Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Measurement of the cross section for inclusive isolated-photon production in pp collisions at √s=13TeV using the ATLAS detector

Inclusive isolated-photon production in pp collisions at a centre-of-mass energy of 13TeVis studied with the ATLAS detector at the LHC using a data set with an integrated luminosity of 3.2fb−1. The cross section is measured as a function of the photon transverse energy above 125GeVin different regions of photon pseudorapidity. Next-to-leading-order perturbative QCD and Monte Carlo event-generator predictions are compared to the cross-section measurements and provide an adequate description of the data

Measurement of the inclusive cross-section for the production of jets in association with a Z boson in proton-proton collisions at 8 TeV using the ATLAS detector

The inclusive cross-section for jet production in association with a Z boson decaying into an electron–positron pair is measured as a function of the transverse momentum and the absolute rapidity of jets using 19.9 fb −1 of s√=8 TeV proton–proton collision data collected with the ATLAS detector at the Large Hadron Collider. The measured Z + jets cross-section is unfolded to the particle level. The cross-section is compared with state-of-the-art Standard Model calculations, including the next-to-leading-order and next-to-next-to-leading-order perturbative QCD calculations, corrected for non-perturbative and QED radiation effects. The results of the measurements cover final-state jets with transverse momenta up to 1 TeV, and show good agreement with fixed-order calculations

Measurements of differential cross-sections in top-quark pair events with a high transverse momentum top quark and limits on beyond the Standard Model contributions to top-quark pair production with the ATLAS detector at √s = 13 TeV

Cross-section measurements of top-quark pair production where the hadronically decaying top quark has transverse momentum greater than 355 GeV and the other top quark decays into ℓνb are presented using 139 fb−1 of data collected by the ATLAS experiment during proton-proton collisions at the LHC. The fiducial cross-section at s = 13 TeV is measured to be σ = 1.267 ± 0.005 ± 0.053 pb, where the uncertainties reflect the limited number of data events and the systematic uncertainties, giving a total uncertainty of 4.2%. The cross-section is measured differentially as a function of variables characterising the tt¯ system and additional radiation in the events. The results are compared with various Monte Carlo generators, including comparisons where the generators are reweighted to match a parton-level calculation at next-to-next-to-leading order. The reweighting improves the agreement between data and theory. The measured distribution of the top-quark transverse momentum is used to search for new physics in the context of the effective field theory framework. No significant deviation from the Standard Model is observed and limits are set on the Wilson coefficients of the dimension-six operators OtG and Otq(8), where the limits on the latter are the most stringent to date. [Figure not available: see fulltext.]

Measurement of the transverse momentum and ϕ∗ηϕη∗ distributions of Drell–Yan lepton pairs in proton–proton collisions at s√=8s=8 TeV with the ATLAS detector

Distributions of transverse momentum p T and the related angular variable φ∗ η of Drell–Yan lepton pairs are measured in 20.3 fb−1 of proton–proton collisions at √s = 8 TeV with the ATLAS detector at the LHC. Measurements in electron-pair and muon-pair final states are corrected for detector effects and combined. Compared to previous measurements in proton–proton collisions at √s = 7 TeV, these new measurements benefit from a larger data sample and improved control of systematic uncertainties. Measurements are performed in bins of lepton-pair mass above, around and below the Z-boson mass peak. The data are compared to predictions from perturbative and resummed QCD calculations. For values of φ∗ η < 1 the predictions from the Monte Carlo generator ResBos are generally consistent with the data within the theoretical uncertainties. However, at larger values of φ∗ η this is not the case. Monte Carlo generators based on the parton-shower approach are unable to describe the data over the full range of p T while the fixed-order prediction of Dynnlo falls below the data at high values of p T . ResBos and the parton-shower Monte Carlo generators provide a much better description of the evolution of the φ∗ η and p T distributions as a function of lepton-pair mass and rapidity than the basic shape of the data. Conte

Context-dependent control of alternative splicing by RNA-binding proteins

Sequence-specific RNA-binding proteins (RBPs) bind to pre-mRNA to control alternative splicing, but it is not yet possible to read the ‘splicing code’ that dictates splicing regulation on the basis of genome sequence. Each alternative splicing event is controlled by multiple RBPs, the combined action of which creates a distribution of alternatively spliced products in a given cell type. As each cell type expresses a distinct array of RBPs, the interpretation of regulatory information on a given RNA target is exceedingly dependent on the cell type. RBPs also control each other’s functions at many levels, including by mutual modulation of their binding activities on specific regulatory RNA elements. In this Review, we describe some of the emerging rules that govern the highly context-dependent and combinatorial nature of alternative splicing regulation

Genitourinary Pathology (Including Adrenal Gland)

Our aims in constructing the Genitourinary Pathology chapter are to describe neoplasms of the adrenal gland, urothelial tract, kidney, penis, prostate, and testis in a manner that is both useful for the practicing surgical pathologist and that may be used as a reference for all students of urologic pathology. Whereas the text and figures describe the salient morphologic, immunohistochemical, and molecular attributes for each tumor type and encompass the latest classification schemes, the narrative integrates the clinical and pathological findings that are commonly encountered during surgical pathology sign-out of these cases. Accordingly, it is our hope that this chapter will serve as a guide for both general and subspecialized pathologists in contemporary practice