Prognostic gene signatures for non-small-cell lung cancer.

Resectable non-small-cell lung cancer (NSCLC) patients have poor prognosis, with 30-50% relapsing within 5 years. Current staging criteria do not fully capture the complexity of this disease. Survival could be improved by identification of those early-stage patients who are most likely to benefit from adjuvant therapy. Molecular classification by using mRNA expression profiles has led to multiple, poorly overlapping signatures. We hypothesized that differing statistical methodologies contribute to this lack of overlap. To test this hypothesis, we analyzed our previously published quantitative RT-PCR dataset with a semisupervised method. A 6-gene signature was identified and validated in 4 independent public microarray datasets that represent a range of tumor histologies and stages. This result demonstrated that at least 2 prognostic signatures can be derived from this single dataset. We next estimated the total number of prognostic signatures in this dataset with a 10-million-signature permutation study. Our 6-gene signature was among the top 0.02% of signatures with maximum verifiability, reaffirming its efficacy. Importantly, this analysis identified 1,789 unique signatures, implying that our dataset contains >500,000 verifiable prognostic signatures for NSCLC. This result appears to rationalize the observed lack of overlap among reported NSCLC prognostic signatures.

TAp73 regulates the spindle assembly checkpoint by modulating BubR1 activity.

The role of various p73 isoforms in tumorigenesis has been controversial. However, as we have recently shown, the generation of TAp73-deficient (TAp73(-/-)) mice reveals that TAp73 isoforms exert tumor-suppressive functions, indicating an emerging role for Trp-73 in the maintenance of genomic stability. Unlike mice lacking all p73 isoforms, TAp73(-/-) mice show a high incidence of spontaneous tumors. Moreover, TAp73(-/-) mice are infertile and produce oocytes exhibiting spindle abnormalities. These data suggest a link between TAp73 activities and the common molecular machinery underlying meiosis and mitosis. Previous studies have indicated that the spindle assembly checkpoint (SAC) complex, whose activation leads to mitotic arrest, also regulates meiosis. In this study, we demonstrate in murine and human cells that TAp73 is able to interact directly with several partners of the SAC complex (Bub1, Bub3, and BubR1). We also show that TAp73 is involved in SAC protein localization and activities. Moreover, we show that decreased TAp73 expression correlates with increases of SAC protein expression in patients with lung cancer. Our results establish TAp73 as a regulator of SAC responses and indicate that TAp73 loss can lead to mitotic arrest defects. Our data suggest that SAC impairment in the absence of functional TAp73 could explain the genomic instability and increased aneuploidy observed in TAp73-deficient cells.

Genomic markers for malignant progression in pulmonary adenocarcinoma with bronchioloalveolar features.

Bronchioloalveolar carcinoma (BAC), a subtype of lung adenocarcinoma (ADC) without stromal, vascular, or pleural invasion, is considered an in situ tumor with a 100% survival rate. However, the histological criteria for invasion remain controversial. BAC-like areas may accompany otherwise invasive adenocarcinoma, referred to as mixed type adenocarcinoma with BAC features (AWBF). AWBF are considered to evolve from BAC, representing a paradigm for malignant progression in ADC. However, the supporting molecular evidence remains forthcoming. Here, we have studied the genomic changes of BAC and AWBF by array comparative genomic hybridization (CGH). We used submegabase-resolution tiling set array CGH to compare the genomic profiles of 14 BAC or BAC with focal area suspicious for invasion with those of 15 AWBF. Threshold-filtering and frequency-scoring analysis found that genomic profiles of noninvasive and focally invasive BAC are indistinguishable and show fewer aberrations than tumor cells in BAC-like areas of AWBF. These aberrations occurred mainly at the subtelomeric chromosomal regions. Increased genomic alterations were noted between BAC-like and invasive areas of AWBF. We identified 113 genes that best differentiated BAC from AWBF and were considered candidate marker genes for tumor invasion and progression. Correlative gene expression analyses demonstrated a high percentage of them to be poor prognosis markers in early stage ADC. Quantitative PCR also validated the amplification and overexpression of PDCD6 and TERT on chromosome 5p and the prognostic significance of PDCD6 in early stage ADC patients. We identified candidate genes that may be responsible for and are potential markers for malignant progression in AWBF.

Glypican-3 is overexpressed in lung squamous cell carcinoma, but not in adenocarcinoma.

Glypican-3 is a membrane-bound proteoglycan whose expression has been linked to malignancies through the existence of both mutations and aberrant protein expression. Reports on glypican-3 expression in lung cancer were limited, with some evidence for loss of expression, which suggested a tumor-suppressor role. We sought to evaluate glypican-3 expression in lung cancer at the protein and mRNA levels and correlate it with clinical, histological and genomic characteristics such as RAS mutation status. We used immunohistochemistry on tissue microarray to study glypican-3 expression in 97 patients, evaluated glypican-3 mRNA levels by quantitative polymerase chain reaction in 143 patients and identified RAS mutations by allele-specific oligonucleotide hybridization. We correlated the results with clinical and histological data. Glypican-3 immunostaining was negative in all normal lung tissues, but positive in 23% of lung carcinoma samples. High protein and mRNA expression was associated with squamous histology (positive stain in 55% of squamous cell carcinoma vs 8% of adenocarcinoma, P<0.0001 for both immunostaining and mRNA). RAS mutations were highly associated with adenocarcinoma and low glypican-3 mRNA expression (P<0.0001 for both). Among smokers, glypican-3 mRNA expression was reduced in adenocarcinoma patients (P=0.013), and was elevated in those with squamous cell carcinoma (P=0.03, interaction P=0.0009). These opposing associations also correlated with the smoking burden. Patients with tumors staining positively for glypican-3 smoked significantly more than patients with tumors staining negatively (P=0.013). No association was found between glypican-3 expression and patient outcome. In conclusion, glypican-3 was overexpressed in cancerous compared with normal lung tissue. Adenocarcinoma and squamous cell carcinoma had differential expression of glypican-3, with predilection to squamous cell carcinoma patients who smoked. Glypican-3 expression in squamous cell carcinoma as an oncofetal protein renders it a potential candidate marker for early detection of lung squamous cell carcinoma.

KIF14 messenger RNA expression is independently prognostic for outcome in lung cancer.

PURPOSE: The mitotic kinesin KIF14 is overexpressed in multiple cancers including lung cancer. Therefore, we investigated KIF14 expression in association with clinical variables and the effect of KIF14 on in vitro colony formation in non-small-cell lung carcinoma. EXPERIMENTAL DESIGN: RNA was extracted from 129 untreated, resected tumors and KIF14 expression was quantified by real-time reverse transcription-PCR. Associations with clinical variables were determined by standard statistical methods. KIF14 expression was knocked down by small interfering RNA in H1299 and HeLa cells; proliferation and growth in soft agar were assayed. RESULTS: Squamous cell carcinoma had the highest KIF14 level, followed by large-cell undifferentiated carcinoma, then adenocarcinoma (P = 0.002). KIF14 level decreased with differentiation (P = 0.01) but was not associated with pathologic stage, T or N stage, or sex. When dichotomized about the median, KIF14 overexpression significantly decreased disease-free survival (Kaplan-Meier log-rank, P = 0.01) and trended toward decreasing overall survival (P = 0.08). In a univariate Cox proportional hazard regression, increasing KIF14 expression decreased disease-free survival [P = 0.01; hazard ratio, 1.44 (95% confidence interval, 1.09-1.91)]. In a multivariate Cox regression, including stage, differentiation, histology, and tumor purity as covariates, KIF14 overexpression remained an independent prognostic factor for disease-free survival [P = 0.01; hazard ratio, 1.45 (95% confidence interval, 1.09-1.94)]. Knockdown of KIF14 in non-small-cell lung carcinoma and cervical carcinoma cell lines decreased proliferation and colony formation in soft agar. CONCLUSIONS: KIF14 expression is independently prognostic for disease-free survival in lung cancer and knockdown decreases tumorigenicity in vitro, showing that it is a clinically relevant oncogene and an exciting therapeutic target for further study.

Genomic DNA functions as a universal external standard in quantitative real-time PCR.

Real-time quantitative PCR (qPCR) is a powerful tool for quantifying specific DNA target sequences. Although determination of relative quantity is widely accepted as a reliable means of measuring differences between samples, there are advantages to being able to determine the absolute copy numbers of a given target. One approach to absolute quantification relies on construction of an accurate standard curve using appropriate external standards of known concentration. We have validated the use of tissue genomic DNA as a universal external standard to facilitate quantification of any target sequence contained in the genome of a given species, addressing several key technical issues regarding its use. This approach was applied to validate mRNA expression of gene candidates identified from microarray data and to determine gene copies in transgenic mice. A simple method that can assist achieving absolute quantification of gene expression would broadly enhance the uses of real-time qPCR and in particular, augment the evaluation of global gene expression studies.

The c-Myc oncogene directly induces the H19 noncoding RNA by allele-specific binding to potentiate tumorigenesis.

The product of the MYC oncogene is widely deregulated in cancer and functions as a regulator of gene transcription. Despite an extensive profile of regulated genes, the transcriptional targets of c-Myc essential for transformation remain unclear. In this study, we show that c-Myc significantly induces the expression of the H19 noncoding RNA in diverse cell types, including breast epithelial, glioblastoma, and fibroblast cells. c-Myc binds to evolutionarily conserved E-boxes near the imprinting control region to facilitate histone acetylation and transcriptional initiation of the H19 promoter. In addition, c-Myc down-regulates the expression of insulin-like growth factor 2 (IGF2), the reciprocally imprinted gene at the H19/IGF2 locus. We show that c-Myc regulates these two genes independently and does not affect H19 imprinting. Indeed, allele-specific chromatin immunoprecipitation and expression analyses indicate that c-Myc binds and drives the expression of only the maternal H19 allele. The role of H19 in transformation is addressed using a knockdown approach and shows that down-regulation of H19 significantly decreases breast and lung cancer cell clonogenicity and anchorage-independent growth. In addition, c-Myc and H19 expression shows strong association in primary breast and lung carcinomas. This work indicates that c-Myc induction of the H19 gene product holds an important role in transformation.

Integrating RAS status into prognostic signatures for adenocarcinomas of the lung.

PURPOSE: While the dysregulation of specific pathways in cancer influences both treatment response and outcome, few current prognostic markers explicitly consider differential pathway activation. Here we explore this concept, focusing on K-Ras mutations in lung adenocarcinoma (present in 25%-35% of patients). EXPERIMENTAL DESIGN: The effect of K-Ras mutation status on prognostic accuracy of existing signatures was evaluated in 404 patients. Genes associated with K-Ras mutation status were identified and used to create a RAS pathway activation classifier to provide a more accurate measure of RAS pathway status. Next, 8 million random signatures were evaluated to assess differences in prognosing patients with or without RAS activation. Finally, a prognostic signature was created to target patients with RAS pathway activation. RESULTS: We first show that K-Ras status influences the accuracy of existing prognostic signatures, which are effective in K-Ras-wild-type patients but fail in patients with K-Ras mutations. Next, we show that it is fundamentally more difficult to predict the outcome of patients with RAS activation (RAS(mt)) than that of those without (RAS(wt)). More importantly, we demonstrate that different signatures are prognostic in RAS(wt) and RAS(mt). Finally, to exploit this discovery, we create separate prognostic signatures for RAS(wt) and RAS(mt) patients and show that combining them significantly improves predictions of patient outcome. CONCLUSIONS: We present a nested model for integrated genomic and transcriptomic data. This model is general and is not limited to lung adenocarcinomas but can be expanded to other tumor types and oncogenes.

Three-gene prognostic classifier for early-stage non small-cell lung cancer.

PURPOSE: Several microarray studies have reported gene expression signatures that classify non-small-cell lung carcinoma (NSCLC) patients into different prognostic groups. However, the prognostic gene lists reported to date overlap poorly across studies, and few have been validated independently using more quantitative assay methods. PATIENTS AND METHODS: The expression of 158 putative prognostic genes identified in previous microarray studies was analyzed by reverse transcription quantitative polymerase chain reaction in the tumors of 147 NSCLC patients. Concordance indices and risk scores were used to identify a stage-independent set of genes that could classify patients with significantly different prognoses. RESULTS: We have identified a three-gene classifier (STX1A, HIF1A, and CCR7) for overall survival (hazard ratio = 3.8; 95% CI, 1.7 to 8.2; P < .001). The classifier was also able to stratify stage I and II patients and further improved the predictive ability of clinical factors such as histology and tumor stage. The predictive value of this three-gene classifier was validated in two large independent microarray data sets from Harvard and Duke Universities. CONCLUSION: We have identified a new three-gene classifier that is independent of and improves on stage to stratify early-stage NSCLC patients with significantly different prognoses. This classifier may be tested further for its potential value to improve the selection of resected NSCLC patients in adjuvant therapy.