HER2 Testing and Clinical Decision Making in Gastroesophageal Adenocarcinoma

CONTEXT: ERBB2 (erb-b2 receptor tyrosine kinase 2 or HER2) is currently the only biomarker established for selection of a specific therapy for patients with advanced gastroesophageal adenocarcinoma (GEA). However, there are no comprehensive guidelines for the assessment of HER2 in patients with GEA. OBJECTIVES: To establish an evidence-based guideline for HER2 testing in patients with GEA, to formalize the algorithms for methods to improve the accuracy of HER2 testing while addressing which patients and tumor specimens are appropriate, and to provide guidance on clinical decision making. DESIGN: The College of American Pathologists, American Society for Clinical Pathology, and American Society of Clinical Oncology convened an expert panel to conduct a systematic review of the literature to develop an evidence-based guideline with recommendations for optimal HER2 testing in patients with GEA. RESULTS: The panel is proposing 11 recommendations with strong agreement from the open-comment participants. RECOMMENDATIONS: The panel recommends that tumor specimen(s) from all patients with advanced GEA, who are candidates for HER2-targeted therapy, should be assessed for HER2 status before the initiation of HER2-targeted therapy. Clinicians should offer combination chemotherapy and a HER2-targeted agent as initial therapy for all patients with HER2-positive advanced GEA. For pathologists, guidance is provided for morphologic selection of neoplastic tissue, testing algorithms, scoring methods, interpretation and reporting of results, and laboratory quality assurance. CONCLUSIONS: This guideline provides specific recommendations for assessment of HER2 in patients with advanced GEA while addressing pertinent technical issues and clinical implications of the results

HER2 Testing and Clinical Decision Making in Gastroesophageal Adenocarcinoma: Guideline From the College of American Pathologists, American Society for Clinical Pathology, and American Society of Clinical Oncology

-ERBB2 (erb-b2 receptor tyrosine kinase 2 or HER2) is currently the only biomarker established for selection of a specific therapy for patients with advanced gastroesophageal adenocarcinoma (GEA). However, there are no comprehensive guidelines for the as

Molecular Biomarkers for the Evaluation of Colorectal Cancer: Guideline From the American Society for Clinical Pathology, College of American Pathologists, Association for Molecular Pathology, and American Society of Clinical Oncology

OBJECTIVES: - To develop evidence-based guideline recommendations through a systematic review of the literature to establish standard molecular biomarker testing of colorectal cancer (CRC) tissues to guide epidermal growth factor receptor (EGFR) therapies and conventional chemotherapy regimens. METHODS: - The American Society for Clinical Pathology, College of American Pathologists, Association for Molecular Pathology, and American Society of Clinical Oncology convened an expert panel to develop an evidence-based guideline to establish standard molecular biomarker testing and guide therapies for patients with CRC. A comprehensive literature search that included more than 4,000 articles was conducted. RESULTS: - Twenty-one guideline statements were established. CONCLUSIONS: - Evidence supports mutational testing for EGFR signaling pathway genes, since they provide clinically actionable information as negative predictors of benefit to anti-EGFR monoclonal antibody therapies for targeted therapy of CRC. Mutations in several of the biomarkers have clear prognostic value. Laboratory approaches to operationalize CRC molecular testing are presented

Molecular Biomarkers for the Evaluation of Colorectal Cancer

Objectives: To develop evidence-based guideline recommendations through a systematic review of the literature to establish standard molecular biomarker testing of colorectal cancer (CRC) tissues to guide epidermal growth factor receptor (EGFR) therapies and conventional chemotherapy regimens

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Expression and function of G-protein-coupled receptorsin the male reproductive tract

This review focuses on the expression and function of muscarinic acetylcholine receptors (mAChRs), α1-adrenoceptors and relaxin receptors in the male reproductive tract. The localization and differential expression of mAChR and α1-adrenoceptor subtypes in specific compartments of the efferent ductules, epididymis, vas deferens, seminal vesicle and prostate of various species indicate a role for these receptors in the modulation of luminal fluid composition and smooth muscle contraction, including effects on male fertility. Furthermore, the activation of mAChRs induces transactivation of the epidermal growth factor receptor (EGFR) and the Sertoli cell proliferation. The relaxin receptors are present in the testis, RXFP1 in elongated spermatids and Sertoli cells from rat, and RXFP2 in Leydig and germ cells from rat and human, suggesting a role for these receptors in the spermatogenic process. The localization of both receptors in the apical portion of epithelial cells and smooth muscle layers of the vas deferens suggests an involvement of these receptors in the contraction and regulation of secretion.Esta revisão enfatiza a expressão e a função dos receptores muscarínicos, adrenoceptores α1 e receptores para relaxina no sistema reprodutor masculino. A expressão dos receptores muscarínicos e adrenoceptores α1 em compartimentos específicos de dúctulos eferentes, epidídimo, ductos deferentes, vesícula seminal e próstata de várias espécies indica o envolvimento destes receptores na modulação da composição do fluido luminal e na contração do músculo liso, incluindo efeitos na fertilidade masculina. Além disso, a ativação dos receptores muscarínicos leva à transativação do receptor para o fator crescimento epidermal e proliferação das células de Sertoli. Os receptores para relaxina estão presentes no testículo, RXFP1 nas espermátides alongadas e células de Sertoli de rato e RXFP2 nas células de Leydig e germinativas de ratos e humano, sugerindo o envolvimento destes receptores no processo espermatogênico. A localização de ambos os receptores na porção apical das células epiteliais e no músculo liso dos ductos deferentes de rato sugere um papel na contração e na regulação da secreção.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Departamento de FarmacologiaUNIFESP, EPM, Depto. de FarmacologiaSciEL

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis