The function of the ELF3 gene and its mechanism in cancers.

E74-like factor 3 (ELF3) is an important member of the E-twenty-six (ETS) transcription factor family. ELF3 is expressed in various types of cells and regulates a variety of biological behaviors, such as cell proliferation, differentiation, apoptosis, migration, and invasion, by binding to DNA to regulate the expression of other genes. In recent years, studies have shown that ELF3 plays an important role in the occurrence and development of many tumors and inflammation and immune related diseases. ELF3 has different functions and expression patterns in different tumors; it can function as a tumor suppressor gene or an oncogene, highlighting its dual effects of tumor promotion and inhibition. ELF3 also affects the levels of tumor immunity-related cytokines and is involved in the regulation and expression of multiple signaling pathways. In tumor therapy, ELF3 is a complex and multifunctional gene and has become a key focus of targeted treatment research. An in-depth study of the biological function of ELF3 can help to elucidate its role in biological processes and provide ideas and a basis for the development and clinical application of ELF3-related therapeutic methods. This review introduces the structure and physiological and cellular functions of the ELF3 gene, summarizes the mechanisms of action of ELF3 in different types of malignant tumors and its role in immune regulation, inflammation, etc., and discusses treatment methods for ELF3-related diseases, providing significant reference value for scholars studying the ELF3 gene and related diseases.

Development of a joint prediction model based on both the radiomics and clinical factors for preoperative prediction of circumferential resection margin in middle-low rectal cancer using T2WI images.

OBJECTIVES: A circumferential resection margin (CRM) is an independent risk factor for local recurrence, distant metastasis, and poor overall survival of rectal cancer. In this study, we developed and validated a radiomics prediction model to predict perioperative surgical margins in patients with middle and low rectal cancer following neoadjuvant treatment and for decisions about treatment plans for patients. METHODS: This study retrospectively analyzed 275 patients from center 1(training cohort) and 120 patients from center 2(verification cohort) with rectal cancer diagnosed at two centers from July 2020 to July 2022 who underwent neoadjuvant therapy and had their CRM status confirmed by preoperative high-resolution magnetic resonance imaging (MRI) scans. Radiomics signatures were extracted and screened from MRI images and a radiomics signature was built by the least absolute shrinkage and selection operator (LASSO) logistic regression model, which was combined with clinical signatures to construct a nomogram. The receiver operating characteristic (ROC) curve and area under the curve (AUC) value, sensitivity, specificity, positive predictive value, negative predictive value, and calibration curve were used to evaluate the predictive performance of the model. RESULTS: In our research, the combined model has the best performance. In the training group, the radiomics model based on high-spatial-resolution T2-weighted imaging (HR-T2WI), clinical model and combined model demonstrated an AUC of 0.819 (0.802-0.833), 0.843 (0.822-0.861), and 0.910 (0.880-0.940), respectively. In the validation group, they demonstrated an AUC of 0.745 (0.715-0.788), 0.827 (0.798-0.850), and 0.848 (0.779-0.917), respectively. The calibration curve confirmed the clinical applicability of the model. CONCLUSIONS: The individualized prediction model established by combining radiomics signatures and clinical signatures can efficiently and objectively predict perioperative margin invasion in patients with middle and low rectal cancer.

Design of MERS-CoV entry inhibitory short peptides based on helix-stabilizing strategies.

Interaction between Middle East respiratory syndrome coronavirus (MERS-CoV) spike (S) protein heptad repeat-1 domain (HR1) and heptad repeat-2 domain (HR2) is critical for the MERS-CoV fusion process. This interaction is mediated by the α-helical region from HR2 and the hydrophobic groove in a central HR1 trimeric coiled coil. We sought to develop a short peptidomimetic to act as a MERS-CoV fusion inhibitor by reproducing the key recognition features of HR2 helix. This was achieved by the use of helix-stabilizing strategies, including substitution with unnatural helix-favoring amino acids, introduction of ion pair interactions, and conjugation of palmitic acid. The resulting 23-mer lipopeptide, termed AEEA-C16, inhibits MERS-CoV S protein-mediated cell-cell fusion at a low micromolar level comparable to that of the 36-mer HR2 peptide HR2P-M2. Collectively, our studies provide new insights into developing short peptide-based antiviral agents to treat MERS-CoV infection.

cDCBLD2 mediates sorafenib resistance in hepatocellular carcinoma by sponging miR-345-5p binding to the TOP2A coding sequence.

Sorafenib is a first-line chemotherapy drug for treating advanced hepatocellular carcinoma (HCC). However, its therapeutic effect has been seriously affected by the emergence of sorafenib resistance in HCC patients. The underlying mechanism of sorafenib resistance is unclear. Here, we report a circular RNA, cDCBLD2, which plays an important role in sorafenib resistance in HCC. We found that cDCBLD2 was upregulated in sorafenib-resistant (SR) HCC cells, and knocking down cDCBLD2 expression could significantly increase sorafenib-related cytotoxicity. Further evidence showed that cDCBLD2 can bind to microRNA (miR)-345-5p through a competing endogenous RNA mechanism, increase type IIA topoisomerase (TOP2A) mRNA stability through a miRNA sponge mechanism, and reduce the effects of sorafenib treatment on HCC by inhibiting apoptosis. Our findings also suggest that miR-345-5p can negatively regulate TOP2A levels by binding to the coding sequence region of its mRNA. Additionally, targeting cDCBLD2 by injecting a specific small interfering RNA (siRNA) could significantly overcome sorafenib resistance in a patient-derived xenograft (PDX) mouse model of HCC. Taken together, our study provides a proof-of-concept for a potential strategy to overcome sorafenib resistance in HCC patients by targeting cDCBLD2 or TOP2A.

Prognostic Analysis of Prophylactic Hyperthermic Intraperitoneal Chemotherapy for Advanced Gastric Cancer: a Propensity Score-Matched Analysis.

PURPOSE: To investigate the efficacy of prophylactic hyperthermic intraperitoneal chemotherapy (HIPEC) for advanced gastric cancer (AGC). METHODS: We included 198 patients treated from December 2016 to January 2019; of these patients, the 132 who had clinical T4 gastric cancer were divided into a hyperthermic intraperitoneal chemotherapy group (HIPEC group) and a radical gastrectomy and D2 lymph node dissection group (control group). Because this study was retrospective, we used propensity score matching (PSM) to reduce selectivity bias; we then assessed risk factors for recurrence and compared prognosis in terms of survival in the gastrectomy and prophylactic HIPEC groups. RESULTS: Prophylactic HIPEC reduced the risk of postoperative peritoneal metastasis (PM: 27.5% vs. 10.5%, P = 0.015) and did not increase the risk of postoperative complications, but there was no significant difference in the effect on hepatic metastases or other distant metastases. Risk factors for recurrence included pT4 staging and positive lymph node metastases. Both disease-free survival (DFS: HR 0.592; 95% CI 0.354-0.990; P = 0.042) and peritoneal recurrence-free survival (PFS: HR 0.314; 95% CI 0.127-0.774; P = 0.008) were better in the prophylactic HIPEC group than in the gastrectomy-only group. In addition, there was no difference in the prognosis of patients between the two groups of raltitrexed (RT) and paclitaxel (PTX) for perfusion dosing. CONCLUSION: Our study showed that prophylactic HIPEC could prevent postoperative PM in patients with AGC and did not increase the incidence of postoperative complications. However, it was not found to be effective in the prevention of other metastases, such as hepatic metastases.

A web-based prediction model for long-term cancer-specific survival of middle-aged patients with early-stage gastric cancer: a multi-institutional retrospective study.

BACKGROUND: This study constructed and validated a prognostic model to evaluate long-term cancer-specific survival (CSS) in middle-aged patients with early gastric cancer (EGC). METHODS: We extracted clinicopathological data from relevant patients between 2004 and 2015 from Surveillance, Epidemiology, and End Results (SEER) database, and randomly divided the patients into a training group (N = 688) and a validation group (N = 292). In addition, 102 Chinese patients were enrolled for external validation. Univariate and multivariate Cox regression models were used to screen for independent prognostic factors, and a nomogram was constructed to predict CSS. We used the concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) to evaluate the predictive performance of the model. RESULTS: Univariate and multivariate COX regression analyses showed that tumor location, differentiation grade, N stage, chemotherapy, and number of regional nodes examined were independent risk factors for prognosis, and these factors were used to construct the nomogram. The C-index of the model in the training cohort, internal validation cohort, and external validation cohort was 0.749 (95% CI 0.699-0.798), 0.744 (95% CI 0.671-0.818), and 0.807 (95% CI 0.721-0.893), respectively. The calibration curve showed that the model had an excellent fit. The DCA curve showed that the model had good predictive performance and practical clinical value. CONCLUSION: This study developed and validated a new nomogram to predict CSS in middle-aged patients with EGC. The prediction model has unique and practical value and can help doctors carry out individualized treatment and judge prognosis.

Combined detection of SDC2/ADHFE1/PPP2R5C methylation in stool DNA for colorectal cancer screening.

BACKGROUND: Colorectal cancer (CRC) is a disease of global concern, and its increasing incidence suggests the need for early and accurate diagnosis. The aim of this study was to investigate the value of combined detection of SDC2, ADHFE1 and PPP2R5C gene methylation in stool samples for early CRC screening. METHODS: Stool samples from patients with CRC (n = 105), advanced adenoma (AA) (n = 54), non-advanced adenoma (NA) (n = 57), hyperplastic or other polyps (HOP) (n = 47) or no evidence of disease (NED) (n = 100) were collected from September 2021 to September 2022. The methylation levels of SDC2, ADHFE1 and PPP2R5C were quantified by quantitative methylation-specific polymerase chain reaction (qMSP), and faecal immunochemical testing (FIT) was performed. The diagnostic value was assessed using reporter operating characteristic (ROC) curve analysis. RESULTS: The sensitivity of combined detection of SDC2/ADHFE1/PPP2R5C methylation in predicting CRC (0-IV) was 84.8%, the specificity was 98.0%, and the AUC was 0.930 (95% CI 0.889-0.970). Compared to FIT and serum tumour biomarkers, it showed better diagnostic performance for different stages of CRC. CONCLUSION: The results of this study verified that the methylation levels of SDC2, ADHFE1 and PPP2R5C in stool DNA were significantly increased in CRC patients. Combined detection of SDC2/ADHFE1/PPP2R5C methylation is a potential non-invasive diagnostic method for CRC and precancerous lesion screening. CLINICAL TRIAL REGISTRATION: Chinese Clinical Trials Registry, ChiCTR2100046662, registered on 26 May 2021, prospective registration.

New scoring system combining computed tomography body composition analysis and inflammatory-nutritional indicators to predict postoperative complications in stage II-III colon cancer.

BACKGROUND AND AIM: Postoperative complications are important clinical outcomes for colon cancer patients. This study aimed to investigate the predictive value of inflammatory-nutritional indicators combined with computed tomography body composition on postoperative complications in patients with stage II-III colon cancer. METHODS: We retrospectively collected data from patients with stage II-III colon cancer admitted to our hospital from 2017 to 2021, including 198 patients in the training cohort and 50 patients in the validation cohort. Inflammatory-nutritional indicators and body composition were included in the univariate and multivariate analyses. Binary regression was used to develop a nomogram and evaluate its predictive value. RESULTS: In the multivariate analysis, the monocyte-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), nutritional risk score (NRS), skeletal muscle index (SMI), and visceral fat index (VFI) were independent risk factors for postoperative complications of stage II-III colon cancer. In the training cohort, the area under the receiver operating characteristic curve of the predictive model was 0.825 (95% confidence interval [CI] 0.764-0.886). In the validation cohort, it was 0.901 (95% CI 0.816-0.986). The calibration curve showed that the prediction results were in good agreement with the observational results. Decision curve analysis showed that colon cancer patients could benefit from the predictive model. CONCLUSIONS: A nomogram combining MLR, SII, NRS, SMI, and VFI with good accuracy and reliability in predicting postoperative complications in patients with stage II-III colon cancer was established, which can help guide treatment decisions.

CT-based radiomics for the identification of colorectal cancer liver metastases sensitive to first-line irinotecan-based chemotherapy.

BACKGROUND: Chemosensitivity prediction in colorectal cancer patients with liver metastases has remained a research hotspot. Radiomics can extract features from patient imaging, and deep learning or machine learning can be used to build models to predict patient outcomes prior to chemotherapy. PURPOSE: In this study, the radiomics features and clinical data of colorectal cancer patients with liver metastases were used to predict their sensitivity to irinotecan-based chemotherapy. METHODS: A total of 116 patients with unresectable colorectal cancer liver metastases who received first-line irinotecan-based chemotherapy from January 2015 to January 2020 in our institution were retrospectively collected. Overall, 116 liver metastases were randomly divided into training (n = 81) and validation (n = 35) cohorts in a 7:3 ratio. The effect of chemotherapy was determined based on Response Evaluation Criteria in Solid Tumors. The lesions were divided into response and nonresponse groups. Regions of interest (ROIs) were manually segmented, and sample sizes of 1×1×1, 3×3×3, 5×5×5 mm3 were used to extract radiomics features. The relevant features were identified through Pearson correlation analysis and the MRMR algorithm, and the clinical data were merged into the artificial neural network. Finally, the p-model was obtained after repeated learning and testing. RESULTS: The p-model could distinguish responders in the training (area under the curve [AUC] 0.754, 95% CI 0.650-0.858) and validation cohorts (AUC 0.752 95% CI 0.581-0.904). AUC values of the pure image group model are 0.720 (95% CI 0.609-0.827) and 0.684 (95% CI 0.529-0.890) for the training and validation cohorts respectively. As for the clinical data model, AUC values of the training and validation cohorts are 0.638 (95% CI 0.500-0.757) and 0.545 (95% CI 0.360-0.785), respectively. The performances of the latter two are less than that of the former. CONCLUSION: The p-model has the potential to discriminate colorectal cancer patients sensitive to chemotherapy. This model holds promise as a noninvasive tool to predict the response of colorectal liver metastases to chemotherapy, allowing for personalized treatment planning.

Quantitative Radiological Features and Deep Learning for the Non-Invasive Evaluation of Programmed Death Ligand 1 Expression Levels in Gastric Cancer Patients: A Digital Biopsy Study.

RATIONALE AND OBJECTIVES: Programmed Death-Ligand 1 (PD-L1) is an important biomarker for patient selection of immunotherapy in gastric cancer (GC). This study aimed to construct and validate a non-invasive virtual biopsy system based on radiological features and clinical factors to predict the PD-L1 expression level in GC. MATERIALS AND METHODS: 217 patients who received gastrectomy for GC were consecutively enrolled in this study, with 157 patients from center 1 as the training cohort and 60 patients from center 2 as the external validation cohort. 1205 quantitative radiomics features were extracted from preprocessed pre-operative contrast-enhanced CT images of enrolled patients. A radiological signature was computed using a regression random forest model and was integrated with clinical factors in a multilayer perceptron. The performance of the digital biopsy system was evaluated by the receiver operating characteristic (ROC) curve and calibration curve in both the training and validation cohort. RESULTS: 15 features were selected for the construction of radiological signature, which was significantly associated with expression levels of PD-L1 in both the training cohort (p<0.0001) and the external validation cohort (p<0.01). The hybrid deep learning model integrating the radiological signature and clinical factor could accurately distinguish GCs with high PD-L1 expression levels in both the training cohort (AUC = 0.806, 95%CI: 0.736-0.875) and the validation cohort (AUC = 0.784, 95%CI: 0.668-0.901). CONCLUSIONS: Our results indicate that the combination of deep learning and quantitative radiological features are potential approaches for the non-invasive evaluation of PD-L1 expression levels in GC. The digital biopsy system could provide valuable suggestive information for clinical decision-making of immunotherapy in GC.

Incidence and risk factors for parastomal hernia with a permanent colostomy.

AIM: This study aims to explore the incidence and risk factors for permanent colostomy complicated with a parastomal hernia (PSH) after rectal cancer resection. METHODS: This was a retrospective study of gastrointestinal surgery performed from January 2013 to December 2017 in patients with colorectal cancer treated at the Affiliated Hospital of Qingdao University. The relevant clinical variables of the patient were analyzed. Kaplan-Meier, univariate, and Cox multivariate analyses were used to evaluate the influencing factors and morbidity of PSH. RESULTS: Among the 211 patients, 65 developed PSH. The cumulative incidence reached 33.5% at 62 months. In the multivariate Cox survival analysis, the results showed that being a woman, aged ≥65 years, having a body mass index (BMI) ≥ 25 kg/m2 , diabetes, and Clavien-Dindo Grade III and IV complications were risk factors for the occurrence of PSH. CONCLUSION: In our study, the incidence of PSH increased annually and reached a maximum of 33.5% after 62 months. Among the patient-related factors, female sex, age ≥65 years, BMI ≥ 25 kg/m2 , diabetes, and postoperative Clavien-Dindo Grade III and IV complications were significantly associated with the development of PSH. Therefore, intervention measures to prevent patients with this risk factor are advisable.

Case Report: Small Bowel Obstruction Owing to Self-Anchoring Barbed Suture Device After TAPP Repair.

Groin hernioplasty is the most performed intervention in the adults worldwide, the minimally invasive inguinal hernia repair techniques widely used by surgeons today are transabdominal preperitoneal patch plasty (TAPP) and total extraperitoneal patch plasty (TEP). We report a 62-year-old man with bowel obstruction caused by the use of self-anchoring barbed suture to close the peritoneum 3 days after TAPP. Surgeons using the barbed suture should be alert to this possibility when encountering this complication of intestinal obstruction, so as to avoid more serious consequences.

Establishment and Applicability of a Diagnostic System for Advanced Gastric Cancer T Staging Based on a Faster Region-Based Convolutional Neural Network.

Background: The accurate prediction of the tumor infiltration depth in the gastric wall based on enhanced CT images of gastric cancer is crucial for screening gastric cancer diseases and formulating treatment plans. Convolutional neural networks perform well in image segmentation. In this study, a convolutional neural network was used to construct a framework for automatic tumor recognition based on enhanced CT images of gastric cancer for the identification of lesion areas and the analysis and prediction of T staging of gastric cancer. Methods: Enhanced CT venous phase images of 225 patients with advanced gastric cancer from January 2017 to June 2018 were retrospectively collected. Ftable LabelImg software was used to identify the cancerous areas consistent with the postoperative pathological T stage. The training set images were enhanced to train the Faster RCNN detection model. Finally, the accuracy, specificity, recall rate, F1 index, ROC curve, and AUC were used to quantify the classification performance of T staging on this system. Results: The AUC of the Faster RCNN operating system was 0.93, and the recognition accuracies for T2, T3, and T4 were 90, 93, and 95%, respectively. The time required to automatically recognize a single image was 0.2 s, while the interpretation time of an imaging expert was ~10 s. Conclusion: In enhanced CT images of gastric cancer before treatment, the application of Faster RCNN to diagnosis the T stage of gastric cancer has high accuracy and feasibility.

The Safety and Efficacy of Laparoscopic Common Bile Duct Exploration Combined with Cholecystectomy for the Management of Cholecysto-choledocholithiasis: An Up-to-date Meta-analysis.

OBJECTIVE: The aim of this study was to compare the efficacy and safety of the laparoscopic common bile duct exploration (LCBDE) and laparoscopic cholecystectomy (LC) with preoperative endoscopic sphincterotomy (pre-EST) and LC for concomitant gallstones and common bile duct (CBD) stones. BACKGROUND: It remains controversial whether LCBDE+LC is better than pre-EST+LC for gallstones and CBD stones. METHODS: A specific search of online databases was performed from January 2006 to October 2017. Relative outcomes of perioperative safety and postoperative efficacy were synthesized. Single-arm meta-analysis and cumulative meta-analysis were also conducted. RESULTS: A total of 13 studies involving 1757 (872 vs 885) patients were included for analysis in our study. The CBD stones clearance rate [94.1% vs 90.1%; odds ratio (OR) 1.56, P = 0.012] was significantly higher in patients who underwent LCBDE+LC than pre-EST+LC, while perioperative complications (7.6% vs 12.0%; OR 0.67, P = 0.015), conversion to other procedure (4.1% vs 7.1%; OR 0.64, P = 0.025), retained stones rate (1.2% vs 7.9%; OR 0.34, P = 0.004), lithiasis recurrence rate (1.8% vs 5.6%, OR 0.32, P = 0.005), operative time [112.28 vs 132.03 minutes; weighted mean difference (WMD) -18.08, P = 0.002], length of hospital stay (4.94 vs 6.62 days; WMD -1.63, P = 0.023), and total charges [standardized mean difference (SMD) -2.76, P = 0.002] were significantly lower in LCBDE+LC. The mortality (0.6% vs 1.1%; OR 0.32, P = 0.117) was similar between the 2 groups. The cumulative meta-analyses indicated the effect sizes of CBD stones clearance rate, perioperative complications, and conversion to other procedure have already stabilized between 2 groups. CONCLUSION: The updated meta-analysis first confirms that LCBDE+LC is superior to pre-EST+LC both in perioperative safety and short- and long-term postoperative efficacy, which should be considered as optimal treatment choice for cholecysto-choledocholithiasis.

ELF3 promotes epithelial-mesenchymal transition by protecting ZEB1 from miR-141-3p-mediated silencing in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignant cancers and currently the third leading cause of cancer-related deaths, worldwide. Epithelial-mesenchymal transition (EMT) plays a major role in HCC progression. In this study, we first found that the expression of E74-like ETS transcription factor 3 (ELF3), a member of the E-twenty-six family of transcription factors, was increased in HCC tissues, and that ELF3 overexpression was associated with poor prognoses for HCC patients. Gain-of-function and loss-of-function studies revealed that increased ELF3 expression promoted HCC cell proliferation, migration, and invasion, while these processes were inhibited when ELF3 was silenced. Additionally, ELF3 was found to promote EMT, which we demonstrated through decreased E-cadherin expression and increased N-cadherin and fibronectin expression. ELF3 knockdown reversed EMT via repressing ZEB1 expression through miR-141-3p upregulation. Chromatin immunoprecipitation assays revealed that ELF3 bound to the miR-141-3p promoter, suppressing miR-141-3p expression. Taken together, our data show that ELF3 repressed E-cadherin and promoted EMT in HCC cells by suppressing miR-141-3p, thereby activating ZEB1. Thus, ELF3 may be a potential prognostic biomarker and/or therapeutic target for HCC.

Increasing AR by HIF-2α inhibitor (PT-2385) overcomes the side-effects of sorafenib by suppressing hepatocellular carcinoma invasion via alteration of pSTAT3, pAKT and pERK signals.

Although sorafenib is currently used as a standard treatment for advanced hepatocellular carcinoma, low response rate, transient and limited efficacy, primary and acquired resistance and negative side-effects gain increasing attentions, suggesting the need for better efficacious combination therapy. Here, we demonstrated that the sorafenib-induced or hypoxia-induced hypoxia inducible factor (HIF)-2α could bind to an hypoxia responsive element within 500 bp region of androgen receptor (AR) promoter and thus transcriptionally suppress AR. Importantly, In vitro and In vivo studies suggested a specific and potent HIF-2α inhibitor, PT-2385, could significantly enhance sorafenib efficacy by suppressing HIF-2α, increasing AR and suppressing downstream pSTAT3/pAKT/pERK pathways. Clinical samples further confirmed the role of HIF-2α and AR. It is promising that PT-2385 could alleviate the undesirable side-effects of sorafenib treatment by sorafenib-PT-2385 combination therapy, which may shed light for late-stage HCC patients.