Posttranscriptional regulation of de novo lipogenesis by glucose-induced O-GlcNAcylation.

O-linked ß-N-acetyl glucosamine (O-GlcNAc) is attached to proteins under glucose-replete conditions; this posttranslational modification results in molecular and physiological changes that affect cell fate. Here we show that posttranslational modification of serine/arginine-rich protein kinase 2 (SRPK2) by O-GlcNAc regulates de novo lipogenesis by regulating pre-mRNA splicing. We found that O-GlcNAc transferase O-GlcNAcylated SRPK2 at a nuclear localization signal (NLS), which triggers binding of SRPK2 to importin α. Consequently, O-GlcNAcylated SRPK2 was imported into the nucleus, where it phosphorylated serine/arginine-rich proteins and promoted splicing of lipogenic pre-mRNAs. We determined that protein nuclear import by O-GlcNAcylation-dependent binding of cargo protein to importin α might be a general mechanism in cells. This work reveals a role of O-GlcNAc in posttranscriptional regulation of de novo lipogenesis, and our findings indicate that importin α is a "reader" of an O-GlcNAcylated NLS.

MetaDegron: multimodal feature-integrated protein language model for predicting E3 ligase targeted degrons.

Protein degradation through the ubiquitin proteasome system at the spatial and temporal regulation is essential for many cellular processes. E3 ligases and degradation signals (degrons), the sequences they recognize in the target proteins, are key parts of the ubiquitin-mediated proteolysis, and their interactions determine the degradation specificity and maintain cellular homeostasis. To date, only a limited number of targeted degron instances have been identified, and their properties are not yet fully characterized. To tackle on this challenge, here we develop a novel deep-learning framework, namely MetaDegron, for predicting E3 ligase targeted degron by integrating the protein language model and comprehensive featurization strategies. Through extensive evaluations using benchmark datasets and comparison with existing method, such as Degpred, we demonstrate the superior performance of MetaDegron. Among functional features, MetaDegron allows batch prediction of targeted degrons of 21 E3 ligases, and provides functional annotations and visualization of multiple degron-related structural and physicochemical features. MetaDegron is freely available at http://modinfor.com/MetaDegron/. We anticipate that MetaDegron will serve as a useful tool for the clinical and translational community to elucidate the mechanisms of regulation of protein homeostasis, cancer research, and drug development.

GPS-Uber: a hybrid-learning framework for prediction of general and E3-specific lysine ubiquitination sites.

As an important post-translational modification, lysine ubiquitination participates in numerous biological processes and is involved in human diseases, whereas the site specificity of ubiquitination is mainly decided by ubiquitin-protein ligases (E3s). Although numerous ubiquitination predictors have been developed, computational prediction of E3-specific ubiquitination sites is still a great challenge. Here, we carefully reviewed the existing tools for the prediction of general ubiquitination sites. Also, we developed a tool named GPS-Uber for the prediction of general and E3-specific ubiquitination sites. From the literature, we manually collected 1311 experimentally identified site-specific E3-substrate relations, which were classified into different clusters based on corresponding E3s at different levels. To predict general ubiquitination sites, we integrated 10 types of sequence and structure features, as well as three types of algorithms including penalized logistic regression, deep neural network and convolutional neural network. Compared with other existing tools, the general model in GPS-Uber exhibited a highly competitive accuracy, with an area under curve values of 0.7649. Then, transfer learning was adopted for each E3 cluster to construct E3-specific models, and in total 112 individual E3-specific predictors were implemented. Using GPS-Uber, we conducted a systematic prediction of human cancer-associated ubiquitination events, which could be helpful for further experimental consideration. GPS-Uber will be regularly updated, and its online service is free for academic research at http://gpsuber.biocuckoo.cn/.

CPLM 4.0: an updated database with rich annotations for protein lysine modifications.

Here, we reported the compendium of protein lysine modifications (CPLM 4.0, http://cplm.biocuckoo.cn/), a data resource for various post-translational modifications (PTMs) specifically occurred at the side-chain amino group of lysine residues in proteins. From the literature and public databases, we collected 450 378 protein lysine modification (PLM) events, and combined them with the existing data of our previously developed protein lysine modification database (PLMD 3.0). In total, CPLM 4.0 contained 592 606 experimentally identified modification events on 463 156 unique lysine residues of 105 673 proteins for up to 29 types of PLMs across 219 species. Furthermore, we carefully annotated the data using the knowledge from 102 additional resources that covered 13 aspects, including variation and mutation, disease-associated information, protein-protein interaction, protein functional annotation, DNA & RNA element, protein structure, chemical-target relation, mRNA expression, protein expression/proteomics, subcellular localization, biological pathway annotation, functional domain annotation, and physicochemical property. Compared to PLMD 3.0 and other existing resources, CPLM 4.0 achieved a >2-fold increase in collection of PLM events, with a data volume of ∼45GB. We anticipate that CPLM 4.0 can serve as a more useful database for further study of PLMs.

EPSD: a well-annotated data resource of protein phosphorylation sites in eukaryotes.

As an important post-translational modification (PTM), protein phosphorylation is involved in the regulation of almost all of biological processes in eukaryotes. Due to the rapid progress in mass spectrometry-based phosphoproteomics, a large number of phosphorylation sites (p-sites) have been characterized but remain to be curated. Here, we briefly summarized the current progresses in the development of data resources for the collection, curation, integration and annotation of p-sites in eukaryotic proteins. Also, we designed the eukaryotic phosphorylation site database (EPSD), which contained 1 616 804 experimentally identified p-sites in 209 326 phosphoproteins from 68 eukaryotic species. In EPSD, we not only collected 1 451 629 newly identified p-sites from high-throughput (HTP) phosphoproteomic studies, but also integrated known p-sites from 13 additional databases. Moreover, we carefully annotated the phosphoproteins and p-sites of eight model organisms by integrating the knowledge from 100 additional resources that covered 15 aspects, including phosphorylation regulator, genetic variation and mutation, functional annotation, structural annotation, physicochemical property, functional domain, disease-associated information, protein-protein interaction, drug-target relation, orthologous information, biological pathway, transcriptional regulator, mRNA expression, protein expression/proteomics and subcellular localization. We anticipate that the EPSD can serve as a useful resource for further analysis of eukaryotic phosphorylation. With a data volume of 14.1 GB, EPSD is free for all users at http://epsd.biocuckoo.cn/.

DrLLPS: a data resource of liquid-liquid phase separation in eukaryotes.

Here, we presented an integrative database named DrLLPS (http://llps.biocuckoo.cn/) for proteins involved in liquid-liquid phase separation (LLPS), which is a ubiquitous and crucial mechanism for spatiotemporal organization of various biochemical reactions, by creating membraneless organelles (MLOs) in eukaryotic cells. From the literature, we manually collected 150 scaffold proteins that are drivers of LLPS, 987 regulators that contribute in modulating LLPS, and 8148 potential client proteins that might be dispensable for the formation of MLOs, which were then categorized into 40 biomolecular condensates. We searched potential orthologs of these known proteins, and in total DrLLPS contained 437 887 known and potential LLPS-associated proteins in 164 eukaryotes. Furthermore, we carefully annotated LLPS-associated proteins in eight model organisms, by using the knowledge integrated from 110 widely used resources that covered 16 aspects, including protein disordered regions, domain annotations, post-translational modifications (PTMs), genetic variations, cancer mutations, molecular interactions, disease-associated information, drug-target relations, physicochemical property, protein functional annotations, protein expressions/proteomics, protein 3D structures, subcellular localizations, mRNA expressions, DNA & RNA elements, and DNA methylations. We anticipate DrLLPS can serve as a helpful resource for further analysis of LLPS.

Development and validation of a novel mRNA signature for predicting early relapse in non-small cell lung cancer.

BACKGROUND: Recurrence after initial primary resection is still a major and ultimate cause of death for non-small cell lung cancer patients. We attempted to build an early recurrence associated gene signature to improve prognostic prediction of non-small cell lung cancer. METHODS: Propensity score matching was conducted between patients in early relapse group and long-term survival group from The Cancer Genome Atlas training series (N = 579) and patients were matched 1:1. Global transcriptome analysis was then performed between the paired groups to identify tumour-specific mRNAs. Finally, using LASSO Cox regression model, we built a multi-gene early relapse classifier incorporating 40 mRNAs. The prognostic and predictive accuracy of the signature was internally validated in The Cancer Genome Atlas patients. RESULTS: A total of 40 mRNAs were finally identified to build an early relapse classifier. With specific risk score formula, patients were classified into a high-risk group and a low-risk group. Relapse-free survival was significantly different between the two groups in both discovery (HR: 3.244, 95% CI: 2.338-4.500, P < 0.001) and internal validation series (HR 1.970, 95% CI 1.181-3.289, P = 0.009). Further analysis revealed that the prognostic value of this signature was independent of tumour stage, histotype and epidermal growth factor receptor mutation (P < 0.05). Time-dependent receiver operating characteristic analysis showed that the area under receiver operating characteristic curve of this signature was higher than TNM stage alone (0.771 vs 0.686, P < 0.05). Further, decision curve analysis curves analysis at 1 year revealed the considerable clinical utility of this signature in predicting early relapse. CONCLUSIONS: We successfully established a reliable signature for predicting early relapse in stage I-III non-small cell lung cancer.

iEKPD 2.0: an update with rich annotations for eukaryotic protein kinases, protein phosphatases and proteins containing phosphoprotein-binding domains.

Here, we described the updated database iEKPD 2.0 (http://iekpd.biocuckoo.org) for eukaryotic protein kinases (PKs), protein phosphatases (PPs) and proteins containing phosphoprotein-binding domains (PPBDs), which are key molecules responsible for phosphorylation-dependent signalling networks and participate in the regulation of almost all biological processes and pathways. In total, iEKPD 2.0 contained 197 348 phosphorylation regulators, including 109 912 PKs, 23 294 PPs and 68 748 PPBD-containing proteins in 164 eukaryotic species. In particular, we provided rich annotations for the regulators of eight model organisms, especially humans, by compiling and integrating the knowledge from 100 widely used public databases that cover 13 aspects, including cancer mutations, genetic variations, disease-associated information, mRNA expression, DNA & RNA elements, DNA methylation, molecular interactions, drug-target relations, protein 3D structures, post-translational modifications, protein expressions/proteomics, subcellular localizations and protein functional annotations. Compared with our previously developed EKPD 1.0 (∼0.5 GB), iEKPD 2.0 contains ∼99.8 GB of data with an ∼200-fold increase in data volume. We anticipate that iEKPD 2.0 represents a more useful resource for further study of phosphorylation regulators.

iUUCD 2.0: an update with rich annotations for ubiquitin and ubiquitin-like conjugations.

Here, we described the updated database iUUCD 2.0 (http://iuucd.biocuckoo.org/) for ubiquitin-activating enzymes (E1s), ubiquitin-conjugating enzymes (E2s), ubiquitin-protein ligases (E3s), deubiquitinating enzymes (DUBs), ubiquitin/ubiquitin-like binding domains (UBDs) and ubiquitin-like domains (ULDs), which act as key regulators in modulating ubiquitin and ubiquitin-like (UB/UBL) conjugations. In total, iUUCD 2.0 contained 136 512 UB/UBL regulators, including 1230 E1s, 5636 E2s, 93 343 E3s, 9548 DUBs, 30 173 UBDs and 11 099 ULDs in 148 eukaryotic species. In particular, we provided rich annotations for regulators of eight model organisms, especially in humans, by compiling and integrating the knowledge from nearly 70 widely used public databases that cover cancer mutations, single nucleotide polymorphisms (SNPs), mRNA expression, DNA and RNA elements, protein-protein interactions, protein 3D structures, disease-associated information, drug-target relations, post-translational modifications, DNA methylation and protein expression/proteomics. Compared with our previously developed UUCD 1.0 (∼0.41 GB), iUUCD 2.0 has a size of ∼32.1 GB of data with a >75-fold increase in data volume. We anticipate that iUUCD 2.0 can be a more useful resource for further study of UB/UBL conjugations.

H3K9me3, H3K36me3, and H4K20me3 Expression Correlates with Patient Outcome in Esophageal Squamous Cell Carcinoma as Epigenetic Markers.

BACKGROUND: Histone methylation, as an essential pattern of posttranslational modifications, contributes to multiple cancer-related biological processes. Dysregulation of histone methylation is now considered a biomarker for cancer prognosis. AIMS: This study investigated and evaluated the potential role of four histone lysine trimethylation markers as biomarkers for esophageal squamous cell carcinoma (ESCC) prognosis. METHODS: Tissue arrays were made from 135 paraffin-embedded ESCC samples and examined for histone markers by immunohistochemistry, and 10 pairs of cancer and noncancerous mucosa tissues from ESCC patients were investigated with Western blot. Chi-squared test, Kaplan-Meier analysis with log-rank test, and Cox proportional hazard trend analyses were performed to assess the prognostic values of the markers. RESULTS: Histone 3 lysine 4 trimethylation (H3K4me3), histone 3 lysine 9 trimethylation (H3K9me3), and histone 4 lysine 20 trimethylation (H4K20me3), but not histone 3 lysine 36 trimethylation (H3K36me3), showed stronger immunostaining signals in tumor tissues than in the corresponding adjacent non-neoplastic mucosa tissues. The expression patterns of H3K36me3, H3K9me3, and H4K20me3 correlated with tumor infiltrating depth, lymph node involvement, and pTNM stage. Low-scoring H3K9me3 and H4K20me3 predicted better prognosis, while H3K36me3 manifested the opposite trend. Poor prognosis occurred in ESCC patients with expression patterns of high levels of H3K9me3, high levels of H4K20me3, and low levels of H3K36me3 expression. CONCLUSIONS: H3K9me3, H4K20me3, and H3K36me3 showed a close relationship with clinical features and were considered independent risk factors for survival of ESCC patients. The combination of H3K9me3, H4K20me3, and H3K36me3 expression, rather than the expression of a single histone marker, is believed to further enhance evaluations of ESCC prognosis and management.

WERAM: a database of writers, erasers and readers of histone acetylation and methylation in eukaryotes.

In this work, we developed a database WERAM (http://weram.biocuckoo.org/) for histone acetyltransferases, histone deacetylases, histone methyltransferases, histone demethylases and acetyl- or methyl-binding proteins, which catalyze, remove and recognize histone acetylation and methylation sites as 'writers', 'erasers' and 'readers', and synergistically determine the 'histone code'. From the scientific literature, we totally collected over 580 experimentally identified histone regulators from eight model organisms, including Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana, Schizosaccharomyces pombe and Saccharomyces cerevisiae We also collected ∼900 site-specific regulator-histone relations from the eight species. According to the experimental evidence, known histone regulators were classified into distinct families. To computationally detect more proteins in eukaryotes, we constructed hidden Markov model (HMM) profiles for histone regulator families. For families without HMM profiles, we also conducted orthologous searches. Totally, WERAM database contained more than 20 thousand non-redundant histone regulators from 148 eukaryotes. The detailed annotations and classification information of histone regulators were provided, together with site-specific histone substrates if available.

Blood lipid abnormality changes the rate of alveolar-capillary uptake of sevoflurane: a prospective, non-interventional, clinical study
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OBJECTIVE: This research studied the influence of different blood lipid components on the rate of alveolar-capillary uptake of sevoflurane. Method: 104 patients aged 20 - 50 years undergoing elective operations under general anesthesia were mechanically ventilated through endotracheal intubation after intravenous injections of midazolam, vecuronium, fentanyl, and etomidate. They inhaled 2% sevoflurane at an oxygen flow of 2 L/min, then the inspired concentrations (FI) and expired concentrations (FA of sevoflurane were recorded at 1, 3, 5, 7, 10, 15, 20, and 30 minutes. These cases were divided into a normal group and an abnormal group according to the lipid levels. Then, based on the lipid criteria, those cases with abnormal lipid levels were classified into a high-triglyceride (TG) and total-cholesterol (TC) group (group TG+TC) and a group with decreased high-density lipoprotein cholesterol (group HDL-C).The values of FA/FI and the times required to reach the titration value FA/FI = 0.8 were calculated were calculated for each group. RESULTS: Compared with the normal group, FA/FI decreased within 7 - 10 minutes (p < 0.05) and the time taken to reach the titration value was prolonged in the abnormal group (p < 0.05). The value of FA/FI decreased during 7 - 10 minutes (p < 0.05) and the time taken to reach the titration value was longer (p < 0.05) in the group TG+TC. CONCLUSIONS: The increased value of blood/gas partition coefficients (B/G) was caused by the increase in the concentrations of TG and TC in blood lipids.
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Caveolin-1 in multi drug resistance and two-field lymphadenectomy for thoracic esophageal squamous cell carcinoma.

Caveolin-1 plays a very important role in the process of tumor cell transformation. In this paper, we studied the relationship between Cav-1 and other multi drug resistance associated proteins. Moreover, the author compares outcomes according to the extent of lymphadenectomy in patients with upper and middle thoracic esophageal squamous cell carcinoma without clinical cervical metastasis. The short-term and long-term data of 842 consecutive patients who underwent esophagectomy with two-field lymphadenectomy (2FL) or three-field lymphadenectomy (3FL) between February 2005 and July 2013 were retrospectively reviewed. If postoperative infection occurred, according to susceptibility test results, patients were given sensitive antibiotics. The yield of lymph nodes harvested was higher in the 3FL group than in 2FL (P=0.000). There was less blood loss (P =0.000), shorter operative time (P=0.000) less post-operative analgesia needed (P=0.000) and earlier hospital discharge (P =0.000) in 2FL than in 3FL.Overall morbidity was similar in the two groups. However, the rate of major complications was higher after 3FL versus 2FL (P=0.015). There was no 30-day mortality in 2FL and 3FL. The 5-year survival (2FL 35% vs 3FL 38%; P=0.297) and disease-free 5-year survival (2FL 26% vs 3FL 21%; P=0.106) were comparable between the two groups. In univariate analyses, extent of lymphadenectomy was not related to overall 5-year survival. Current results indicated that 2FL may be the preferred lymphadenectomy for upper and middle thoracic esophageal squamous cell carcinoma without clinical cervical metastasis.

m7GRegpred: substrate prediction of N7-methylguanosine (m7G) writers and readers based on sequencing features.

N7-Methylguanosine (m7G) is important RNA modification at internal and the cap structure of five terminal end of message RNA. It is essential for RNA stability of RNA, the efficiency of translation, and various intracellular RNA processing pathways. Given the significance of the m7G modification, numerous studies have been conducted to predict m7G sites. To further elucidate the regulatory mechanisms surrounding m7G, we introduce a novel bioinformatics framework, m7GRegpred, designed to forecast the targets of the m7G methyltransferases METTL1 and WDR4, and m7G readers QKI5, QKI6, and QKI7 for the first time. We integrated different features to build predictors, with AUROC scores of 0.856, 0.857, 0.780, 0.776, 0.818 for METTL1, WDR4, QKI5, QKI6, and QKI7, respectively. In addition, the effect of window lengths and algorism were systemically evaluated in this work. The finial model was summarized in a user-friendly webserver: http://modinfor.com/m7GRegpred/. Our research indicates that the substrates of m7G regulators can be identified and may potentially advance the study of m7G regulators under unique conditions.

Combination of neutrophil-to-lymphocyte ratio and albumin concentration to predict the prognosis of esophageal squamous cell cancer patients undergoing esophagectomy.

Background: Esophageal squamous cell cancer (ESCC) is an aggressive cancer with high incidence and mortality. It is crucial to predict prognosis of these patients individually. Neutrophil-to-lymphocyte ratio (NLR) has been reported as a prognostic indicator in several tumors, including esophageal cancer. Besides inflammatory factors, nutritional status can impact survival of cancer patients. Albumin (Alb) concentration is an easily obtained indicator to reflect nutritional status. Methods: In this study, we retrospectively collected the data of patients with ESCC and used univariate and multivariate analysis to investigate the relationship between combination of NLR and Alb (NLR-Alb) and survival. Meanwhile, we compared clinical features among NLR-Alb cohorts. Results: Univariate analysis showed that age (P=0.013), gender (P=0.021), surgical type (P=0.031), preoperative therapy (P=0.007), NLR-Alb (P=0.001), and tumor-node-metastasis (TNM) status (P<0.001) were associated with 5-year overall survival (OS). In multivariate analysis, NLR-Alb [hazard ratio (HR) =2.53, 95% confidence interval (95% CI): 1.38-4.63, P=0.003] and TNM status (HR =4.76, 95% CI: 3.09-7.33, P<0.001) were independent predictive factors for 5-year OS. The 5-year OS rates were 83%, 62%, and 55% for NLR-Alb 1, NLR-Alb 2, and NLR-Alb 3, respectively (P=0.001). Conclusions: In summary, pre-operative NLR-Alb is a favorable and cost-effective index to predict prognosis of patients with ESCC individually.

Characterization of Tumor Mutation Burden-Based Gene Signature and Molecular Subtypes to Assist Precision Treatment in Gastric Cancer.

Objective: Tumor mutation burden (TMB) represents a useful biomarker for predicting survival outcomes and immunotherapy response. Here, we aimed to conduct TMB-based gene signature and molecular subtypes in gastric cancer. Methods: Based on differentially expressed genes (DEGs) between high- and low-TMB groups in TCGA, a LASSO model was developed for predicting overall survival (OS) and disease-free survival (DFS). The predictive performance was externally verified in the GSE84437 dataset. Molecular subtypes were conducted via consensus clustering approach based on TMB-related DEGs. The immune microenvironment was estimated by ESTIMATE and ssGSEA algorithms. Results: High-TMB patients had prolonged survival duration. TMB-related DEGs were distinctly enriched in cancer- (MAPK, P53, PI3K-Akt, and Wnt pathways) and immune-related pathways (T cell selection and differentiation). The TMB-based gene model was developed (including MATN3, UPK1B, GPX3, and RGS2), and high-risk score was predictive of poor prognosis and recurrence. ROC and multivariate analyses revealed the well predictive performance, which was confirmed in the external cohort. Furthermore, we established the nomogram containing the risk score, age, and stage for personalized prediction of OS and DFS. High-risk score was characterized by high stromal score, increased immune checkpoints, immune cell infiltrations, and enhanced sensitivity to gefitinib, vinorelbine, and gemcitabine. Three TMB-based molecular subtypes were conducted, characterized by distinct prognosis, immune microenvironment, and drug sensitivity. Conclusion: Collectively, we established a prognostic signature and three distinct molecular subtypes based on TMB features for gastric cancer, which might be beneficial for prognostic prediction and clinical decision-making.

iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death.

Programmed cell death (PCD) is an essential biological process involved in many human pathologies. According to the continuous discovery of new PCD forms, a large number of proteins have been found to regulate PCD. Notably, post-translational modifications play critical roles in PCD process and the rapid advances in proteomics have facilitated the discovery of new PCD proteins. However, an integrative resource has yet to be established for maintaining these regulatory proteins. Here, we briefly summarize the mainstream PCD forms, as well as the current progress in the development of public databases to collect, curate and annotate PCD proteins. Further, we developed a comprehensive database, with integrated annotations for programmed cell death (iPCD), which contained 1,091,014 regulatory proteins involved in 30 PCD forms across 562 eukaryotic species. From the scientific literature, we manually collected 6493 experimentally identified PCD proteins, and an orthologous search was then conducted to computationally identify more potential PCD proteins. Additionally, we provided an in-depth annotation of PCD proteins in eight model organisms, by integrating the knowledge from 102 additional resources that covered 16 aspects, including post-translational modification, protein expression/proteomics, genetic variation and mutation, functional annotation, structural annotation, physicochemical property, functional domain, disease-associated information, protein-protein interaction, drug-target relation, orthologous information, biological pathway, transcriptional regulator, mRNA expression, subcellular localization and DNA and RNA element. With a data volume of 125 GB, we anticipate that iPCD can serve as a highly useful resource for further analysis of PCD in eukaryotes.

Multi-Region Genomic Landscape Analysis for the Preoperative Prediction of Lymph Node Metastasis in Esophageal Carcinoma.

Objective: Esophageal cancer is an aggressive malignant tumor, with 90 percent of the patients prone to recurrence and metastasis. Although recent studies have identified some potential biomarkers, these biomarkers' clinical or pathological significance is still unclear. Therefore, it is urgent to further identify and study novel molecular changes occurring in esophageal cancer. It has positive clinical significance to identify a tumor-specific mutation in patients after surgery for an effective intervention to improve the prognosis of patients. Methods: In this study, we performed whole-exome sequencing (WES) on 33 tissue samples from six esophageal cancer patients with lymph node metastasis, compared the differences in the genomic and evolutionary maps in different tissues, and then performed pathway enrichment analysis on non-synonymous mutation genes. Finally, we sorted out the somatic mutation data of all patients to analyze the subclonality of each tumor. Results: There were significant differences in somatic mutations between the metastatic lymph nodes and primary lesions in the six patients. Clustering results of pathway enrichment analysis indicated that the metastatic lymph nodes had certain commonalities. Tumors of the cloned exploration results illustrated that five patients showed substantial heterogeneity. Conclusion: WES technology can be used to explore the differences in regional evolutionary maps, heterogeneity, and detect patients' tumor-specific mutations. In addition, an in-depth understanding of the ontogeny and phylogeny of tumor heterogeneity can help to further find new molecular changes in esophageal cancer, which can improve the prognosis of EC patients and provide a valuable reference for their diagnosis.

PIM1 promotes hepatic conversion by suppressing reprogramming-induced ferroptosis and cell cycle arrest.

Protein kinase-mediated phosphorylation plays a critical role in many biological processes. However, the identification of key regulatory kinases is still a great challenge. Here, we develop a trans-omics-based method, central kinase inference, to predict potentially key kinases by integrating quantitative transcriptomic and phosphoproteomic data. Using known kinases associated with anti-cancer drug resistance, the accuracy of our method denoted by the area under the curve is 5.2% to 29.5% higher than Kinase-Substrate Enrichment Analysis. We further use this method to analyze trans-omic data in hepatocyte maturation and hepatic reprogramming of human dermal fibroblasts, uncovering 5 kinases as regulators in the two processes. Further experiments reveal that a serine/threonine kinase, PIM1, promotes hepatic conversion and protects human dermal fibroblasts from reprogramming-induced ferroptosis and cell cycle arrest. This study not only reveals new regulatory kinases, but also provides a helpful method that might be extended to predict central kinases involved in other biological processes.

Comparison of a modified one-piece mechanical and double-layer hand-sewn anastomosis in McKeown esophagogastrectomy: A single-institute retrospective study.

The present study aimed to introduce a novel method of cervical esophagogastric anastomosis, so-called 'modified one-piece mechanical anastomosis' (MOMA) in McKeown esophagogastrectomy and to compare its feasibility, efficacy and safety with those of 'conventionally double-layer hand-sewn anastomosis' (CDHA). Between March 2016 and March 2018, 80 consecutive patients with thoracic esophageal squamous cell carcinoma undergoing McKeown esophagogastrectomy with a curative intent were included in the present study. Among them, 40 received MOMA and the other 40 received CDHA. Their medical records, including operation time, anastomotic time, estimated blood loss, postoperative complications within 30 days, as well as survival rate, were retrospectively reviewed, analyzed and compared. Total operation time, anastomotic time and estimated blood loss in the MOMA group were significantly decreased compared with those in the CDHA group (207.73±2.66 vs. 225.40±3.43 min; 10.95±0.44 vs. 23.03±0.47 min; 144.50±21.14 vs. 241.75±23.75 ml; all P<0.01). Anastomotic leakage was present in 1 patient in the CDHA group, but no patients in the MOMA group (P=1.000). Anastomotic stenosis was documented in 4 and 2 patients in the MOMA and CDHA group, respectively (P=0.392). The 30-day operative mortality was 0% and no significant difference was demonstrated in postoperative complications within groups (P>0.05). Furthermore, the disease-free and overall survival was compared by means of Kaplan-Meier survival estimates and log-rank tests and no statistical difference was determined (P=0.5114 and P=0.7875, respectively). McKeown esophagogastrectomy with MOMA may be a feasible, effective and reproducible alternative with relatively satisfactory postoperative outcomes for the treatment of TE-SCC, providing shorter operation and anastomosis times, and less estimated intraoperative blood loss.