A new prognostic model of esophageal squamous cell carcinoma based on Cloud-least squares support vector machine.

Background: In view of the low accuracy of the prognosis model of esophageal squamous cell carcinoma (ESCC), this study aimed to optimize the least squares support vector machine (LSSVM) algorithm to determine the uncertain prognostic factors using a Cloud model, and consequently, to establish a new high-precision prognosis model of ESCC. Methods: We studied 4,771 ESCC patients(training samples) from the Surveillance, Epidemiology, and End Results (SEER) database and 635 ESCC patients(validation samples) from the Henan Provincial Center for Disease Control and Prevention (HCDC) database, with the same exclusion criteria and inclusion criteria for both databases, and obtained permission to obtain a research data file in the SEER database from the National Cancer Institute. The independent risk factors were analyzed using the log-rank method, survival curves, univariate and multivariate Cox analysis. Finally, the independent prognostic factors were used to construct the nomogram, random forest and Cloud-LSSVM prognostic models were utilized for validation. Results: The overall median survival time of the SEER database was 14 months (HCDC samples was 46 months), the mean survival time was 26.5 months (HCDC samples was 36.8 months), and the 3-year survival rate was 65.8%. This is because most of the patients with Henan samples are early ESCC, and most of the Seer patients are T3 and T4 people. The multivariate Cox analysis showed that age at diagnosis (P<0.001), sex (P=0.001), race (P=0.002), differentiation grade (P<0.001), pathologic T category (P<0.001), and pathologic M category (P<0.001) were the factors affecting the prognosis of ESCC patients. The SEER data and HCDC database results showed that the accuracy of the Cloud-LSSVM (C-index =0.71, 0.689) model is higher than the differentiation grade (C-index =0.548, 0.506), random forest (C-index =0.649, 0.498), and nomogram (C-index =0.659, 0.563). This new model can realize the unity of the randomness and fuzziness of the Cloud model and utilize the powerful learning and non-linear mapping abilities of LSSVM. Conclusions: Due to the difference of clans between training samples and test samples, the accuracy of prediction is generally not high, but the accuracy of Cloud-LSSVM model is much higher than other models. The new model provides a clear prognostic superiority over the random forest, nomogram, and other models.

N-linked glycoproteomic profiling in esophageal squamous cell carcinoma.

BACKGROUND: Mass spectrometry-based proteomics and glycomics reveal post-translational modifications providing significant biological insights beyond the scope of genomic sequencing. AIM: To characterize the N-linked glycoproteomic profile in esophageal squamous cell carcinoma (ESCC) via two complementary approaches. METHODS: Using tandem multilectin affinity chromatography for enrichment of N-linked glycoproteins, we performed N-linked glycoproteomic profiling in ESCC tissues by two-dimensional gel electrophoresis (2-DE)-based and isobaric tags for relative and absolute quantification (iTRAQ) labeling-based mass spectrometry quantitation in parallel, followed by validation of candidate glycoprotein biomarkers by Western blot. RESULTS: 2-DE-based and iTRAQ labeling-based quantitation identified 24 and 402 differentially expressed N-linked glycoproteins, respectively, with 15 in common, demonstrating the outperformance of iTRAQ labeling-based quantitation over 2-DE and complementarity of these two approaches. Proteomaps showed the distinct compositions of functional categories between proteins and glycoproteins with differential expression associated with ESCC. Western blot analysis validated the up-regulation of total procathepsin D and high-mannose procathepsin D, and the down-regulation of total haptoglobin, high-mannose clusterin, and GlcNAc/sialic acid-containing fraction of 14-3-3ζ in ESCC tissues. The serum levels of glycosylated fractions of clusterin, proline-arginine-rich end leucine-rich repeat protein, and haptoglobin in patients with ESCC were remarkably higher than those in healthy controls. CONCLUSION: Our study provides insights into the aberrant N-linked glycoproteome associated with ESCC, which will be a valuable resource for future investigations.

A Prognostic Model Based on mRNA Expression Analysis of Esophageal Squamous Cell Carcinoma.

Background: The aim of this study was to identify prognostic markers for esophageal squamous cell carcinoma (ESCC) and build an effective prognostic nomogram for ESCC. Methods: A total of 365 patients with ESCC from three medical centers were divided into four cohorts. In the discovery phase of the study, we analyzed transcriptional data from 179 cancer tissue samples and identified nine marker genes using edgeR and rbsurv packages. In the training phase, penalized Cox regression was used to select the best marker genes and clinical characteristics in the 179 samples. In the verification phase, these marker genes and clinical characteristics were verified by internal validation cohort (n = 58) and two external cohorts (n = 81, n = 105). Results: We constructed and verified a nomogram model based on multiple clinicopathologic characteristics and gene expression of a patient cohort undergoing esophagectomy and adjuvant radiochemotherapy. The predictive accuracy for 4-year overall survival (OS) indicated by the C-index was 0.75 (95% CI, 0.72-0.78), which was statistically significantly higher than that of the American Joint Committee on Cancer (AJCC) seventh edition (0.65). Furthermore, we found two marker genes (TM9SF1, PDZK1IP) directly related to the OS of esophageal cancer. Conclusion: The nomogram presented in this study can accurately and impersonally predict the prognosis of ESCC patients after partial resection of the esophagus. More research is required to determine whether it can be applied to other patient populations. Moreover, we found two marker genes directly related to the prognosis of ESCC, which will provide a basis for future research.

Porphyromonas gingivalis promotes progression of esophageal squamous cell cancer via TGFß-dependent Smad/YAP/TAZ signaling.

Microbial dysbiosis in the upper digestive tract is linked to an increased risk of esophageal squamous cell carcinoma (ESCC). Overabundance of Porphyromonas gingivalis is associated with shorter survival of ESCC patients. We investigated the molecular mechanisms driving aggressive progression of ESCC by P. gingivalis. Intracellular invasion of P. gingivalis potentiated proliferation, migration, invasion, and metastasis abilities of ESCC cells via transforming growth factor-ß (TGFß)-dependent Drosophila mothers against decapentaplegic homologs (Smads)/Yes-associated protein (YAP)/Transcriptional coactivator with PDZ-binding motif (TAZ) activation. Smads/YAP/TAZ/TEA domain transcription factor1 (TEAD1) complex formation was essential to initiate downstream target gene expression, inducing an epithelial-mesenchymal transition (EMT) and stemness features. Furthermore, P. gingivalis augmented secretion and bioactivity of TGFß through glycoprotein A repetitions predominant (GARP) up-regulation. Accordingly, disruption of either the GARP/TGFß axis or its activated Smads/YAP/TAZ complex abrogated the tumor-promoting role of P. gingivalis. P. gingivalis signature genes based on its activated effector molecules can efficiently distinguish ESCC patients into low- and high-risk groups. Targeting P. gingivalis or its activated effectors may provide novel insights into clinical management of ESCC.

[Effect and mechanism of Bidens pilosa decoction on non-alcoholic fatty liver induced by high fat and high glucose in mice].

This study aimed to investigate the effect and possible mechanism of Bidens pilosa decoction on non-alcoholic fatty liver disease(NAFLD) induced by high fat and high glucose in mice. Bald/c mice were randomly divided into normal group, model group, metformin(200 mg·kg~(-1)) treatment group, Bidens pilosa decoction(10 g·kg~(-1)) treatment group, metformin and B. pilosa decoction(100 mg·kg~(-1)+5 g·kg~(-1)) treatment group. Except for the normal group, mice in the other four groups were fed with high-fat and high-glucose diet for 8 weeks to establish the non-alcoholic fatty liver model. After 4 weeks of treatment, blood was collected from the eyeballs, the mice were sacrificed, and relevant indicators were detected. The results showed that compared with the model group, blood lipid and blood glucose levels of each treatment group were significantly lower(P<0.05); HE staining results showed that liver pathological damage in each treatment group was significantly improved; oil red O staining results showed fat distribution in each treatment group significantly reduced(P<0.01); immunohistochemical staining showed that glucose regulated the protein expression of protein 78(GRP78) in liver tissues of each treatment group was also significantly reduced(P<0.01); Western blot results showed that endoplasmic reticulum stress signal pathway-related factors GRP78, phosphorylated-protein kinase R-like ER kinase(p-PERK), eukaryotic translation-initiation factor 2α(eIF2α), activating transcription factor 4(ATF4), C/EBP homologous protein(Chop), inositol requiring 1α(IRE1α), and cleaved-cysteinyl aspartate specific proteinase 12(cleaved-caspase-12) were significantly reduced(P<0.01). The results of the combined drug treatment group were better than those of the single drug treatment group. These results showed that B. pilosa decoction had the effect in improving non-alcoholic fatty liver, and its mechanism may be related to the down-regulation of the expression of endoplasmic reticulum stress(ERS)-related factors, and the reduction of the apoptosis of hepatocytes caused by ERS and the down-regulation of blood lipid and blood glucose levels.

Macrophage migration inhibitory factor promotes tumor aggressiveness of esophageal squamous cell carcinoma via activation of Akt and inactivation of GSK3ß.

The pleiotropic pro-inflammatory cytokine, macrophage migration inhibitory factor (MIF), represents an important link between chronic inflammation and tumorigenesis. Although accumulating evidence demonstrates that MIF overexpression is implicated in the development and progression of multiple cancers, including esophageal squamous cell carcinoma (ESCC), the molecular mechanisms underlying its tumor-promoting roles in ESCC remain unclear. In the present study, we observed that MIF is overexpressed in ESCC and correlated significantly with lymph node metastasis, advanced clinical stage, and poor survival of ESCC. MIF knockdown attenuated the proliferation, migration, and invasion of ESCC cells in vitro and in vivo. Moreover, blockage of MIF expression decreased the activation of the Akt, MEK/ERK, and NF-κB pathways and enhanced sensitivity to apoptosis. Meanwhile, repression of MIF expression resulted in activation of glycogen synthase kinase 3 beta (GSK3ß) and subsequent decrease of active ß-catenin, as well as its downstream targets including cyclin D1, matrix metalloproteinase (MMP)-7, c-myc, and c-Jun. Collectively, our results provided mechanistic insights into the tumor-promoting role of MIF in ESCC, and suggested that MIF represents a potential therapeutic target for treatment of ESCC.