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.

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.

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.

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.

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.

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.

Combination of albumin concentration and neutrophil-to-lymphocyte ratio for predicting overall survival of patients with non-small cell lung cancer.

BACKGROUND: Lung cancer contributes significantly to the total of cancer-linked deaths globally, accounting for 1.3 million deaths each year. Preoperative albumin (Alb) concentration and neutrophil-to-lymphocyte ratio (NLR) may reflect chronic inflammation and be used to predict lung cancer outcomes. METHODS: The clinical records of 293 patients with non-small cell lung cancer (NSCLC) in Fujian Medical University Cancer Hospital & Fujian Cancer Hospital were reviewed retrospectively in this current study. Clinicopathologic pretreatment, including NLR, Glasgow prognostic score (GPS), and post-treatment value, such as tumor-node-metastasis (TNM) were documented. The cut-off finder application was employed to calculate the optimal threshold values. The significance of Alb concentration combined with NLR (COA-NLR) on the prediction of overall survival (OS) was explored using Kaplan-Meier analysis along with Cox proportional hazards. RESULTS: The results revealed that COA-NLR could independently assess the OS of patients with NSCLC [hazard ratio (HR) =1.952, 95% confidence interval (CI): 1.367 to 2.647, P<0.001]. Moreover, the 3-year OS rates were 87.2%, 68.5%, and 52.8% for the COA-NLR =0, COA-NLR =1, and COA-NLR =2, respectively (P<0.001). CONCLUSIONS: Preoperative COA-NLR value can effectively stratifies prognosis in NSCLC patients by classified patients into three independent groups. It can be adopted as an effective biomarker for prognosis in NSCLC patients treated with resection.

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.

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.

Hypoxia-inducible factor-1α cooperates with histone Lys methylation to predict prognosis in esophageal squamous cell carcinoma.

Aim: To investigate hypoxia-inducible factor-1α (HIF-1α) and histone methylation markers as potential indicators of prognosis in esophageal squamous cell carcinoma (ESCC). Patients & methods: The prognostic value of HIF-1α and histone methylation markers levels was analyzed using Kaplan-Meier survival analysis. Results: HIF-1α protein expression was higher in ESCC tumors than in paracancerous tissues. Histone H3 Lys9 trimethylation (H3K9me3), histone H3 Lys27 trimethylation (H3K27me3), histone H3 Lys4 trimethylation (H3K4me3) and histone H4 Lys20 trimethylation (H4K20me3) were significantly upregulated in ESCC tissues. HIF-1α was only positively correlated with H3K9me3 and H3K4me3 expression. Kaplan-Meier analysis indicated that H3K9me3, H3K27me3, H4K20me3 and histone H3 Lys36 trimethylation (H3K36me3) were independent indicators of prognosis for ESCC. Conclusion: This study identified a pattern of epigenetic methylation markers and HIF-1α expression in ESCC, and their combined evaluation might improve survival prediction for ESCC patients.

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.

Atg9-centered multi-omics integration reveals new autophagy regulators in Saccharomyces cerevisiae.

In Saccharomyces cerevisiae, Atg9 is an important autophagy-related (Atg) protein, and interacts with hundreds of other proteins. How many Atg9-interacting proteins are involved in macroautophagy/autophagy is unclear. Here, we conducted a multi-omic profiling of Atg9-dependent molecular landscapes during nitrogen starvation-induced autophagy, and identified 290 and 256 genes to be markedly regulated by ATG9 in transcriptional and translational levels, respectively. Unexpectedly, we found most of known Atg proteins and autophagy regulators that interact with Atg9 were not significantly changed in the mRNA or protein level during autophagy. Based on a hypothesis that proteins with similar molecular characteristics might have similar functions, we developed a new method named inference of functional interacting partners (iFIP) to integrate the transcriptomic, proteomic and interactomic data, and predicted 42 Atg9-interacting proteins to be potentially involved in autophagy, including 15 known Atg proteins or autophagy regulators. We validated 2 Atg9-interacting partners, Glo3 and Scs7, to be functional in both bulk and selective autophagy. The mRNA and protein expressions but not subcellular localizations of Glo3 and Scs7 were affected with or without ATG9 during autophagy, whereas the colocalizations of the 2 proteins and Atg9 were markedly enhanced at early stages of the autophagic process. Further analyses demonstrated that Glo3 but not Scs7 regulates the retrograde transport of Atg9 during autophagy. A working model was illustrated to highlight the importance of the Atg9 interactome. Taken together, our study not only provided a powerful method for analyzing the multi-omics data, but also revealed 2 new players that regulate autophagy.Abbreviations: ALP: alkaline phosphatase; Arf1: ADP-ribosylation factor 1; Atg: autophagy-related; Co-IP: co-immunoprecipitation; Cvt: cytoplasm-to-vacuole targeting; DEM: differentially expressed mRNA; DEP: differentially expressed protein; DIC: differential interference contrast; E-ratio: enrichment ratio; ER: endoplasmic reticulum; ES: enrichment score; FC: fold change; FPKM: fragments per kilobase of exon per million fragments mapped; GAP: GTPase-activating protein; GFP: green fluorescent protein; GO: gene ontology; GSEA: gene set enrichment analysis; GST: glutathione S-transferase; HA: hemagglutinin; iFIP: inference of functional interacting partners; KO: knockout; LR: logistic regression; OE: over-expression; PAS: phagophore assembly site; PPI: protein-protein interaction; RFP: red fluorescence protein; RNA-seq: RNA sequencing; RT-PCR: real-time polymerase chain reaction; SCC: Spearman's correlation coefficient; SD-N: synthetic minimal medium lacking nitrogen; THANATOS: The Autophagy, Necrosis, ApopTosis OrchestratorS; Vsn: variance stabilization normalization; WT: wild-type.

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/.

Impact of treatment modality on long-term survival of stage IA small-cell lung cancer patients: a cohort study of the U.S. SEER database.

BACKGROUND: The optimal treatment modality for patients with stage IA (T1N0M0) small-cell lung cancer (SCLC) is still unclear. METHODS: Patients who received surgical resection or chemo-radiotherapy (CRT) between January 2004 and December 2014 were identified from The Surveillance, Epidemiology and End Results (SEER) database. Surgical resection included lobectomy, wedge resection, segmentectomy with lymphadenectomy [examined lymph node (ELN) ≥1]. Propensity score match analysis was utilized to balance the baseline characteristics. RESULTS: A total of 686 stage IA SCLC cases were included: 337 patients underwent surgery and 349 patients were treated by CRT alone. Surgery achieved a better outcome than CRT alone, with an adjusted hazard ratio (HR) of 0.495. Patients who underwent lobectomy demonstrated a longer overall survival (OS), compared to those who received sublobectomy (crude cohort, median OS, 69 vs. 38 months; match cohort, median OS, 67 vs. 38 months). Patients with ELN >7 presented with longer OS than those with ELN ≤7 (crude cohort, median OS, 91 vs. 49 months; matched cohort, median OS, 91 vs. 54 months). The additional efficacy of chemotherapy or radiotherapy in patients receiving lobectomy was observed. The best prognosis was achieved in the lobectomy plus CRT cohort, with a 5-year survival rate of 73.5%. CONCLUSIONS: The prolonged survival associated with lobectomy and chemotherapy or radiotherapy presents a viable treatment option in the management of patients with stage IA SCLC.

PTMsnp: A Web Server for the Identification of Driver Mutations That Affect Protein Post-translational Modification.

High-throughput sequencing technologies have identified millions of genetic mutations in multiple human diseases. However, the interpretation of the pathogenesis of these mutations and the discovery of driver genes that dominate disease progression is still a major challenge. Combining functional features such as protein post-translational modification (PTM) with genetic mutations is an effective way to predict such alterations. Here, we present PTMsnp, a web server that implements a Bayesian hierarchical model to identify driver genetic mutations targeting PTM sites. PTMsnp accepts genetic mutations in a standard variant call format or tabular format as input and outputs several interactive charts of PTM-related mutations that potentially affect PTMs. Additional functional annotations are performed to evaluate the impact of PTM-related mutations on protein structure and function, as well as to classify variants relevant to Mendelian disease. A total of 4,11,574 modification sites from 33 different types of PTMs and 1,776,848 somatic mutations from TCGA across 33 different cancer types are integrated into the web server, enabling identification of candidate cancer driver genes based on PTM. Applications of PTMsnp to the cancer cohorts and a GWAS dataset of type 2 diabetes identified a set of potential drivers together with several known disease-related genes, indicating its reliability in distinguishing disease-related mutations and providing potential molecular targets for new therapeutic strategies. PTMsnp is freely available at: http://ptmsnp.renlab.org.

LINC00673 Represses CDKN2C and Promotes the Proliferation of Esophageal Squamous Cell Carcinoma Cells by EZH2-Mediated H3K27 Trimethylation.

Long non-coding RNAs (lncRNAs), some of the most abundant epigenetic regulators, play an important role in esophageal squamous cell carcinoma (ESCC). In the current study, the functions and mechanisms of the lncRNA LINC00673 were investigated. The expression levels of LINC00673 and its potential target genes were assessed by quantitative real-time polymerase chain reaction (qPCR) in ESCC surgical specimens and ESCC cell lines. RNA fluorescence in situ hybridization (RNA FISH) was employed to detect the subcellular location and the levels of LINC00673 in ESCC samples from patients with different survival times. LINC00673 function in ESCC carcinogenesis was also evaluated in vivo and in vitro. Cell cycle synchronization was performed using serum withdrawal; the cell cycle was monitored by fluorescence analysis and cellular DNA was detected by flow cytometry. The molecular mechanisms underlying LINC00673 were explored via Western blotting, chromatin immunoprecipitation (ChIP), and ChIP-PCR. Up-regulated LINC00673 was associated with poor prognosis in ESCC patients and promoted the proliferation of ESCC cells both in vitro and in vivo. Compared to the control group, depletion of LINC00673 in ESCC cells arrested the cell cycle, at least, at the G1/S checkpoint. Knockdown of LINC00673 significantly enhanced posttranscriptional expression of CDKN2C, and histone 3 lysine 27 trimethylation (H3K27me3) was enriched at the promoter region of CDKN2C. After inhibiting EZH2, the CDKN2C expression levels were increased. The present findings are the first to reveal that LINC00673 represses CDKN2C expression and promotes ESCC cell proliferation by elevating EZH2-mediated H3K27me3 levels. These data suggest that LINC00673 regulates the cell cycle in ESCC and that it is a promising target for clinical therapy.

Evaluating the Potential of T Cell Receptor Repertoires in Predicting the Prognosis of Resectable Non-Small Cell Lung Cancers.

For resectable cancer patients, a method that could precisely predict the risk of postoperative recurrence would be crucial for guiding adjuvant treatment. Since T cell receptor (TCR) repertoires had been shown to be closely related to the dynamics of cancers, here we enrolled a cohort of patients to evaluate the potential of TCR repertoires in predicting the prognosis of resectable non-small cell lung cancers. Specifically, TCRß repertoires were analyzed in surgical tumor tissues and matched adjacent non-tumor tissues from 39 patients enrolled with resectable non-small cell lung cancer, through target enrichment and high-throughput sequencing. As a result, there are significant differences between the TCR repertories of tumor samples and those of matched adjacent non-tumor samples as evaluated by criteria like the number of clonotypes. In addition, TCR repertoires were significantly associated with a few clinical features, as well as somatic mutations. Finally, certain TCRß variable-joining (V-J) pairings were featured to build a logistic regression model in predicting postoperative recurrence of resectable non-small cell lung cancers with a testing area under the receiver operating characteristic curve (AUC) of around 0.9. Thus, we hypothesize that TCR repertoires could be potentially used to predict prognosis after curative surgery for non-small cell lung cancer patients.

Integrated omics in Drosophila uncover a circadian kinome.

Most organisms on the earth exhibit circadian rhythms in behavior and physiology, which are driven by endogenous clocks. Phosphorylation plays a central role in timing the clock, but how this contributes to overt rhythms is unclear. Here we conduct phosphoproteomics in conjunction with transcriptomic and proteomic profiling using fly heads. By developing a pipeline for integrating multi-omics data, we identify 789 (~17%) phosphorylation sites with circadian oscillations. We predict 27 potential circadian kinases to participate in phosphorylating these sites, including 7 previously known to function in the clock. We screen the remaining 20 kinases for effects on circadian rhythms and find an additional 3 to be involved in regulating locomotor rhythm. We re-construct a signal web that includes the 10 circadian kinases and identify GASKET as a potentially important regulator. Taken together, we uncover a circadian kinome that potentially shapes the temporal pattern of the entire circadian molecular landscapes.

Reduction sensitive nanocarriers mPEG-g-γ-PGA/SSBPEI@siRNA for effective targeted delivery of survivin siRNA against NSCLC.

Poly γ-glutamic acid (γ-PGA) is attractive due to its desirable biological properties such as nontoxicity, excellent biocompatibility, and minimal immunogenicity. Additionally, γ-PGA could be recognized by γ-glutamyl transpeptidase, which is regarded as a potential biomarker for many tumors. In this study, we have developed a new biodegradable, reduction sensitive, and tumor-specific gene nano-delivery platform consisting of a cationic carrier (SSBPEI) for siRNA condensation, mPEG shell for nanoparticle stabilization, and γ-PGA for accelerated cellular uptake. Disulfide bonds (-SS-) could be reduced specifically in the tumor environment, which is full of reductants such as glutathione reductase. Conjugating polyethylene glycol (PEG) to the γ-PGA led to the formation of mPEG-g-γ-PGA, with a decreased positive charge on the surface of SSBPEI@siRNA and substantially higher stability in an aqueous medium. As a result, mPEG-g-γ-PGA/SSBPEI@siRNA nanoparticles could protect siRNAs from RNase A degradation and release siRNAs in a reduction sensitive way. The multifunctional delivery system was shown to silence the Survivin gene and further promote chemotherapeutic drug-induced apoptosis in the A549 NSCLC cell line efficiently, thereby representing a novel promising platform for the delivery of siRNAs.