TANGO1 interacts with NRTN to promote hepatocellular carcinoma progression by regulating the PI3K/AKT/mTOR signaling pathway.

Transport and Golgi organization 1 (TANGO1) also known as MIA3, belongs to the melanoma inhibitory activity gene (MIA) family together with MIA, MIA2 and OTOR; these members play different roles in different tumors, but the mechanism underlying TANGO1s effect on hepatocellular carcinoma (HCC) is unclear. Our study confirmed that TANGO1 is a promoter of HCC, In HCC cells, TANGO1 can promote proliferation, inhibit apoptosis, promote EMT. These changes were reversed after TANGO1 inhibition. We explored the molecular mechanism of TANGO1 and HCC and found that the promoting effect of TANGO1 on HCC related to neurturin (NRTN) and the PI3K/AKT/mTOR signaling pathway based on RNA-seq results. NRTN is not only related to neuronal growth, differentiation and maintenance but is also involved in a variety of tumorigenic processes, and PI3K/AKT/mTOR signaling pathway has been shown to be involved in HCC progression. We verified that TANGO1 interacts with NRTN in HCC cells using endogenous Co-IP and confocal localization, and both promote HCC progression by activating the PI3K/AKT/mTOR signaling pathway. Our results reveal the mechanism by which TANGO1 promotes HCC progression, suggesting that the TANGO1/NRTN axis may be a potential therapeutic target for HCC worthy of further investigation.

Integration of IDPC Clustering Analysis and Interpretable Machine Learning for Survival Risk Prediction of Patients with ESCC.

Precise forecasting of survival risk plays a pivotal role in comprehending and predicting the prognosis of patients afflicted with esophageal squamous cell carcinoma (ESCC). The existing methods have the problems of insufficient fitting ability and poor interpretability. To address this issue, this work proposes a novel interpretable survival risk prediction method for ESCC patients based on extreme gradient boosting improved by whale optimization algorithm (WOA-XGBoost) and shapley additive explanations (SHAP). Given the imbalanced nature of the data set, the adaptive synthetic sampling (ADASYN) is first used to generate the samples with high survival risk. Then, an improved clustering by fast search and find of density peaks (IDPC) algorithm based on cosine distance and K nearest neighbors is used to cluster the patients. Next, the prediction model for each cluster is obtained by WOA-XGBoost and the constructed model is visualized with SHAP to uncover the factors hidden in the structured model and improve the interpretability of the black-box model. Finally, the effectiveness of the proposed scheme is demonstrated by analyzing the data collected from the First Affiliated Hospital of Zhengzhou University. The results of the analysis reveal that the proposed methodology exhibits superior performance, as indicated by the area under the receiver operating characteristic curve (AUROC) of 0.918 and accuracy of 0.881.

The High Expression of p53 Is Predictive of Poor Survival Rather TP53 Mutation in Esophageal Squamous Cell Carcinoma.

TP53 is a well-known tumor suppressor gene and one of the most common genetic alterations in human cancers. However, the role of p53 as a prognostic marker of esophageal squamous cell carcinoma (ESCC) is controversial in the association between TP53 alterations and clinical outcomes. To address this issue, we evaluated TP53 mutations, p53 protein expression, clinicopathological parameters, and survivals rates in a large scale of patients with ESCC. Two cohorts were included in this study: TP53 mutations were detected by next-generation sequencing in 316 ESCC patients, and p53 protein expression was tested by immunohistochemistry in 6,028 ESCC patients. Survival analysis was performed using the Kaplan-Meier curve and the Cox proportional hazards model. TP53 mutations were found in ESCC patients from 241 of 316 (76.3%), and the rate of positive expression of p53 protein was 59.1% in 6,028 ESCC patients (including 1819 with high expression of p53 protein), respectively. Most mutations were missense, which has a high expression of p53 protein. Compared with wild-typeTP53, TP53 gene mutations were not significantly associated with survival time (p=0.083). In multivariate analysis, the p53 protein expression was an independent prognostic factor for ESCC. The high-expression group of p53 protein has poor survival (p < 0.001) compared to low-expression group in patients with ESCC. The high expression of the p53 protein, not the TP53 mutation, is predictive of poor survival in patients with ESCC, and p53 protein expression might have the potential to be a prognosis biomarker and therapy target in ESCC.

Krüppel-like Factor 13 Promotes HCC Progression by Transcriptional Regulation of HMGCS1-mediated Cholesterol Synthesis.

Background and Aims: Krüppel-like factor (KLF) has a role in the occurrence, development and metabolism of cancer. We aimed to explore the role and potential molecular mechanism of KLF13 in the growth and migration of liver cancer cells. Methods: The expression of KLF13 in hepatocellular carcinoma (HCC) tissues was higher than that in normal tissues according to analysis of The Cancer Genome Atlas (TCGA) database. Lentiviral plasmids were used for overexpression and plasmid knockdown of KLF13. Real-time quantitative polymerase chain reaction (qPCR) and western blotting were used to detect mRNA and protein expression in HCC tissues and cells. Cell counting kit-8 (CCK-8), colony formation, cell migration and invasion, and flow cytometry assays were used to assess the in vitro function of KLF13 in HCC cells. The effect of KLF13 on xenograft tumor growth in vivo was evaluated. The cholesterol content of HCC cells was determined by an indicator kit. A dual-luciferase reporter assay and chromatin immunoprecipitation sequencing (ChIP-seq) revealed the binding relationship between KLF13 and HMGCS1. Results: The expression of KLF13 was upregulated in HCC tissues and TCGA database. KLF13 knockdown inhibited the proliferation, migration and invasion of HepG2 and Huh7 cells and increased the apoptosis of Huh7 cells. The opposite effects were observed with the overexpression of KLF13 in SK-Hep1 and MHCC-97H cells. The overexpression of KLF13 promoted the growth of HCC in nude mice and KLF13 transcription promoted the expression of HMGCS1 and the biosynthesis of cholesterol. KLF13 knockdown inhibited cholesterol biosynthesis mediated by HMGCS1 and inhibited the growth and metastasis of HCC cells. Conclusions: KLF13 acted as a tumor promoter in HCC by positively regulating HMGCS1-mediated cholesterol biosynthesis.

Multistrategy Improved Sparrow Search Algorithm Optimized Deep Neural Network for Esophageal Cancer.

Deep neural network is a complex pattern recognition network system. It is widely favored by scholars for its strong nonlinear fitting ability. However, training deep neural network models on small datasets typically realizes worse performance than shallow neural network. In this study, a strategy to improve the sparrow search algorithm based on the iterative map, iterative perturbation, and Gaussian mutation is developed. This optimized strategy improved the sparrow search algorithm validated by fourteen benchmark functions, and the algorithm has the best search accuracy and the fastest convergence speed. An algorithm based on the iterative map, iterative perturbation, and Gaussian mutation improved sparrow search algorithm is designed to optimize deep neural networks. The modified sparrow algorithm is exploited to search for the optimal connection weights of deep neural network. This algorithm is implemented for the esophageal cancer dataset along with the other six algorithms. The proposed model is able to achieve 0.92 under all the eight scoring criteria, which is better than the performance of the other six algorithms. Therefore, an optimized deep neural network based on an improved sparrow search algorithm with iterative map, iterative perturbation, and Gaussian mutation is an effective approach to predict the survival rate of esophageal cancer.

Clinicopathological characterization of ten patients with primary malignant melanoma of the esophagus and literature review.

BACKGROUND: Primary malignant melanoma of the esophagus (PMME) is a rare malignant disease and has not been well characterized in terms of clinicopathology and survival. AIM: To investigate the clinical features and survival factors in Chinese patients with PMME. METHODS: The clinicopathological findings of ten cases with PMME treated at Henan Provincial People's Hospital were summarized. Moreover, the English- and Chinese-language literature that focused on Chinese patients with PMME from 1980 to September 2021 was reviewed and analyzed. Univariate and multivariate analyses were employed to investigate the clinicopathologic factors that might be associated with survival. RESULTS: A total of 290 Chinese patients with PMME, including ten from our hospital and 280 from the literature were enrolled in the present study. Only about half of the patients (55.8%) were accurately diagnosed before surgery. Additionally, 91.1% of the patients received esophagectomy, and 88 patients (36.5%) received adjuvant therapy after surgery. The frequency of lymph node metastasis (LNM) was 51.2% (107/209), and LNM had a positive rate of 45.3% even when the tumor was confined to the submucosal layer. The risk of LNM increased significantly with the pT stage [P < 0.001, odds ratio (OR): 2.47, 95% confidence interval (CI): 1.72-3.56] and larger tumor size (P = 0.006, OR: 1.21, 95%CI: 1.05-1.38). The median overall survival (OS) was 11.0 mo (range: 1-204 mo). The multivariate Cox analysis showed both the pT stage [P = 0.005, hazard ratio (HR): 1.70, 95%CI: 1.17-2.47] and LNM (P = 0.009, HR: 1.78, 95%CI: 1.15-2.74) were independent prognostic factors for OS. The median disease-free survival (DFS) was 5.3 mo (range: 0.8-114.1 mo). The multivariate analysis indicated that only the advanced pT stage (P = 0.02, HR: 1.93, 95%CI: 1.09-3.42) was a significant independent indicator of poor RFS in patients with PMME. CONCLUSION: The correct diagnosis of PMME before surgery is low, and physicians should pay more attention to avoid a misdiagnosis or missed diagnosis. Extended lymph node dissection should be emphasized in surgery for PMME even though the tumor is confined to the submucosal layer. Both the LNM and pT stage are independent prognosis factors for OS, and the pT stage is the prognosis factor for DFS in patients with PMME.

Alpha-linolenic acid inhibits hepatocellular carcinoma cell growth through Farnesoid X receptor/ß-catenin signaling pathway.

BACKGROUND: Altered lipid profiles are frequently present in cancer, and it is necessary to elucidate the role of changed lipid profiles in hepatocellular carcinoma (HCC). We conducted this study to investigate the changed lipid profile in HCC tissues and discover some remarkably changed lipid components, and to explore the function of changed lipid components in HCC development. METHODS: Gas chromatography/mass spectrometer (GC/MS analysis) was employed to measure the abundance of fatty acids between HCC tissues and adjacent noncancerous tissues. The proliferative ability of HCC cells was determined by Cell Counting Kit-8 and EdU assays. Transwell and wound healing assays were employed to determine the migratory ability of HCC cells. Protein expression was assessed by western blot assay. RESULTS: GC/MS analysis revealed that alpha-linolenic acid was present at lower levels in HCC tissues than that in the adjacent noncancerous tissues. Alpha-linolenic acid inhibited the proliferation, migration and invasion of HCC cells in vitro. Western blotting showed that alpha-linolenic acid treatment increased Farnesoid X receptor expression and decreased ß-catenin and cyclinD1 expression. CONCLUSIONS: Alpha-linolenic acid suppresses HCC progression through the FXR/Wnt/ß-catenin signaling pathway. Rational use of alpha-linolenic acid may prevent the occurrence of liver cancer in the future.

Survival Prediction Model for Patients with Esophageal Squamous Cell Carcinoma Based on the Parameter-Optimized Deep Belief Network Using the Improved Archimedes Optimization Algorithm.

Esophageal squamous cell carcinoma (ESCC) is one of the highest incidence and mortality cancers in the world. An effective survival prediction model can improve the quality of patients' survival. Therefore, a parameter-optimized deep belief network based on the improved Archimedes optimization algorithm is proposed in this paper for the survival prediction of patients with ESCC. Firstly, a combination of features significantly associated with the survival of patients is found by the minimum redundancy and maximum relevancy (MRMR) algorithm. Secondly, a DBN network is introduced to make predictions for survival of patients. Aiming at the problem that the deep belief network model is affected by parameters in the construction process, this paper uses the Archimedes optimization algorithm to optimize the learning rate α and batch size ß of DBN. In order to overcome the problem that AOA is prone to fall into local optimum and low search accuracy, an improved Archimedes optimization algorithm (IAOA) is proposed. On this basis, a survival prediction model for patients with ESCC is constructed. Finally, accuracy comparison tests are carried out on IAOA-DBN, AOA-DBN, SSA-DBN, PSO-DBN, BES-DBN, IAOA-SVM, and IAOA-BPNN models. The results show that the IAOA-DBN model can effectively predict the five-year survival rate of patients and provide a reference for the clinical judgment of patients with ESCC.

Survival Risk Prediction of Esophageal Squamous Cell Carcinoma Based on BES-LSSVM.

Esophageal squamous cell carcinoma (ESCC) is one of the highest incidence and mortality cancers in the world. An effective survival prediction model can improve the quality of patients' survival. In this study, ten indicators related to the survival of patients with ESCC are founded using genetic algorithm feature selection. The prognostic index (PI) for ESCC is established using the binary logistic regression. PI is divided into four stages, and each stage can reasonably reflect the survival status of different patients. By plotting the ROC curve, the critical threshold of patients' age could be found, and patients are divided into the high-age groups and the low-age groups. PI and ten survival-related indicators are used as independent variables, based on the bald eagle search (BES) and least-squares support vector machine (LSSVM), and a survival prediction model for patients with ESCC is established. The results show that five-year survival rates of patients are well predicted by the bald eagle search-least-squares support vector machine (BES-LSSVM). BES-LSSVM has higher prediction accuracy than the existing particle swarm optimization-least-squares support vector machine (PSO-LSSVM), grasshopper optimization algorithm-least-squares support vector machine (GOA-LSSVM), differential evolution-least-squares support vector machine (DE-LSSVM), sparrow search algorithm-least-squares support vector machine (SSA-LSSVM), bald eagle search-back propagation neural network (BES-BPNN), and bald eagle search-extreme learning machine (BES-ELM).

Increased prognostic value of clinical-reproductive model in Chinese female patients with esophageal squamous cell carcinoma.

BACKGROUND: In China, it has been well recognized that some female patients with esophageal squamous cell carcinoma (ESCC) have different overall survival (OS) time, even with the same tumor-node-metastasis (TNM) stage, challenging the prognostic value of the TNM system alone. An effective predictive model is needed to accurately evaluate the prognosis of female ESCC patients. AIM: To construct a novel prognostic model with clinical and reproductive data for Chinese female patients with ESCC, and to assess the incremental prognostic value of the full model compared with the clinical model and TNM stage. METHODS: A new prognostic nomogram incorporating clinical and reproductive features was constructed based on univariatie and Cox proportional hazards survival analysis from a training cohort (n = 175). The results were recognized using the internal (n = 111) and independent external (n = 85) validation cohorts. The capability of the clinical-reproductive model was evaluated by Harrell's concordance index (C-index), Kaplan-Meier curve, time-dependent receiver operating characteristic (ROC), calibration curve and decision curve analysis. The correlations between estrogen response and immune-related pathways and some gene markers of immune cells were analyzed using the TIMER 2.0 database. RESULTS: A clinical-reproductive model including incidence area, age, tumor differentiation, lymph node metastasis (N) stage, estrogen receptor alpha (ESR1) and beta (ESR2) expression, menopausal age, and pregnancy number was constructed to predict OS in female ESCC patients. Compared to the clinical model and TNM stage, the time-dependent ROC and C-index of the clinical-reproductive model showed a good discriminative ability for predicting 1-, 3-, and 5-years OS in the primary training, internal and external validation sets. Based on the optimal cut-off value of total prognostic scores, patients were classified into high- and low-risk groups with significantly different OS. The estrogen response was significantly associated with p53 and apoptosis pathways in esophageal cancer. CONCLUSION: The clinical-reproductive prognostic nomogram has an incremental prognostic value compared with the clinical model and TNM stage in predicting OS in Chinese female ESCC patients.

Identification of a seven-cell cycle signature predicting overall survival for gastric cancer.

While genetic alterations in several regulators of the cell cycle have a significant impact on the gastric carcinogenesis process, the prognostic role of them remains to be further elucidated. The TCGA-STAD training set were downloaded and the mRNA expression matrix of cell cycle genes was extracted and corrected for further analysis after taking the intersection with GSE84437 dataset. Differentially expressed mRNAs were identified between tumor and normal tissue samples in TCGA-STAD. Univariate Cox regression analysis and lasso Cox regression model established a novel seven-gene cell cycle signature (including GADD45B, TFDP1, CDC6, CDC25A, CDC7, SMC1A and MCM3) for GC prognosis prediction. Patients in the high-risk group shown significantly poorer survival than patients in the low-risk group. The signature was found to be an independent prognostic factor for GC survival. Nomogram including the signature shown some clinical net benefit for overall survival prediction. The signature was further validated in the GSE84437 dataset. In tissue microarray, CDC6 and MCM3 protein expression were significant differences by the immunohistochemistry-based H-score between tumor tissues and adjacent tissues, and CDC6 is an independent prognostic factor for GC. Interestingly, our GSEA revealed that low-risk patients were more related to cell cycle pathways and might benefit more from therapies targeting cell cycle. Our study identified a novel robust seven-gene cell cycle signature for GC prognosis prediction that may serve as a beneficial complement to clinicopathological staging. The signature might provide potential biomarkers for the application of cell cycle regulators to therapies and treatment response prediction.

Focal adhesion kinase-related non-kinase ameliorates liver fibrosis by inhibiting aerobic glycolysis via the FAK/Ras/c-myc/ENO1 pathway.

BACKGROUND: Hepatic stellate cell (HSC) hyperactivation is a central link in liver fibrosis development. HSCs perform aerobic glycolysis to provide energy for their activation. Focal adhesion kinase (FAK) promotes aerobic glycolysis in cancer cells or fibroblasts, while FAK-related non-kinase (FRNK) inhibits FAK phosphorylation and biological functions. AIM: To elucidate the effect of FRNK on liver fibrosis at the level of aerobic glycolytic metabolism in HSCs. METHODS: Mouse liver fibrosis models were established by administering CCl4, and the effect of FRNK on the degree of liver fibrosis in the model was evaluated. Transforming growth factor-ß1 was used to activate LX-2 cells. Tyrosine phosphorylation at position 397 (pY397-FAK) was detected to identify activated FAK, and the expression of the glycolysis-related proteins monocarboxylate transporter 1 (MCT-1) and enolase1 (ENO1) was assessed. Bioinformatics analysis was performed to predict putative binding sites for c-myc in the ENO1 promoter region, which were validated with chromatin immunoprecipitation (ChIP) and dual-luciferase reporter assays. RESULTS: The pY397-FAK level was increased in human fibrotic liver tissue. FRNK knockout promoted liver fibrosis in mouse models. It also increased the activation, migration, proliferation and aerobic glycolysis of primary hepatic stellate cells (pHSCs) but inhibited pHSC apoptosis. Nevertheless, opposite trends for these phenomena were observed after exogenous FRNK treatment in LX-2 cells. Mechanistically, the FAK/Ras/c-myc/ENO1 pathway promoted aerobic glycolysis, which was inhibited by exogenous FRNK. CONCLUSION: FRNK inhibits aerobic glycolysis in HSCs by inhibiting the FAK/Ras/c-myc/ENO1 pathway, thereby improving liver fibrosis. FRNK might be a potential target for liver fibrosis treatment.

Characterization of E-cadherin expression in normal mucosa, dysplasia and adenocarcinoma of gastric cardia and its influence on prognosis.

BACKGROUND: Gastric cardia adenocarcinoma (GCA), which has been classified as type II adenocarcinoma of the esophagogastric junction in western countries, is of similar geographic distribution with esophageal squamous cell carcinoma in China, and even referred as "sister cancer" by Chinese oncologists. The molecular mechanism for GCA is largely unknown. Recent studies have shown that decreased expression of E-cadherin is associated with the invasion and metastasis of multiple cancers. However, the E-cadherin expression has not been well characterized in gastric cardia carcinogenesis and its effect on GCA prognosis. AIM: To characterize E-cadherin expression in normal gastric cardia mucosa, dysplasia and GCA tissues, and its influence on prognosis for GCA. METHODS: A total of 4561 patients with GCA were enrolled from our previously established GCA and esophageal cancer databases. The enrollment criteria included radical surgery for GCA, but without any radio- or chemo-therapy before operation. The GCA tissue from 4561 patients and matched adjacent normal epithelial tissue (n = 208) and dysplasia lesions (n = 156) were collected, and processed as tissue microarray for immunohistochemistry. The clinicopathological characteristics were retrieved from the medical records in hospital and follow-up was carried out through letter, telephone or home interview. E-cadherin protein expression was determined by two step immunohistochemistry. Kaplan-Meier and Cox regression analyses were used to correlate E-cadherin protein expression with survival of GCA patients. RESULTS: Of the 4561 GCA patients, there were 3607 males with a mean age of 61.6 ± 8.8 and 954 females with a mean age of 61.9 ± 8.6 years, respectively. With the lesions progressed from normal gastric cardia mucosa to dysplasia and GCA, the positive immunostaining rates for E-cadherin decreased significantly from 100% to 93.0% and 84.1%, respectively (R2 = 0.9948). Furthermore, E-cadherin positive immunostaining rate was significantly higher in patients at early stage (0 and I) than in those at late stage (II and III) (92.7% vs 83.7%, P = 0.001). E-cadherin positive expression rate was significantly associated with degree of differentiation (P = 0.001) and invasion depth (P < 0.001). Multivariate analysis showed that the GCA patients with positive E-cadherin immunostaining had better survival than those with negative (P = 0.026). It was noteworthy that E-cadherin positive expression rate was similar in patients with positive and negative lymph node metastasis. However, in patients with negative lymph node metastasis, those with positive expression of E-cadherin had better survival than those with negative expression (P = 0.036). Similarly, in patients with late stage GCA, those with positive expression of E-cadherin had better survival than those with negative expression (P = 0.011). CONCLUSION: E-cadherin expression may be involved in gastric cardia carcinogenesis and low expression of E-cadherin may be a promising early biomarker and overall survival predictor for GCA.

Long-term effect of hospital volume on the postoperative prognosis of 158,618 patients with esophageal squamous cell carcinoma in China.

Background: The impact of hospital volume on the long-term survival of esophageal squamous cell carcinoma (ESCC) has not been well assessed in China, especially for stage I-III stage ESCC. We performed a large sample size study to assess the relationships between hospital volume and the effectiveness of ESCC treatment and the hospital volume value at the lowest risk of all-cause mortality after esophagectomy in China. Aim: To investigate the prognostic value of hospital volume for assessing postoperative long-term survival of ESCC patients in China. Methods: The date of 158,618 patients with ESCC were collected from a database (1973-2020) established by the State Key Laboratory for Esophageal Cancer Prevention and Treatment, the database includes 500,000 patients with detailed clinical information of pathological diagnosis and staging, treatment approaches and survival follow-up for esophageal and gastric cardia cancers. Intergroup comparisons of patient and treatment characteristics were conducted with the X2 test and analysis of variance. The Kaplan-Meier method with the log-rank test was used to draw the survival curves for the variables tested. A Multivariate Cox proportional hazards regression model was used to analyze the independent prognostic factors for overall survival. The relationship between hospital volume and all-cause mortality was assessed using restricted cubic splines from Cox proportional hazards models. The primary outcome was all-cause mortality. Results: In both 1973-1996 and 1997-2020, patients with stage I-III stage ESCC who underwent surgery in high volume hospitals had better survival than those who underwent surgery in low volume hospitals (both P<0.05). And high volume hospital was an independent factor for better prognosis in ESCC patients. The relationship between hospital volume and the risk of all-cause mortality was half-U-shaped, but overall, hospital volume was a protective factor for esophageal cancer patients after surgery (HR<1). The concentration of hospital volume associated with the lowest risk of all-cause mortality was 1027 cases/year in the overall enrolled patients. Conclusion: Hospital volume can be used as an indicator to predict the postoperative survival of ESCC patients. Our results suggest that the centralized management of esophageal cancer surgery is meaningful to improve the survival of ESCC patients in China, but the hospital volume should preferably not be higher than 1027 cases/year. Core tip: Hospital volume is considered to be a prognostic factor for many complex diseases. However, the impact of hospital volume on long-term survival after esophagectomy has not been well evaluated in China. Based on a large sample size of 158,618 ESCC patients in China spanning 47 years (1973-2020), We found that hospital volume can be used as a predictor of postoperative survival in patients with ESCC, and identified hospital volume thresholds with the lowest risk of death from all causes. This may provide an important basis for patients to choose hospitals and have a significant impact on the centralized management of hospital surgery.

Diagnostic Value of VDR in Bone Metastasis and Prognosis of Patients with Breast Cancer and Expression Correlation between Vitamin D Receptor and Hairless Protein.

BACKGROUND: Breast cancer is more likely to metastasize to the bone. Previous researches have revealed that the vitamin D receptor (VDR) contributes to breast cancer progression and bone metastasis in mouse and human breast cells, and hairless (Hr) protein interacts with VDR in the mammalian hair cycle. This study aimed to explore the expression of VDR/Hr in breast cancer, and the correlation between VDR/Hr and prognosis, bone metastasis, and metastasis-related prognosis. METHODS: The expression of VDR and Hr was analyzed on 119 breast cancer tissues and corresponding normal breast tissue from each of the breast cancer samples by immunohistochemistry staining, and the databases were supplemented as well. RESULTS: The expression of the VDR protein was significantly decreased in breast cancer patients (p < 0.05), inversely, the UALCAN (p = 0.000) and GEPIA (p > 0.05) databases showed that the VDR mRNA expression tended to be higher in tumor tissues. The Hr protein was expressed at a low level within breast cancer specimens (p < 0.05), which was in agreement with the level of Hr mRNA in UALCAN (p = 0.005) and GEPIA (p > 0.05). The protein levels of VDR and Hr were positively correlated (p > 0.05), while the mRNA levels suggested a close relationship with GEPIA (p < 0.05). Low expression of Hr protein displayed a tendency for longer overall survival (OS) and recurrence-free survival (RFS), and its mRNA data also revealed the same trend in the Kaplan-Meier dataset (both p > 0.05). However, VDR protein and mRNA with low expression had markedly shorter OS and RFS (both p < 0.05). The downregulation of VDR protein was significantly associated with an advanced stage (p < 0.05). Low VDR protein was an independent risk factor for poor prognosis (p < 0.05) and was negatively correlated with bone metastasis (p < 0.05). VDR protein and mRNA levels were both downregulated in breast cancer with bone metastasis (both p < 0.05). The area under ROC curve (AUC) for VDR protein expression to identify patients with bone metastasis was 0.661 (p < 0.05) and the AUC for VDR level to predict 1-year, 3-year, and 5-year OS was 0.621, 0.664, and 0.805 in patients with bone metastasis, respectively (p < 0.05). VDR with low expression accelerated bone metastasis and metastasis-related poor survival (both p < 0.05). CONCLUSION: VDR expression is a notable prognostic factor in primary breast cancer patients for predicting bone metastases and unfavorable clinical outcome.

Development and validation of a prognostic nomogram model for Chinese patients with primary small cell carcinoma of the esophagus.

BACKGROUND: Primary small cell carcinoma of the esophagus (PSCE) is a highly invasive malignant tumor with a poor prognosis compared with esophageal squamous cell carcinoma. Due to the limited samples size and the short follow-up time, there are few reports on elucidating the prognosis of PSCE, especially on the establishment and validation of a survival prediction nomogram model covering general information, pathological factors and specific biological proteins of PSCE patients. AIM: To establish an effective nomogram to predict the overall survival (OS) probability for PSCE patients in China. METHODS: The nomogram was based on a retrospective study of 256 PSCE patients. Univariate analysis and multivariate Cox proportional hazards regression analysis were used to examine the prognostic factors associated with PSCE, and establish the model for predicting 1-, 3-, and 5-year OS based on the Akaike information criterion. Discrimination and validation were assessed by the concordance index (C-index) and calibration curve and decision curve analysis (DCA). Histology type, age, tumor invasion depth, lymph node invasion, detectable metastasis, chromogranin A, and neuronal cell adhesion molecule 56 were integrated into the model. RESULTS: The C-index was prognostically superior to the 7th tumor node metastasis (TNM) staging in the primary cohort [0.659 (95%CI: 0.607-0.712) vs 0.591 (95%CI: 0.517-0.666), P = 0.033] and in the validation cohort [0.700 (95%CI: 0.622-0.778) vs 0.605 (95%CI: 0.490-0.721), P = 0.041]. Good calibration curves were observed for the prediction probabilities of 1-, 3-, and 5-year OS in both cohorts. DCA analysis showed that our nomogram model had a higher overall net benefit compared to the 7th TNM staging . CONCLUSION: Our nomogram can be used to predict the survival probability of PSCE patients, which can help clinicians to make individualized survival predictions.

Focal amplifications are associated with chromothripsis events and diverse prognoses in gastric cardia adenocarcinoma.

The role of focal amplifications and extrachromosomal DNA (ecDNA) is unknown in gastric cardia adenocarcinoma (GCA). Here, we identify frequent focal amplifications and ecDNAs in Chinese GCA patient samples, and find focal amplifications in the GCA cohort are associated with the chromothripsis process and may be induced by accumulated DNA damage due to local dietary habits. We observe diverse correlations between the presence of oncogene focal amplifications and prognosis, where ERBB2 focal amplifications positively correlate with prognosis and EGFR focal amplifications negatively correlate with prognosis. Large-scale ERBB2 immunohistochemistry results from 1668 GCA patients show survival probability of ERBB2 positive patients is lower than that of ERBB2 negative patients when their surviving time is under 2 years, however, the tendency is opposite when their surviving time is longer than 2 years. Our observations indicate that the ERBB2 focal amplifications may represent a good prognostic marker in GCA patients.

NAP1L1 Functions as a Tumor Promoter via Recruiting Hepatoma-Derived Growth Factor/c-Jun Signal in Hepatocellular Carcinoma.

NAP1L1 has been reported to be significantly involved in the carcinogenesis of hepatocellular carcinoma (HCC). Yet, its detailed molecular basis is still to be determined. Based on the analysis of The Cancer Genome Atlas (TCGA) database, NAP1L1 mRNA was found to be upregulated and predicted the poor prognosis initially. Subsequently, consistent with the prediction, the upregulated expression of NAP1L1 mRNA and protein levels was confirmed by quantitative polymerase chain reaction (qPCR), Western blot, and immunohistochemistry assays. Upregulated NAP1L1 protein positively promoted the disease progression and poor prognosis of HCC. In addition, NAP1L1 protein expression was considered as an independent prognostic factor in HCC. Inhibition of NAP1L1 expression by siRNA or shRNA pathway significantly reduced the cell proliferation and cell cycle transformation in vitro and in vivo. Mechanism analysis first showed that the function of NAP1L1 was to recruit hepatoma-derived growth factor (HDGF), an oncogene candidate widely documented in tumors. Furthermore, the latter interacted with c-Jun, a key oncogenic transcription factor that can induce the expression of cell cycle factors and thus stimulate the cell growth in HCC. Finally, transfecting HDGF or c-Jun could reverse the suppressive effects on HCC growth in NAP1L1-suppressed HCC cells. Our data indicate that NAP1L1 is a potential oncogene and acts via recruiting HDGF/c-Jun in HCC.

Mitochondrial malic enzyme 2 promotes breast cancer metastasis via stabilizing HIF-1α under hypoxia.

OBJECTIVE: α-ketoglutarate (α-KG) is the substrate to hydroxylate collagen and hypoxia-inducible factor-1α (HIF-1α), which are important for cancer metastasis. Previous studies have shown that the upregulation of collagen prolyl 4-hydroxylase in breast cancer cells stabilizes the expression of HIF-1α by depleting α-KG levels. We hypothesized that mitochondrial malic enzyme 2 (ME2) might also affect HIF-1α expression via modulating α-KG levels in breast cancer cells. METHODS: We evaluated ME2 protein expression in 100 breast cancer patients using immunohistochemistry and correlated with clinicopathological indicators. The effect of ME2 knockout on cancer metastasis was evaluated using an orthotopic breast cancer model. The effect of ME2 knockout or knockdown on the levels of α-KG and HIF-1α proteins in breast cancer cell lines was determined both in vitro and in vivo. RESULTS: ME2 was found to be upregulated in the human breast cancerous tissues compared with the matched precancerous tissues (P<0.001). The elevated expression of ME2 was associated with a poor prognosis (P=0.019). ME2 upregulation was also related to lymph node metastasis (P=0.016), pathological staging (P=0.033), and vascular cancer embolus (P=0.014). Also, ME2 knockout significantly inhibited lung metastasisin vivo. In the tumors formed by ME2 knockout cells, the levels of α-KG were significantly increased and collagen hydroxylation level did not change significantly but HIF-1α protein expression was significantly decreased, compared to the control samples. In cell culture, cells with ME2 knockout or knockdown demonstrated significantly higher α-KG levels but significantly lower HIF-1α protein expression than control cells under hypoxia. Exogenous malate and α-KG exerted similar effect on HIF-1α in breast cancer cells to ME2 knockout or knockdown. Additionally, treatment with malate significantly decreased 4T1 breast cancer lung metastasis. ME2 expression was associated with HIF-1α levels in human breast cancer samples (P=0.008). CONCLUSIONS: Our results provide evidence that upregulation of ME2 is associated with a poor prognosis of breast cancer patients and propose a mechanistic understanding of a link between ME2 and breast cancer metastasis.

TRAIL promotes epithelial-to-mesenchymal transition by inducing PD-L1 expression in esophageal squamous cell carcinomas.

BACKGROUND: Tumor necrosis factor-associated apoptosis-inducing ligand (TRAIL) was initially considered an immunity guard; however, its function remains controversial. Besides immune cells, lung and colon cancer cells have also been reported to express TRAIL, which can promote tumor invasion and metastasis. However, the biological function and underlying mechanism of action of TRAIL in esophageal squamous cell carcinoma (ESCC) remain poorly elucidated. METHODS: The ESCC cells stemness, migration, and proliferation ability was assessed by sphere formation, Transwell, and CCK8 assay. The stemness- and epithelial-mesenchymal transition (EMT)- related genes expression levels were analyzed by Western blot and RT-qPCR. The signal activation was conducted by Western blot. The xenograft mouse experiments and lung metastasis model were performed to confirm our findings in vitro. RESULTS: Herein, we found that TRAIL is a negative predictor in patients with ESCC. To further investigate the biological function of TRAIL, we established TRAIL knockdown and overexpression ESCC cell lines and found that TRAIL induced EMT and promoted tumor aggressiveness. Furthermore, we demonstrated that TRAIL- overexpressing cells upregulated PD-L1 expression, which was dependent on the p-ERK/STAT3 signaling pathway. We obtained similar results when using recombinant human TRAIL. Finally, we validated the biological role and mechanism of action of TRAIL in vivo. CONCLUSIONS: These findings demonstrate that TRAIL promotes ESCC progression by enhancing PD-L1 expression, which induces EMT. This may explain the failure of TRAIL preclinical trials.