massiveGST: A Mann-Whitney-Wilcoxon Gene-Set Test Tool That Gives Meaning to Gene-Set Enrichment Analysis.

Gene-set enrichment analysis is the key methodology for obtaining biological information from transcriptomic space's statistical result. Since its introduction, Gene-set Enrichment analysis methods have obtained more reliable results and a wider range of application. Great attention has been devoted to global tests, in contrast to competitive methods that have been largely ignored, although they appear more flexible because they are independent from the source of gene-profiles. We analyzed the properties of the Mann-Whitney-Wilcoxon test, a competitive method, and adapted its interpretation in the context of enrichment analysis by introducing a Normalized Enrichment Score that summarize two interpretations: a probability estimate and a location index. Two implementations are presented and compared with relevant literature methods: an R package and an online web tool. Both allow for obtaining tabular and graphical results with attention to reproducible research.

Per-sample standardization and asymmetric winsorization lead to accurate clustering of RNA-seq expression profiles.

MOTIVATION: Data transformations are an important step in the analysis of RNA-seq data. Nonetheless, the impact of transformation on the outcome of unsupervised clustering procedures is still unclear. RESULTS: Here, we present an Asymmetric Winsorization per-Sample Transformation (AWST), which is robust to data perturbations and removes the need for selecting the most informative genes prior to sample clustering. Our procedure leads to robust and biologically meaningful clusters both in bulk and in single-cell applications. AVAILABILITY AND IMPLEMENTATION: The AWST method is available at https://github.com/drisso/awst. The code to reproduce the analyses is available at https://github.com/drisso/awst_analysis. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Tomb of the Diver and the frescoed tombs in Paestum (southern Italy): New insights from a comparative archaeometric study.

The Tomb of the Diver has been subject for many decades of fierce debate among archaeologists and classicists. Since its discovery in 1968, some scholars have considered it a unique example of the lost tradition of Greek painting, others have emphasized Etruscan or Italic parallels. More recently, a possible local production has been suggested. With the aim of trying to solve the archaeological question, an archaeometric comparison among this well-known artwork and several frescoed tombs coming from Hellenistic and Lucan necropolis was carried out. The multi-analytical study was focused on the identification of peculiar features of executive techniques and raw materials since the first period of the archaeological site. The analytical investigation has been preliminary based on a non-destructive approach, performed in-situ by portable equipment including imaging diagnostics and compositional spectroscopic techniques for identifying pigments and the conservation state of original painted surface; subsequently, a further deepening by using destructive techniques was performed in-lab for the mortar-based supports characterization. Archaeometric study suggested that technological choices slightly changed in a time span of about two centuries, highlighting important markers that allow clustering the contemporary artistic productions. Moreover, a comparison with mortars from temples decorations was provided to better understand the whole artistic context. The archaeometric data showed that the Tomb of the Diver could be traced back to a local artisanal tradition and therefore is neither Etruscan nor Greek, but the first and foremost an expression of the local elite culture of Paestum.

A recurrent point mutation in PRKCA is a hallmark of chordoid gliomas.

Chordoid glioma (ChG) is a characteristic, slow growing, and well-circumscribed diencephalic tumor, whose mutational landscape is unknown. Here we report the analysis of 16 ChG by whole-exome and RNA-sequencing. We found that 15 ChG harbor the same PRKCA D463H mutation. PRKCA encodes the Protein kinase C (PKC) isozyme alpha (PKCα) and is mutated in a wide range of human cancers. However the hot spot PRKCA D463H mutation was not described in other tumors. PRKCA D463H is strongly associated with the activation of protein translation initiation (EIF2) pathway. PKCαD463H mRNA levels are more abundant than wild-type PKCα transcripts, while PKCαD463H is less stable than the PCKαWT protein. Compared to PCKαWT, the PKCαD463H protein is depleted from the cell membrane. The PKCαD463H mutant enhances proliferation of astrocytes and tanycytes, the cells of origin of ChG. In conclusion, our study identifies the hallmark mutation for chordoid gliomas and provides mechanistic insights on ChG oncogenesis.

Comparison between invasive breast cancer with extensive peritumoral vascular invasion and inflammatory breast carcinoma: a clinicopathologic study of 161 cases.

OBJECTIVES: Extensive peritumoral neoplastic lymphovascular invasion (ePVI) is a marker of aggressiveness in invasive breast carcinoma (BC). METHODS: We explored the impact of ePVI on different BC subtypes. In a total of 2,116 BCs, 91 ePVI-BCs, 70 inflammatory breast carcinomas (IBCs), and 114 casual BCs as a control group (CG-BC) were recruited. RESULTS: Patients affected by ePVI-BC were younger, had larger tumors, higher histologic grade, elevated Ki-67 score, Her2/neu overexpressed, and more lymph node metastases compared with CG-BC (P < .001). Interestingly, only younger mean age at diagnosis differentiated patients with ePVI-BC from patients affected by IBC. ePVI-BC showed a clinical outcome intermediate between the prognoses of IBC and CG-BC. CONCLUSIONS: Results suggest that ePVI-BC and IBC may share some pathologic processes, providing a novel perspective on the heterogeneity of BC. Epidemiologic data and molecular studies on gene expression features are needed to rationally classify these tumors into their identified subtypes.

Ensemble of gene signatures identifies novel biomarkers in colorectal cancer activated through PPARγ and TNFα signaling.

We describe a novel bioinformatic and translational pathology approach, gene Signature Finder Algorithm (gSFA) to identify biomarkers associated with Colorectal Cancer (CRC) survival. Here a robust set of CRC markers is selected by an ensemble method. By using a dataset of 232 gene expression profiles, gSFA discovers 16 highly significant small gene signatures. Analysis of dichotomies generated by the signatures results in a set of 133 samples stably classified in good prognosis group and 56 samples in poor prognosis group, whereas 43 remain unreliably classified. AKAP12, DCBLD2, NT5E and SPON1 are particularly represented in the signatures and selected for validation in vivo on two independent patients cohorts comprising 140 tumor tissues and 60 matched normal tissues. Their expression and regulatory programs are investigated in vitro. We show that the coupled expression of NT5E and DCBLD2 robustly stratifies our patients in two groups (one of which with 100% survival at five years). We show that NT5E is a target of the TNF-α signaling in vitro; the tumor suppressor PPARγ acts as a novel NT5E antagonist that positively and concomitantly regulates DCBLD2 in a cancer cell context-dependent manner.

Finding recurrent copy number alterations preserving within-sample homogeneity.

MOTIVATION: Copy number alterations (CNAs) represent an important component of genetic variation and play a significant role in many human diseases. Development of array comparative genomic hybridization (aCGH) technology has made it possible to identify CNAs. Identification of recurrent CNAs represents the first fundamental step to provide a list of genomic regions which form the basis for further biological investigations. The main problem in recurrent CNAs discovery is related to the need to distinguish between functional changes and random events without pathological relevance. Within-sample homogeneity represents a common feature of copy number profile in cancer, so it can be used as additional source of information to increase the accuracy of the results. Although several algorithms aimed at the identification of recurrent CNAs have been proposed, no attempt of a comprehensive comparison of different approaches has yet been published. RESULTS: We propose a new approach, called Genomic Analysis of Important Alterations (GAIA), to find recurrent CNAs where a statistical hypothesis framework is extended to take into account within-sample homogeneity. Statistical significance and within-sample homogeneity are combined into an iterative procedure to extract the regions that likely are involved in functional changes. Results show that GAIA represents a valid alternative to other proposed approaches. In addition, we perform an accurate comparison by using two real aCGH datasets and a carefully planned simulation study. AVAILABILITY: GAIA has been implemented as R/Bioconductor package. It can be downloaded from the following page http://bioinformatics.biogem.it/download/gaia. CONTACT: ceccarelli@unisannio.it; morganella@unisannio.it. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.