Gene Expression-Based Classification of Non-Small Cell Lung Carcinomas and Survival Prediction

Abstract

BackgroundCurrent clinical therapy of non-small cell lung cancer depends on histo-pathological classification. This approach poorly predicts clinical outcome for individual patients. Gene expression profiling holds promise to improve clinical stratification, thus paving the way for individualized therapy.Methodology and Principal FindingsA genome-wide gene expression analysis was performed on a cohort of 91 patients. We used 91 tumor- and 65 adjacent normal lung tissue samples. We defined sets of predictor genes (probe sets) with the expression profiles. The power of predictor genes was evaluated using an independent cohort of 96 non-small cell lung cancer- and 6 normal lung samples. We identified a tumor signature of 5 genes that aggregates the 156 tumor and normal samples into the expected groups. We also identified a histology signature of 75 genes, which classifies the samples in the major histological subtypes of non-small cell lung cancer. Correlation analysis identified 17 genes which showed the best association with post-surgery survival time. This signature was used for stratification of all patients in two risk groups. Kaplan-Meier survival curves show that the two groups display a significant difference in post-surgery survival time (p = 5.6E-6). The performance of the signatures was validated using a patient cohort of similar size (Duke University, n = 96). Compared to previously published prognostic signatures for NSCLC, the 17 gene signature performed well on these two cohorts.ConclusionsThe gene signatures identified are promising tools for histo-pathological classification of non-small cell lung cancer, and may improve the prediction of clinical outcome.

Expression of G Protein-Coupled Receptor 19 in Human Lung Cancer Cells Is Triggered by Entry into S-Phase and Supports G2–M Cell-Cycle Progression

“…We addressed the question whether coexpression of E2F transcription factors and Gpr19 could be observed in patient samples as well. Indeed, on the basis of 2 published studies (21,22) and our in-house study described in Fig. 1A-C, a good correlation of the expression of Gpr19 and E2F transcription factors E2f-1 to E2f-3 could be detected (Fig.…”

“…Gene expression data of human lung-derived samples from Hou and colleagues (21) and Rohrbeck and colleagues (22) were extracted from the Oncomine data platform (Compendia Bioscience) and analyzed using Spotfire DecisionSite 9.1.2 (TIBCO).…”

Smoker and non-smoker lung adenocarcinoma is characterized by distinct tumor immune microenvironments

“…We queried Gene Expression Omnibus (GEO) with the keyword “lung” and with the platform set to “GPL570” or “GPL96,” and then selected datasets with a sample size of more than 30. As a result, we got six datasets on platform GPL570, including GSE10245 (n = 40), 34 GSE19188 (n = 110), 35 GSE30219 (n = 83), 36 GSE31210 (n = 224), 37,38 GSE37745 (n = 91), 39 and GSE50081 (n = 128), 40 and five datasets on platform GPL96, including GSE10072 (n = 107), 41 GSE14814 (n = 71), 42 GSE31547 (n = 50), 43 GSE68465 (n = 353), 44 and GSE7670 (n = 54). 45 Detailed information about the datasets is presented in Table 1; the sample numbers are the result of removing patients treated with chemotherapy or radiotherapy.…”

Tripartite Motif Containing 28 (Trim28) Can Regulate Cell Proliferation by Bridging HDAC1/E2F Interactions

“…The study of Hou et al (11) included 91 NSCLC patients (45 adenocarcinomas, 27 squamous cell carcinomas, and 19 large cell carcinomas) and 65 paired normal tissues. This database allowed us to determine whether Trim28 has differential expression between tumor and normal tissue, as well as among the three histological types of NSCLC.…”