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NCT00897533 Clinical Trial

Development of a Model to Predict Progression-Free Survival After Erlotinib in Patients With Non-Small Cell Lung Cancer

Lung Cancer Clinical Trial

Official title:
Development of a Model to Predict Progression Free Survival After Treatment With Erlotinib in E3503

Clinical Trial Details — Status: Completed

Administrative data
NCT number NCT00897533
Other study ID # CDR0000543981
Secondary ID ECOG-E3503T1
Status Completed
Phase N/A
First received May 9, 2009
Last updated May 17, 2017
Start date April 13, 2007
Est. completion date April 13, 2008

Study information
Verified date May 2017
Source Eastern Cooperative Oncology Group
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

RATIONALE: Studying samples of tissue from patients with cancer in the laboratory may help doctors learn more about changes that occur in DNA and identify biomarkers related to cancer. It may also help doctors predict how patients respond to treatment with erlotinib.

PURPOSE: This laboratory study is developing a model to predict progression-free survival after erlotinib in patients with non-small cell lung cancer.

Description:

OBJECTIVES:

- Assess mesenchymal and epithelial markers in tissues from patients with non-small cell lung cancer treated with erlotinib hydrochloride on clinical trial ECOG-E3503.

- Determine the loss of epithelial markers (E-cadherin) and gain of mesenchymal markers (vimentin/cytokeratin co-expression) in these patients.

- Assess whether mesenchymal and epithelial markers are predictive of progression-free survival (PFS) of these patients.

- Identify a single nucleotide polymorphism profile via whole genome mapping and other known biomarkers to predict PFS of these patients.

OUTLINE: Tissue samples are analyzed by whole genome mapping for single nucleotide polymorphism (SNP) rate and by signal detection rate and by quantitative immunohistochemistry for mesenchymal (vimentin/cytokeratin) and epithelial (E-cadherin) marker transitions. After biomarker identification and gene mapping are complete, a model to predict progression-free survival in these patients is developed.

PROJECTED ACCRUAL: A total of 137 samples will be accrued for this study.

Recruitment information / eligibility
Status Completed
Enrollment 137
Est. completion date April 13, 2008
Est. primary completion date April 13, 2008
Accepts healthy volunteers No
Gender All
Age group N/A to 120 Years
Eligibility DISEASE CHARACTERISTICS:

- Diagnosis of non-small cell lung cancer, including any of the following subtypes:

- Adenocarcinoma

- Squamous cell carcinoma

- Bronchoalveolar carcinoma

- Carcinoid

- Stage IIIB or IV or recurrent disease

- Must have received treatment with erlotinib hydrochloride on clinical trial ECOG-E3503

PATIENT CHARACTERISTICS:

- Not specified

PRIOR CONCURRENT THERAPY:

- See Disease Characteristics

Study Design

Related Conditions & MeSH terms

Intervention

Genetic:
• gene mapping

• polymorphism analysis

Other:
• diagnostic laboratory biomarker analysis

• immunohistochemistry staining method

Locations
Country Name City State
n/a

Sponsors (2)
Lead Sponsor Collaborator
ECOG-ACRIN Cancer Research Group National Cancer Institute (NCI)

References & Publications (1)

Amann JM, Lee JW, Roder H, Brahmer J, Gonzalez A, Schiller JH, Carbone DP. Genetic and proteomic features associated with survival after treatment with erlotinib in first-line therapy of non-small cell lung cancer in Eastern Cooperative Oncology Group 350 — View Citation

Outcome
Type Measure Description Time frame Safety issue
Primary Mesenchymal and epithelial markers Mesenchymal and epithelial markers 1 month
Primary Loss of epithelial markers (E-cadherin) and gain of mesenchymal markers (vimentin/cytokeratin co-expression) Loss of epithelial markers (E-cadherin) and gain of mesenchymal markers 1 month
Primary Correlation of progression-free survival (PFS) by mesenchymal and epithelial markers Correlation of progression-free survival (PFS) by mesenchymal and epithelial markers 1 month
Primary Identification of a single nucleotide polymorphism profile via whole genome mapping and other known biomarkers to predict PFS Identification of a single nucleotide polymorphism profile via whole genome mapping and other known biomarkers to predict PFS 1 month
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