Plakins are involved in the regulation of centrosome position in polarized epithelial cells.

BACKGROUND INFORMATION: The control of epithelial cell polarity is key to their function. Its dysregulation is a major cause of tissue transformation. In polarized epithelial cells,the centrosome is off-centred toward the apical pole. This asymmetry determines the main orientation of the microtubule network and intra-cellular traffic. However, the mechanism regulating centrosome positioning at the apical pole of polarized epithelial cells is still poorly undertood. RESULTS: In this study we used transcriptomic data from breast cancer cells to identify molecular changes associated with the different stages of tumour transformation. We correlated these changes with variations in centrosome position or with cell progression along the epithelial-to-mesenchymal transition (EMT), a process that involves centrosome repositioning. We found that low levels of epiplakin, desmoplakin and periplakin correlated with centrosome mispositioning in cells that had progressed through EMT or tissue transformation. We further tested the causal role of these plakins in the regulation of centrosome position by knocking down their expression in a non-tumorigenic breast epithelial cell line (MCF10A). The downregulation of periplakin reduced the length of intercellular junction, which was not affected by the downregulation of epiplakin or desmoplakin. However, down-regulating any of them disrupted centrosome polarisation towards the junction without affecting microtubule stability. CONCLUSIONS: Altogether, these results demonstrated that epiplakin, desmoplakin and periplakin are involved in the maintenance of the peripheral position of the centrosome close to inter-cellular junctions. They also revealed that these plakins are downregulated during EMT and breast cancer progression, which are both associated with centrosome mispositioning. SIGNIFICANCE: These results revealed that the down-regulation of plakins and the consequential centrosome mispositioning are key signatures of disorganised cytoskeleton networks, inter-cellular junction weakening, shape deregulation and the loss of polarity in breast cancer cells. These metrics could further be used as a new readouts for early phases of tumoral development.

Prognosis of lasso-like penalized Cox models with tumor profiling improves prediction over clinical data alone and benefits from bi-dimensional pre-screening.

BACKGROUND: Prediction of patient survival from tumor molecular '-omics' data is a key step toward personalized medicine. Cox models performed on RNA profiling datasets are popular for clinical outcome predictions. But these models are applied in the context of "high dimension", as the number p of covariates (gene expressions) greatly exceeds the number n of patients and e of events. Thus, pre-screening together with penalization methods are widely used for dimensional reduction. METHODS: In the present paper, (i) we benchmark the performance of the lasso penalization and three variants (i.e., ridge, elastic net, adaptive elastic net) on 16 cancers from TCGA after pre-screening, (ii) we propose a bi-dimensional pre-screening procedure based on both gene variability and p-values from single variable Cox models to predict survival, and (iii) we compare our results with iterative sure independence screening (ISIS). RESULTS: First, we show that integration of mRNA-seq data with clinical data improves predictions over clinical data alone. Second, our bi-dimensional pre-screening procedure can only improve, in moderation, the C-index and/or the integrated Brier score, while excluding irrelevant genes for prediction. We demonstrate that the different penalization methods reached comparable prediction performances, with slight differences among datasets. Finally, we provide advice in the case of multi-omics data integration. CONCLUSIONS: Tumor profiles convey more prognostic information than clinical variables such as stage for many cancer subtypes. Lasso and Ridge penalizations perform similarly than Elastic Net penalizations for Cox models in high-dimension. Pre-screening of the top 200 genes in term of single variable Cox model p-values is a practical way to reduce dimension, which may be particularly useful when integrating multi-omics.

miRViz: a novel webserver application to visualize and interpret microRNA datasets.

MicroRNAs (miRNAs) are small non-coding RNAs that are involved in the regulation of major pathways in eukaryotic cells through their binding to and repression of multiple mRNAs. With high-throughput methodologies, various outcomes can be measured that produce long lists of miRNAs that are often difficult to interpret. A common question is: after differential expression or phenotypic screening of miRNA mimics, which miRNA should be chosen for further investigation? Here, we present miRViz (http://mirviz.prabi.fr/), a webserver application designed to visualize and interpret large miRNA datasets, with no need for programming skills. MiRViz has two main goals: (i) to help biologists to raise data-driven hypotheses and (ii) to share miRNA datasets in a straightforward way through publishable quality data representation, with emphasis on relevant groups of miRNAs. MiRViz can currently handle datasets from 11 eukaryotic species. We present real-case applications of miRViz, and provide both datasets and procedures to reproduce the corresponding figures. MiRViz offers rapid identification of miRNA families, as demonstrated here for the miRNA-320 family, which is significantly exported in exosomes of colon cancer cells. We also visually highlight a group of miRNAs associated with pluripotency that is particularly active in control of a breast cancer stem-cell population in culture.

Selective BMP-9 Inhibition Partially Protects Against Experimental Pulmonary Hypertension.

RATIONALE: Although many familial cases of pulmonary arterial hypertension exhibit an autosomal dominant mode of inheritance with the majority having mutations in essential constituents of the BMP (bone morphogenetic protein) signaling, the specific contribution of the long-term loss of signal transduction triggered by the BMPR2 (type 2 BMP receptor) remains poorly characterized. OBJECTIVE: To investigate the role of BMP9, the main ligand of ALK1 (Activin receptor-like kinase 1)/BMPR2 heterocomplexes, in pulmonary hypertension. METHOD AND RESULTS: The absence of BMP9 in Bmp9-/- mice and its inhibition in C57BL/6 mice using neutralizing anti-BMP9 antibodies substantially prevent against chronic hypoxia-induced pulmonary hypertension judged by right ventricular systolic pressure measurement, right ventricular hypertrophy, and pulmonary distal arterial muscularization. In agreement with these observations, we found that the BMP9/BMP10 ligand trap ALK1ECD administered in monocrotaline or Sugen/hypoxia (SuHx) rats substantially attenuate proliferation of pulmonary vascular cells, inflammatory cell infiltration, and regresses established pulmonary hypertension in rats. Our data obtained in human pulmonary endothelial cells derived from controls and pulmonary arterial hypertension patients indicate that BMP9 can affect the balance between endothelin-1, apelin, and adrenomedullin. We reproduced these in vitro observations in mice chronically exposed to hypoxia, with Bmp9-/- mice exhibiting lower mRNA levels of the vasoconstrictor peptide ET-1 (endothelin-1) and higher levels of the 2 potent vasodilator factors apelin and ADM (adrenomedullin) compared with Bmp9+/+ littermates. CONCLUSIONS: Taken together, our data indicate that the loss of BMP9, by deletion or inhibition, has beneficial effects against pulmonary hypertension onset and progression.

MiR-483-5p and miR-139-5p promote aggressiveness by targeting N-myc downstream-regulated gene family members in adrenocortical cancer.

Adrenocortical carcinoma (ACC) is a tumor with poor prognosis in which overexpression of a panel of microRNAs has been associated with malignancy but a very limited number of investigations on their role in ACC pathogenesis have been conducted. We examined the involvement of miR-483-5p and miR-139-5p in adrenocortical cancer aggressiveness. Using bioinformatics predictions and mRNA/miRNA expression profiles, we performed an integrated analysis to identify inversely correlated miRNA-mRNA pairs in ACC. We identified N-myc downstream-regulated gene family members 2 and 4 (NDRG2 and NDRG4) as targets of miR-483-5p and miR-139-5p, respectively. NDRG2 and NDRG4 expressions were inversely correlated respectively with miR-483-5p and miR-139-5p levels in aggressive ACC samples from two independent cohorts of 20 and 44 ACC. Moreover, upregulation of miR-139-5p and downregulation of NDRG4 demonstrated a striking prognostic value. A direct interaction between miR-483-5p or miR-139-5p and their targets was demonstrated in reporter assays. Downregulation of miR-483-5p or miR-139-5p in the ACC cell lines NCI-H295R and SW13 increased NDRG2 or NDRG4 mRNA and protein expression, compromised adrenocortical cancer cell invasiveness and anchorage-independent growth. MiR-483-5p or miR-139-5p overexpression and NDRG2 or NDRG4 inhibition produce similar changes, which are rescued by NDRG2 or NDRG4 ectopic expression. We established that key factors mediating epithelial-to-mesenchymal transition are downstream effectors of miR-483-5p/NDRG2 and miR-139-5p/NDRG4 pathways. Collectively, our data show for the first time that miR-483-5p/NDRG2 and miR-139-5p/NDRG4 axes promote ACC aggressiveness, with potential implications for prognosis and therapeutic interventions in adrenocortical malignancies.

Incorporating interaction networks into the determination of functionally related hit genes in genomic experiments with Markov random fields.

MOTIVATION: Incorporating gene interaction data into the identification of 'hit' genes in genomic experiments is a well-established approach leveraging the 'guilt by association' assumption to obtain a network based hit list of functionally related genes. We aim to develop a method to allow for multivariate gene scores and multiple hit labels in order to extend the analysis of genomic screening data within such an approach. RESULTS: We propose a Markov random field-based method to achieve our aim and show that the particular advantages of our method compared with those currently used lead to new insights in previously analysed data as well as for our own motivating data. Our method additionally achieves the best performance in an independent simulation experiment. The real data applications we consider comprise of a survival analysis and differential expression experiment and a cell-based RNA interference functional screen. AVAILABILITY AND IMPLEMENTATION: We provide all of the data and code related to the results in the paper. CONTACT: sean.j.robinson@utu.fi or laurent.guyon@cea.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MicroRNA degeneracy and pluripotentiality within a Lavallière-tie architecture confers robustness to gene expression networks.

Modularity, feedback control, functional redundancy and bowtie architecture have been proposed as key factors that confer robustness to complex biological systems. MicroRNAs (miRNAs) are highly conserved but functionally dispensable. These antinomic properties suggest that miRNAs fine-tune gene expression rather than act as genetic switches. We synthesize published and unpublished data and hypothesize that miRNA pluripotentiality acts to buffer gene expression, while miRNA degeneracy tunes the expression of targets, thus providing robustness to gene expression networks. Furthermore, we propose a Lavallière-tie architecture by integrating signal transduction, miRNAs and protein expression data to model complex gene expression networks.

Condensation of helium in aerogel and athermal dynamics of the random-field Ising model.

High resolution measurements reveal that condensation isotherms of (4)He in high porosity silica aerogel become discontinuous below a critical temperature. We show that this behavior does not correspond to an equilibrium phase transition modified by the disorder induced by the aerogel structure, but to the disorder-driven critical point predicted for the athermal out-of-equilibrium dynamics of the random-field Ising model. Our results evidence the key role of nonequilibrium effects in the phase transitions of disordered systems.

COL7A1 Expression Improves Prognosis Prediction for Patients with Clear Cell Renal Cell Carcinoma Atop of Stage.

Clear-cell renal cell carcinoma (ccRCC) accounts for 75% of kidney cancers. Due to the high recurrence rate and treatment options that come with high costs and potential side effects, a correct prognosis of patient survival is essential for the successful and effective treatment of patients. Novel biomarkers could play an important role in the assessment of the overall survival of patients. COL7A1 encodes for collagen type VII, a constituent of the basal membrane. COL7A1 is associated with survival in many cancers; however, the prognostic value of COL7A1 expression as a standalone biomarker in ccRCC has not been investigated. With five publicly available independent cohorts, we used Kaplan-Meier curves and the Cox proportional hazards model to investigate the prognostic value of COL7A1, as well as gene set enrichment analysis to investigate genes co-expressed with COL7A1. COL7A1 expression stratifies patients in terms of aggressiveness, where the 5-year survival probability of each of the four groups was 72.4%, 59.1%, 34.15%, and 8.6% in order of increasing expression. Additionally, COL7A1 expression was successfully used to further divide patients of each stage and histological grade into groups of high and low risk. Similar results were obtained in independent cohorts. In vitro knockdown of COL7A1 expression significantly affected ccRCC cells' ability to migrate, leading to the hypothesis that COL7A1 may have a role in cancer aggressiveness. To conclude, we identified COL7A1 as a new prognosis marker that can stratify ccRCC patients.

Optimal microRNA Sequencing Depth to Predict Cancer Patient Survival with Random Forest and Cox Models.

(1) Background: tumor profiling enables patient survival prediction. The two essential parameters to be calibrated when designing a study based on tumor profiles from a cohort are the sequencing depth of RNA-seq technology and the number of patients. This calibration is carried out under cost constraints, and a compromise has to be found. In the context of survival data, the goal of this work is to benchmark the impact of the number of patients and of the sequencing depth of miRNA-seq and mRNA-seq on the predictive capabilities for both the Cox model with elastic net penalty and random survival forest. (2) Results: we first show that the Cox model and random survival forest provide comparable prediction capabilities, with significant differences for some cancers. Second, we demonstrate that miRNA and/or mRNA data improve prediction over clinical data alone. mRNA-seq data leads to slightly better prediction than miRNA-seq, with the notable exception of lung adenocarcinoma for which the tumor miRNA profile shows higher predictive power. Third, we demonstrate that the sequencing depth of RNA-seq data can be reduced for most of the investigated cancers without degrading the prediction abilities, allowing the creation of independent validation sets at a lower cost. Finally, we show that the number of patients in the training dataset can be reduced for the Cox model and random survival forest, allowing the use of different models on different patient subgroups.

Resolution of strongly competitive product channels with optimal dynamic discrimination: application to flavins.

Fundamental molecular selectivity limits are probed by exploiting laser-controlled quantum interferences for the creation of distinct spectral signatures in two flavin molecules, erstwhile nearly indistinguishable via steady-state methods. Optimal dynamic discrimination (ODD) uses optimally shaped laser fields to transiently amplify minute molecular variations that would otherwise go unnoticed with linear absorption and fluorescence techniques. ODD is experimentally demonstrated by combining an optimally shaped UV pump pulse with a time-delayed, fluorescence-depleting IR pulse for discrimination amongst riboflavin and flavin mononucleotide in aqueous solution, which are structurally and spectroscopically very similar. Closed-loop, adaptive pulse shaping discovers a set of UV pulses that induce disparate responses from the two flavins and allows for concomitant flavin discrimination of ∼16σ. Additionally, attainment of ODD permits quantitative, analytical detection of the individual constituents in a flavin mixture. The successful implementation of ODD on quantum systems of such high complexity bodes well for the future development of the field and the use of ODD techniques in a variety of demanding practical applications.

MicroRNA Therapeutics in Cancer: Current Advances and Challenges.

The discovery of microRNAs (miRNAs) in 1993 has challenged the dogma of gene expression regulation. MiRNAs affect most of cellular processes from metabolism, through cell proliferation and differentiation, to cell death. In cancer, deregulated miRNA expression leads to tumor development and progression by promoting acquisition of cancer hallmark traits. The multi-target action of miRNAs, which enable regulation of entire signaling networks, makes them attractive tools for the development of anti-cancer therapies. Hence, supplementing downregulated miRNA by synthetic oligonucleotides or silencing overexpressed miRNAs through artificial antagonists became a common strategy in cancer research. However, the ultimate success of miRNA therapeutics will depend on solving pharmacokinetic and targeted delivery issues. The development of a number of nanocarrier-based platforms holds significant promises to enhance the cell specific controlled delivery and safety profile of miRNA-based therapies. In this review, we provide among the most comprehensive assessments to date of promising nanomedicine platforms that have been tested preclinically, pertaining to the treatment of selected solid tumors including lung, liver, breast, and glioblastoma tumors as well as endocrine malignancies. The future challenges and potential applications in clinical oncology are discussed.

Cooperative Blockade of CK2 and ATM Kinases Drives Apoptosis in VHL-Deficient Renal Carcinoma Cells through ROS Overproduction.

Kinase-targeted agents demonstrate antitumor activity in advanced metastatic clear cell renal cell carcinoma (ccRCC), which remains largely incurable. Integration of genomic approaches through small-molecules and genetically based high-throughput screening holds the promise of improved discovery of candidate targets for cancer therapy. The 786-O cell line represents a model for most ccRCC that have a loss of functional pVHL (von Hippel-Lindau). A multiplexed assay was used to study the cellular fitness of a panel of engineered ccRCC isogenic 786-O VHL- cell lines in response to a collection of targeted cancer therapeutics including kinase inhibitors, allowing the interrogation of over 2880 drug-gene pairs. Among diverse patterns of drug sensitivities, investigation of the mechanistic effect of one selected drug combination on tumor spheroids and ex vivo renal tumor slice cultures showed that VHL-defective ccRCC cells were more vulnerable to the combined inhibition of the CK2 and ATM kinases than wild-type VHL cells. Importantly, we found that HIF-2α acts as a key mediator that potentiates the response to combined CK2/ATM inhibition by triggering ROS-dependent apoptosis. Importantly, our findings reveal a selective killing of VHL-deficient renal carcinoma cells and provide a rationale for a mechanism-based use of combined CK2/ATM inhibitors for improved patient care in metastatic VHL-ccRCC.

Copper-free click chemistry for highly luminescent quantum dot conjugates: application to in vivo metabolic imaging.

Quantum dots (QD) are inorganic nanocrystals with outstanding optical properties, specially suited for biological imaging applications. Their attachment to biomolecules in mild aqueous conditions for the design of bioconjugates is therefore highly desirable. 1,3-dipolar [3 + 2] cycloaddition between azides and terminal alkynes ("click chemistry") could represent an attractive QD functionalization method. Unfortunately, the use of the popular Cu(I)-catalyzed version of this reaction is not applicable for achieving this goal, since the presence of copper dramatically alters the luminescence properties of QD dispersions. We demonstrate here that copper-free click chemistry, between strained cyclooctyne functionalized QD and azido-biomolecules, leads to highly luminescent conjugates. In addition, we show that QD-cyclooctyne can be used at previously unreported low concentration (250 nM) for imaging the incorporation of azido-modified sialic acid in cell membrane glycoproteins.

Early Postoperative Circulating miR-483-5p Is a Prognosis Marker for Adrenocortical Cancer.

We have previously identified serum miR-483-5p as a preoperative diagnosis and prognosis biomarker for adrenocortical cancer (ACC). Here, we aimed to determine whether circulating miR-483-5p levels measured 3 months post-operatively distinguished patients with good prognosis (no recurrence for at least 3 years; NR3yrs) from patients with poor prognosis (recurrence or death within 3 years after surgery; R < 3yrs). We conducted a single-center retrospective analysis using sera from 48 patients with ACC that were initially non-metastatic and treated by surgery. Sera sampled within 3 months after surgery were available in 26 patients. MiR-483-5p absolute circulating levels were measured using quantitative PCR. Thirteen patients showed a recurrence before 3 years (=R < 3yrs). Thirteen patients showed no recurrence within 3 years, including 11 patients with a follow-up longer than 3 years (=NR3yrs). Serum miR-483-5p levels were higher in R < 3yrs than in NR3yrs: 1,541,990 ± 428,377 copies/mL vs. 388,457 ± 62,169 copies/mL (p = 0.002). Receiver operating characteristic analysis showed that a value of 752,898 copies/mL distinguished R < 3yrs from NR3yrs with 61.5% sensitivity (CI 31.6-86.1) and 100% specificity (CI 71.5-100) with an area under the curve of 0.853. Patients with a value below this threshold had a significantly longer recurrence-free and overall survival. In multivariate analysis, miR-483-5p provided the single best prognostic value for recurrence-free survival (RFS) (hazard ratio (HR) for recurrence 5.98, p < 0.011) but not for overall survival. Our study suggests that serum miR-483-5p is a potent early post-operative biomarker for ACC prognosis that might be a better predictor of RFS than currently used markers.

Mycoplasma hyopneumoniae J elicits an antioxidant response and decreases the expression of ciliary genes in infected swine epithelial cells.

Mycoplasma hyopneumoniae is the most costly pathogen for swine production. Although several studies have focused on the host-bacterium association, little is known about the changes in gene expression of swine cells upon infection. To improve our understanding of this interaction, we infected swine epithelial NPTr cells with M. hyopneumoniae strain J to identify differentially expressed mRNAs and miRNAs. The levels of 1,268 genes and 170 miRNAs were significantly modified post-infection. Up-regulated mRNAs were enriched in genes related to redox homeostasis and antioxidant defense, known to be regulated by the transcription factor NRF2 in related species. Down-regulated mRNAs were enriched in genes associated with cytoskeleton and ciliary functions. Bioinformatic analyses suggested a correlation between changes in miRNA and mRNA levels, since we detected down-regulation of miRNAs predicted to target antioxidant genes and up-regulation of miRNAs targeting ciliary and cytoskeleton genes. Interestingly, most down-regulated miRNAs were detected in exosome-like vesicles suggesting that M. hyopneumoniae infection induced a modification of the composition of NPTr-released vesicles. Taken together, our data indicate that M. hyopneumoniae elicits an antioxidant response induced by NRF2 in infected cells. In addition, we propose that ciliostasis caused by this pathogen is partially explained by the down-regulation of ciliary genes.

Ex-Vivo Treatment of Tumor Tissue Slices as a Predictive Preclinical Method to Evaluate Targeted Therapies for Patients with Renal Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the third type of urologic cancer. At time of diagnosis, 30% of cases are metastatic with no effect of chemotherapy or radiotherapy. Current targeted therapies lead to a high rate of relapse and resistance after a short-term response. Thus, a major hurdle in the development and use of new treatments for ccRCC is the lack of good pre-clinical models that can accurately predict the efficacy of new drugs and allow the stratification of patients into the correct treatment regime. Here, we describe different 3D cultures models of ccRCC, emphasizing the feasibility and the advantage of ex-vivo treatment of fresh, surgically resected human tumor slice cultures of ccRCC as a robust preclinical model for identifying patient response to specific therapeutics. Moreover, this model based on precision-cut tissue slices enables histopathology measurements as tumor architecture is retained, including the spatial relationship between the tumor and tumor-infiltrating lymphocytes and the stromal components. Our data suggest that acute treatment of tumor tissue slices could represent a benchmark of further exploration as a companion diagnostic tool in ccRCC treatment and a model to develop new therapeutic drugs.

Chi2 analysis for estimating the accuracy of optical properties derived from time resolved diffuse-reflectance.

Weighted residuals and the reduced chi(2) (chi(R) (2)) value are investigated with regard to their relevance for assessing optical property estimates using the diffusion equation for time-resolved measurements in turbid media. It is shown and explained, for all photon counting experiments including lifetime estimation, why chi(R) (2) increases linearly with the number of photons when there is a model bias. Only when a sufficient number of photons has been acquired, chi(R) (2) is a pertinent value for assessing the accuracy of mu(a) and mu(s)' estimates. It was concluded that chi(R) (2) is of particular interest for cases of small interfiber separation, low-level scattering, strong absorption and incorrect measurement of instrument response function. It was also found that chi(R) (2) is less pertinent for judging mu(a) in case of air boundary effects.

Targeting AU-rich element-mediated mRNA decay with a truncated active form of the zinc-finger protein TIS11b/BRF1 impairs major hallmarks of mammary tumorigenesis.

Altered expression of regulatory RNA-binding proteins (RBPs) in cancer leads to abnormal expression of mRNAs encoding many factors involved in cancer hallmarks. While conventional anticancer therapies usually target one pathway at a time, targeting key RBP would affect multiple genes and thus overcome drug resistance. Among the Tristetraprolin family of RBP, TIS11b/BRF1/ZFP36L1 mediates mRNA decay through binding to Adenylate/Uridylate (AU-rich elements) in mRNA 3'-untranslated region and recruitment of mRNA degradation enzymes. Here, we show that TIS11b is markedly underexpressed in three breast cancer cell lines, as well as in breast tumor samples. We hypothesized that restoring intracellular TIS11b levels could impair cancer cell phenotypic traits. We thus generated a derivative of TIS11b called R9-ZnCS334D, by combining N-terminal domain deletion, serine-to-aspartate substitution at position 334 to enhance the function of the protein and fusion to the cell-penetrating peptide polyarginine R9. R9-ZnCS334D not only blunted secretion of vascular endothelial growth factor (VEGF) but also inhibited proliferation, migration, invasion, and anchorage-independent growth of murine 4T1 or human MDA-MB-231 breast cancer cells. Moreover, R9-ZnCS334D prevented endothelial cell organization into vessel-like structures, suggesting that it could potentially target various cell types within the tumor microenvironment. In vivo, injection of R9-ZnCS334D in 4T1 tumors impaired tumor growth, decreased tumor hypoxia, and expression of the epithelial-to-mesenchymal transition (EMT) markers Snail, Vimentin, and N-cadherin. R9-ZnCS334D also hindered the expression of chemokines and proteins involved in cancer-related inflammation and invasion including Fractalkine (CX3CL1), SDF-1 (CXCL12), MCP-1 (CCL2), NOV (CCN3), and Pentraxin-3 (PTX3). Collectively, our data indicate that R9-ZnCS334D counteracts multiple traits of breast cancer cell aggressiveness and suggest that this novel protein could serve as the basis for innovative multi-target therapies in cancer.

Bioinformatics Methods to Select Prognostic Biomarker Genes from Large Scale Datasets: A Review.

With the increased availability of survival datasets, that comprise both molecular information (e.g., gene expression), and clinical information (e.g., patient survival), numerous genes are proposed as prognostic biomarkers. Despite efforts and money invested, very few of these biomarkers have been clinically validated and are used routinely. A high false discovery rate is assumed to be largely responsible for this, in particular as the number of tested genes is extremely high relative to the number of patients followed. Here, after describing the historical methodologies on which recent developments have often been based, this review describes studies that have been performed in the last few years. The concepts will be illustrated for a renal cancer dataset, and the corresponding scripts are provided (Supporting Information). These new developments belong to three main fields of applications. First, variable selection concerns various improvements to lasso penalization. Second, accurate definition of p-values and control of the false discovery rate have also been the subject of many studies. Third, the incorporation of biological knowledge, often through the form of networks or pathways, can be used as an a priori and/or to reduce dimensionality. These new and promising developments deserve benchmarking by independent groups not involved in their development, with various independent datasets. Further work on the methodologies is also still required.