Lung cancer is the leading cause of cancer related deaths in the United States. Despite undergoing curative surgery, a majority of patients with resected (Stage I -III) non-small cell lung cancer (NSCLC) will die from recurrent disease within five years. Adjuvant chemotherapy in an unselected group of patients with resected stage l-lll produces only modest improvement in survival. It is critical to develop molecular predictors for recurrence. In a recent study, we applied a meta-analysis of data sets from seven different microarray studies on lung cancer for differentially expressed genes related to survival and identified a gene expression signature consisting of 64 genes that is highly predictive of recurrence. The central hypothesis is that this 64-gene signature can accurately predict survival of patients with stage I NSCLC.
Two aims are proposed to test this hypothesis.
In Aim 1, we will validate the 64-gene signature using a custom-designed array in 300 stage I NSCLC cases from the Cancer and Leukemia Group B (CALGB) lung cancer study 140202. The goal is to develop a diagnostic gene signature that can guide the treatment options for these patients.
In Aim 2, we will validate the 64-gene signature using the Tissue Microarray (TMA) approach. We will determine whether the 64-gene signature of mRNA changes can be confirmed on the protein level using existing lung cancer TMA, and we will evaluate a subset of the 64-gene signature in a new TMA created from tumor tissues from the CALGB 140202 study. Using the newly identified 64-gene signature and the unique patient populations already developed by the CALGB lung cancer study (140202), the proposed studies will help clinicians in selecting the most effective treatment options for stage I lung cancer. Lung cancer is the leading cause of cancer related death in the United States. Nearly 50% of patients with stage I and II NSCLC will die from recurrent disease despite surgical resection. Adjuvant chemotherapy improves survival in patients with resected stage I-III NSCLC. There are no reliable clinical or molecular predictors for identifying those at high risk for developing recurrent disease. If developed, this high risk subgroup could be selected for adjuvant therapy. Future studies on adjuvant therapy would then focus on this high risk group. Conversely, the low risk group can be spared the side effects of adjuvant therapy. In a recent study, we applied a meta-analysis of data sets from seven different microarray studies on lung cancer for differentially expressed genes related to survival (less than 2 years and greater than 5 years) (Lu et al. 2006). We identified a 64 gene - molecular marker set that is highly predictive of which stage I lung cancer patients may benefit from more aggressive therapy. Our study has shown that the 64-gene molecular marker set clearly demonstrated that the high and low-risk groups are significantly different in their overall survival. The objective of this proposal is to systematically validate the 64-gene molecular marker set to predicting survival of patients with stage I NSCLC. One major resource for our proposal is direct and full access to more than 300 well- characterized human stage I lung cancer tissues from CALGB study 140202 with relevant clinical information. The central hypothesis is that the 64-gene molecular marker set can accurately predict survival of patients with stage I NSCLC. This proposal is organized into two specific aims.
Aim 1 will conduct a validation study of the 64-gene molecular marker set using a custom-designed array in more than 300 stage I NSCLC from the CALGB lung cancer study (140202). Frozen samples from eligible patients will be used for RNA extraction and microarray analysis. All paraffin-embedded tumor samples from the same patients in the validation series will be examined by a pathologist to verify histopathology. Microarray analysis will be performed using a custom-designed array with the 64 genes in triplicate.
Aim 2 will validate the 64-gene molecular marker set using Tissue Microarrays (TMAs). We will determine whether mRNA changes of the 64-gene molecular marker set genes can be confirmed on the protein level using multiple independent sets of lung cancer with a TMA approach. At least two independent sets of lung cancer including CALGAB 140202, and archival samples with clinical outcome data from RPCI will be used for TMA construction. We believe that the 64-gene molecular marker set are validated, adjuvant therapy could be selectively administered to those patients at high risk for relapse.
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