Epithelial Mesenchymal Transition (EMT) Based Prognostic Signature for Non-small Cell Lung Cancer Recent advances in proteomics and genome sequencing have revolutionized an era of cancer therapy where clinical, proteomic and genomic information are used in assessing an individual’s risk for disease, prevention and treatment. Researchers at the University of Michigan used a TGF-β induced EMT model to quantitatively profile and identify differentially secreted proteins in the media of a lung adenocarcinoma cell line cultured in the presence or absence of TGF-β. The protein profile (EMT secretome) was used in combination with EMT gene expression data to identify a 97 gene EMT Associated Secretory Phenotype (EASP) that were upregulated at both protein and mRNA levels upon EMT induction. The EASP showed strong correlation to metastasis, stage, histological grade and predicted survival of lung adenocarcinoma patients in training and independent test sets. The EASP was further refined to a 20 gene signature (rEASP) which was effective in predicting survival in early stage NSCLC. Meta-analysis using different lung cancer gene expression data sets established the effectiveness of rEASP in stratifying lung cancer patients into low, medium and high risk groups with distinct survival times. The EASP provides a mechanism based, clinically relevant biomarkers with prognostic value for use in NSCLC.
Epithelial-Mesenchymal Transition and Lung Cancer
Epithelial-mesenchymal transition (EMT) is a process where polarized epithelial cells lose cell-cell adhesion and cell polarity and acquire a motile and invasive phenotype that allows the cancer cells to migrate through the blood and lymphatic vessels to distant sites. EMT has been shown to be involved in the metastasis, treatment resistance, acquisition of characteristics of cancer stem-like cells, and associated with the progression of many type of tumors. EMT can be induced by several growth factors with Transforming Growth Factor- β (TGF- β) as the most extensively studied inducer of EMT. TGF-β binding to its receptors triggers a signaling cascade that activates a transcriptional response that promotes EMT. Cancer cells increase their production of TGF- β that not only induces EMT, but also enhances angiogenesis in tumor microenvironment, providing an exit route for migrating mesenchymal cells. Lung cancer is the leading cause of cancer-related death worldwide. Lung cancer is a malignancy arising from the cells of the respiratory epithelium and has two major forms: small-cell lung cancer and non–small-cell lung cancer (NSCLC). Small cell lung cancer accounts for approximately 15% of lung cancer cases and NSCLC accounts for the remaining 85%. NSCLC is divided into three major histologic subtypes: squamous-cell carcinoma, adenocarcinoma, and large-cell lung cancer. Treatment options, depending on disease stage, include surgery, radiation therapy, chemotherapy, and any combination of these options. The current system for staging NSCLC is the tumor-node-metastasis (TNM) classification, which includes assessment of the size of primary tumor (T), the degree of spread to regional lymph nodes (N), and the presence of metastases beyond lymph nodes and lung tissue(M). NSCLC that has not yet metastasized to the lymph nodes or distal organs have a five-year survival of approximately 50%. Early stage patients treated with surgical resection alone will have recurrence within 3 years suggesting the presence of occult micrometastatic disease. Adjuvant chemotherapy has been shown to significantly increase survival rate in early stage NSCLC patients. Metastasis and resistance to therapy are the major causes of failure in lung cancer treatment. This is reflected in the poor prognosis and low five-year survival rates for lung cancer at 15% in the United States. Evidence suggests that patients with identical histology, location and disease stage determined by the TMN classification that receive similar therapy have varied survival rates indicating a heterogenous nature of the disease and suggesting that the current methods of tumor classification and staging are not sufficient for determining best therapeutic strategy and prognosis. In addition, some patients are intrinsically resistant or eventually develop resistance to current available therapy. Taken together, these emphasize the need to identify additional disease markers that may be used to: 1) identify early stage patients at a high risk of recurrence or metastatic disease, 2) determine the best treatment strategy, 3) serve as better prognostic markers and 4) identify therapeutic targets for the development of more effective therapies for NSCLC.
- Molecular markers for staging non-small cell lung cancer
- Prognostic markers for non-small cell lung cancer
- Therapeutic targets for developing non-small cell lung cancer therapy
- Novel molecular and prognostic markers for non-small cell lung cancer
- More accurate and personalized staging of non-small lung cancer
- New tool for designing better and targeted therapy