Identification of BBX proteins as rate-limiting cofactors of HY5.

As a source of both energy and environmental information, monitoring of incoming light is crucial for plants to optimize growth throughout development1. Concordantly, the light signalling pathways in plants are highly integrated with numerous other regulatory pathways2,3. One of these signal integrators is the basic leucine zipper domain (bZIP) transcription factor LONG HYPOCOTYL 5 (HY5), which has a key role as a positive regulator of light signalling in plants4,5. Although HY5 is thought to act as a DNA-binding transcriptional regulator6,7, the lack of any apparent transactivation domain8 makes it unclear how HY5 is able to accomplish its many functions. Here we describe the identification of three B-box containing proteins (BBX20, BBX21 and BBX22) as essential partners for HY5-dependent modulation of hypocotyl elongation, anthocyanin accumulation and transcriptional regulation. The bbx20 bbx21 bbx22 (bbx202122) triple mutant mimics the phenotypes of hy5 in the light and its ability to suppress the cop1 mutant phenotype in darkness. Furthermore, 84% of genes that exhibit differential expression in bbx202122 are also regulated by HY5, and we provide evidence that HY5 requires the B-box proteins for transcriptional regulation. Finally, expression of a truncated dark-stable version of HY5 (HY5(ΔN77)) together with BBX21 mutated in its VP motif strongly promoted de-etiolation in dark-grown seedlings, demonstrating the functional interdependence of these factors. In sum, this work clarifies long-standing questions regarding HY5 action and provides an example of how a master regulator might gain both specificity and dynamicity through the obligate dependence of cofactors.

Identification of sample annotation errors in gene expression datasets.

The comprehensive transcriptomic analysis of clinically annotated human tissue has found widespread use in oncology, cell biology, immunology, and toxicology. In cancer research, microarray-based gene expression profiling has successfully been applied to subclassify disease entities, predict therapy response, and identify cellular mechanisms. Public accessibility of raw data, together with corresponding information on clinicopathological parameters, offers the opportunity to reuse previously analyzed data and to gain statistical power by combining multiple datasets. However, results and conclusions obviously depend on the reliability of the available information. Here, we propose gene expression-based methods for identifying sample misannotations in public transcriptomic datasets. Sample mix-up can be detected by a classifier that differentiates between samples from male and female patients. Correlation analysis identifies multiple measurements of material from the same sample. The analysis of 45 datasets (including 4913 patients) revealed that erroneous sample annotation, affecting 40 % of the analyzed datasets, may be a more widespread phenomenon than previously thought. Removal of erroneously labelled samples may influence the results of the statistical evaluation in some datasets. Our methods may help to identify individual datasets that contain numerous discrepancies and could be routinely included into the statistical analysis of clinical gene expression data.

Loss of circadian clock gene expression is associated with tumor progression in breast cancer.

Several studies suggest a link between circadian rhythm disturbances and tumorigenesis. However, the association between circadian clock genes and prognosis in breast cancer has not been systematically studied. Therefore, we examined the expression of 17 clock components in tumors from 766 node-negative breast cancer patients that were untreated in both neoadjuvant and adjuvant settings. In addition, their association with metastasis-free survival (MFS) and correlation to clinicopathological parameters were investigated. Aiming to estimate functionality of the clockwork, we studied clock gene expression relationships by correlation analysis. Higher expression of several clock genes (e.g., CLOCK, PER1, PER2, PER3, CRY2, NPAS2 and RORC) was found to be associated with longer MFS in univariate Cox regression analyses (HR<1 and FDR-adjusted P < 0.05). Stratification according to molecular subtype revealed prognostic relevance for PER1, PER3, CRY2 and NFIL3 in the ER+/HER2- subgroup, CLOCK and NPAS2 in the ER-/HER2- subtype, and ARNTL2 in HER2+ breast cancer. In the multivariate Cox model, only PER3 (HR = 0.66; P = 0.016) and RORC (HR = 0.42; P = 0.003) were found to be associated with survival outcome independent of established clinicopathological parameters. Pairwise correlations between functionally-related clock genes (e.g., PER2-PER3 and CRY2-PER3) were stronger in ER+, HER2- and low-grade carcinomas; whereas, weaker correlation coefficients were observed in ER- and HER2+ tumors, high-grade tumors and tumors that progressed to metastatic disease. In conclusion, loss of clock genes is associated with worse prognosis in breast cancer. Coordinated co-expression of clock genes, indicative of a functional circadian clock, is maintained in ER+, HER2-, low grade and non-metastasizing tumors but is compromised in more aggressive carcinomas.

An integrative analysis of the tumorigenic role of TAZ in human non-small cell lung cancer.

PURPOSE: TAZ, also known as WWTR1, has recently been suggested as an oncogene in non-small cell lung cancer (NSCLC). We investigated the clinical relevance of TAZ expression and its functional role in NSCLC tumorigenesis. EXPERIMENTAL DESIGN: We characterized TAZ at the DNA (n=192), mRNA (n=196), and protein levels (n=345) in an NSCLC patient cohort. Gene expression analysis was complemented by a meta-analysis of public datasets (n=1,382). The effects of TAZ on cell proliferation and cell cycle were analyzed in cell cultures and on tumor growth in mice. TAZ-dependent microarray-based expression profiles in NSCLC cells were combined with molecular profiles in human NSCLC tissues for in silico analysis. RESULTS: Higher TAZ mRNA and protein levels were associated with shorter patient survival. Transduction of TAZ enhanced cell proliferation and tumorigenesis in bronchial epithelial cells, whereas TAZ silencing suppressed cell proliferation and induced cell cycle arrest in NSCLC cells. Microarray and cell culture experiments showed that ErbB ligands (amphiregulin, epiregulin, and neuregulin 1) are downstream targets of TAZ. Our in silico analysis revealed a TAZ signature that substantiated the clinical impact of TAZ and confirmed its relationship to the epidermal growth factor receptor signaling pathway. CONCLUSION: TAZ expression defines a clinically distinct subgroup of patients with NSCLC. ErbB ligands are suggested to mediate the effects of TAZ on lung cancer progression. Our findings emphasize the tumorigenic role of TAZ and may serve as the basis for new treatment strategies.

Aberrantly activated claudin 6 and 18.2 as potential therapy targets in non-small-cell lung cancer.

Claudins (CLDNs) are central components of tight junctions that regulate epithelial-cell barrier function and polarity. Altered CLDN expression patterns have been demonstrated in numerous cancer types and lineage-specific CLDNs have been proposed as therapy targets. The objective of this study was to assess which fraction of patients with non-small-cell lung cancer (NSCLC) express CLDN6 and CLDN18 isoform 2 (CLDN18.2). Protein expression of CLDN6 and CLDN18.2 was examined by immunohistochemistry on a tissue microarray (n = 355) and transcript levels were supportively determined based on gene expression microarray data from fresh-frozen NSCLC tissues (n = 196). Both were analyzed with regard to frequency, distribution and association with clinical parameters. Immunohistochemical analysis of tissue sections revealed distinct membranous positivity of CLDN6 (6.5%) and CLDN18.2 (3.7%) proteins in virtually non-overlapping subgroups of adenocarcinomas and large-cell carcinomas. Pneumocytes and bronchial epithelial cells were consistently negative. Corresponding to the protein expression, in subsets of non-squamous lung carcinoma high mRNA levels of CLDN6 (7-16%) and total CLDN18 (5-12%) were observed. Protein expression correlated well with total mRNA expression of the corresponding gene (rho = 0.4-0.8). CLDN18.2 positive tumors were enriched among slowly proliferating, thyroid transcription factor 1 (TTF-1)-negative adenocarcinomas, suggesting that isoform-specific CLDN expression may delineate a specific subtype. Noteworthy, high CLDN6 protein expression was associated with worse prognosis in lung adenocarcinoma in the univariate [hazard ratio (HR): 1.8; p = 0.03] and multivariate COX regression model (HR: 1.9; p = 0.02). These findings encourage further clinical exploration of targeting ectopically activated CLDN expression as a valuable treatment concept in NSCLC.

Interferon-inducible guanylate binding protein (GBP2) is associated with better prognosis in breast cancer and indicates an efficient T cell response.

BACKGROUND: Recently, interferon-inducible guanylate binding protein (GBP2) has been discussed as a possible control factor in tumor development, which is controlled by p53, and inhibits NF-Kappa B and Rac protein as well as expression of matrix metalloproteinase 9. However, the potential role that GBP2 plays in tumor development and prognosis has not yet been studied. METHODS: We analyzed whether GBP2 mRNA levels are associated with metastasis-free interval in 766 patients with node negative breast carcinomas who did not receive systemic chemotherapy. Furthermore, response to anthracycline-based chemotherapy was studied in 768 breast cancer patients. RESULTS: High expression of GBP2 in breast carcinomas was associated with better prognosis in the univariate (P < 0.001, hazard ratio 0.763, 95 % CI 0.650-0.896) as well as in the multivariate Cox analysis (P = 0.008, hazard ratio 0.731, 95 % CI 0.580-0.920) adjusted to the established clinical factors age, pT stage, grading, hormone and ERBB2 receptor status. The association was particularly strong in subgroups with high proliferation and positive estrogen receptor status but did not reach significance in carcinomas with low expression of proliferation associated genes. Besides its prognostic capacity, GBP2 also predicted pathologically complete response to anthracycline-based chemotherapy (P = 0.0037, odds ratio 1.39, 95 % CI 1.11-1.74). Interestingly, GBP2 correlated with a recently established T cell signature, indicating tumor infiltration with T cells (R = 0.607, P < 0.001). CONCLUSION: GBP2 is associated with better prognosis in fast proliferating tumors and probably represents a marker of an efficient T cell response.

The prognostic relevance of tumour-infiltrating plasma cells and immunoglobulin kappa C indicates an important role of the humoral immune response in non-small cell lung cancer.

A prognostic impact of immunoglobulin kappa C (IGKC) expression has been described in cancer. We analysed the influence of B-cell and plasma cell markers, as well as IGKC expression, in non-small lung cancer (NSCLC) using immunohistochemistry on a tissue microarray. IGKC protein expression was independently associated with longer survival, with particular impact in the adenocarcinoma subgroup. Moreover, a correlation was seen with CD138+ cells, but not with CD20. CD138 expression revealed a comparable association with survival. In conclusion, IGKC expression in stroma-infiltrating plasma cells is a prognostic marker in NSCLC, supporting emerging treatment concepts that exploit the humoral immune response.

Biomarker discovery in non-small cell lung cancer: integrating gene expression profiling, meta-analysis, and tissue microarray validation.

PURPOSE: Global gene expression profiling has been widely used in lung cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis and therapy response. So far, the value of these multigene signatures in clinical practice is unclear, and the biologic importance of individual genes is difficult to assess, as the published signatures virtually do not overlap. EXPERIMENTAL DESIGN: Here, we describe a novel single institute cohort, including 196 non-small lung cancers (NSCLC) with clinical information and long-term follow-up. Gene expression array data were used as a training set to screen for single genes with prognostic impact. The top 450 probe sets identified using a univariate Cox regression model (significance level P < 0.01) were tested in a meta-analysis including five publicly available independent lung cancer cohorts (n = 860). RESULTS: The meta-analysis revealed 14 genes that were significantly associated with survival (P < 0.001) with a false discovery rate <1%. The prognostic impact of one of these genes, the cell adhesion molecule 1 (CADM1), was confirmed by use of immunohistochemistry on tissue microarrays from 2 independent NSCLC cohorts, altogether including 617 NSCLC samples. Low CADM1 protein expression was significantly associated with shorter survival, with particular influence in the adenocarcinoma patient subgroup. CONCLUSIONS: Using a novel NSCLC cohort together with a meta-analysis validation approach, we have identified a set of single genes with independent prognostic impact. One of these genes, CADM1, was further established as an immunohistochemical marker with a potential application in clinical diagnostics.

Optimal strategies for sequential validation of significant features from high-dimensional genomic data.

High-dimensional genomic studies play a key role in identifying critical features that are significantly associated with a phenotypic outcome. The two most important examples are the detection of (1) differentially expressed genes from genome-wide gene expression studies and (2) single-nucleotide polymorphisms (SNPs) from genome-wide association studies. Such experiments are often associated with high noise levels, and the validity of statistical conclusions suffers from low sample size compared to large number of features. The corresponding multiple testing problem calls for the identification of optimal strategies for controlling the numbers of false discoveries and false nondiscoveries. In addition, a frequent validation problem is that features identified as important in one study are often less so in another study. Adjustment for multiple testing in both studies separately increases the risk of missing the crucial features even further. These problems can be addressed by sequential validation strategies, where only significant features identified in one study enter as candidates in the next study. The quality associated with different studies, for example, in terms of noise levels, may vary considerably. By performing simulation studies it is possible to demonstrate that the optimal order for this stepwise procedure is to sort experimental studies according to their quality in descending order. The impact of the method for multiple testing adjustment (Bonferroni-Holm, FDR) was also analyzed. Finally, the sequential validation strategy was applied to three large breast cancer studies with gene expression measurements, confirming the crucial impact of the order of the validation steps in a real-world application.

A comprehensive analysis of human gene expression profiles identifies stromal immunoglobulin κ C as a compatible prognostic marker in human solid tumors.

PURPOSE: Although the central role of the immune system for tumor prognosis is generally accepted, a single robust marker is not yet available. EXPERIMENTAL DESIGN: On the basis of receiver operating characteristic analyses, robust markers were identified from a 60-gene B cell-derived metagene and analyzed in gene expression profiles of 1,810 breast cancer; 1,056 non-small cell lung carcinoma (NSCLC); 513 colorectal; and 426 ovarian cancer patients. Protein and RNA levels were examined in paraffin-embedded tissue of 330 breast cancer patients. The cell types were identified with immunohistochemical costaining and confocal fluorescence microscopy. RESULTS: We identified immunoglobulin κ C (IGKC) which as a single marker is similarly predictive and prognostic as the entire B-cell metagene. IGKC was consistently associated with metastasis-free survival across different molecular subtypes in node-negative breast cancer (n = 965) and predicted response to anthracycline-based neoadjuvant chemotherapy (n = 845; P < 0.001). In addition, IGKC gene expression was prognostic in NSCLC and colorectal cancer. No association was observed in ovarian cancer. IGKC protein expression was significantly associated with survival in paraffin-embedded tissues of 330 breast cancer patients. Tumor-infiltrating plasma cells were identified as the source of IGKC expression. CONCLUSION: Our findings provide IGKC as a novel diagnostic marker for risk stratification in human cancer and support concepts to exploit the humoral immune response for anticancer therapy. It could be validated in several independent cohorts and carried out similarly well in RNA from fresh frozen as well as from paraffin tissue and on protein level by immunostaining.

Arabidopsis female gametophyte gene expression map reveals similarities between plant and animal gametes.

The development of multicellular organisms is controlled by differential gene expression whereby cells adopt distinct fates. A spatially resolved view of gene expression allows the elucidation of transcriptional networks that are linked to cellular identity and function. The haploid female gametophyte of flowering plants is a highly reduced organism: at maturity, it often consists of as few as three cell types derived from a common precursor [1, 2]. However, because of its inaccessibility and small size, we know little about the molecular basis of cell specification and differentiation in the female gametophyte. Here we report expression profiles of all cell types in the mature Arabidopsis female gametophyte. Differentially expressed posttranscriptional regulatory modules and metabolic pathways characterize the distinct cell types. Several transcription factor families are overrepresented in the female gametophyte in comparison to other plant tissues, e.g., type I MADS domain, RWP-RK, and reproductive meristem transcription factors. PAZ/Piwi-domain encoding genes are upregulated in the egg, indicating a role of epigenetic regulation through small RNA pathways-a feature paralleled in the germline of animals [3]. A comparison of human and Arabidopsis egg cells for enrichment of functional groups identified several similarities that may represent a consequence of coevolution or ancestral gametic features.