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.

One of the most common regulatory elements is the GC box and the related GT/CACC box, which are widely distributed in promoters, enhancers and locus control regions of housekeeping as well as tissue-specific genes. For long it was generally thought that Sp1 is the major factor acting through these motifs. Recent discoveries have shown that Sp1 is only one of many transcription factors binding and acting through these elements. Sp1 simply represents the first identified and cloned protein of a family of transcription factors characterised by a highly conserved DNA-binding domain consisting of three zinc fingers. Currently this new family of transcription factors has at least 16 different mammalian members. Here, we will summarise and discuss recent advances that have been directed towards understanding the biological role of these proteins.

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Hereditary Persistence of Fetal Hemoglobin (HPFH) is characterized by persistent high levels of fetal hemoglobin (HbF) in adults. Several contributory factors, both genetic and environmental, have been identified 1, but others remain elusive. Ten of twenty-seven members from a Maltese family presented with HPFH. A genome-wide SNP scan followed by linkage analysis revealed a candidate region on chromosome 19p13.12–13. Sequencing identified a nonsense mutation in the KLF1 gene, p.K288X, ablating the DNA binding domain of this key erythroid transcriptional regulator 2. Only HPFH family members were heterozygote carriers of this mutation. Expression profiling on primary erythroid progenitors revealed down-regulation of KLF1 target genes in HPFH samples. Functional assays demonstrated that, in addition to its established role in adult globin expression, KLF1 is a critical activator of the BCL11A gene, encoding a suppressor of HbF expression 3. These observations provide a rationale for the effects of KLF1 haploinsufficiency on HbF levels.