Neoplasms

All Conditions

Digestive System Diseases

Rare Diseases

Carcinoma

Stomach Neoplasms

Carcinoma, Signet Ring Cell

Neoplasms, Glandular and Epithelial

Neoplasms by Histologic Type

Adenocarcinoma

Neoplasms, Cystic, Mucinous, and Serous

Stomach Cancer

Diffuse Gastric Cancer

There were no special interventions for the two groups.

Without any intervention

Gastric signet ring cell carcinoma (GSRCC) possesses unique epidemiology and pathogenesis in the field of cancer, but its incidence is low. Unfortunately, there is currently a lack of systematic research focusing on the prognostic proteomic features of GSRCC. Given this knowledge gap, this study aims to comprehensively characterize the proteomic landscape of GSRCC using a reliable and reproducible DIA-PCT method. This study objectives include characterizing the heterogeneity of GSRCC, performing molecular typing, identifying potential biomarkers and therapeutic targets, and providing a resource for stratified analysis of GSRCC. To achieve these goals, the investigators selected a cohort of 112 GSRCC patients from a pool of over 10,000 gastric cancer patients and conducted a proteomic analysis using the DIA-PCT method. This meticulous approach revealed four novel proteomic subtypes of GSRCC, each exhibiting unique molecular characteristics. Additionally, the investigators discovered that PRDX2 and DDX27 can serve as predictive biomarkers for GSRCC, which were further validated in an independent cohort of 75 GSRCC patients. Furthermore, the investigators paid particular attention to the MLT-GSRCC subgroup and identified three distinct proteomic clusters among MLT-GSRCC patients. Subtype 2 within this subgroup demonstrated the poorest prognosis. Through a rigorous screening process, the investigators determined potential targets for the treatment of GSRCC. In conclusion, these findings contribute to the investigators understanding of the heterogeneity of GSRCC and provide valuable resources for future clinical stratification and targeted treatment strategies.

Biological samples are used for proteomic analysis.

Mechanism of Gastric Signet Ring Cell Carcinoma Based on Microproteomics

This study does not involve drug clinical trials but focuses on ensuring the confidentiality of patient information. To protect patient privacy, a coding system was used instead of real names when entering patient information such as names and ages. Each patient was assigned a study identification number upon enrollment. Throughout the entire study, only the main researchers in the research team have the authority to access the true personal data of patients obtained from the electronic database (such as names and ages), and it is strictly prohibited to circulate or share this information. During the publication of the research article, the main researchers in the research team will use sample coding to replace patient privacy information (such as names) to achieve de-identification. Additionally, the protection of personal information for study participants must be maintained throughout the entire research process, and it is strictly forbidden to circulate or leak such information.

The samples diagnosed as GSRCC by pathology were selected as the samples with signet ring cell content \> 70% as judged by 2 pathologists of associate chief physician or above and without previous radiotherapy and chemotherapy. Tumor tissues and paired nat were collected from the same patient at the time of tumor resection and stored in formalin-fixed paraffin embedding (FFPE). Liquid chromatography-mass spectrometry (LC-MS) was used to detect the proteomics in the samples. The proteins in the samples were extracted, and the proteomics in the samples was detected by LC-MS. Qualitative and quantitative analysis was performed to detect the types and content of proteins in the samples.

Zhejiang Cancer Hospital

Secretary of the party committee

Gastrointestinal Neoplasms

Digestive System Neoplasms

Gastrointestinal Diseases

Stomach Diseases

In the study, the investigators obtained gastric cancer tissues from 480 gastric cancer patients who had undergone surgery at the Zhejiang Cancer Hospital's biospecimen bank between 2012-2019, and obtained relevant clinical information. The gastric cancer tissues were subjected to transcriptomic, metabolomic and other multi-omics testing, and analyzed for the metabolic changes of gastric cancer, and proposed to discover relevant therapeutic targets.

A Multi-omics-based Metabolic Typing Study of Gastric Cancer

Clinical Study on Metabolic Typing of Gastric Cancer Based on Transcriptome, Metabolome and Other Multi-omics

The differences of the metabolism information between gastric cancer tissues and non-cancerous gastric cancer tissues. These data included Metabolizing enzyme mRNA expression and metabolite content.

Symptoms and General Pathology

Constriction, Pathologic

Rectal Neoplasms

Colorectal Neoplasms

Intestinal Neoplasms

Intestinal Diseases

Rectal Diseases

Pathological Conditions, Anatomical

without any intervention, patients diagnose as anastomotic stricture after rectal cancer surgery

without any intervention, patients does not diagnose as anastomotic stricture after rectal cancer surgery

without any intervention

Background: Anastomotic stricture significantly impacts patients' quality of life and long-term prognosis. However, current clinical practice lacks accurate tools for predicting anastomotic stricture. This study aimed to develop a nomogram to predict anastomotic stricture in patients with rectal cancer who have undergone anterior resection.

Methods: 1542 eligible patients will be recruited for the study. Least absolute shrinkage selection operator (Lasso) analysis will be used to preliminarily select predictors. A prediction model will be constructed using multivariate logistic regression and presented as a nomogram. The performance of the nomogram will be evaluated using receiver operating characteristic (ROC) curves, calibration diagrams, and decision curve analysis (DCA). Internal validation will be conducted by assessing the model's performance on a validation cohort.

A Prediction Model of Anastomotic Stricture After Rectal Cancer

A Prediction Model of Anastomotic Stricture After Rectal Cancer: a Retrospective Cohort Analysis

Within six months after rectal cancer surgery, the patient was diagnosed with benign stricture of the rectal anastomosis

Within six months after rectal cancer surgery, the patient was not diagnosed with benign stricture of the rectal anastomosis

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Mechanism of Gastric Signet Ring Cell Carcinoma Based on Microproteomics	NCT05985577	Gastric Cancer Signet Ring Cel...	Without any int...	-	Zhejiang Cancer Hospital
A Multi-omics-based Metabolic Typing Study of Gastric Cancer	NCT06134011	Gastric Cancer Multi-omics Diagnosis	Without any int...	18 Years - 80 Years	Zhejiang Cancer Hospital
A Prediction Model of Anastomotic Stricture After Rectal Cancer	NCT06404554	Colorectal Canc... Rectal Cancer Anastomotic Ste...	without any int...	18 Years - 80 Years	Northern Jiangsu People's Hospital
A Prediction Model of Anastomotic Stricture After Rectal Cancer	NCT06404554	Colorectal Canc... Rectal Cancer Anastomotic Ste...	without any int...	18 Years - 80 Years	Northern Jiangsu People's Hospital
A Multi-omics-based Metabolic Typing Study of Gastric Cancer	NCT06134011	Gastric Cancer Multi-omics Diagnosis	Without any int...	18 Years - 80 Years	Zhejiang Cancer Hospital

Spots Global Cancer Trial Database for without any intervention