A5091216176- Gastric Cancer Management and Outcomes
- Radiomics and Machine Learning in Medical Imaging
- Immune cells in cancer
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Gastrointestinal Tumor Research and Treatment
- Cancer Immunotherapy and Biomarkers
- AI in cancer detection
- Gene expression and cancer classification
- Neutrophil, Myeloperoxidase and Oxidative Mechanisms
- Metastasis and carcinoma case studies
- Cytokine Signaling Pathways and Interactions
- Colorectal Cancer Treatments and Studies
- Colorectal and Anal Carcinomas
- Solar and Space Plasma Dynamics
- Helicobacter pylori-related gastroenterology studies
- Lung Cancer Diagnosis and Treatment
- Cancer-related molecular mechanisms research
- Cancer Genomics and Diagnostics
- Colorectal Cancer Screening and Detection
- Medical Image Segmentation Techniques
- Medical Imaging Techniques and Applications
- Advanced Radiotherapy Techniques
- Liver Disease Diagnosis and Treatment
- Advanced X-ray and CT Imaging
- Medical Imaging and Analysis
Wake Forest University
2023-2025
Stanford University
2004-2025
First Affiliated Hospital of Wannan Medical College
2016-2024
Palo Alto University
2023-2024
Beihang University
2024
Southern Medical University
2014-2023
Nanfang Hospital
2014-2023
First Affiliated Hospital of Zhengzhou University
2023
Sichuan University
2022
Key Laboratory of Guangdong Province
2020-2021
We postulated that the ImmunoScore (IS) could markedly improve prediction of postsurgical survival and chemotherapeutic benefits in gastric cancer (GC).A model for GC patients was developed using data from 879 consecutive patients.The expression 27 immune features detected 251 specimens by immunohistochemistry, a 5-feature-based ISGC then constructed LASSO Cox regression model. Testing validation cohorts were included to validate model.Using model, we established an classifier based on 5...
Importance Tertiary lymphoid structures (TLSs) are associated with a favorable prognosis and improved response to cancer immunotherapy. The current approach for evaluation of TLSs is limited by interobserver variability high complexity cost specialized imaging techniques. Objective To develop machine learning model automated quantitative based on routine histopathology images. Design, Setting, Participants In this multicenter, international diagnostic/prognostic study, an interpretable was...
To develop and validate a radiomics signature for the prediction of gastric cancer (GC) survival chemotherapeutic benefits. In this multicenter retrospective analysis, we analyzed features portal venous-phase computed tomography in 1591 consecutive patients. A was generated by using Lasso-Cox regression model 228 patients validated internal external validation cohorts. Radiomics nomograms integrating were constructed, demonstrating incremental value to traditional staging system...
Purpose: Elevated levels of neutrophils have been associated with poor survival in various cancers, but direct evidence supporting a role for the immunopathogenesis human cancers is lacking.Experimental Design: A total 573 patients gastric cancer were enrolled this study. Immunohistochemistry and real-time PCR performed to analyze distribution clinical relevance different microanatomic regions. The regulation function assessed both vitro vivoResults: Increased neutrophil counts peripheral...
LIM and SH3 protein 1 (LASP-1), initially identified from a cDNA library of metastatic axillary lymph nodes breast cancer patients, is specific focal adhesion involved in numerous biological pathological processes. The overexpression LASP-1 has been described several types cancers, but the role colorectal (CRC) unknown. In previous study, comparative proteomic analysis was performed as CRC-associated those patients with CRC.Using immunohistochemistry, we analysed expression 126...
The current staging system of gastric cancer is not adequate for defining a prognosis and predicting the patients most likely to benefit from chemotherapy.To construct survival prediction model based on specific tumor patient characteristics that enables individualized predictions net adjuvant chemotherapy with stage II or III cancer.In this multicenter retrospective analysis, was constructed using data training cohort 746 who satisfied study's inclusion criteria underwent surgery between...
Purpose: Current tumor-node-metastasis (TNM) staging system cannot provide adequate information for prediction of prognosis and chemotherapeutic benefits. We constructed a classifier to predict identify subset patients who can benefit from adjuvant chemotherapy.Experimental Design: detected expression 15 immunohistochemistry (IHC) features in tumors 251 gastric cancer (GC) evaluated the association their level with overall survival (OS) disease-free (DFS). Then, integrating multiple...
We aimed to evaluate whether radiomic feature-based fluorine 18 ( F) fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging signatures allow prediction of gastric cancer (GC) survival and chemotherapy benefits.Methods: A total 214 GC patients (training (n = 132) or validation 82) cohort) were subjected feature extraction (80 features).Radiomic features in the training cohort a LASSO cox analysis predict disease-free (DFS) overall (OS) validated cohort.A radiomics nomogram with...
Current gastric cancer staging alone cannot predict prognosis and adjuvant chemotherapy benefits in stage II III cancer. Tumor immune microenvironment biomarkers tumor-cell chemosensitivity might add predictive value to staging. This study aimed construct a signature integrating tumor chemosensitivity-related features improve the prediction of survival patients with We used IHC assess 26 related tumor, stroma, tumors from 223 evaluated association disease-free (DFS) overall (OS). Support...
MicroRNAs (miRNAs) play important roles in regulating tumour development and progression.Here we show that miR-647 is repressed gastric cancer (GC), associated with GC metastasis.Moreover, identify can suppress cell migration invasion vitro.Mechanistically, confirm directly binds to the 3' untranslated regions of SRF mRNA, CArG box located at MYH9 promoter.CCG-1423, an inhibitor RhoA/SRF-mediated gene transcription, inhibits expression MYH9, especially downregulated cells.Overexpression MGC...
<h3>Importance</h3> Occult peritoneal metastasis frequently occurs in patients with advanced gastric cancer and is poorly diagnosed currently available tools. Because the presence of precludes possibility curative surgery, there an unmet need for a noninvasive approach to reliably identify occult metastasis. <h3>Objective</h3> To assess use deep learning model predicting based on preoperative computed tomography images. <h3>Design, Setting, Participants</h3> In this multicenter,...
Objective: We aimed to develop a deep learning-based signature predict prognosis and benefit from adjuvant chemotherapy using preoperative computed tomography (CT) images. Background: Current staging methods do not accurately the risk of disease relapse for patients with gastric cancer. Methods: proposed novel neural network (S-net) construct CT predicting disease-free survival (DFS) overall in training cohort 457 patients, independently tested it an external validation 1158 patients. An...
BACKGROUND. Specific features of the tumor microenvironment (TME) may provide useful prognostic information. We conducted a systematic investigation cellular composition and landscape TME in gastric cancer.
Abstract The tumor immune microenvironment (TIME) is associated with prognosis and immunotherapy response. Here we develop validate a CT-based radiomics score (RS) using 2272 gastric cancer (GC) patients to investigate the relationship between imaging biomarker neutrophil-to-lymphocyte ratio (NLR) in TIME, including its correlation response advanced GC. RS achieves an AUC of 0.795–0.861 predicting NLR TIME. Notably, indistinguishable from IHC-derived status DFS OS each cohort (HR range:...
The tumor microenvironment (TME) plays a critical role in disease progression and is key determinant of therapeutic response cancer patients. Here, we propose noninvasive approach to predict the TME status from radiological images by combining radiomics deep learning analyses. Using multi-institution cohorts 2,686 patients with gastric cancer, show that model accurately predicted an independent prognostic factor beyond clinicopathologic variables. further predicts benefit adjuvant...
Substantial progress has been made in using deep learning for cancer detection and diagnosis medical images. Yet, there is limited success on prediction of treatment response outcomes, which important implications personalized strategies. A significant hurdle clinical translation current data-driven models lack interpretability, often attributable to a disconnect from the underlying pathobiology. Here, we present biology-guided approach that enables simultaneous tumor immune stromal...
BACKGROUND. The tumor immune microenvironment can provide prognostic and therapeutic information. We aimed to develop noninvasive imaging biomarkers from computed tomography (CT) for comprehensive evaluation of context, investigate their associations with prognosis immunotherapy response in gastric cancer (GC).
Background Only a subset of patients with gastric cancer experience long-term benefits from immune checkpoint inhibitors (ICIs). Currently, there is deficiency in precise predictive biomarkers for ICI efficacy. The aim this study was to develop and validate pathomics-driven ensemble model predicting the response ICIs cancer, using H&E-stained whole slide images (WSI). Methods This multicenter retrospectively collected analyzed WSIs clinical data 584 cancer. An model, integrating four...
Defects in natural killer (NK) cell functions are necessary for tumor immune escape, but their underlying regulatory mechanisms human cancers remain largely unknown. Here we showed, detailed studies of NK cells from 235 untreated patients with gastric cancer (GC), the density GC tissues could predict improved survival patients. However, were significantly decreased number advanced-stage GC. A multivariate Cox analysis revealed that intratumoral was an independent prognostic factor overall...
Background: To evaluate whether radiomic feature-based computed tomography (CT) imaging signatures allow prediction of lymph node (LN) metastasis in gastric cancer (GC) and to develop a preoperative nomogram for predicting LN status. Methods: We retrospectively analyzed radiomics features CT images 1,689 consecutive patients from three centers. The model was developed the training cohort validated internal external validation cohorts. Lasso regression utilized select build signature....
Lymph node metastasis (LNM) in gastric cancer is a prognostic factor and has implications for the extent of lymph dissection. The lymphatic drainage stomach involves multiple nodal stations with different risks metastases. aim this study was to develop deep learning system predicting LNMs based on preoperative CT images patients cancer.Preoperative from who underwent gastrectomy dissection at two medical centres were analysed retrospectively. Using discovery patient cohort, convolutional...
Background: Activated hepatic stellate cells (aHSCs) regulate the function of immune during liver fibrosis. As major innate in liver, macrophages have inducible plasticity. Nevertheless, mechanisms through which aHSCs macrophages' phenotype and fibrosis cirrhosis remain unclear. In this study, we examined immunoregulatory explored their role regulating macrophage function. Methods: A total 96 patients with different stages chronic hepatitis B-related were recruited study. Metavir score...
The rapid advances in deep learning-based computational pathology and radiology have demonstrated the promise of using whole slide images (WSIs) for survival prediction cancer patients. However, most image-based methods are limited to either histology or alone, leaving integrated approaches across relatively underdeveloped. There two main challenges integrating WSIs images: (1) gigapixel nature (2) vast difference spatial scales between images. To address these challenges, this work, we...