tbuckley/cabot-search huggingface dataset:
Extensively Parameterized Mutation–Selection Models Reliably Capture Site-Specific Selective Constraint
Authors: Stephanie J. Spielman, Claus O. Wilke
Journal: Molecular Biology and Evolution (2016)

The mutation–selection model of coding sequence evolution has received renewed attention for its use in estimating site-specific amino acid propensities and selection coefficient distributions. Two computationally tractable mutation–selection inference frameworks have been introduced: One framework employs a fixed-effects, highly parameterized maximum likelihood approach, whereas the other employs a random-effects Bayesian Dirichlet Process approach. While both implementations follow the same model, they appear to make distinct predictions about the distribution of selection coefficients. The fixed-effects framework estimates a large proportion of highly deleterious substitutions, whereas the random-effects framework estimates that all substitutions are either nearly neutral or weakly deleterious. It remains unknown, however, how accurately each method infers evolutionary constraints at individual sites. Indeed, selection coefficient distributions pool all site-specific inferences, thereby obscuring a precise assessment of site-specific estimates. Therefore, in this study, we use a simulation-based strategy to determine how accurately each approach recapitulates the selective constraint at individual sites. We find that the fixed-effects approach, despite its extensive parameterization, consistently and accurately estimates site-specific evolutionary constraint. By contrast, the random-effects Bayesian approach systematically underestimates the strength of natural selection, particularly for slowly evolving sites. We also find that, despite the strong differences between their inferred selection coefficient distributions, the fixed- and random-effects approaches yield surprisingly similar inferences of site-specific selective constraint. We conclude that the fixed-effects mutation–selection framework provides the more reliable software platform for model application and future development.
Abstract 3366: NCL targeting impairs the progression of pancreatic ductal adenocarcinoma and promotes tumor vessel normalization through Ang-2 inhibition
Authors: Maud-Emmanuelle Gilles, Federica Maione, Mélissande Cossutta, Gilles Carpentier, Laure Caruana, Silvia Di Maria, Damien Destouches, Ksenya Shchors, Christopher Prochasson, Anne Couvelard, José Courty, Enrico Giraudo, Ilaria Cascone
Journal: Cancer Research (2016)

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive tumor, mostly resistant to the standard treatments. NCL is overexpressed in cancers and its inhibition impairs tumor growth. Herein we described, that NCL was overexpressed in human specimens of PDAC, and low NCL staining patients had increased overall survival. Previously, we described a family of multivalent pseudopeptides binding to NCL and inhibiting tumour growth. Here, NCL antagonist N6L, strongly impaired tumor growth, liver metastasis formation and angiogenesis in an orthothopic mouse model of PDAC. N6L inhibited both human and mouse tumor cell proliferation and invasion. Proteome analysis of endothelial cell secreted proteins showed that NCL inhibition decreased Ang-2 levels and switched a pro-angiogenic signature. Importantly, Ang-2 levels were decreased in plasma of N6L-treated PDAC mice. The analysis of tumor vasculature revealed a strong increase of pericyte coverage and vessel perfusion in parallel to an inhibition of tumor hypoxia. As consequence of N6L-induced tumor vessel normalization, pre-treatment with N6L efficiently improved chemotherapeutic drug delivery and increased the anti-tumor properties of gemcitabine in PDAC mice. In conclusion, NCL inhibition is a new anti-tumor therapeutic strategy that dually blocks tumor progression and normalizes tumor vessels improving the delivery and efficacy of chemotherapeutic drugs in PDAC cancers. Moreover, we identified Ang-2 as a potential target and suitable response biomarker for N6L treatment in PDAC. Citation Format: Maud-Emmanuelle Gilles, Federica Maione, Mélissande Cossutta, Gilles Carpentier, Laure Caruana, Silvia Di Maria, Damien Destouches, Ksenya Shchors, Christopher Prochasson, Anne Couvelard, José Courty, Enrico Giraudo, Ilaria Cascone. NCL targeting impairs the progression of pancreatic ductal adenocarcinoma and promotes tumor vessel normalization through Ang-2 inhibition. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3366.
Report from the fifth international consensus meeting to harmonize core outcome measures for atopic eczema/dermatitis clinical trials (HOME initiative)
Authors: J.R. Chalmers, K.S. Thomas, C. Apfelbacher, H.C. Williams, C.A. Prinsen, P.I. Spuls, E. Simpson, L.A.A. Gerbens, M. Boers, S. Barbarot, J.F. Stalder, K. Abuabara, V. Aoki, M. Ardeleanu, J. Armstrong, B. Bang, T.L. Berents, T. Burton, L. Butler, T. Chubachi, A. Cresswell-Melville, A. DeLozier, L. Eckert, L. Eichenfield, C. Flohr, M. Futamura, A. Gadkari, E.S. Gjerde, K.F. van Halewijn, C. Hawkes, L. Howells, L. Howie, R. Humphreys, H.A. Ishii, Y. Kataoka, I. Katayama, W. Kouwenhoven, S.M. Langan, Y.A. Leshem, S. Merhand, P. Mina-Osorio, H. Murota, T. Nakahara, F.P. Nunes, U. Nygaard, M. Nygårdas, Y. Ohya, E. Ono, E. Rehbinder, N.K. Rogers, G.L.E. Romeijn, M.L.A. Schuttelaar, A.V. Sears, M.A. Simpson, J.A. Singh, J. Srour, B. Stuart, Å. Svensson, G. Talmo, H. Talmo, H.D. Teixeira, J.P. Thyssen, G. Todd, F. Torchet, A. Volke, L. von Kobyletzki, E. Weisshaar, A. Wollenberg, M. Zaniboni
Journal: British Journal of Dermatology (2018)

This is the report from the fifth meeting of the Harmonising Outcome Measures for Eczema initiative (HOME V). The meeting was held on 12–14 June 2017 in Nantes, France, with 81 participants. The main aims of the meeting were (i) to achieve consensus over the definition of the core domain of long‐term control and how to measure it and (ii) to prioritize future areas of research for the measurement of the core domain of quality of life (QoL) in children. Moderated whole‐group and small‐group consensus discussions were informed by presentations of qualitative studies, systematic reviews and validation studies. Small‐group allocations were performed a priori to ensure that each group included different stakeholders from a variety of geographical regions. Anonymous whole‐group voting was carried out using handheld electronic voting pads according to predefined consensus rules. It was agreed by consensus that the long‐term control domain should include signs, symptoms, quality of life and a patient global instrument. The group agreed that itch intensity should be measured when assessing long‐term control of eczema in addition to the frequency of itch captured by the symptoms domain. There was no recommendation of an instrument for the core outcome domain of quality of life in children, but existing instruments were assessed for face validity and feasibility, and future work that will facilitate the recommendation of an instrument was agreed upon.
Human equilibrative nucleoside transporter 1 as a predictor of efficacy to gemcitabine in angiosarcoma and leiomyosarcoma.
Authors: Bruno Vincenzi, Silvia Stacchiotti, Paola Collini, Francesco Pantano, Giuseppe Perrone, Michele Iuliani, Alfonso Baldi, Giuseppe Badalamenti, Roberta Sanfilippo, Daniele Santini, Andrea Onetti-Muda, Alessandro Gronchi, Paolo Giovanni Casali, Angelo Paolo Dei Tos, Giuseppe Tonini
Journal: Journal of Clinical Oncology (2016)

11062 Background: Human equilibrative nucleoside transporter 1 (hENT1) is the major gemcitabine transporter into cells. Gemcitabine is an active drug in different sarcoma subtypes including leiomyosarcoma and angiosarcoma. The aim of the study was to retrospectively determine the expression levels of hENT1 in samples derived from leiomyosarcoma and angiosarcoma patients and, for those treated with gemcitabine, to define the correlation between hENT1expression and gemcitabine efficacy in terms of Time to Progression (TTP) and Overall Survival (OS). Methods: We retrospectively included 71 metastatic or locally advanced patients (pts) affected by angiosarcoma (26 pts) and leiomyosarcoma (45 pts) identified from Italian reference centers for treatment of sarcoma. Among the 71 patients, 44 pts (15 angiosarcoma and 34 leiomyosarcoma) received gemcitabine as first line chemotherapy (1000 mg/m i.v. every week for 3 weeks every 4 weeks), while 27 were not treated.For all patients, formalin-fixed paraffin-embedded surgical specimens, obtained from naïve tumor, were collected. hENT1 expression was analyzed by Real Time PCR. Kaplan Meier analysis was performed to correlate hENT1 expression and clinical outcome in gemcitabine treated patients. Results: hENT1 expression was detected in leiomyosarcoma and angiosarcoma samples (median 2-DCt : 9.3 and 1.25 respectively). Leiomyosarcoma and angiosarcoma patients were dichotomized into “high” expression and “low” expression groups according to the median value. We found a significant correlation between high hENT1 expression levels and favourable outcome in terms of TTP (6.8 vs 3.2 months; P = 0.004) and OS (14.9 vs 8.5 months; P = 0.007) in leiomyosarcoma patients treated with gemcitabine. Similarly, angiosarcoma patients that exhibited high hENT1 expression showed a longer TTP (9.3 vs 4.5 months; P = 0.02) and an improvement in OS (20.6 vs 10.8 months; P = 0.001). Conclusions: These findings suggest that hENT1 overexpression may predict favorable outcome and response to gemcitabine both in leiomyosarcoma and angiosarcoma patients and, if confirmed in a larger prospective series, could be used as a molecular biomarker for gemcitabine efficacy.
Relative Contributions of Agricultural Drift, Para-Occupational, and Residential Use Exposure Pathways to House Dust Pesticide Concentrations: Meta-Regression of Published Data
Authors: Nicole C. Deziel, Laura E. Beane Freeman, Barry I. Graubard, Rena R. Jones, Jane A. Hoppin, Kent Thomas, Cynthia J. Hines, Aaron Blair, Dale P. Sandler, Honglei Chen, Jay H. Lubin, Gabriella Andreotti, Michael C. R. Alavanja, Melissa C. Friesen
Journal: Environmental Health Perspectives (2016)

Increased pesticide concentrations in house dust in agricultural areas have been attributed to several exposure pathways, including agricultural drift, para-occupational, and residential use.To guide future exposure assessment efforts, we quantified relative contributions of these pathways using meta-regression models of published data on dust pesticide concentrations.From studies in North American agricultural areas published from 1995 to 2015, we abstracted dust pesticide concentrations reported as summary statistics [e.g., geometric means (GM)]. We analyzed these data using mixed-effects meta-regression models that weighted each summary statistic by its inverse variance. Dependent variables were either the log-transformed GM (drift) or the log-transformed ratio of GMs from two groups (para-occupational, residential use).For the drift pathway, predicted GMs decreased sharply and nonlinearly, with GMs 64% lower in homes 250 m versus 23 m from fields (interquartile range of published data) based on 52 statistics from seven studies. For the para-occupational pathway, GMs were 2.3 times higher [95% confidence interval (CI): 1.5, 3.3; 15 statistics, five studies] in homes of farmers who applied pesticides more recently or frequently versus less recently or frequently. For the residential use pathway, GMs were 1.3 (95% CI: 1.1, 1.4) and 1.5 (95% CI: 1.2, 1.9) times higher in treated versus untreated homes, when the probability that a pesticide was used for the pest treatment was 1-19% and ≥ 20%, respectively (88 statistics, five studies).Our quantification of the relative contributions of pesticide exposure pathways in agricultural populations could improve exposure assessments in epidemiologic studies. The meta-regression models can be updated when additional data become available. Citation: Deziel NC, Beane Freeman LE, Graubard BI, Jones RR, Hoppin JA, Thomas K, Hines CJ, Blair A, Sandler DP, Chen H, Lubin JH, Andreotti G, Alavanja MC, Friesen MC. 2017. Relative contributions of agricultural drift, para-occupational, and residential use exposure pathways to house dust pesticide concentrations: meta-regression of published data. Environ Health Perspect 125:296-305; http://dx.doi.org/10.1289/EHP426.
Ultrasound Mediated Drug-Loaded Nanoparticles Crossing Cell Membranes as a New Strategy to Reverse Multidrug Resistance In Human Leukemia Cell Line K562/A02
Authors: Bao-An Chen, Hai-jun Zhang, Xue-mei Wang, Hui Jiang, Chong Gao, Feng Gao, Jia-hua Ding, Jian Cheng, Yun-yu Sun, Jun Wang, Hui-hui Song, Wen Bao
Journal: Blood (2010)
Surveillance du paludisme dans les pays de l’Union Européenne
Authors: F Legros, M Danis
Journal: Eurosurveillance (1998)

Le paludisme est l’affection parasitaire la plus importante dans le monde (1,2). Il est endemique dans 91 pays ou 300 a 500 millions de cas cliniques sont estimes chaque annee. Le paludisme est essentiellement intertropical dans sa forme grave. Il se place au septieme rang des causes de deces, avec environ 2 millions de morts annuels, et son controle demeure un probleme prioritaire de sante publique.
Abstract 2373: Assessing intra-tumor heterogeneity and tracking longitudinal and spatial clonal evolution by next-generation sequencing
Authors: Yuchao Jiang, Yu Qiu, Andy J. Minn, Nancy R. Zhang
Journal: Cancer Research (2016)

Abstract Cancer is a disease driven by genetic and epigenetic alterations that follows Darwinian evolution. Recently, there have been increasing efforts to sequence the tumor from the same patient at multiple time points and/or from multiple spatially separated resections. Different snapshots of the same tumor have proved invaluable for identifying subclonal populations and inferring the tumor's history. We propose a method, Canopy, for estimating the clonal history and for longitudinal and spatial comparison of mutation profiles from one or more samples derived from a single patient. Canopy accounts for normal cell contamination and reconstructs subclonal phylogeny utilizing both somatic copy number alterations (CNAs) and somatic single nucleotide alterations (SNAs). Canopy provides a general mathematical framework that enumerates all possible CNA-SNA phases and temporal orderings. Taking as input the mutant and reference allele frequencies for SNAs, and depth of coverage for CNAs, Canopy gives confidence assessments of all possible configurations of the cancer's clonal evolution. Canopy is applied to three cancer sequencing datasets of varying study design, as well as to an extensive simulation study. On a whole-exome study of a transplantable metastasis model derived from human breast cancer cell line MDA-MB-231, Canopy successfully deconvolutes the mixed cell sublines, using the single cell sublines as ground truth, and identifies DNA signatures that can be prognostic of distant metastasis. On a whole-genome sequencing dataset of the primary tumor and relapse genome of a leukemia patient, Canopy predicts phylogenetic histories in concordance with existing knowledge. On a whole-genome sequencing dataset of the breast cancer tumor and its subsequent metastatic xenograft, Canopy's inferred clonal phylogeny is concordant with genomic markers of major clonal genotype and is confirmed by single-cell sequencing. Finally, through simulations, we explore the effects of various parameters on deconvolution accuracy, and evaluate performance with comparison against existing methods. Collectively, Canopy provides a rigorous foundation for statistical inference on repeated sequencing experiments from evolving populations delineated temporally and spatially. Citation Format: Yuchao Jiang, Yu Qiu, Andy J. Minn, Nancy R. Zhang. Assessing intra-tumor heterogeneity and tracking longitudinal and spatial clonal evolution by next-generation sequencing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2373.
Abstract 3982: Prediction and selection of cancer drug treatments using personalized tumor models or models with matching genomic profiles
Authors: Jingjing Jiang, Ying Yan, Zhongguang Luo, Jia He, Tengfei Yu, Wei Du, Xuqin Yang, Jiali Gu, Xin K. Ye, Guanglei Zhuang, Jie Liu, Zhenyu Gu
Journal: Cancer Research (2016)

Abstract The main purpose of precision medicine is to find the right drug for the right patient at the right time. Current progress in cancer drug target identification and development of new targeted drugs has presented many successful examples. However, for majority of patients, finding treatments based on the unique mutations in their own tumor cells are still hard. New approaches for precision medicine are in great needs and thus being investigated. A mouse “avatar”, also known as Patient-Derived Xenograft (PDX) model, is a personalized cancer model derived from a patient tumor sample and used to test different drugs for the patient. “GIFTS” (or Genomic Information Fitting based Therapeutics Selection) is a method with which a patient's cancer genomic information is compared to PDX model genomic profiles to find the best genomic fit and related therapeutic options in GenenDesign Drug Response Database and Genomic Information database. So far we have successfully derived more than 1000 PDX models from patient tumor tissues of various cancer types including lung, gastric, liver, esophageal, colorectal, pancreatic and many other cancers. In some cases, both patients and their avatars were tested with same cancer drugs including targeted drugs and chemotherapies. By comparing drug responses in mouse avatars with patient clinical results, we found high correlations between them in both sensitivity and unresponsiveness. We have also developed a bioinformatics algorithm to analyze PDX model genomic and drug response information. Both drug sensitivity and resistance biomarkers have been used in matching cancer patient genomic profiles to those of PDX models in GenenDesign database as a part of our GIFTS method. Our preliminary results show that there are high degree of similarities in drug response profiles between patients and their matched PDX models. Avatar and GIFTS methods can provide predictions of therapeutic effectiveness on both targeted drugs and chemotherapies. Avatar is a drug screening based method, while GIFTS is a genomic profile matching based method. Both methods are especially useful for patients, whose tumors could not be treated with known targeted drugs. Citation Format: Jingjing Jiang, Ying Yan, Zhongguang Luo, Jia He, Tengfei Yu, Wei Du, Xuqin Yang, Jiali Gu, Xin K. Ye, Guanglei Zhuang, Jie Liu, Zhenyu Gu. Prediction and selection of cancer drug treatments using personalized tumor models or models with matching genomic profiles. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3982.
Persistent barriers to active surveillance adoption.
Authors: Shellie D. Ellis, Emily Jones, Kim Kimminau, Laurie Petty, J. Brantley Thrasher
Journal: Journal of Clinical Oncology (2016)

e16618 Background: Management of low-risk prostate cancer with active surveillance (AS) has increased, but AS is still underused. We sought to identify whether urologists' perceptions of barriers vary by setting and how barriers contribute to limited AS adoption. Methods: We conducted semi-structured interviews with US urologists at the 2015 AUA annual meeting and by phone. Interviews were audio recorded, transcribed and coded to identify barriers by type of potential intervention. We ranked barriers by frequency mentioned and assessed difference in response by practice setting (academic vs. community). Results: Twenty-two urologists from 11 states participated from 11 community and 11 academic settings (16 in-person, 6 by phone). Participants stated enthusiasm for AS as a management strategy for appropriate patients. Urologists reported barriers to both patient acceptance and their own reluctance to offer AS. The most frequently perceived patient acceptance barriers included misperceptions of the severity of cancer diagnoses, discomfort with biopsies, and patient and family preference for curative therapy. The most frequently cited concerns about offering AS included fear of missing aggressive cancer due to biopsy sampling, lack of evidence-based AS follow-up protocol, discomfort recommending AS to young men, perceived patient anxiety, and concerns about some patients' ability to adhere to AS. Only community urologists mentioned fear of litigation as a barrier, but litigation facilitated the offer of AS for some. Academic urologists assumed financial incentives would be a barrier for community physicians. Community physicians indicated high patient volume insulated them from financial pressures and described few AS-eligible men and less patient acceptance compared to academic physicians. Conclusions: Physician-focused interventions to promote the offer of AS could target improving understanding of the relationship between sampling and risk of missing aggressive disease, providing evidence-based AS protocols, explicit recommendations for young men, and objectively measuring patients' anxiety and ability to adhere to an AS protocol. Using standardized language to structure the offer of AS may reduce barriers to patients' acceptance of AS.