Abstract Lung adenocarcinoma is the most common type of primary lung cancer. Previous studies have shown that gene expression signatures may predict clinical outcome. In this study, we used a systems biology approach, weighted gene co-expression network analysis (WGCNA), to identify survival related networks and gene signatures. We first analyzed whole genome gene expression profiles in 82 lung adenocarcinoma tumor tissues from never smokers (smoked <100 cigarettes lifetime) and found a significant correlation of an expression module with tumor grade of differentiation (r=0.38, p=4×10−4) and overall survival (OS, p =0.027, HR, 1.71; 95% CI, 1.06-2.74) after adjusting for potential confounders (age and tumor grade). When this module signature was incorporated and compared to the conventional model consisting of clinical variables only, the survival prediction accuracy was increased from 0.70 to 0.75. Gene Ontology (GO) enrichment analysis indicated this module was significantly enriched in biological process GO term “cell cycle” (p = 2.1×10−53). To explore the effect of this network module at germline level, we performed the WGCNA on normal lung tissues derived from 78 of the 82 patients and observed significant association of an expression module with OS (adjusted p=3×10−4, HR=1.98; 95% CI, 1.36-2.87). Interestingly, this module was also significantly enriched in cell cycle-related genes (p=4.1×10−41). To further validate this result, we analyzed an independent microarray gene expression dataset including 442 lung adenocarcinoma patients from NCI Director's Challenge Consortium. We found the same association: the cell cycle-enriched module was correlated with tumor grade of cell differentiation (r=0.55, p-value=5×10−37) and OS (adjusted p=7.4×10−3; HR, 1.20; 95% CI, 1.05-1.37). We further identified 30 genes in the OS-related module that overlapped between the discovery and validation data sets. Furthermore, all these 30 genes were found to be up-regulated in adenocarcinoma compared to adjacent normal lung tissues in the discovery data set. Of the 30 genes, three key genes, UBE2C, TPX2 and MELK, were identified with highest connectivity in cell cycle-enriched module; their expression levels were significantly associated with OS in both discovery and validation sets. UBE2C and TPX2 have been reported as gene signatures for human lung cancer prognosis in vitro lung carcinogenesis system; MELK was identified as a key regulator of the proliferation of malignant brain tumors and malignant grade in human astrocytomas, and was also associated with breast cancer prognosis. Our results suggest that genes involved in cell-cycle are likely related with tumor aggressiveness and therefore can predict survival in lung adenocarcinoma. Further studies are needed to validate the key genes that could improve survival prediction and provide potential new targets to intervene progression of lung adenocarcinoma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5060. doi:10.1158/1538-7445.AM2011-5060
Novel late-onset Alzheimer disease loci variants associate with brain gene expression
Abstract Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-186.
Whole Genome Profiling of Formalin-Fixed, Paraffin-Embedded Tissue Distinguishes HER2-Positive and -Negative Breast Tumors.
Abstract Background: Gene expression profiling is an important tool in prediction, prognosis, and cancer modeling. The DASL® assay (cDNA –mediated Annealing, extension, Selection, and Ligation; Illumina; San Diego, CA) is a gene expression profiling system designed for degraded RNAs such as those derived from formalin-fixed paraffin-embedded (FFPE) tumor samples. FFPE tumor samples are invaluable resources for cancer research, being the most widely available materials for which patient outcomes are known. Purpose: The objective of this study was to evaluate the performance of Illumina's Whole Genome DASL platform (24,526; 24K) at distinguishing HER2-positive (HER2+) from HER2-negative (HER2-) FFPE breast tumors. Methods: We measured the relative gene expression of biological and technical replicates using nine HER2+ and 11 HER2- primary breast tumors from patients that were all node-positive and estrogen receptor-positive. The HER2 status of the tumors was determined using the Dako Hercept Test following the 2007 ASCO/CAP guidelines for HER2 positivity. The non-background corrected probe-expression data were exported from Illumina BeadStudio software and normalized using the software R and the function fastlo. Log2 transformed expression values were used to obtain the relative gene expression per probe. Spearman correlations were calculated between both types of replicates. Unequal-variance t-tests were conducted to test for differences in expression levels between HER2+ and HER2- tumors. An overall ERBB2 gene expression level was calculated by taking the average of the three ERBB2 probes for each tumor across all replicates. To simulate the possible outcome if only one replicate of each tumor was measured for gene expression, differential expression was tested for all possible combinations of single replicate probe expression values. Results: Spearman correlations for technical and biological replicates within tumor samples ranged from 0.9804 – 0.9946, and 0.9822 – 0.9945, respectively. The overall ERBB2 gene expression was significantly lower in HER2- tumors than in HER2+ tumors (p = 0.0000018). The top five most differentially expressed genes (p < 0.0005) included ERBB2, GRB7, C17ORF37, PERLD1, and ASF1B. For each of the three ERBB2 probes, there were 65,536 possible ways to combine the individual probe expression values. The p-values for testing differential expression in each of these 65,536 combinations of HER2+ tumors versus HER2- tumors ranged from 0.00029 – 0.0091 for ILMN_1717902, 0.0000078 – 0.00026 for ILMN_1728761, and 0.000000002 – 0.0000032 for ILMN-2352131. Conclusions: Illumina's Whole Genome Platform provided highly reproducible gene expression values among biological and technical replicates of breast tumors. This platform also demonstrated significant differential ERBB2 gene expression between HER2+ and HER- breast tumors, which correctly classified the breast tumors as HER2+ and HER2-. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6127.
Overexpression of Phospho-eIF4E Is Associated with Survival through AKT Pathway in Non–Small Cell Lung Cancer
Abstract Purpose: The eukaryotic translation initiation factor complex 4E (eIF4E) is downstream in the mammalian target of rapamycin (mTOR) pathway. This study explored expression of eIF4E and its relationship with the PTEN/AKT and RAS/MEK/ERK pathways in non–small cell lung carcinoma (NSCLC). Experimental Design: The status of phosphorylated eIF4E (p-eIF4E), phosphorylated AKT (p-AKT), PTEN, phosphorylated tuberin (p-TSC2), phosphorylated mTOR (p-mTOR), phosphorylated S6 (p-S6), and phosphorylated Erk1/2 (p-Erk1/2) was studied using immunohistochemical analysis applied to a tissue microarray containing 300 NSCLCs. Staining results for each antibody were compared with clinical and pathologic features, and the relationship between staining results was explored. Results: Overexpression of p-eIF4E, p-AKT, p-TSC2, p-mTOR, p-S6, and p-Erk1/2 in NSCLC was found in 39.9%, 78.8%, 5.1%, 46.7%, 27.1%, and 16.6% of tumors, respectively. The phenotype of p-eIF4E correlated positively with that of p-AKT, p-TSC2, and p-S6 (P < 0.001). Overall survival in NSCLC patients was significantly shorter in cases with overexpression of p-eIF4E and p-AKT alone and in combination (log-rank P < 0.001, each). Cases with underexpression of PTEN were limited (6.4%), and this phenotype did not correlate with any clinical variable. In cluster analysis, the p-AKT/p-mTOR/p-eIF4E/p-S6–positive group had significantly shorter survival compared with the survival of all cases (P < 0.001). Multivariate analysis showed that p-eIF4E overexpression is an independent prognostic factor for NSCLC (P = 0.004). Conclusions: This study shows that p-eIF4E expression in addition to p-AKT predicts poor prognosis in NSCLC. Moreover, the correlation between expression of p-eIF4E with p-AKT, as well as p-TSC2 and p-S6, indicates that eIF4E activation through the AKT pathway plays an important role in the progression of NSCLC. Clin Cancer Res; 16(1); OF1–9
Childhood Exposure to Secondhand Smoke and Functional Mannose Binding Lectin Polymorphisms Are Associated with Increased Lung Cancer Risk
Abstract Background: Exposure to secondhand smoke during adulthood has detrimental health effects, including increased lung cancer risk. Compared with adults, children may be more susceptible to secondhand smoke. This susceptibility may be exacerbated by alterations in inherited genetic variants of innate immunity genes. We hypothesized a positive association between childhood secondhand smoke exposure and lung cancer risk that would be modified by genetic polymorphisms in the mannose binding lectin-2 (MBL2) gene resulting in well-known functional changes in innate immunity. Methods: Childhood secondhand smoke exposure and lung cancer risk was assessed among men and women in the ongoing National Cancer Institute-Maryland Lung Cancer (NCI-MD) study, which included 624 cases and 348 controls. Secondhand smoke history was collected via in-person interviews. DNA was used for genotyping the MBL2 gene. To replicate, we used an independent case-control study from Mayo Clinic consisting of 461 never smokers, made up of 172 cases and 289 controls. All statistical tests were two-sided. Results: In the NCI-MD study, secondhand smoke exposure during childhood was associated with increased lung cancer risk among never smokers [odds ratio (OR), 2.25; 95% confidence interval (95% CI), 1.04-4.90]. This was confirmed in the Mayo study (OR, 1.47; 95% CI, 1.00-2.15). A functional MBL2 haplotype associated with high circulating levels of MBL and increased MBL2 activity was associated with increased lung cancer risk among those exposed to childhood secondhand smoke in both the NCI-MD and Mayo studies (OR, 2.52; 95% CI, 1.13-5.60, and OR, 2.78; 95% CI, 1.18-3.85, respectively). Conclusions: Secondhand smoke exposure during childhood is associated with increased lung cancer risk among never smokers, particularly among those possessing a haplotype corresponding to a known overactive complement pathway of the innate immune system. (Cancer Epidemiol Biomarkers Prev 2009;18(12):3375–83)