Analysis of T cell receptor clonotypes in tumor microenvironment identifies shared cancer-type-specific signatures.

Despite the conventional view that a truly random V(D)J recombination process should generate a highly diverse immune repertoire, emerging reports suggest that there is a certain bias toward the generation of shared/public immune receptor chains. These studies were performed in viral diseases where public T cell receptors (TCR) appear to confer better protective responses. Selective pressures generating common TCR clonotypes are currently not well understood, but it is believed that they confer a growth advantage. As very little is known about public TCR clonotypes in cancer, here we set out to determine the extent of shared TCR clonotypes in the intra-tumor microenvironments of virus- and non-virus-driven head and neck cancers using TCR sequencing. We report that tumor-infiltrating T cell clonotypes were indeed shared across individuals with the same cancer type, where the majority of shared sequences were specific to the cancer type (i.e., viral versus non-viral). These shared clonotypes were not particularly enriched in EBV-associated nasopharynx cancer but, in both cancers, exhibited distinct characteristics, namely shorter CDR3 lengths, restricted V- and J-gene usages, and also demonstrated convergent V(D)J recombination. Many of these shared TCRs were expressed in patients with a shared HLA background. Pattern recognition of CDR3 amino acid sequences revealed strong convergence to specific pattern motifs, and these motifs were uniquely found to each cancer type. This suggests that they may be enriched for specificity to common antigens found in the tumor microenvironment of different cancers. The identification of shared TCRs in infiltrating tumor T cells not only adds to our understanding of the tumor-adaptive immune recognition but could also serve as disease-specific biomarkers and guide the development of future immunotherapies

Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

Uterine papillary serous and clear cell carcinomas predict for poorer survival compared to grade 3 endometrioid corpus cancers

To compare the survival of women with uterine papillary serous carcinoma (UPSC) and clear cell carcinoma (CC) to those with grade 3 endometrioid uterine carcinoma (G3EC). Demographic, pathologic, treatment, and survival information were obtained from the Surveillance, Epidemiology, and End Results Program from 1988 to 2001. Data were analysed using Kaplan–Meier and Cox proportional hazards regression methods. Of 4180 women, 1473 had UPSC, 391 had CC, and 2316 had G3EC cancers. Uterine papillary serous carcinoma and CC patients were older (median age: 70 years and 68 vs 66 years, respectively; P<0.0001) and more likely to be black compared to G3EC (15 and 12% vs 7%; P<0.0001). A higher proportion of UPSC and CC patients had stage III–IV disease compared to G3EC patients (52 and 36% vs 29%; P<0.0001). Uterine papillary serous carcinoma, CC and G3EC patients represent 10, 3, and 15% of endometrial cancers but account for 39, 8, and 27% of cancer deaths, respectively. The 5-year disease-specific survivals for women with UPSC, CC and G3EC were 55, 68, and 77%, respectively (P<0.0001). The survival differences between UPSC, CC and G3EC persist after controlling for stage I–II (74, 82, and 86%; P<0.0001) and stage III–IV disease (33, 40, and 54; P<0.0001). On multivariate analysis, more favourable histology (G3EC), younger age, and earlier stage were independent predictors of improved survival. Women with UPSC and CC of the uterus have a significantly poorer prognosis compared to those with G3EC. These findings should be considered in the counselling, treating and designing of future trials for these high-risk patients

Prevalence of JC Virus in Chinese Patients with Colorectal Cancer

BACKGROUND: JCV is a DNA polyomavirus very well adapted to humans. Although JCV DNA has been detected in colorectal cancers (CRC), the association between JCV and CRC remains controversial. In China, the presence of JCV infection in CRC patients has not been reported. Here, we investigated JCV infection and viral DNA load in Chinese CRC patients and to determine whether the JCV DNA in peripheral blood (PB) can be used as a diagnostic marker for JCV-related CRC. METHODOLOGY/PRINCIPAL FINDINGS: Tumor tissues, non-cancerous tumor-adjacent tissues and PB samples were collected from 137 CRC patients. In addition, 80 normal colorectal tissue samples from patients without CRC and PB samples from 100 healthy volunteers were also harvested as controls. JCV DNA was detected by nested PCR and glass slide-based dot blotting. Viral DNA load of positive samples were determined by quantitative real-time PCR. JCV DNA was detected in 40.9% (56/137) of CRC tissues at a viral load of 49.1 to 10.3×10(4) copies/µg DNA. Thirty-four (24.5%) non-cancerous colorectal tissues (192.9 to 4.4×10(3) copies/µg DNA) and 25 (18.2%) PB samples (81.3 to 4.9×10(3) copies/µg DNA) from CRC patients were positive for JCV. Tumor tissues had higher levels of JCV than non-cancerous tissues (P = 0.003) or PB samples (P<0.001). No correlation between the presence of JCV and demographic or medical characteristics was observed. The JCV prevalence in PB samples was significantly associated with the JCV status in tissue samples (P<0.001). Eleven (13.8%) normal colorectal tissues and seven (7.0%) PB samples from healthy donors were positive for JCV. CONCLUSIONS/SIGNIFICANCE: JCV infection is frequently present in colorectal tumor tissues of CRC patients. Although the association between JCV presence in PB samples and JCV status in tissue samples was identified in this study, whether PB JCV detection can serve as a marker for JCV status of CRC requires further study

An integrated 1D–2D hydraulic modelling approach to assess the sensitivity of a coastal region to compound flooding hazard under climate change

Coastal regions are dynamic areas that often lie at the junction of different natural hazards. Extreme events such as storm surges and high precipitation are significant sources of concern for flood management. As climatic changes and sea-level rise put further pressure on these vulnerable systems, there is a need for a better understanding of the implications of compounding hazards. Recent computational advances in hydraulic modelling offer new opportunities to support decision-making and adaptation. Our research makes use of recently released features in the HEC-RAS version 5.0 software to develop an integrated 1D–2D hydrodynamic model. Using extreme value analysis with the Peaks-Over-Threshold method to define extreme scenarios, the model was applied to the eastern coast of the UK. The sensitivity of the protected wetland known as the Broads to a combination of fluvial, tidal and coastal sources of flooding was assessed, accounting for different rates of twenty-first century sea-level rise up to the year 2100. The 1D–2D approach led to a more detailed representation of inundation in coastal urban areas, while allowing for interactions with more fluvially dominated inland areas to be captured. While flooding was primarily driven by increased sea levels, combined events exacerbated flooded area by 5–40% and average depth by 10–32%, affecting different locations depending on the scenario. The results emphasise the importance of catchment-scale strategies that account for potentially interacting sources of flooding

Studying the Underlying Event in Drell-Yan and High Transverse Momentum Jet Production at the Tevatron

We study the underlying event in proton-antiproton collisions by examining the behavior of charged particles (transverse momentum pT > 0.5 GeV/c, pseudorapidity |\eta| < 1) produced in association with large transverse momentum jets (~2.2 fb-1) or with Drell-Yan lepton-pairs (~2.7 fb-1) in the Z-boson mass region (70 < M(pair) < 110 GeV/c2) as measured by CDF at 1.96 TeV center-of-mass energy. We use the direction of the lepton-pair (in Drell-Yan production) or the leading jet (in high-pT jet production) in each event to define three regions of \eta-\phi space; toward, away, and transverse, where \phi is the azimuthal scattering angle. For Drell-Yan production (excluding the leptons) both the toward and transverse regions are very sensitive to the underlying event. In high-pT jet production the transverse region is very sensitive to the underlying event and is separated into a MAX and MIN transverse region, which helps separate the hard component (initial and final-state radiation) from the beam-beam remnant and multiple parton interaction components of the scattering. The data are corrected to the particle level to remove detector effects and are then compared with several QCD Monte-Carlo models. The goal of this analysis is to provide data that can be used to test and improve the QCD Monte-Carlo models of the underlying event that are used to simulate hadron-hadron collisions.Comment: Submitted to Phys.Rev.

Precision measurement of the top quark mass from dilepton events at CDF II

We report a measurement of the top quark mass, M_t, in the dilepton decay channel of $t\bar{t}\to b\ell'^{+}\nu_{\ell'}\bar{b}\ell^{-}\bar{\nu}_{\ell}$ using an integrated luminosity of 1.0 fb^{-1} of p\bar{p} collisions collected with the CDF II detector. We apply a method that convolutes a leading-order matrix element with detector resolution functions to form event-by-event likelihoods; we have enhanced the leading-order description to describe the effects of initial-state radiation. The joint likelihood is the product of the likelihoods from 78 candidate events in this sample, which yields a measurement of M_{t} = 164.5 \pm 3.9(\textrm{stat.}) \pm 3.9(\textrm{syst.}) \mathrm{GeV}/c^2, the most precise measurement of M_t in the dilepton channel.Comment: 7 pages, 2 figures, version includes changes made prior to publication by journa

Measurement of the Ratios of Branching Fractions B(Bs -> Ds pi pi pi) / B(Bd -> Dd pi pi pi) and B(Bs -> Ds pi) / B(Bd -> Dd pi)

Using 355 pb^-1 of data collected by the CDF II detector in \ppbar collisions at sqrt{s} = 1.96 TeV at the Fermilab Tevatron, we study the fully reconstructed hadronic decays B -> D pi and B -> D pi pi pi. We present the first measurement of the ratio of branching fractions B(Bs -> Ds pi pi pi) / B(Bd -> Dd pi pi pi) = 1.05 pm 0.10 (stat) pm 0.22 (syst). We also update our measurement of B(Bs -> Ds pi) / B(Bd -> Dd pi) to 1.13 pm 0.08 (stat) pm 0.23 (syst) improving the statistical uncertainty by more than a factor of two. We find B(Bs -> Ds pi) = [3.8 pm 0.3 (stat) pm 1.3 (syst)] \times 10^{-3} and B(Bs -> Ds pi pi pi) = [8.4 pm 0.8 (stat) pm 3.2 (syst)] \times 10^{-3}.Comment: 7 pages, 2 figure