Changhai Multimodal Esophageal Cancer Cohort (CMECC)

Prediction of Immune Infiltration Level and Immunotherapy Efficacy of Esophageal Squamous Cell Carcinoma Based on Multimodal Deep Learning

The burden of esophageal squamous cell carcinoma (ESCC) in China is substantial, with 85% of the cancers being in the progressive stage. The treatment for advanced ESCC are extremely limited, and immunotherapy, represented by PD-1 inhibitors, has demonstrated a promising application potential. However, the effectiveness of PD-1 inhibitors varies significantly among patients with different types of ESCC, and currently, there is no effective method to predict the response to PD-1 inhibitors. In this study, investigators aim to construct a multimodal deep learning-based model to predict the level of immune infiltration and the efficacy of immunotherapy for ESCC, integrating both pathological image features and clinical information of patients with ESCC, thereby enhancing the level of individualized and precise treatment for ESCC.

Study Overview

• Status: Active, not recruiting
• Conditions: Esophageal Squamous Cell Carcinoma
• Intervention / Treatment: Diagnostic test: DNA Sequencing, RNA Sequencing

• Study Type: Observational
• Enrollment (Estimated): 110

Contacts and Locations

Study Locations

• China
  • Shanghai, China
    • Changhai Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

110 patients with ESCC in the Changhai hospital

Description

Inclusion Criteria:

1. Availability of Hematoxylin and Eosin (H&E) stained images, molecular data obtained through RNA sequencing (RNA-Seq, DNA-seq), and comprehensive clinical information including patient age, gender, history of alcohol consumption, history of smoking, AJCC Tumor, Node, Metastasis Stage, specific location of oesophageal cancer occurrence, and history of reflux.
2. The sample collection is restricted to cancerous tissue, encompassing both primary tumor samples and those from metastatic sites.

Exclusion Criteria:

1. Patients diagnosed with adenosquamous carcinoma or presenting with a combination of other types of oesophageal cancers;
2. Cases involving combined adenocarcinoma affecting the gastroesophageal junction;
3. Individuals with high-grade tumors that have not penetrated the basement membrane, as confirmed by postoperative pathological examination;
4. Subjects in whom postoperative pathology confirms an absence of residual malignant tissue.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

esophageal squamous cell carcinoma

Diagnostic test: DNA Sequencing, RNA Sequencing; High-coverage Whole-Exome Sequencing sequencing of DNA samples from ESCC was performed. RNA expression was analyzed using the NanoString PanCancer Immuno-Oncology 360TM Panel that includes a set of more than 700 genes involved in the main biological pathways of human immunity. These experiments were performed by the Genomics platform of Institut Curie. Total RNAs were used as templates.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
Immunogene signatures with predictive value for immunotherapy of ESCC	After undergoes surgery.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Prognosis and immunotherapy tolerance in ESCC patients	The prognosis was determined through follow-up, while tolerance to immunotherapy was anticipated utilizing gene sequencing methodologies.	Follow-up for at least 1 year after undergoing surgery

Collaborators and Investigators

• Sponsor: Wangluowei
• Investigators: Study Chair: Luowei Wang, Changhai Hospital

Study record dates

Study Major Dates

• Study Start (Actual): June 13, 2018
• Primary Completion (Actual): October 21, 2022
• Study Completion (Estimated): October 1, 2024

Study Registration Dates

• First Submitted: May 2, 2024
• First Submitted That Met QC Criteria: May 10, 2024
• First Posted (Actual): May 13, 2024

Study Record Updates

• Last Update Posted (Actual): May 13, 2024
• Last Update Submitted That Met QC Criteria: May 10, 2024
• Last Verified: May 1, 2024

More Information

Terms related to this study

• Keywords: Esophageal Squamous Cell Carcinoma; deep learning; immune infiltration
• Additional Relevant MeSH Terms: Digestive System Diseases; Neoplasms by Histologic Type; Neoplasms; Neoplasms by Site; Neoplasms, Glandular and Epithelial; Gastrointestinal Neoplasms; Digestive System Neoplasms; Gastrointestinal Diseases; Head and Neck Neoplasms; Esophageal Diseases; Neoplasms, Squamous Cell; Esophageal Neoplasms; Carcinoma; Carcinoma, Squamous Cell; Esophageal Squamous Cell Carcinoma
• Other Study ID Numbers: CMECC

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED
• IPD Plan Description: A planned initiative that includes sharing DNA and RNA sequencing data, alongside the provision of calculating code.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No