Identifying clinically useful biomarkers in neurodegenerative disease through a collaborative approach: the NeuroToolKit.

BACKGROUND: Alzheimer's disease (AD) is a complex and heterogeneous disease, which requires reliable biomarkers for diagnosis and monitoring disease activity. Preanalytical protocol and technical variability associated with biomarker immunoassays makes comparability of biomarker data across multiple cohorts difficult. This study aimed to compare cerebrospinal fluid (CSF) biomarker results across independent cohorts, including participants spanning the AD continuum. METHODS: Measured on the NeuroToolKit (NTK) prototype panel of immunoassays, 12 CSF biomarkers were evaluated from three cohorts (ALFA+, Wisconsin, and Abby/Blaze). A correction factor was applied to biomarkers found to be affected by preanalytical procedures (amyloid-ß1-42, amyloid-ß1-40, and alpha-synuclein), and results between cohorts for each disease stage were compared. The relationship between CSF biomarker concentration and cognitive scores was evaluated. RESULTS: Biomarker distributions were comparable across cohorts following correction. Correlations of biomarker values were consistent across cohorts, regardless of disease stage. Disease stage differentiation was highest for neurofilament light (NfL), phosphorylated tau, and total tau, regardless of the cohort. Correlation between biomarker concentration and cognitive scores was comparable across cohorts, and strongest for NfL, chitinase-3-like protein-1 (YKL40), and glial fibrillary acidic protein. DISCUSSION: The precision of the NTK enables merging of biomarker datasets, after correction for preanalytical confounders. Assessment of multiple cohorts is crucial to increase power in future studies into AD pathogenesis.

Transcriptome network of the papillary thyroid carcinoma radiation marker CLIP2.

BACKGROUND: We present a functional gene association network of the CLIP2 gene, generated by de-novo reconstruction from transcriptomic microarray data. CLIP2 was previously identified as a potential marker for radiation induced papillary thyroid carcinoma (PTC) of young patients in the aftermath of the Chernobyl reactor accident. Considering the rising thyroid cancer incidence rates in western societies, potentially related to medical radiation exposure, the functional characterization of CLIP2 is of relevance and contributes to the knowledge about radiation-induced thyroid malignancies. METHODS: We generated a transcriptomic mRNA expression data set from a CLIP2-perturbed thyroid cancer cell line (TPC-1) with induced CLIP2 mRNA overexpression and siRNA knockdown, respectively, followed by gene-association network reconstruction using the partial correlation-based approach GeneNet. Furthermore, we investigated different approaches for prioritizing differentially expressed genes for network reconstruction and compared the resulting networks with existing functional interaction networks from the Reactome, Biogrid and STRING databases. The derived CLIP2 interaction partners were validated on transcript and protein level. RESULTS: The best reconstructed network with regard to selection parameters contained a set of 20 genes in the 1st neighborhood of CLIP2 and suggests involvement of CLIP2 in the biological processes DNA repair/maintenance, chromosomal instability, promotion of proliferation and metastasis. Peptidylprolyl Isomerase Like 3 (PPIL3), previously identified as a potential direct interaction partner of CLIP2, was confirmed in this study by co-expression at the transcript and protein level. CONCLUSION: In our study we present an optimized preselection approach for genes subjected to gene-association network reconstruction, which was applied to CLIP2 perturbation transcriptome data of a thyroid cancer cell culture model. Our data support the potential carcinogenic role of CLIP2 overexpression in radiation-induced PTC and further suggest potential interaction partners of the gene.

Genomic amplification of Fanconi anemia complementation group A (FancA) in head and neck squamous cell carcinoma (HNSCC): Cellular mechanisms of radioresistance and clinical relevance.

Radio (chemo) therapy is a crucial treatment modality for head and neck squamous cell carcinoma (HNSCC), but relapse is frequent, and the underlying mechanisms remain largely elusive. Therefore, novel biomarkers are urgently needed. Previously, we identified gains on 16q23-24 to be associated with amplification of the Fanconi anemia A (FancA) gene and to correlate with reduced progression-free survival after radiotherapy. Here, we analyzed the effects of FancA on radiation sensitivity in vitro, characterized the underlying mechanisms, and evaluated their clinical relevance. Silencing of FancA expression in HNSCC cell lines with genomic gains on 16q23-24 resulted in significantly impaired clonogenic survival upon irradiation. Conversely, overexpression of FancA in immortalized keratinocytes conferred increased survival accompanied by improved DNA repair, reduced accumulation of chromosomal translocations, but no hyperactivation of the FA/BRCA-pathway. Downregulation of interferon signaling as identified by microarray analyses, enforced irradiation-induced senescence, and elevated production of the senescence-associated secretory phenotype (SASP) appeared to be candidate mechanisms contributing to FancA-mediated radioresistance. Data of the TCGA HNSCC cohort confirmed the association of gains on 16q24.3 with FancA overexpression and impaired overall survival. Importantly, transcriptomic alterations similar to those observed upon FancA overexpression in vitro strengthened the clinical relevance. Overall, FancA amplification and overexpression appear to be crucial for radiotherapeutic failure in HNSCC.

Natural Cubic Spline Regression Modeling Followed by Dynamic Network Reconstruction for the Identification of Radiation-Sensitivity Gene Association Networks from Time-Course Transcriptome Data.

Gene expression time-course experiments allow to study the dynamics of transcriptomic changes in cells exposed to different stimuli. However, most approaches for the reconstruction of gene association networks (GANs) do not propose prior-selection approaches tailored to time-course transcriptome data. Here, we present a workflow for the identification of GANs from time-course data using prior selection of genes differentially expressed over time identified by natural cubic spline regression modeling (NCSRM). The workflow comprises three major steps: 1) the identification of differentially expressed genes from time-course expression data by employing NCSRM, 2) the use of regularized dynamic partial correlation as implemented in GeneNet to infer GANs from differentially expressed genes and 3) the identification and functional characterization of the key nodes in the reconstructed networks. The approach was applied on a time-resolved transcriptome data set of radiation-perturbed cell culture models of non-tumor cells with normal and increased radiation sensitivity. NCSRM detected significantly more genes than another commonly used method for time-course transcriptome analysis (BETR). While most genes detected with BETR were also detected with NCSRM the false-detection rate of NCSRM was low (3%). The GANs reconstructed from genes detected with NCSRM showed a better overlap with the interactome network Reactome compared to GANs derived from BETR detected genes. After exposure to 1 Gy the normal sensitive cells showed only sparse response compared to cells with increased sensitivity, which exhibited a strong response mainly of genes related to the senescence pathway. After exposure to 10 Gy the response of the normal sensitive cells was mainly associated with senescence and that of cells with increased sensitivity with apoptosis. We discuss these results in a clinical context and underline the impact of senescence-associated pathways in acute radiation response of normal cells. The workflow of this novel approach is implemented in the open-source Bioconductor R-package splineTimeR.

Transcriptomic analyses of the radiation response in head and neck squamous cell carcinoma subclones with different radiation sensitivity: time-course gene expression profiles and gene association networks.

BACKGROUND: Acquired and inherent radioresistance of tumor cells is related to tumor relapse and poor prognosis - not only in head and neck squamous cell carcinoma (HNSCC). The underlying molecular mechanisms are largely unknown. Therefore, systemic in-depth analyses are needed to identify key regulators of radioresistance. In the present study, subclones of the CAL-33 HNSCC cell line with different radiosensitivity were analyzed to identify signaling pathways related to the different phenotypes. METHODS: Subclones with altered radiosensitivity were generated by fractionated irradiation of the parental CAL-33 cells. Differences in radiosensitivity were confirmed in colony formation assays. Selected subclones were characterized at the genomic and transcriptomic level by SKY, array CGH, and mRNA-microarray analyses. Time-course gene expression analyses upon irradiation using a natural cubic spline regression model identified temporally differentially expressed genes. Moreover, early and late responding genes were identified. Gene association networks were reconstructed using partial correlation. The Reactome pathway database was employed to conduct pathway enrichment analyses. RESULTS: The characterization of two subclones with enhanced radiation resistance (RP) and enhanced radiosensitivity (SP) revealed distinct genomic and transcriptomic changes compared to the parental cells. Differentially expressed genes after irradiation shared by both subclones pointed to important pathways of the early and late radiation response, including senescence, apoptosis, DNA repair, Wnt, PI3K/AKT, and Rho GTPase signaling. The analysis of the most important nodes of the gene association networks revealed pathways specific to the radiation response in different phenotypes of radiosensitivity. Exemplarily, for the RP subclone the senescence-associated secretory phenotype (SASP) together with GPCR ligand binding were considered as crucial. Also, the expression of endogenous retrovirus ERV3-1in response to irradiation has been observed, and the related gene association networks have been identified. CONCLUSIONS: Our study presents comprehensive gene expression data of CAL-33 subclones with different radiation sensitivity. The resulting networks and pathways associated with the resistant phenotype are of special interest and include the SASP. The radiation-associated expression of ERV3-1 also appears highly attractive for further studies of the molecular mechanisms underlying acquired radioresistance. The identified pathways may represent key players of radioresistance, which could serve as potential targets for molecularly designed, therapeutical intervention.

CFAssay: statistical analysis of the colony formation assay.

BACKGROUND: Colony formation assay is the gold standard to determine cell reproductive death after treatment with ionizing radiation, applied for different cell lines or in combination with other treatment modalities. Associated linear-quadratic cell survival curves can be calculated with different methods. For easy code exchange and methodological standardisation among collaborating laboratories a software package CFAssay for R (R Core Team, R: A Language and Environment for Statistical Computing, 2014) was established to perform thorough statistical analysis of linear-quadratic cell survival curves after treatment with ionizing radiation and of two-way designs of experiments with chemical treatments only. METHODS: CFAssay offers maximum likelihood and related methods by default and the least squares or weighted least squares method can be optionally chosen. A test for comparision of cell survival curves and an ANOVA test for experimental two-way designs are provided. RESULTS: For the two presented examples estimated parameters do not differ much between maximum-likelihood and least squares. However the dispersion parameter of the quasi-likelihood method is much more sensitive for statistical variation in the data than the multiple R (2) coefficient of determination from the least squares method. CONCLUSION: The dispersion parameter for goodness of fit and different plot functions in CFAssay help to evaluate experimental data quality. As open source software interlaboratory code sharing between users is facilitated. AVAILABILITY: The package is available at http://www.bioconductor.org/packages/release/bioc/html/CFAssay.html .

The impact of antiandrogen 2-hydroxyflutamide on the expression of steroidogenic enzymes in cultured porcine ovarian follicles.

We used our model system for agonism and antagonism of the androgen receptor (AR), in which the porcine ovarian follicles were exposed on the excessive concentration of an AR agonist- testosterone (T) or an AR antagonist- 2-hydroxyflutamide (2-Hf) to: (1) analyze the spatiotemporal expression of ovarian 3ß-hydroxysteroid dehydrogenase (3ß-HSD), cytochrome P450 17α-hydroxylase/c17,20-lyase (P450c17) and cytochrome P450 aromatase (P450arom); (2) to determine the contribution of AR-mediated action during steroidogenesis and (3) to establish some correlations between the onset and expression pattern of the investigated proteins. Whole follicles (6-8 mm in diameter) isolated from mature porcine ovaries have been incubated (for 24 h) in an organ culture system in the presence of T (10(-7 )M), 2-Hf (1.7 × 10(-4) M) or both T and 2-hydroxyflutamide (T+2-Hf, at the same concentrations as when added separately). Thereafter, sections obtained from cultured follicles were processed for main steroidogenic enzymes detection by immunohistochemistry. Moreover, expression of their mRNA and protein was determined by real-time PCR and Western blot analysis. Progesterone, androgens and estradiol concentrations in the culture media were measured by radioimmunoassays (RIA). Our results demonstrated that 2-Hf can influence the steroidogenic activity of porcine follicles in vitro through the blockade of AR. It was shown that follicular 2-Hf treatment brought about dramatic decline in the production of the investigated steroids. What is more the addition of 2-Hf separately caused a negative effect on 3ß-HSD and P450c17 mRNA and protein expression by ovarian follicles, while it was without effect on P450arom mRNA level. Quite opposite effect was observed in case of the simultaneous addition of 2-Hf and T. It caused high increase, in both P450arom mRNA and its protein. What was interesting, addition T+2-Hf evoked 3ß-HSD and P450c17 increase on mRNA level, but decreased their protein expression. This was against our expectations but the reason for that finding remains undiscovered, intriguing and worth reporting. These results suggest that alike, steroidogenic enzymes activity and their expression is associated with the presence of androgens and AR in the porcine ovary.