of chest CT for the diagnostic work-up for patients with suspected infection of coronavirus disease 2019 (COVID-19). METHODS: The clinical data and imaging findings of the first nucleic acid-negative COVID-19 patients were analyzed and compared with the first nucleic acid-positive patients. RESULTS: Compared with the first nucleic acid-positive patients, the onset time of the first nucleic acid-negative patients was shorter [(3.58±2.94) d], but the diagnosis was longer [(3.92±3.66) d]. There were no significant differences in the characteristics of the clinical data and radiological findings between the 2 groups (P>0.05). CONCLUSION: Chest CT examination is important to avoid COVID-19 missed diagnosis due to false negative nucleic acid.

MicroRNA-375-3p inhibitor suppresses angiotensin II-induced cardiomyocyte hypertrophy by promoting lactate dehydrogenase B expression.

Cardiac hypertrophy is a myocardial enlargement due to overload pressure, and the primary cause of heart failure. We investigated the function of miR-375-3p in cardiac hypertrophy and its regulating mechanisms. miR-375-3p was upregulated in hearts of the transverse aortic constriction rat model and angiotensin II (Ang II)-induced primary cardiomyocyte hypertrophy model; the opposite was observed for lactate dehydrogenase B (LDHB) protein expression. miR-375-3p knockdown reduced the surface area of primary cardiomyocytes increased by Ang II treatment and decreased the B-natriuretic peptide (BNP) and ß-myosin heavy chain (ß-MHC) messenger RNA (mRNA) and protein levels. miR-375-3p was also observed to directly target LDHB. LDHB knockdown increased the surface area of Ang II-treated primary cardiomyocytes and increased the BNP and ß-MHC mRNA and protein levels. LDHB knockdown attenuated the effects of miR-375-3p on the surface area of primary cardiomyocytes and BNP and ß-MHC levels. Therefore, miR-375-3p inhibitor suppresses Ang II-induced cardiomyocyte hypertrophy by promoting LDHB expression.

SIZE OF THE LARGEST METASTATIC FOCUS TO THE LYMPH NODE IS ASSOCIATED WITH INCOMPLETE RESPONSE OF PN1 PAPILLARY THYROID CARCINOMA.

Objective: To evaluate the influence of the size of the metastatic focus in lymph nodes (LNs) on therapeutic response among papillary thyroid cancer (PTC) and cervical pathologically proven LN metastases (pN1). Methods: Patients with pN1 PTC who underwent total or near-total thyroidectomy, LN dissection, and postoperative radioactive iodine therapy in a university hospital between 2014 and 2016 were retrospectively reviewed. Furthermore, 554 patients were assigned to three groups according to the size of the metastatic focus in the LNs (≤0.2 cm, 0.2 to 1.0 cm, ≥1.0 cm). Structural incomplete response (SIR) was defined as structural or functional evidence of disease with any thyroglobulin level and/or anti-thyroglobulin antibodies. Results: Among the 554 patients, the proportion of patients with SIR was 2.5% (4/161) in group 1, 13.9% (37/267) in group 2, and 46.8% (59/126) in group 3 (χ2 = 100.073; P<.001). The optimal cutoff value of the size of the largest metastatic focus to the LNs was 0.536 cm to predict SIR with a corresponding sensitivity of 0.82, a specificity of 0.716, and an area under the curve of 0.821 (95% confidence interval [CI], 0.777 to 0.864; P<.001). Size of the largest metastatic focus to the LNs was confirmed to be an independent predictive factor for SIR (odds ratio, 9.650; 95% CI, 4.925 to 18.909; P<.001). Conclusion: In patients with pN1 PTC, there is an association between the size of the largest metastatic focus to the LNs and incomplete response. Abbreviations: AJCC = American Joint Committee on Cancer; ATA = American Thyroid Association; BIR = biochemical incomplete response; CI = confidence interval; ER = excellent response; ETE = extranodal extension; 18F-FDG = 18F-fluorodeoxyglucose; IDR = indeterminate response; LN = lymph node; OR = odds ratio; PET/CT = positron emission tomography/computed tomography; pN1 = pathologically proven LN metastases; PTC = papillary thyroid carcinoma; RAI = radioactive iodine; ROC = receiver operating characteristic; SIR = structural incomplete response; sTg = stimulated thyroglobulin; TgAb = anti-thyroglobulin antibody; TSH = thyroid-stimulating hormone.

Characterization of kinase gene expression and splicing profile in prostate cancer with RNA-Seq data.

BACKGROUND: Alternative splicing is a ubiquitous post-transcriptional regulation mechanism in most eukaryotic genes. Aberrant splicing isoforms and abnormal isoform ratios can contribute to cancer development. Kinase genes are key regulators of multiple cellular processes. Many kinases are found to be oncogenic and have been intensively investigated in the study of cancer and drugs. RNA-Seq provides a powerful technology for genome-wide study of alternative splicing in cancer besides the conventional gene expression profiling. But this potential has not been fully demonstrated yet. METHODS: We characterized the transcriptome profile of prostate cancer using RNA-Seq data from viewpoints of both differential expression and differential splicing, with an emphasis on kinase genes and their splicing variations. We built a pipeline to conduct differential expression and differential splicing analysis, followed by functional enrichment analysis. We performed kinase domain analysis to identify the functionally important candidate kinase gene in prostate cancer, and calculated the expression levels of isoforms to explore the function of isoform switching of kinase genes in prostate cancer. RESULTS: We identified distinct gene groups from differential expression and splicing analyses, which suggested that alternative splicing adds another level to gene expression regulation. Enriched GO terms of differentially expressed and spliced kinase genes were found to play different roles in regulation of cellular metabolism. Function analysis on differentially spliced kinase genes showed that differentially spliced exons of these genes are significantly enriched in protein kinase domains. Among them, we found that gene CDK5 has isoform switching between prostate cancer and benign tissues, which may affect cancer development by changing androgen receptor (AR) phosphorylation. The observation was validated in another RNA-Seq dataset of prostate cancer cell lines. CONCLUSIONS: Our work characterized the expression and splicing profiles of kinase genes in prostate cancer and proposed a hypothetical model on isoform switching of CDK5 and AR phosphorylation in prostate cancer. These findings bring new understanding to the role of alternatively spliced kinases in prostate cancer and also demonstrate the use of RNA-Seq data in studying alternative splicing in cancer.

Development of [18F]AlF-NOTA-NT as PET Agents of Neurotensin Receptor-1 Positive Pancreatic Cancer.

Several studies have suggested that neurotensin receptors (NTRs) and neurotensin (NT) greatly affect the growth and survival of pancreatic ductal adenocarcinoma (PDAC). Developing NTR-targeted PET probes could therefore be important for the management of a pancreatic cancer patient by providing key information on the NTR expression profile noninvasively. Despite the initial success on the synthesis of 18F-labeled NT PET probes, the labeling procedure generally requires lengthy steps including azeotropic drying of 18F. Using a straightforward chelation method, here we report the simple preparation of aluminum-18F-NOTA-NT starting from aqueous 18F. The cell binding test demonstrated that [19F]AlF-NOTA-NT maintained high receptor-binding affinity to NTR1. This probe was then further evaluated in NTR1 positive pancreatic tumor models (AsPC-1 and PANC-1). After the administration of [18F]AlF-NOTA-NT, small animal PET studies showed a high contrast between tumor and background in both models at 1 and 4 h time points. A blocking experiment was performed to demonstrate the receptor specificity: the tumor uptake in AsPC1 without and with blocking agent was 1.0 ± 0.2 and 0.1 ± 0.0%ID/g, respectively, at 4 h post injection. In summary, a NTR specific PET agent, [18F]AlF-NOTA-NT, was prepared through the simple chelation method. This NTR-targeted PET probe may not only be used to detect NTR1 positive pancreatic tumors (diagnosis), but also it may be fully integrated to NTR target therapy leading to personalized medicine (theranostic).

Radiation dose rates of differentiated thyroid cancer patients after 131I therapy.

Postoperative 131I treatment for differentiated thyroid cancer (DTC) can create a radiation hazard for nearby persons. The present prospective study aimed to investigate radiation dose rates in 131I-treated DTC patients to provide references for radiation protection. A total of 141 131I-treated DTC patients were enrolled, and grouped into a singular treatment (ST) group and a repeated treatment (RT) group. The radiation dose rate of 131I-treated patients was measured. The rate of achieving discharge compliance and restricted contact time were analyzed based on Chinese regulations. Multivariate logistic regression analysis was used to analyze the independent factors associated with the clearance of radioiodine. The rate of achieving discharge compliance (131I retention < 400 MBq) was 79.8 and 93.7% at day 2 (D2) for the ST and RT groups, respectively, and reached 100% at D7 and D4, respectively. The restricted contact time with 131I-treated patients at 0.5 m for medical staff, caregivers, family members, and the general public ranged from 4 to 7 days. Multivariate logistic regression analysis showed that the 24-h iodine uptake rate was the only significant factor associated with radioiodine clearance. For the radiation safety of 131I-treated DTC patients, the present results can provide radiometric data for radiation protection.

Hepatitis B virus core antigen mutations predict post-operative prognosis of patients with primary hepatocellular carcinoma.

The aim of this study was to explore the relationship between hepatitis B virus (HBV) core antigen (HBc) mutations and the post-operative prognosis of HBV-related hepatocellular carcinoma (HCC). In total, 98 patients suffering from HBV-related HCC and treated with surgery were enrolled, with a 48 month follow-up. The preCore/Core region of the HBV genome from tumour tissue (TT) and paired adjacent non-tumour tissue (ANTT) of these patients was sequenced, and a phylogenetic tree was reconstructed. The correlations between the viral features and evolutionary divergence of preCore/Core amino acid sequences from 67 paired TTs and ANTTs were analysed. Cox proportional hazard model analysis was applied for post-operative hazard risk evaluation. Phylogenetic analysis revealed that all of the sequences were ascribed to genotype C. The evolutionary divergence of amino acid sequences from matched TTs and ANTTs was significantly negatively correlated with serum and intrahepatic HBV DNA levels. Multivariate analysis showed that the HBc E77 mutation was associated with shorter overall survival, and HBc S87 and P156 mutations were independent risk factors for relapse. Furthermore, in contrast to with patients without the S87 mutation, no correlation was observed between serum HBV DNA and intrahepatic HBV DNA in HCC patients with the S87 mutation. Analysis of the intrahepatic sequence may advance our understanding of viral status; thus, it is useful for prognosis prediction for HBV-related HCC.

Serum N-glycans outperform CA19-9 in diagnosis of extrahepatic cholangiocarcinoma.

Extensive efforts have been devoted to improve the diagnosis of extrahepatic cholangiocarcinoma (ECCA) due to its silent clinical character and lack of effective diagnostic biomarkers. Specific alterations in N-glycosylation of glycoproteins are considered a key component in cancer progression, which can serve as a distinct molecular signature for cancer detection. This study aims to find potential serum N-glycan markers for ECCA. In total, 255 serum samples from patients with ECCA (n = 106), benign bile tract disease (BBD, n = 60) and healthy controls (HC, n = 89) were recruited. Only 2 µL of serum from individual patients was used in this assay where the N-glycome of serum glycoproteins was profiled by DNA sequencer-assisted fluorophore-assisted capillary electrophoresis (DSA-FACE) technology. Multi-parameter models were constructed by combining the N-glycans and carbohydrate antigen 19-9 (CA19-9) which is currently used clinically. Quantitative analyses showed that among 13 N-glycan structures, the bifucosylated triantennary N-glycan (peak10, NA3F2) presented the best diagnostic performance for distinguishing ECCA from BBD and HC. Two diagnostic models (Glycotest1 and Glycotest2) performed better than single N-glycan or CA19-9. Additionally, two N-glycan structures (peak9, NA3Fb; peak12, NA4Fb) were tightly related to lymph node metastasis in ECCA patients. In conclusion, sera of ECCA showed relatively specific N-glycome profiling patterns. Serum N-glycan markers and models are novel, valuable and noninvasive alternatives in ECCA diagnosis and progression monitoring.

RISK FACTORS FOR NONREMISSION AND PROGRESSION-FREE SURVIVAL AFTER I-131 THERAPY IN PATIENTS WITH LUNG METASTASIS FROM DIFFERENTIATED THYROID CANCER: A SINGLE-INSTITUTE, RETROSPECTIVE ANALYSIS IN SOUTHERN CHINA.

OBJECTIVE: Prognostic factors related to progression-free survival (PFS) have not received much attention in the literature regarding iodine-131 ((131)I) therapy for patients with differentiated thyroid cancer and lung metastases. We sought to explore the factors associated with PFS and nonremission in a group of patients with differentiated thyroid cancer and pulmonary metastases at initial diagnosis and to investigate the impact of (131)I therapy on pulmonary function and peripheral blood counts in the same cohort of patients. METHODS: The medical records of 1,050 patients with differentiated thyroid cancer treated at the Zhujiang Hospital of Southern Medical University from January 2006 to January 2015 were retrospectively reviewed. Among them, 107 patients fulfilled the inclusion criteria. RESULTS: Multivariate Cox regression analysis indicated that age ≥45 years and (131)I nonavidity were independent risk factors for disease progression. Multivariate logistic regression analysis revealed that pulmonary nodule size ≥1 cm and (131)I nonavidity were the strongest risk factors predicting nonremission. Varying cumulative (131)I dosage had no association with posttreatment pulmonary function or peripheral blood cell counts. CONCLUSION: Similar to earlier studies, our results confirm that (131)I nonavidity was associated with an increased risk of disease progression and greater odds of nonremission. In addition, patients with differentiated thyroid cancer and lung metastases with pulmonary nodules ≥1 cm had a reduced likelihood of achieving remission. Furthermore, special attention is needed when monitoring patients over 45 years at a higher risk of disease progression. ABBREVIATIONS: CI = confidence interval DTC = differentiated thyroid cancer (18)F-FDG = fluoro-18 fluorodeoxyglucose FEF = forced expiratory flow FTC = follicular thyroid cancer FVC = forced vital capacity GR = granulocytes Hb = hemoglobin HR = hazard ratio (131)I = iodine-131 LN = lymph node OR = odds ratio OS = overall survival PET/CT = positive positron emission tomography/computed tomography PFS = progression-free survival PT = partial thyroidectomy PTC = papillary thyroid cancer RAI = radioactive iodine RBC = red blood cell Tg = thyroglobulin TgAb = thyroglobulin antibody TSH = thyroid-stimulating hormone TT = total thyroidectomy WBC = white blood cells WBS = whole body scan.

Reverse engineering neuron type-specific and type-orthogonal splicing-regulatory networks using single-cell transcriptomes.

Cell type-specific alternative splicing (AS) enables differential gene isoform expression between diverse neuron types with distinct identities and functions. Current studies linking individual RNA-binding proteins (RBPs) to AS in a few neuron types underscore the need for holistic modeling. Here, we use network reverse engineering to derive a map of the neuron type-specific AS regulatory landscape from 133 mouse neocortical cell types defined by single-cell transcriptomes. This approach reliably inferred the regulons of 350 RBPs and their cell type-specific activities. Our analysis revealed driving factors delineating neuronal identities, among which we validated Elavl2 as a key RBP for MGE-specific splicing in GABAergic interneurons using an in vitro ESC differentiation system. We also identified a module of exons and candidate regulators specific for long- and short-projection neurons across multiple neuronal classes. This study provides a resource for elucidating splicing regulatory programs that drive neuronal molecular diversity, including those that do not align with gene expression-based classifications.

Structure-based prediction and characterization of photo-crosslinking in native protein-RNA complexes.

UV-crosslinking of protein and RNA in direct contacts has been widely used to study protein-RNA complexes while our understanding of the photo-crosslinking mechanisms remains poor. This knowledge gap is due to the challenge of precisely mapping the crosslink sites in protein and RNA simultaneously in their native sequence and structural contexts. Here we systematically analyze protein-RNA interactions and photo-crosslinking by bridging crosslinked nucleotides and amino acids mapped using different assays with protein-RNA complex structures. We developed a computational method PxR3D-map which reliably predicts crosslink sites using structural information characterizing protein-RNA interaction interfaces. Analysis of the informative features revealed that photo-crosslinking is facilitated by base stacking with not only aromatic residues, but also dipeptide bonds that involve glycine, and distinct mechanisms are utilized by different RNA-binding domains. Our work suggests protein-RNA photo-crosslinking is highly selective in the cellular environment, which can guide data interpretation and further technology development for UV-crosslinking-based assays.

Risks and Clinical Predictors of Hepatocellular Carcinoma in Chinese Populations: A Real-World Study of 10,359 Patients in Six Medical Centers.

Purpose: Early detection of hepatocellular carcinoma (HCC) through surveillance could reduce this cancer-associated mortality. We aimed to develop and validate algorithms using panel serum biomarkers to identify HCC in a real-world multi-center study in China. Patients and Methods: A total of 10,359 eligible subjects, including HCCs and benign liver diseases (BLDs), were recruited from six Chinese medical centers. The three nomograms were built using logistic regression and their sensitivities and specificities were carefully assessed in training and validation cohorts. HCC patients after surgical resection were followed to determine the prognostic values of these algorithms. Prospective surveillance performance was assessed in a cohort of chronic hepatitis B patients during 144 weeks follow-up. Results: Independent risk factors such as alpha-fetoprotein (AFP), lens cuinaris agglutinin-reactive fraction of AFP (AFP-L3), des-gamma-carboxy prothrombin (DCP), albumin (ALB), and total bilirubin (TBIL) obtained from train cohort were used to construct three nomograms (LAD, C-GALAD, and TAGALAD) using logistic regression. In the training and two validation cohorts, their AUCs were all over 0.900, and the higher AUCs appeared in TAGALAD and C-GALAD. Furthermore, the three nomograms could effectively stratify HCC into two groups with different survival and recurrence outcomes in follow-up validation. Notably, TAGALAD could predict HCC up to 48 weeks (AUC: 0.984) and 24 weeks (AUC: 0.900) before clinical diagnosis. Conclusion: The proposed nomograms generated from real-world Chinese populations are effective and easy-to use for HCC surveillance, diagnosis, as well as prognostic evaluation in various clinical scenarios based on data feasibility.