10 research outputs found

    Annotated Bibliography of Recent Research on Chicanos and Latinos in Minnesota.

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    This 1980 bibliography includes both published and unpublished works of merit. Research is presented in four categories: policy and issue-oriented studies, immigrant affairs, data sources and descriptive studies, and specific program studies. At least one verified location (in 1980) of where to obtain each study is given.Minnesota Spanish-Speaking Research and Data Collection Task Force

    Identification of a Blood-Based Protein Biomarker Panel for Lung Cancer Detection

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    Lung cancer is the deadliest cancer worldwide, mainly due to its advanced stage at the time of diagnosis. A non-invasive method for its early detection remains mandatory to improve patients’ survival. Plasma levels of 351 proteins were quantified by Liquid Chromatography-Parallel Reaction Monitoring (LC-PRM)-based mass spectrometry in 128 lung cancer patients and 93 healthy donors. Bootstrap sampling and least absolute shrinkage and selection operator (LASSO) penalization were used to find the best protein combination for outcome prediction. The PanelomiX platform was used to select the optimal biomarker thresholds. The panel was validated in 48 patients and 49 healthy volunteers. A 6-protein panel clearly distinguished lung cancer from healthy individuals. The panel displayed excellent performance: area under the receiver operating characteristic curve (AUC) = 0.999, positive predictive value (PPV) = 0.992, negative predictive value (NPV) = 0.989, specificity = 0.989 and sensitivity = 0.992. The panel detected lung cancer independently of the disease stage. The 6-protein panel and other sub-combinations displayed excellent results in the validation dataset. In conclusion, we identified a blood-based 6-protein panel as a diagnostic tool in lung cancer. Used as a routine test for high- and average-risk individuals, it may complement currently adopted techniques in lung cancer screening.publishedVersio

    Identification of a Blood-Based Protein Biomarker Panel for Lung Cancer Detection

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    Lung cancer is the deadliest cancer worldwide, mainly due to its advanced stage at the time of diagnosis. A non-invasive method for its early detection remains mandatory to improve patients’ survival. Plasma levels of 351 proteins were quantified by Liquid Chromatography-Parallel Reaction Monitoring (LC-PRM)-based mass spectrometry in 128 lung cancer patients and 93 healthy donors. Bootstrap sampling and least absolute shrinkage and selection operator (LASSO) penalization were used to find the best protein combination for outcome prediction. The PanelomiX platform was used to select the optimal biomarker thresholds. The panel was validated in 48 patients and 49 healthy volunteers. A 6-protein panel clearly distinguished lung cancer from healthy individuals. The panel displayed excellent performance: area under the receiver operating characteristic curve (AUC) = 0.999, positive predictive value (PPV) = 0.992, negative predictive value (NPV) = 0.989, specificity = 0.989 and sensitivity = 0.992. The panel detected lung cancer independently of the disease stage. The 6-protein panel and other sub-combinations displayed excellent results in the validation dataset. In conclusion, we identified a blood-based 6-protein panel as a diagnostic tool in lung cancer. Used as a routine test for high- and average-risk individuals, it may complement currently adopted techniques in lung cancer screening

    CD40 agonistic monoclonal antibody APX005M (sotigalimab) and chemotherapy, with or without nivolumab, for the treatment of metastatic pancreatic adenocarcinoma: an open-label, multicentre, phase 1b study

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    Background Standard chemotherapy remains inadequate in metastatic pancreatic adenocarcinoma. Combining an agonistic CD40 monoclonal antibody with chemotherapy induces T-cell-dependent tumour regression in mice and improves survival. In this study, we aimed to evaluate the safety of combining APX005M (sotigalimab) with gemcitabine plus nab-paclitaxel, with and without nivolumab, in patients with pancreatic adenocarcinoma to establish the recommended phase 2 dose.Methods This non-randomised, open-label, multicentre, four-cohort, phase 1b study was done at seven academic hospitals in the USA. Eligible patients were adults aged 18 years and older with untreated metastatic pancreatic adenocarcinoma, Eastern Cooperative Oncology Group performance status score of 0-1, and measurable disease by Response Evaluation Criteria in Solid Tumors version 1.1. All patients were treated with 1000 mg/m(2) intravenous gemcitabine and 125 mg/m(2) intravenous nab-paclitaxel. Patients received 0.1 mg/kg intravenous APX005M in cohorts B1 and Cl and 0.3 mg/kg in cohorts B2 and C2. In cohorts Cl and C2, patients also received 240 mg intravenous nivolumab. Primary endpoints comprised incidence of adverse events in all patients who received at least one dose of any study drug, incidence of dose-limiting toxicities (DITs) in all patients who had a DLT or received at least two doses of gemcitabine plus nab-paclitaxel and one dose of APX005M during cycle 1, and establishing the recommended phase 2 dose of intravenous APX005M. Objective response rate in the DLT-evaluable population was a key secondary endpoint. This trial (PRINCE, PICI0002) is registered with ClinicalTrials.gov, NCT03214250 and is ongoing.Findings Between Aug 22, 2017, and July 10, 2018, of 42 patients screened, 30 patients were enrolled and received at least one dose of any study drug; 24 were DLT-evaluable with median follow-up 17.8 months (IQR 16.0-19.4; cohort B1 22.0 months [21.4-22.7], cohort B2 18.2 months [17.0-18.9], cohort C1 17.9 months [14.3-19.7], cohort C2 15.9 months 112.7-16.11). Two DLTs, both febrile neutropenia, were observed, occurring in one patient each for cohorts B2 (grade 3) and C1 (grade 4). The most common grade 3-4 treatment-related adverse events were lymphocyte count decreased (20 [67%]; five in B1, seven in B2, four in C1, four in C2), anaemia (11 [37%]; two in B1, four in B2, four in C1, one in C2), and neutrophil count decreased (nine [30%]; three in B1, three in B2, one in C1, two in C2). 14 (47%) of 30 patients (four each in Bi, B2, C1; two in C2) had a treatment-related serious adverse event. The most common serious adverse event was pyrexia (six [20%[ of 30; one in B2, three in C1, two in C2). There were two chemotherapy-related deaths due to adverse events: one sepsis in B1 and one septic shock in Cl. The recommended phase 2 dose of APX005M was 0.3 mg/kg. Responses were observed in 14 (58%) of 24 DLT-evaluable patients (four each in B1, C1, C2; two in B2).Interpretation APX005M and gemcitabine plus nab-paditaxel, with or without nivolumab, is tolerable in metastatic pancreatic adenocarcinoma and shows clinical activity. If confirmed in later phase trials, this treatment regimen could replace chemotherapy-only standard of care in this population. Copyright (C) 2020 Elsevier Ltd. All rights reserved

    Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

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    Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community

    Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

    No full text
    Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community
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