Circulating Tumor Cells Enumeration from the Portal Vein for Risk Stratification in Early Pancreatic Cancer Patients

Background. Effective biomarkers are needed to enable personalized medicine for pancreatic cancer patients. This study analyzes the prognostic value, in early pancreatic cancer, of single circulating tumor cell (CTC) and CTC clusters from the central venous catheter (CVC) and portal blood (PV). Methods. In total, 7 mL of PV and CVC blood from 35 patients with early pancreatic cancer were analyzed. CTC were isolated using a positive immunomagnetic selection. The detection and identification of CTC were performed by immunocytochemistry (ICC) and were analyzed by Epi-fluorescence and confocal microscopy. Results. CTC and the clusters were detected both in PV and CVC. In both samples, the CTC number per cluster was higher in patients with grade three or poorly differentiated tumors (G3) than in patients with well (G1) or moderately (G2) differentiated. Patients with fewer than 185 CTC in PV exhibited a longer OS than patients with more than 185 CTC (24.5 vs. 10.0 months; p = 0.018). Similarly, patients with fewer than 15 clusters in PV showed a longer OS than patients with more than 15 clusters (19 vs. 10 months; p = 0.004). These significant correlations were not observed in CVC analyses. Conclusions. CTC presence in PV could be an important prognostic factor to predict poor prognosis in early pancreatic cancer. In addition, the number of clustered-CTC correlate to a tumor negative differentiation degree and, therefore, could be used as a diagnostic biomarker for pancreatic cancer.

Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma

Background Radiomics may provide more objective and accurate predictions for extrahepatic cholangiocarcinoma (ECC). In this study, we developed radiomics models based on magnetic resonance imaging (MRI) and machine learning to preoperatively predict differentiation degree (DD) and lymph node metastasis (LNM) of ECC. Methods A group of 100 patients diagnosed with ECC was included. The ECC status of all patients was confirmed by pathology. A total of 1200 radiomics features were extracted from axial T1 weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion weighted imaging (DWI), and apparent diffusion coefficient (ADC) images. A systematical framework considering combinations of five feature selection methods and ten machine learning classification algorithms (classifiers) was developed and investigated. The predictive capabilities for DD and LNM were evaluated in terms of area under precision recall curve (AUPRC), area under the receiver operating characteristic (ROC) curve (AUC), negative predictive value (NPV), accuracy (ACC), sensitivity, and specificity. The prediction performance among models was statistically compared using DeLong test. Results For DD prediction, the feature selection method joint mutual information (JMI) and Bagging Classifier achieved the best performance (AUPRC = 0.65, AUC = 0.90 (95% CI 0.75–1.00), ACC = 0.85 (95% CI 0.69–1.00), sensitivity = 0.75 (95% CI 0.30–0.95), and specificity = 0.88 (95% CI 0.64–0.97)), and the radiomics signature was composed of 5 selected features. For LNM prediction, the feature selection method minimum redundancy maximum relevance and classifier eXtreme Gradient Boosting achieved the best performance (AUPRC = 0.95, AUC = 0.98 (95% CI 0.94–1.00), ACC = 0.90 (95% CI 0.77–1.00), sensitivity = 0.75 (95% CI 0.30–0.95), and specificity = 0.94 (95% CI 0.72–0.99)), and the radiomics signature was composed of 30 selected features. However, these two chosen models were not significantly different to other models of higher AUC values in DeLong test, though they were significantly different to most of all models. Conclusion MRI radiomics analysis based on machine learning demonstrated good predictive accuracies for DD and LNM of ECC. This shed new light on the noninvasive diagnosis of ECC.

m5C Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characterization in Papillary Thyroid Carcinoma

Recently, immune response modulation at the epigenetic level is illustrated in studies, but the possible function of RNA 5-methylcytosine (m5C) modification in cell infiltration within the tumor microenvironment (TME) is still unclear. Three different m5C modification patterns were identified, and high differentiation degree was observed in the cell infiltration features within TME under the above three identified patterns. A low m5C-score, which was reflected in the activated immunity, predicted the relatively favorable prognostic outcome. A small amount of effective immune infiltration was seen in the high m5C-score subtype, indicating the dismal patient survival. Our study constructed a diagnostic model using the 10 signature genes highly related to the m5C-score, discovered that the model exhibited high diagnostic accuracy for PTC, and screened out five potential drugs for PTC based on this m5C-score model. m5C modification exerts an important part in forming the TME complexity and diversity. It is valuable to evaluate the m5C modification patterns in single tumors, so as to enhance our understanding towards the infiltration characterization in TME.

Role of miR-138 on Radio Sensitivity of Gastric Carcinoma Cells and Its Molecular Mechanism

To explore FOXP4 and miR-138 in gastric carcinoma (GC) and its related mechanisms. Sixty-eight GC patients from January 2018 to January 2019 were selected as group A, and 66 healthy people as group B. GC cells and gastric mucosal epithelial cells were purchased, sh-FOXP4, si-FOXP4, NC, miR-138-inhibitor, and miR-138-mimics were transfected into MKN-45 and NCI-N87 cells. The FOXP4 and miR-138 expression levels in samples were tested by qRT-PCR, and N-cadherin, vimentin, Fibronectin, Slug, E-Cadherin and Y-catenin downstream proteins in cells were detected by WB. The proliferation was tested by MTT assay, invasion was tested by Transwell assay, and apoptosis was detected by flow cytometry assay. F0XP4 was highly expressed in GC, miR-138 was poorly expressed in GC, and AUC of FOXP4 and miR-138 was > 0.8. FOXP4 and miR-138 were tied to the age, gender, tumor invasion, differentiation degree, tumor location and TNM stage of GC patients. Silent expression of FOXP4 and overexpression of miR-138 can promote apoptosis, inhibit cell growth and epithelial-mesenchymal transition (ETM). The two also can inhibit N-cadherin, vimentin, Fibronectin and Slug proteins, and promote E-Cadherin and y-catenin. Dual luciferase report confirmed that FOXP4 and miR-138 had targeted relationship. In terms of radiological parameters, the SF2 and D0 (Gy) values of transfected miR-138mimic+pcDNA3. 1-FOXP4 were dramatically higher than those of transfected miR-138mimic+pcDNA3. 1 cells, and SER was lower than those of transfected miR-138 mimic+ pcDNA3. 1 cells (P<0.05), suggesting FOXP4 partially adjusted the radiosensitization role of miR-138. In conclusion, miR-138 can regulate EMT of GC cells by adjusting F0XP4 and enhance radiosensitivity of those cells.

Development and Validation of a Nomogram to Predict Survival in Pancreatic Head Ductal Adenocarcinoma After Pancreaticoduodenectomy

BackgroundPancreatic head ductal adenocarcinoma (PHDAC) patients with the same tumor-node-metastasis (TNM) stage may share different outcomes after pancreaticoduodenectomy (PD). Therefore, a novel method to identify patients with poor prognosis after PD is urgently needed. We aimed to develop a nomogram to estimate survival in PHDAC after PD.MethodsTo estimate survival after PD, a nomogram was developed using the Tongji Pancreatic cancer cohort comprising 355 PHDAC patients who underwent PD. The nomogram was validated under the same conditions in another cohort (N = 161) from the National Taiwan University Hospital. Prognostic factors were assessed using LASSO and multivariate Cox regression models. The nomogram was internally validated using bootstrap resampling and then externally validated. Performance was assessed using concordance index (c-index) and calibration curve. Clinical utility was evaluated using decision curve analysis (DCA), X-tile program, and Kaplan–Meier curve in both training and validation cohorts.ResultsOverall, the median follow-up duration was 32.17 months, with 199 deaths (64.82%) in the training cohort. Variables included in the nomogram were age, preoperative CA 19-9 levels, adjuvant chemotherapy, Tongji classification, T stage, N stage, and differentiation degree. Harrell’s c-indices in the internal and external validation cohorts were 0.79 (95% confidence interval [CI], 0.76–0.82) and 0.83 (95% CI, 0.78–0.87), respectively, which were higher than those in other staging systems. DCA showed better clinical utility.ConclusionThe nomogram was better than TNM stage and Tongji classification in predicting PHDAC patients’ prognosis and may improve prognosis-based selection of patients who would benefit from PD.

Prediction of serosal invasion in gastric cancer: development and validation of multivariate models integrating preoperative clinicopathological features and radiographic findings based on late arterial phase CT images

Background To develop and validate multivariate models integrating endoscopic biopsy, tumor markers, and CT findings based on late arterial phase (LAP) to predict serosal invasion in gastric cancer (GC). Methods The preoperative differentiation degree, tumor markers, CT morphological characteristics, and CT value-related and texture parameters of 154 patients with GC were analyzed retrospectively. Multivariate models based on regression analysis and machine learning algorithms were performed to improve the diagnostic efficacy. Results The differentiation degree, carbohydrate antigen (CA) 199, CA724, CA242, and multiple CT findings based on LAP differed significantly between T1–3 and T4 GCs in the primary cohort (all P < 0.05). Multivariate models based on regression analysis and random forest achieved AUCs of 0.849 and 0.865 in the primary cohort, respectively. Conclusion We developed and validated multivariate models integrating endoscopic biopsy, tumor markers, CT morphological characteristics, and CT value-related and texture parameters to predict serosal invasion in GCs and achieved favorable performance.

A Distinct Clinicopathological Feature and Prognosis of Young Gastric Cancer Patients Aged ≤ 45 Years Old

PurposeThe aim of this retrospective study was to probe into clinicopathological features and prognosis of early-onset gastric cancer (EOGC) patients aged ≤ 45 years old.MethodsThis study selected 154 young gastric cancer patients aged ≤ 45 years old and 158 elderly gastric cancer patients aged &gt; 50 years old admitted to West China Hospital of Sichuan University in 2009-2019 as the research object. These patients were further divided into two groups according to whether tumor can be resected radically. The following parameters were analyzed: age, gender, helicobacter pylori (HP) infection status, Her-2 status, pathological type and stage, chemotherapy, tumor differentiation degree, overall survival (OS).ResultsMore than 3,000 patients with gastric carcinoma were screened, and 154 young gastric cancer patients aged ≤ 45 years old were identified as EOGC. Among them, the number of female patients in EOGC group was significantly higher than that of males, accounting for 63.6%. In addition, EOGC were associated with diffuse Laur´en type and poorly differentiated tumors. Interestingly, the Kaplan–Meier method showed that the OS of unresectable EOGC group was significantly lower than that of unresectable LOGC group (P = 0.0005) and chemotherapy containing paclitaxel tended to be more effective in the young people (P = 0.0511). Nevertheless, there was no significant difference in OS between young and elderly patients with gastric cancer in the radical resection group (P = 0.3881).ConclusionEOGC patients have a worse prognosis than late-onset gastric cancer (LOGC) patients with advanced unresectable gastric cancer. Palliative surgery or chemotherapy containing paclitaxel may improve the OS of unresectable young individuals with gastric cancer. Additional randomized controlled trials are required for guiding clinical practice.

What is The Impact of CSN5 on The Prognosis of Digestive System Cancers: A Systematic Review and Meta-Analysis

Background: Despite the understanding of COP9 signalosome subunit 5 (CSN5) in tumor genesis, there is no conclusive evidence on CSN5 value to predict digestive system tumor patients' survival and prognosis. The article was performed to evaluate the impact of CSN5 expression levels on survival consequence and clinicopathological parameters of digestive system neoplasm patients.Methods: A comprehensive search was conducted through four databases. We utilized Hazard Ratio (HR) with a 95% confidence interval (CI) to evaluate the prognostic value of CSN5 in overall survival (OS) and recurrence free survival (RFS). We estimated the connection between CSN5 and clinicopathological parameters based on Odds Ratio (OR) with a corresponding 95% CI. Results: The meta-analysis contained 22 studies, involving 2,193 patients diagnosed with digestive system tumor. High CSN5 expression level was indicated to predict poorer OS (HR = 2.28, 95% CI: 1.71–3.03; p < 0.00001). Additionally, high CSN5 was correlated with worse invasion depth (OR = 0.49, 95% CI: 0.25-0.96, p = 0.04), positive lymphatic metastasis (OR = 0.28, 95% CI: 0.16-0.47, p = 0.00001), positive distant metastasis (OR = 0.32, 95% CI: 0.13-0.76, p = 0.01) and poorer differentiation degree (OR = 0.34, 95% CI: 0.19-0.60, p = 0.0003). However, we could not find a correlation between CSN5 expression and age, gender, tumor stage, tumor size or vascular invasion. Furthermore, no significant publication bias was detected.Conclusion: This meta-analysis demonstrated that the overexpression of CSN5 level could foresee poorer OS in digestive system cancer patients. Additionally, CSN5 level was related to tumor invasion depth, lymphatic metastasis, distant metastasis and differentiation degree.

MicroRNA-34c-5p Inhibition of NUF2 Suppresses Lung Adenocarcinoma Cell Viability and Invasion

Background. Lung cancer continues to be a burden worldwide with an estimated 2.09 million new cases of lung cancer and 1.76 million deaths in 2018. MicroRNAs (miRs) are key regulators of gene expression and show their oncogenic or antioncogenic role in human cancers including lung cancer. In this study, we test the hypothesis that miR-34c-5p functions as a candidate antioncomiR in lung adenocarcinoma by targeting NUF2. Methods. The expression pattern of miR-34c-5p and NUF2 was evaluated in 202 biopsy specimens from patients with lung adenocarcinoma and 176 biopsy specimens from patients with benign lung diseases. Interaction between miR-34c-5p and NUF2 was verified by the luciferase-based assay. Cell viability and invasion assays were carried out in cultured A549 cells treated with miR-34c-5p mimic, inhibitor, and siRNA against NUF2. Results. NUF2 was highly expressed in lung adenocarcinoma samples and related to the differentiation degree, TNM stage, and presence of lymph node metastasis (LNM). Patients with NUF2 overexpression had reduced overall survival (OS) and disease-free survival (DFS) compared to patients with underexpression. Cox multivariate analysis revealed that high expression of NUF2, advanced TNM stage, well/moderate differentiation, and existence of LNM were unfavorable prognostic factors. siRNA-mediated knockdown of NUF2 inhibits A549 cell viability and invasion. miR-34c-5p was expressed at a poor level in lung adenocarcinoma samples and related to the differentiation degree, TNM stage, and presence of LNM. miR-34c-5p underexpression contributes to reduced OS and DFS, which was demonstrated as an unfavorable prognostic factor by Cox multivariate analysis. siRNA-mediated knockdown of NUF2 could ablate miR-34c-5p inhibition-mediated effects on A549 cells. Conclusion. Our results prove the hypothesis that miR-34c-5p could suppress lung adenocarcinoma progression by binding to the NUF2 gene. The study is a significant step towards extending our understanding of the mode of miRNA regulation in lung adenocarcinoma.

Downregulation of snoRNA SNORA52 and Its Clinical Significance in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and aggressive tumors in the world while the accuracy of the present tests for detecting HCC is poor. A novel diagnostic and prognostic biomarker for HCC is urgently needed. Overwhelming evidence has demonstrated the regulatory roles of small nucleolar RNA (snoRNA) in carcinogenesis. This study is aimed at analyzing the expression of a snoRNA, SNORA52, in HCC and exploring the correlation between its expression and various clinical characteristics of HCC patients. By using quantitative real-time PCR, we found that SNORA52 was downregulated in HCC cell lines ( P < 0.05 ) and HCC tissues ( P < 0.001 ). Correlation analysis showed that the expression of SNORA52 was obviously associated with tumor size ( P = 0.011 ), lesion number ( P = 0.007 ), capsular invasion ( P = 0.011 ), tumor differentiation degree ( P = 0.046 ), and TNM stage ( P = 0.004 ). The disease-free survival (DFS) and overall survival (OS) analysis showed that patients with lower SNORA52 expression had a worse prognosis ( P < 0.001 ). Univariate and multivariate Cox regression analysis showed that SNORA52 expression was a completely independent prognostic factor to predict DFS ( P = 0.009 ) and OS ( P = 0.012 ) of HCC patients. Overall, our findings showed SNORA52 expression levels were downregulated in HCC tissues and correlated with multiple clinical variables, and SNORA52 was an independent prognostic factor for HCC patients, which suggested that SNORA52 could function as a potential diagnostic and prognostic biomarker for HCC patients.