Comprehensive Analysis of Gene Mutation Profile in Chinese NSCLC Patients by Next-generation Sequencing

NCT03609918 | Completed

• 1 other identifier: E2016060A
• Study Type: observational
• Target: 513
• Locations: 0 countries
• Sites: N/A

Brief Summary

In recent years, the development of lung cancer has been improved from pathological level to the molecular level. Research showed that there are many gene mutations in non-small cell lung cancer (NSCLC), and some activating mutations have become the hotspots in target therapy area. With the development of targeted drug research, the molecular classification of NSCLC will be more and more important. But a large number of clinical data showed that gene mutation in Chinese NSCLC patients is significantly different from Caucasian population, which suggesting that it is necessary to identify gene mutation profile in Chinese patients with NSCLC. Six hundred NSCLC paraffin tissue samples was collected during operation from Tianjin Cancer hospital in 2009-2012, which including lung squamous cell carcinoma and adenocarcinoma. The target area of 295 genes, including lung cancer drive genes, important signal pathway genes, drug resistance genes will be detected by next-generation sequencing deep (average 1000X). We will identify gene mutation profile for Chinese lung squamous cell carcinoma and adenocarcinoma patients. The aim is to find related predictor and prognostic factors by analysing the relationship between these gene mutations and clinical characteristics and follow-up treatment.

Conditions

NSCLC

Keywords

Chinese NSCLC; next-generation sequencing

Outcome Measures

Primary Outcomes (1)

• The correlation between gene mutations and survival

  The Log-rank test will be used to explore the relationship between the clinical outcomes (DFS and OS, respectively) and gene mutations (present or absent) or each of the clinical features (gender, age, smoking status, TNM staging, histology, tumor location, recurrence, number of lymph node metastasis, tumor size, postoperative adjuvant treatment, DFS and OS). Then a Cox Proportional Hazards model will be constructed to evaluate the effect of multiple variables (genomic and clinical features) on DFS, and OS, respectively. Benjamini-Hochberg false discovery rate (FDR) method is used to adjust the p-value and calculate the statistically differences. All p values were two-sided, and P\<0.05 was assumed to be significant.

  December 2017

Secondary Outcomes (1)

• The correlation between gene mutations and clinical parameters.

  December 2017

Eligibility Criteria

• Sex: all
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

From May 2009 to November 2012, diagnosed lung cancer patients at Tianjin Medical University Cancer Institute \& Hospital were enrolled

You may qualify if:

• Patients enrolled from 2009 to 2012. Histological confirmed NSCLC.

You may not qualify if:

• Received any systemic or local treatment before surgery. Along with other malignant tumors. Lack up intact follow-up information.

Sponsors & Collaborators

• Tianjin Medical University Cancer Institute and Hospital: lead
• AstraZeneca: collaborator
• Guangzhou Burning Rock Dx Co., Ltd.: collaborator

Biospecimen

Retention: SAMPLES WITH DNA

fresh frozen tissues and FFPE tissues

Study Officials

• Changli Wang, Prof.

  Tianjin Medical University Cancer Institute and Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 23, 2018
• First Posted: August 1, 2018
• Study Start: September 27, 2016
• Primary Completion: September 27, 2017
• Study Completion: February 1, 2018
• Last Updated: August 7, 2018

Record last verified: 2016-09