Peripheral Lymphocyte Changes Associate With the Progression of Necrotizing Enterocolitis in Infants.

INTRODUCTION: Immune factors are important antecedents in the pathophysiology of necrotizing enterocolitis (NEC). However, studies on the peripheral blood lymphocyte subsets changes in NEC patients among different Bell stages and in patients requiring surgery are scarce. METHODS: 34 infants with NEC and 33 age-matched controls were included. Peripheral blood was collected within 48 h after NEC diagnosis. Peripheral blood B and T lymphocytes subsets were detected by 12-color flow cytometry. Cell ratios were calculated, and their relationship to disease severity and their roles as indicators for surgery were assessed. RESULTS: NEC patients showed elevated percentages of unSwB cells (CD27+IgD+ unswitched memory/activated B cells)/B cells, SwB cells (CD27+IgD-switched memory B cells)/B cells, CD8+ T (CD3+CD8+ T cells)/T cells, Tem (CD45RA-CCR7-effector memory T cells)/CD4+ T cells, Tem/CD8+ T cells and decreased Bn (CD27-IgD+ naïve B cells)/B cells, CD4+T (CD3+CD4+ T cells)/T cells, CD45RA+ CCR7+ naïve T cells (CD45RA+CCR7+ naïve T cells)/CD8+T cells. Compared to NEC patients at BELL stage I + II, patients at BELL stage III showed increased percentages of SwB cells/B cells, antibody secreting cell (ASC, CD3-CD20-CD27high CD38high ASCs)/B cells and Tem/CD4+ T cells, and decreased percentages of CD45RA+CCR7+ naïve T cells/CD4+ T cells. The Receiver Operating Characteristic Curve analysis showed that the sensitivity of ASC/B cells ratio (0.52%) is 86.67% and the specificity of Tem/CD4+T ratio (5.22%) is 100%, indicating that NEC patients required surgery. CONCLUSIONS: The severity of NEC exhibits codirectional changes with the maturation of B and T lymphocytes, especially CD4+ T cells. The increased ASC/B and Tem/CD4+ T cells could serve as potential indicators for NEC patients requiring surgery.

Evidence-based advances in minimally invasive surgery in infants with congenital gastrointestinal anomalies: a narrative review.

Background and Objective: Minimally invasive surgery (MIS) has been widely utilized to manage congenital gastrointestinal (GI) anomalies in children during the last two decades. Currently, MIS has a proven track-record for its feasibility and provides multiple benefits including better cosmesis, less trauma, and faster recovery in neonates and infants. However, it remains controversial whether MIS provides better definitive outcomes in pediatric patients with GI anomalies, especially among neonates. We aim to review the recent developments of MIS in infants with GI defects, assisting surgeons in making decisions and improving patient outcomes. Methods: A comprehensive literature search of PubMed and Web of Science's core collection was performed using terms of MIS techniques and congenital GI anomalies. Key Content and Findings: This review summarizes recent evidence-based advances of MIS in infants with congenital GI defects and potential future strategies based on evidence. Better cosmetic results, less postoperative pain, and an accelerated recovery have been shown to be common advantages of MIS relative to open approaches. Technical hurdles and metabolic disturbance were reported to be the main reasons for the decisions of open approach. Conclusions: Advanced techniques of MIS have made more precise manipulations and better outcomes possible, even for newborns. At the same time, surgeons should not be afraid to use an open approach in certain circumstances due to technical limitations or patient tolerance. The difficulty infants face in expressing their true feelings underscores the need for systematic and objective assessment tools to evaluate surgical outcomes.

Advanced Gastric Cancer: CT Radiomics Prediction of Lymph Modes Metastasis After Neoadjuvant Chemotherapy.

This study aims to create and assess machine learning models for predicting lymph node metastases following neoadjuvant treatment in advanced gastric cancer (AGC) using baseline and restaging computed tomography (CT). We evaluated CT images and pathological data from 158 patients with resected stomach cancer from two institutions in this retrospective analysis. Patients were eligible for inclusion if they had histologically proven gastric cancer. They had received neoadjuvant chemotherapy, with at least 15 lymph nodes removed. All patients received baseline and preoperative abdominal CT and had complete clinicopathological reports. They were divided into two cohorts: (a) the primary cohort (n = 125) for model creation and (b) the testing cohort (n = 33) for evaluating models' capacity to predict the existence of lymph node metastases. The diagnostic ability of the radiomics-model for lymph node metastasis was compared to traditional CT morphological diagnosis by radiologist. The radiomics model based on the baseline and preoperative CT images produced encouraging results in the training group (AUC 0.846) and testing cohort (AUC 0.843). In the training cohort, the sensitivity and specificity were 81.3% and 77.8%, respectively, whereas in the testing cohort, they were 84% and 75%. The diagnostic sensitivity and specificity of the radiologist were 70% and 42.2% (using baseline CT) and 46.3% and 62.2% (using preoperative CT). In particular, the specificity of radiomics model was higher than that of conventional CT in diagnosing N0 cases (no lymph node metastasis). The CT-based radiomics model could assess lymph node metastasis more accurately than traditional CT imaging in AGC patients following neoadjuvant chemotherapy.

Donafenib inhibits PARP1 expression and induces DNA damage, in combination with PARP1 inhibitors promotes apoptosis in liver cancer cells.

Liver cancer is a prevalent malignant tumor globally. The newly approved first-line drug, donafenib, is a novel oral small molecule multi-tyrosine kinase inhibitor that has significant antitumor effects on liver cancer. This study aims to investigate the antitumor effects of donafenib on liver cancer and to explore its potential mechanisms. Donafenib significantly inhibited the viability of Huh-7 and HCCLM3 cells, inhibited malignant cell proliferation, and promoted cell apoptosis, as demonstrated by CCK-8, EdU, and Calcein/PI (propidium iodide) staining experiments. The results of DNA damage detection experiments and western blot analysis indicate that donafenib caused considerable DNA damage in liver cancer cells. The analysis of poly (ADP-ribose) polymerase 1 (PARP1) in liver cancer patients using online bioinformatics data websites such as TIMER2.0, GEPIA, UALCAN, cBioPortal, Kaplan-Meier Plotter, and HPA revealed a high expression of PARP1, which is associated with poor prognosis. Molecular docking and western blot analysis demonstrated that donafenib can directly target and downregulate the protein expression of PARP1, a DNA damage repair protein, thereby promoting DNA damage in liver cancer cells. Western blot and immunofluorescence detection showed that the group treated with donafenib combined with PARP1 inhibitor had significantly higher expression of γ-H2AX and 8-OHdG compared to the groups treated with donafenib or PARP1 inhibitors alone, the combined treatment suppresses the expression of the antiapoptotic protein Bcl2 and enhances the protein expression level of the proapoptotic protein Bcl-2-associated X protein (BAX). These data suggest that the combination of donafenib and a PARP1 inhibitor results in more significant DNA damage in cells and promotes cell apoptosis. Thus, the combination of donafenib and PARP1 inhibitors has the potential to be a treatment option for liver cancer.

[Research progress on ferroptosis in tumor immunity].

Ferroptosis is a novel form of cell death that is induced by excessive accumulation of ferrous ions and lipid peroxides. It triggers the release of damage-associated molecular patterns through autophagy-dependent mechanisms, serving as an adjunct to immunogenic cell death and activating both adaptive and innate immunity. In the tumor microenvironment, the regulation and influence of tumor cells and immune cells undergoing ferroptosis are regulated by various factors, which plays a crucial role in tumor development, treatment, and prognosis. This article provides an overview of the biological effects of ferroptosis on immune cells such as T cells, macrophages, neutrophils and B cells and tumor cells in the tumor microenvironment.

Iron metabolism: backfire of cancer cell stemness and therapeutic modalities.

Cancer stem cells (CSCs), with their ability of self-renewal, unlimited proliferation, and multi-directional differentiation, contribute to tumorigenesis, metastasis, recurrence, and resistance to conventional therapy and immunotherapy. Eliminating CSCs has long been thought to prevent tumorigenesis. Although known to negatively impact tumor prognosis, research revealed the unexpected role of iron metabolism as a key regulator of CSCs. This review explores recent advances in iron metabolism in CSCs, conventional cancer therapies targeting iron biochemistry, therapeutic resistance in these cells, and potential treatment options that could overcome them. These findings provide important insights into therapeutic modalities against intractable cancers.

Spontaneous intestinal perforation among very preterm infants in China: a multicenter cohort study.

Background: Spontaneous intestinal perforation (SIP) is one of the most serious surgical bowel conditions affecting preterm infants. There are limited data on the mortality and morbidities of very preterm infants [VPIs, <32 weeks' gestational age (GA)] with SIP in China. The study aimed to describe the prevalence, treatment, and outcomes of SIP among VPIs in China. Methods: This retrospective cohort study included all infants born at 24+0-31+6 weeks GA from January 1, 2019, to December 31, 2020, and admitted within seven days after birth to the neonatal intensive care units in the Chinese Neonatal Network. The primary outcome was survival without major morbidities. The association between SIP and neonatal outcomes was evaluated using multivariate logistic regression controlling for possible confounders. Results: Out of the 15,814 enrolled infants, 150 (1.0%) developed SIP with a median onset age of four (IQR 2-6) days. Infants with GA 24+0-25+6 weeks had the highest incidence of SIP (13/532, 2.4%), followed by those with GA 26+0-27+6 weeks (22/2,005, 1.1%), 28+0-29+6 weeks (44/5,269, 0.8%) and 30+0-31+6 weeks (71/8,008, 0.9%). Ten SIP cases were lost to follow-up with unknown survival status and 41 (29.3%) of the remaining 140 infants with SIP died during hospitalization. Only 29.3% of infants with SIP survived without major morbidities, significantly lower than those without SIP (59.2%; P<0.01). Multivariate analysis revealed SIP was associated with a higher risk of overall death (adjusted OR 3.36; 95% CI: 1.85 to 6.08), late-onset sepsis (adjusted OR 2.10; 95% CI: 1.02 to 4.31), and bronchopulmonary dysplasia (adjusted OR 2.49; 95% CI: 1.44 to 4.30). Among all infants with SIP, 28 (18.7%) did not receive any surgical intervention. Laparotomy was provided to 113 (92.6%) of the remaining 122 infants, solely (84/122, 68.9%) or following peritoneal drainage (29/122, 23.8%), while nine (7.4%) infants underwent peritoneal drainage only. Conclusions: Around 1% of VPIs in China developed SIP, associated with increased risk of mortality and morbidities. Over 90% of VPIs with SIP underwent laparotomy as initial or subsequent surgical treatment. Effective and evidence-based strategies are needed for the prevention and management of SIP.

Prognostic predictive value of urothelial carcinoma of the bladder after TURBT based on multiphase CT radiomics.

OBJECTIVE: To investigate multiphase computed tomography (CT) radiomics-based combined with clinical factors to predict overall survival (OS) in patients with bladder urothelial carcinoma (BLCA) who underwent transurethral resection of bladder tumor (TURBT). METHODS: Data were retrospectively collected from 114 patients with primary BLCA from February 2016 to February 2018. The regions of interest (ROIs) of the plain, arterial, and venous phase images were manually segmented. The Cox regression algorithm was used to establish 3 basic models for the plain phase (PP), arterial phase (AP), and venous phase (VP) and 2 combination models (AP + VP and PP + AP + VP). The highest-performing radiomics model was selected to calculate the radiomics score (Rad-score), and independent risk factors affecting patients' OS were analyzed using Cox regression. The Rad-score and clinical risk factors were combined to construct a joint model and draw a visualized nomogram. RESULTS: The combined model of PP + AP + VP showed the best performance with the Akaike Information Criterion (AIC) and Consistency Index (C-index) in the test group of 130.48 and 0.779, respectively. A combined model constructed with two independent risk factors (age and Ki-67 expression status) in combination with the Rad-score outperformed the radiomics model alone; AIC and C-index in the test group were 115.74 and 0.840, respectively. The calibration curves showed good agreement between the predicted probabilities of the joint model and the actual (p < 0.05). The decision curve showed that the joint model had good clinical application value within a large range of threshold probabilities. CONCLUSION: This new model can be used to predict the OS of patients with BLCA who underwent TURBT.

TRAF6 enhances PD-L1 expression through YAP1-TFCP2 signaling in melanoma.

Immunotherapy represented by programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) monoclonal antibodies has led tumor treatment into a new era. However, the low overall response rate and high incidence of drug resistance largely damage the clinical benefits of existing immune checkpoint therapies. Recent studies correlate the response to PD-1/PD-L1 blockade with PD-L1 expression levels in tumor cells. Hence, identifying molecular targets and pathways controlling PD-L1 protein expression and stability in tumor cells is a major priority. In this study, we performed a Stress and Proteostasis CRISPR interference screening to identify PD-L1 positive modulators. Here, we identified TRAF6 as a critical regulator of PD-L1 in melanoma cells. As a non-conventional E3 ubiquitin ligase, TRAF6 is inclined to catalyze the synthesis and linkage of lysine-63 (K63) ubiquitin which is related to the stabilization of substrate proteins. Our results showed that suppression of TRAF6 expression down-regulates PD-L1 expression on the membrane surface of melanoma cells. We then used in vitro and in vivo assays to investigate the biological function and mechanism of TRAF6 and its downstream YAP1/TFCP2 signaling in melanoma. TRAF6 stabilizes YAP1 by K63 poly-ubiquitination modification, subsequently promoting the formation of YAP1/TFCP2 transcriptional complex and PD-L1 transcription. Inhibition of TRAF6 by Bortezomib enhanced cytolytic activity of CD8+ T cells by reduction of endogenous PD-L1. Notably, Bortezomib enhances anti-tumor immunity to an extent comparable to anti-PD-1 therapies with no obvious toxicity. Our findings reveal the potential of inhibiting TRAF6 to stimulate internal anti-tumor immunological effect for TRAF6-PD-L1 overexpressing cancers.

Cancer-associated fibroblasts in pancreatic ductal adenocarcinoma therapy: Challenges and opportunities.

Pancreatic ductal adenocarcinoma (PDAC) is a solid organ malignancy with a high mortality rate. Statistics indicate that its incidence has been increasing as well as the associated deaths. Most patients with PDAC show poor response to therapies making the clinical management of this cancer difficult. Stromal cells in the tumor microenvironment (TME) contribute to the development of resistance to therapy in PDAC cancer cells. Cancer-associated fibroblasts (CAFs), the most prevalent stromal cells in the TME, promote a desmoplastic response, produce extracellular matrix proteins and cytokines, and directly influence the biological behavior of cancer cells. These multifaceted effects make it difficult to eradicate tumor cells from the body. As a result, CAF-targeting synergistic therapeutic strategies have gained increasing attention in recent years. However, due to the substantial heterogeneity in CAF origin, definition, and function, as well as high plasticity, majority of the available CAF-targeting therapeutic approaches are not effective, and in some cases, they exacerbate disease progression. This review primarily elucidates on the effect of CAFs on therapeutic efficiency of various treatment modalities, including chemotherapy, radiotherapy, immunotherapy, and targeted therapy. Strategies for CAF targeting therapies are also discussed.

A comparative study of mono-exponential and advanced diffusion-weighted imaging in differentiating stage IA endometrial carcinoma from benign endometrial lesions.

PURPOSE: The purpose of the current investigation is to compare the efficacy of different diffusion models and diffusion kurtosis imaging (DKI) in differentiating stage IA endometrial carcinoma (IAEC) from benign endometrial lesions (BELs). METHODS: Patients with IAEC, endometrial hyperplasia (EH), or a thickened endometrium confirmed between May 2016 and August 2022 were retrospectively enrolled. All of the patients underwent a preoperative pelvic magnetic resonance imaging (MRI) examination. The apparent diffusion coefficient (ADC) from the mono-exponential model, pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) from the bi-exponential model, distributed diffusion coefficient (DDC), water molecular diffusion heterogeneity index from the stretched-exponential model, diffusion coefficient (Dk) and diffusion kurtosis (K) from the DKI model were calculated. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic efficiency. RESULTS: A total of 90 patients with IAEC and 91 patients with BELs were enrolled. The values of ADC, D, DDC and Dk were significantly lower and D* and K were significantly higher in cases of IAEC (p < 0.05). Multivariate analysis showed that K was the only predictor. The area under the ROC curve of K was 0.864, significantly higher compared with the ADC (0.601), D (0.811), D* (0.638), DDC (0.743) and Dk (0.675). The sensitivity, specificity and accuracy of K were 78.89%, 85.71% and 80.66%, respectively. CONCLUSION: Advanced diffusion-weighted imaging models have good performance for differentiating IAEC from EH and endometrial thickening. Among all of the diffusion parameters, K showed the best performance and was the only independent predictor. Diffusion kurtosis imaging was defined as the most valuable model in the current context.

Fully semantic segmentation for rectal cancer based on post-nCRT MRl modality and deep learning framework.

PURPOSE: Rectal tumor segmentation on post neoadjuvant chemoradiotherapy (nCRT) magnetic resonance imaging (MRI) has great significance for tumor measurement, radiomics analysis, treatment planning, and operative strategy. In this study, we developed and evaluated segmentation potential exclusively on post-chemoradiation T2-weighted MRI using convolutional neural networks, with the aim of reducing the detection workload for radiologists and clinicians. METHODS: A total of 372 consecutive patients with LARC were retrospectively enrolled from October 2015 to December 2017. The standard-of-care neoadjuvant process included 22-fraction intensity-modulated radiation therapy and oral capecitabine. Further, 243 patients (3061 slices) were grouped into training and validation datasets with a random 80:20 split, and 41 patients (408 slices) were used as the test dataset. A symmetric eight-layer deep network was developed using the nnU-Net Framework, which outputs the segmentation result with the same size. The trained deep learning (DL) network was examined using fivefold cross-validation and tumor lesions with different TRGs. RESULTS: At the stage of testing, the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD) were applied to quantitatively evaluate the performance of generalization. Considering the test dataset (41 patients, 408 slices), the average DSC, HD95, and MSD were 0.700 (95% CI: 0.680-0.720), 17.73 mm (95% CI: 16.08-19.39), and 3.11 mm (95% CI: 2.67-3.56), respectively. Eighty-two percent of the MSD values were less than 5 mm, and fifty-five percent were less than 2 mm (median 1.62 mm, minimum 0.07 mm). CONCLUSIONS: The experimental results indicated that the constructed pipeline could achieve relatively high accuracy. Future work will focus on assessing the performances with multicentre external validation.

Overcoming the limitations of immunotherapy in pancreatic ductal adenocarcinoma: Combining radiotherapy and metabolic targeting therapy.

As a novel anticancer therapy, immunotherapy has demonstrated robust efficacy against a few solid tumors but poor efficacy against pancreatic ductal adenocarcinoma (PDAC). This poor outcome is primarily attributable to the intrinsic cancer cell resistance and T-cell exhaustion, which is also the reason for the failure of conventional therapy. The present review summarizes the current PDAC immunotherapy avenues and the underlying resistance mechanisms. Then, the review discusses synergistic combination therapies, such as radiotherapy (RT) and metabolic targeting. Research suggests that RT boosts the antigen of PDAC, which facilitates the anti-tumor immune cell infiltration and exerts function. Metabolic reprogramming contributes to restoring the exhausted T cell function. The current review will help in tailoring combination regimens to enhance the efficacy of immunotherapy. In addition, it will help provide new approaches to address the limitations of the immunosuppressive tumor microenvironment (TME) by examining the relationship among immunotherapy, RT, and metabolism targeting therapy in PDAC.

The efficacy and safety of tislelizumab combined with gemcitabine plus cisplatin in the treatment of postoperative patients with muscle-invasive upper tract urothelial carcinoma.

BACKGROUND: A combination of immune checkpoint inhibitors (ICIs) and chemotherapy has demonstrated excellent clinical efficacy and safety in treating a variety of cancers, including urothelial carcinoma (UC). However, its efficacy and safety in patients with muscle-invasive upper tract urothelial carcinoma (UTUC) who are undergoing radical surgery remain uncertain. The purpose of this retrospective study was to examine the effectiveness and safety of tislelizumab combined with gemcitabine plus cisplatin (TGC) as a first-line postoperative adjuvant treatment in this population. METHODS: This single-center, real-world study retrospectively analyzed the data from 71 patients with muscle-invasive UTUC who had radical nephroureterectomy (RNU) at the Affiliated Hospital of Xuzhou Medical University between November 1, 2020, and November 1, 2023. Among the 71 patients, 30 received adjuvant therapy of TGC within 90 days after RNU and 41 underwent surveillance. No patients receive preoperative neoadjuvant therapy. The TGC therapy group received adjuvant therapy every 3 weeks postoperatively until the first recurrence, first metastasis, or death due to any reason, whichever occurred first. The patients were followed up telephonically and through outpatient visits to record and evaluate their disease-free survival (DFS) and treatment-related adverse events (TRAEs). RESULTS: This study assessed the DFS of 41 and 30 patients in the surveillance group and TGC therapy group, respectively. The median DFS of the surveillance group was 16.5 [95% confidence interval (CI), 14.7-18.3] months, while the median DFS of the TGC group has not yet reached [hazard ratio (HR) 0.367 (95% CI, 0.169-0.796); p = 0.008], with 21 patients still undergoing follow-up. Compared with the surveillance group, the TGC therapy group had dramatically improved DFS after RNU and reduced risk by 63.3%. Of the 30 patients receiving combination therapy, 28 experienced TRAEs; all TRAEs were consistent with the frequently reported events in the chemotherapy-alone regimens, and there were no treatment-related deaths. CONCLUSION: This study demonstrates that TGC therapy exhibits excellent clinical efficacy in patients undergoing radical surgery, significantly improving DFS and displaying great safety.

Inflammatory markers predict survival in patients with postoperative urothelial carcinoma receiving tislelizumab (PD-1 inhibitor) adjuvant therapy.

BACKGROUND: In the management of urothelial carcinoma, patient selection for immunotherapy, particularly with immune checkpoint inhibitors such as PD-1 (programmed cell death protein 1), is important for treatment efficacy. Inflammatory markers are useful for predicting treatment outcomes and immune-related adverse events (irAEs). This study aims to retrospectively explore the associations between inflammatory markers and outcomes in patients with postoperative urothelial carcinoma undergoing tislelizumab (PD-1 inhibitor) adjuvant therapy. METHODS: A retrospective analysis was conducted on 133 patients with postoperative urothelial carcinoma who received tislelizumab adjuvant therapy at the Affiliated Hospital of Xuzhou Medical University from April 2020 to August 2023. The prognostic effects of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) on disease-free survival (DFS) and overall survival (OS) were assessed using Cox regression models. The correlation between inflammatory markers and the onset of irAEs was analyzed using logistic regression models. RESULTS: NLR < 5 and MLR < 0.31 were significantly associated with better outcomes compared to NLR >5 and MLR >0.31, respectively. Multivariate analysis revealed that an NLR < 5 was independently associated with better DFS and OS. However, there was no significant effect on the DFS and OS between PLR < 135 and PLR >135. Patients who experienced irAEs had longer DFS and OS. Multivariate analysis demonstrated that irAEs were an independent prognostic risk factor for DFS and OS. There was no significant difference in the occurrence of irAEs among different NLR, PLR, and MLR groups. CONCLUSION: In patients with postoperative urothelial carcinoma receiving tislelizumab adjuvant therapy, the assessment of NLR and MLR before treatment may serve as valuable predictive markers of clinical outcome.

Intratumoral and peritumoral CT-based radiomics for predicting the microsatellite instability in gastric cancer.

PURPOSE: To investigate the value of intratumoral and peritumoral radiomics based on contrast-enhanced computer tomography (CECT) to preoperatively predict microsatellite instability (MSI) status in gastric cancer (GC) patients. METHODS: A total of 189 GC patients, including 63 patients with MSI-high (MSI-H) and 126 patients with MSI-low/stable (MSI-L/S), were randomly divided into the training cohort and validation cohort. Intratumoral and 5-mm peritumoral regions' radiomics features were extracted from CECT images. The features were standardized by Z-score, and the Inter- and intraclass correlation coefficient, univariate logistic regression analysis, and least absolute shrinkage and selection operator (LASSO) were applied to select the optimal radiomics features. Radiomics scores (Rad-score) based on intratumoral regions, peritumoral regions, and intratumoral + 5-mm peritumoral regions were calculated by weighting the linear combination of the selected features with their respective coefficients to construct the intratumoral model, peritumoral model, and intratumoral + peritumoral model. Logistic regression was used to establish a combined model by combining clinical characteristics, CT semantic features, and Rad-score of intratumoral and peritumoral regions. RESULTS: Eleven radiomics features were selected to establish a radiomics intratumoral + peritumoral model. CT-measured tumor length and tumor location were independent risk factors for MSI status. The established combined model obtained the highest area under the receiver operating characteristic (ROC) curve (AUC) of 0.830 (95% CI, 0.727-0.906) in the validation cohort. The calibration curve and decision curve demonstrated its good model fitness and clinical application value. CONCLUSION: The combined model based on intratumoral and peritumoral CECT radiomics features and clinical factors can predict the MSI status of GS with moderate accuracy before surgery, which helps formulate personalized treatment strategies.

Radiomics analysis from magnetic resonance imaging in predicting the grade of nonfunctioning pancreatic neuroendocrine tumors: a multicenter study.

OBJECTIVES: To explore the potential of radiomics features to predict the histologic grade of nonfunctioning pancreatic neuroendocrine tumor (NF-PNET) patients using non-contrast sequence based on MRI. METHODS: Two hundred twenty-eight patients with NF-PNETs undergoing MRI at 5 centers were retrospectively analyzed. Data from center 1 (n = 115) constituted the training cohort, and data from centers 2-5 (n = 113) constituted the testing cohort. Radiomics features were extracted from T2-weighted images and the apparent diffusion coefficient. The least absolute shrinkage and selection operator was applied to select the most important features and to develop radiomics signatures. The area under receiver operating characteristic curve (AUC) was performed to assess models. RESULTS: Tumor boundary, enhancement homogeneity, and vascular invasion were used to construct the radiological model to stratify NF-PNET patients into grade 1 and 2/3 groups, which yielded AUC of 0.884 and 0.684 in the training and testing groups. A radiomics model including 4 features was constructed, with an AUC of 0.941 and 0.871 in the training and testing cohorts. The fusion model combining the radiomics signature and radiological characteristics showed good performance in the training set (AUC = 0.956) and in the testing set (AUC = 0.864), respectively. CONCLUSION: The developed model that integrates radiomics features with radiological characteristics could be used as a non-invasive, dependable, and accurate tool for the preoperative prediction of grade in NF-PNETs. CLINICAL RELEVANCE STATEMENT: Our study revealed that the fusion model based on a non-contrast MR sequence can be used to predict the histologic grade before operation. The radiomics model may be a new and effective biological marker in NF-PNETs. KEY POINTS: The diagnostic performance of the radiomics model and fusion model was better than that of the model based on clinical information and radiological features in predicting grade 1 and 2/3 of nonfunctioning pancreatic neuroendocrine tumors (NF-PNETs). Good performance of the model in the four external testing cohorts indicated that the radiomics model and fusion model for predicting the grades of NF-PNETs were robust and reliable, indicating the two models could be used in the clinical setting and facilitate the surgeons' decision on risk stratification. The radiomics features were selected from non-contrast T2-weighted images (T2WI) and diffusion-weighted imaging (DWI) sequence, which means that the administration of contrast agent was not needed in grading the NF-PNETs.

Preoperative Noninvasive Evaluation of Tumor Budding in Rectal Cancer Using Multiparameter MRI Radiomics.

RATIONALE AND OBJECTIVES: To assess the value of a multiparametric magnetic resonance imaging (MRI)-based model integrating radiomics features with clinical and MRI semantic features for preoperative evaluation of tumor budding (TB) in rectal cancer. MATERIALS AND METHODS: A total of 120 patients with pathologically confirmed rectal cancer were retrospectively analyzed. The patients were randomized into training and validation cohorts in a 6:4 ratio. Radiomics features were extracted and selected from preoperative T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted imaging (T1CE) sequences, after which the corresponding radiomics score (RS) was calculated, and the radiomics models (T2WI model, DWI model, and T1CE model) were constructed. Logistic regression analysis was selected to develop a combined model integrated RST2WI, RSDWI, RST1CE, and clinical and MRI semantic features. The efficacy of each model in diagnosing TB grade was observed by the receiver operating characteristic (ROC) curve. Decision curve analysis (DCA) was used to assess the clinical benefits of the models. RESULTS: Seven features were extracted and selected from each T2WI, DWI, and T1CE sequence to calculate the corresponding RS and construct the corresponding radiomics model. MRI reported N stage was an independent risk factor for TB. The area under the ROC curve of the combined model was 0.961 and 0.891 in the training and validation cohorts, respectively. The combined model showed better performance than the other models. DCA showed that the net benefit of the combined model was better than that of the other models in the vast majority of threshold probabilities. CONCLUSION: A combined model integrating radiomics features and MRI semantic features allows for noninvasive preoperative evaluation of TB grading in patients with rectal cancer.

CT radiomics in the identification of preoperative understaging in patients with clinical stage T1-2N0 esophageal squamous cell carcinoma.

Background: Predicting preoperative understaging in patients with clinical stage T1-2N0 (cT1-2N0) esophageal squamous cell carcinoma (ESCC) is critical to customizing patient treatment. Radiomics analysis can provide additional information that reflects potential biological heterogeneity based on computed tomography (CT) images. However, to the best of our knowledge, no studies have focused on identifying CT radiomics features to predict preoperative understaging in patients with cT1-2N0 ESCC. Thus, we sought to develop a CT-based radiomics model to predict preoperative understaging in patients with cT1-2N0 esophageal cancer, and to explore the value of the model in disease-free survival (DFS) prediction. Methods: A total of 196 patients who underwent radical surgery for cT1-2N0 ESCC were retrospectively recruited from two hospitals. Among the 196 patients, 134 from Peking University Cancer Hospital were included in the training cohort, and 62 from Henan Cancer Hospital were included in the external validation cohort. Radiomics features were extracted from patients' CT images. Least absolute shrinkage and selection operator (LASSO) regression was used for feature selection and model construction. A clinical model was also built based on clinical characteristics, and the tumor size [the length, thickness and the thickness-to-length ratio (TLR)] was evaluated on the CT images. A radiomics nomogram was established based on multivariate logistic regression. The diagnostic performance of the models in predicting preoperative understaging was assessed by the area under the receiver operating characteristic curve (AUC). Kaplan-Meier curves with the log-rank test were employed to analyze the correlation between the nomogram and DFS. Results: Of the patients, 50.0% (67/134) and 51.6% (32/62) were understaged in the training and validation groups, respectively. The radiomics scores and the TLRs of the tumors were included in the nomogram. The AUCs of the nomogram for predicting preoperative understaging were 0.874 [95% confidence interval (CI): 0.815-0.933] in the training cohort and 0.812 (95% CI: 0.703-0.912) in the external validation cohort. The diagnostic performance of the nomogram was superior to that of the clinical model (P<0.05). The nomogram was an independent predictor of DFS in patients with cT1-2N0 ESCC. Conclusions: The proposed CT-based radiomics model could be used to predict preoperative understaging in patients with cT1-2N0 ESCC who have undergone radical surgery.

Delta- like ligand 4- expressing macrophages and human diseases: Insights into pathophysiology and therapeutic opportunities.

Macrophages are key players in the immune response and have been implicated in various human diseases, including atherosclerosis, cancer, and chronic inflammatory disorders. While numerous studies have delved into the nuances of macrophage behavior in these conditions, there remains a gap in understanding the specific role of Delta-like ligand 4 (Dll4)-expressing macrophages and their overarching implications across these diseases. Among the plethora of factors expressed by macrophages, Dll4 has emerged as a molecule of particular interest. Recent studies have highlighted its unique role in modulating macrophage functions and its potential implications in various diseases. This review seeks to consolidate existing knowledge, address this gap, and present a comprehensive overview of Dll4-expressing macrophages in the context of these disorders and highlight their potential as therapeutic targets. We examined the involvement of Dll4-expressing macrophages in multiple human diseases such as atherosclerosis, cancer and chronic inflammatory diseases, emphasizing their influence on disease progression. We also discussed the challenges, limitations, and emerging research areas in targeting Dll4-expressing macrophages and provide an outlook on potential therapeutic strategies for the treatment of these diseases. By addressing the previously existing research gap, we've provided a roadmap that brings together fragmented insights, paving the way for more holistic research and potentially more effective therapeutic strategies centered on Dll4-expressing macrophages.