Project Details
Abstract
Lung cancer is one of the most prominent causes of cancer death over the world. Non-small cell lung
cancer (NSCLC) is the most common lung cancer type, comprising ~80% of all lung cancers. The stage
of lung cancer is highly correlated to prognosis and mortality, specifically, the degree of cancer spread to
lymph nodes (LNs) is the determining factor in the accurate staging and would be the basis for surgery
and adjuvant treatment. However, because of the limited diagnostic approach, the diagnosis/prognosis of
NSCLC patients has improved only minimally in the past decade. Thus, it is emergent to find a good
biomarkers for detection of disease progress or metastasis to stratify the patients with the respect of risk
for micrometastasis and disease aggressiveness. In this proposal, to gain the metastasis-related biomarkers,
we first generate the differentially expressed protein profiles from two types of clinical specimens by
quantitative proteomics technologies. One is the lung cancer tissues with different extent of LN
involvement (N0, no regional LN involvement; N1, involvement of ipsilateral intrapulmonary,
peribronchial, or hilar LNs; N2, involvement of ipsilateral mediastinal or subcarinal LNs; M, distant
metastasis) and the other is the pleural effusion (PE) from NSCLC patients with malignancy or benign
pulmonary diseases. The tissue proteome/phosphoproteome allows us to search the biomarkers as well as
molecular mechanisms underlying lung cancer tumorigenesis. We will also integrate the differential tissue
proteome/phosphoproteome, PE proteome and cancer cell secretome to generate a potential body fluid
accessible biomarker dataset for lung cancer metastasis based on literature search, functional
classification, network analysis and novelty. The potential metastasis-related biomarkers will be validated
by using large scale of clinical specimens. To address the molecular mechanisms of these
metastasis-related biomarkers, we will combine molecular biology, cell biology, quantitative proteomics
and xenograft mice models to characterize the regulations of these proteins involved in lung cancer
progression. This proposal would be the first study to search metastasis-related biomarker for NSCLC by
integration of quantitative tissue proteome, PE proteome and secretome. The goal of this proposal is to
discover clinical useful biomarker and address the mechanism of metastasis-related biomarker for
prognosis and therapeutic development of NSCLC.
Our specific aims are:
1. Generate metastasis-related biomarker datasets for NSCLC.
a. Generate a metastasis-related tissue proteome/phosphoproteome dataset by identification and
quantification of protein profiles from paired adenocarcinoma cancer tissues with different extent
of LN involvement.
b. Generate a malignancy-related PE proteome dataset by identification and quantification of protein
profiles from six types of PEs.
2. Develop a biomarker panel for prognosis of NSCLC.
a. Pathway analysis of metastasis-related tissue proteome/phosphoproteome.
b. Combine tissue proteome, PE proteome and cancer cell secretome to search metastasis-related
biomarker candidates those are originating from cancer cells and could be detected in body fluids.
c. Select potential biomarkers based on literature search, functional classification, network analysis
and novelty.
d. Validate the clinical significance of metastasis-related biomarkers by using large scale of clinical
specimens.
3. Determine the molecular mechanism of the promising biomarkers in lung cancer metastasis.
a. Characterize the biological functions of biomarker in cell and xenograft mouse model.
b. Define the relationship between promising biomarker and well-known signaling molecules or
discover the novel interaction network of promising biomarker by quantitative proteomic strategy
Project IDs
Project ID:PC10108-0878
External Project ID:NSC101-2320-B182-035-MY3
External Project ID:NSC101-2320-B182-035-MY3
Status | Finished |
---|---|
Effective start/end date | 01/08/12 → 31/07/13 |
Keywords
- Non-small cell lung cancer
- metastasis
- lymph node
- tissue proteome
- phosphoproteome
- pleural effusion
- biomarker
- quantitative proteomics
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