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388 results for “immune checkpoint inhibitors”
RNA datasets to derive predictors for immune checkpoint inhibitor therapy of non-small cell lung cancer
<p>Nanostring nCounter datasets and corresponding clinical data of tumor samples of patients with advanced NSCLC who received anti-PD-1 immuntherapy. Prospectively divided into a discovery and a validation cohort.</p> <p>Please cite the corresponding publication in Annals of Oncology (10.1093/annonc/mdz049)</p>
OSE2101 Versus Chemotherapy in HLA-A2 Positive Patients With Advanced NSCLC After Immune Checkpoint Inhibitor Failure
ClinicalTrials.gov study NCT02654587. IPD Sharing: NO. Countries: 10. Publications: 1.
Pretreatment Neutrophil-to-Lymphocyte Ratio, Mutational Load, and Outcomes in Patients Treated with Immune Checkpoint Inhibitors
<p>This dataset has been used to analyze the association between pre-treatment neutrophil-to-lymphocyte ratio and tumour mutational burden with survival and response to treatment in immunotherapy-treated patients with cancer. The dataset contains clinical and genomic data for 2,037 patients with 18 cancer types.</p>
Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors
<p>R markdown files and source data to reproduce figures from the manuscript "Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors"</p>
Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors - Dataset
<p>Dataset used from the publication "Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab" published in </p> <p>Cell. 2017 Nov 2;171(4):934-949.e16.</p> <p> doi: 10.1016/j.cell.2017.09.028. Epub 2017 Oct 12.</p>
Hepatotoxicity in immune checkpoint inhibitors: A pharmacovigilance study from 2014–2021
<p><span>Adverse events(AEs) related to hepatotoxicity have been reported in patients treated with immune checkpoint inhibitors (ICIs). As the number of adverse events increases, it is necessary to assess the differences in each immune checkpoint inhibitor regimen. The purpose of this study was to examine the relationship between ICIs and hepatotoxicity in a scientific and systematic manner. Data were obtained from the FDA Adverse Event Reporting System database (FAERS) and included data from the first quarter of 2014 to the fourth quarter of 2021. Disproportionality analysis assessed the association between drugs and adverse reactions based on the reporting odds ratio (ROR) and information components (IC). 9,806 liver adverse events were reported in the FAERS database. A strong signal was detected in older patients (≥65 years) associated with ICIs. Hepatic adverse events were most frequently reported with Nivolumab (36.17%). Abnormal liver function, hepatitis, and autoimmune hepatitis were most frequently reported, and hepatitis and immune-mediated hepatitis signals were generated in all regimens. In clinical use, patients should be alert to these adverse effects, especially in elderly patients, who may be aggravated by the use of ICI.</span></p>
The entanglement of extracellular matrix molecules and immune checkpoint inhibitors in cancer: a systematic review of the literature
<p><strong>The datasets include the results obtained upon a literature search on different databases: Web of science, Scopus and Pubmed.</strong></p> <p>The combination of mesh terms searched in the databases were “extracellular matrix molecules” or “extracellular matrix remodeling” and “immune checkpoint inhibitors” or “immunotherapy”.</p>
Personalizing Immune Checkpoint Inhibitor Therapy
ClinicalTrials.gov study NCT03409341. IPD Sharing: YES. Countries: 1. Publications: 6.
Arginase Inhibitor INCB001158 as a Single Agent and in Combination With Immune Checkpoint Therapy in Patients With Advanced/Metastatic Solid Tumors
ClinicalTrials.gov study NCT02903914. IPD Sharing: NO. Countries: 4. Publications: 2.
Immune-checkpoint Inhibitors and Surrogate Endpoints in Cancer Trials (SURROGATE-ICI)
ClinicalTrials.gov study NCT03963518. IPD Sharing: NO. Countries: 1. Publications: 2.
A Study of Atezolizumab in Combination With Cabozantinib Compared to Cabozantinib Alone in Participants With Advanced Renal Cell Carcinoma After Immune Checkpoint Inhibitor Treatment
ClinicalTrials.gov study NCT04338269. IPD Sharing: YES. Countries: 15. Publications: 2.
AbataCept for the Treatment of Immune-cHeckpoint Inhibitors Induced mYocarditiS
ClinicalTrials.gov study NCT05195645. IPD Sharing: YES. Countries: 1. Publications: 1.
Study of Combination Therapy With the MEK Inhibitor, Cobimetinib, Immune Checkpoint Blockade, Atezolizumab, and the AUTOphagy Inhibitor, Hydroxychloroquine in KRAS-mutated Advanced Malignancies
ClinicalTrials.gov study NCT04214418. IPD Sharing: YES. Countries: 1. Publications: 0.
Hepatotoxicity in immune checkpoint inhibitors: A pharmacovigilance study from 2014–2021
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Assessment of clinical outcomes with immune checkpoint inhibitor therapy in melanoma patients with CDKN2A and TP53 pathogenic mutations
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Biomarkers in Metastatic Castration-Resistant Prostate Cancer for efficiency of Immune Checkpoint Inhibitors
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Upfront whole blood transcriptional patterns in patients receiving immune checkpoint inhibitors associate with clinical outcome
<p>This repository contains supplementary materials for the research paper "Upfront whole blood transcriptional patterns in patients receiving immune checkpoint inhibitors associate with clinical outcome". The materials are organized in the following folders:</p> <ul> <li>01_code: code to reproduce the results</li> <li>02_raw_data_public: raw gene count data of the 14,085 whole blood transcriptomes from public datasets (PUBLIC)</li> <li>03_raw_data_primero: raw gene count data of the 145 pre-ICI whole blood samples from the PRIMERO cohort, including sample annotation with response data ("primero_sample_anno.tsv")</li> <li>04_ica: results of the independent component analysis on the PUBLIC dataset, including the transcriptional components ("ica_public_flipped_consensus_independent_components.tsv"), the gene set enrichment analysis results on these components, and the projected activities of the PRIMERO samples for these transcriptional components ("ica_primero_mixing_matrix_projected_corrected.tsv")<br><br></li> </ul>
Immune signatures predict development of autoimmune toxicity in immune checkpoint inhibitor-treated patients with cancer
<p><strong>Immune signatures predict development of autoimmune toxicity in immune</strong><strong> checkpoint inhibitor-treated patients with cancer</strong></p> <p> </p> <p>Nicolas Gonzalo Nuñez<sup>1</sup>*, Fiamma Berner<sup>2</sup>*, Ekaterina Friebel<sup>1</sup>*, Susanne Unger<sup>1</sup>, Nina Wyss<sup>2,3</sup>, Julia Martinez Gomez<sup>4</sup>, Mette-Triin Purde<sup>2</sup>, Rebekka Niederer<sup>2,3</sup>, Maximilian Porsch<sup>5</sup>, Christa Lichtensteiger<sup>2</sup>, Rafaela Kramer<sup>6</sup>, Michael Erdmann<sup>6</sup>, Christina Schmitt<sup>7</sup>, Lucy Heinzerling<sup>6,7</sup>, Marie-Therese Abdou<sup>2</sup>, Julia Karbach<sup>8</sup>, Dirk Schadendorf<sup>9</sup>, Lisa Zimmer<sup>9</sup>, Selma Ugurel<sup>9</sup>, Niklas Klümper<sup>10,11,12</sup>, Michael Hölzel<sup>10,11</sup>, Laura Power<sup>1</sup>, Stefanie Kreutmair<sup>1</sup>, Mariaelena Capone<sup>13</sup>, Gabriele Madonna<sup>13</sup>, Lacin Cevhertas<sup>14,15</sup>, Anja Heider<sup>14</sup>, Teresa Amaral<sup>16,17</sup>, Omar Hasan Ali<sup>2,3,4,18</sup>, David Bomze<sup>2,19</sup>, Florentia Dimitriou<sup>4</sup>, Stefan Diem<sup>20</sup>, Paolo Antonio Ascierto<sup>13</sup>, Reinhard Dummer<sup>4</sup>, Elke Jäger<sup>8</sup>, Christoph Driessen<sup>20</sup>, Mitchell P. Levesque<sup>4</sup>, Willem van de Veen<sup>14</sup>, Markus Joerger<sup>20</sup>, Martin Früh<sup>20,21</sup>, Burkhard Becher<sup>1</sup>**, Lukas Flatz<sup>2,3,4,20,22</sup>**</p> <p> </p> <p>*/** these authors contributed equally</p> <p> Affiliations</p> <p>1. Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland</p> <p>2. Institute of Immunobiology, Medical Research Center, Kantonsspital St. Gallen, St.Gallen, Switzerland</p> <p>3. Department of Dermatology, Kantonsspital St. Gallen, St.Gallen, Switzerland</p> <p>4. Department of Dermatology, University Hospital Zurich, Zurich, Switzerland</p> <p>5. Department of Radiology, Kantonsspital St. Gallen, St.Gallen, Switzerland</p> <p>6. Department of Dermatology, University of Erlangen-Nuremberg, Erlangen, Germany</p> <p>7. Ludwig Maximilian University of Munich, Munich, Germany</p> <p>8. Department of Oncology and Hematology, Krankenhaus Nordwest, Frankfurt, Germany</p> <p>9. Department of Dermatology, Comprehensive Cancer Center (Westdeutsches Tumorzentrum) University Hospital Essen, Essen, Germany</p> <p>10. Institute for Experimental Oncology, University Hospital Bonn, Bonn, Germany</p> <p>11. Center for Integrated Oncology Cologne/Bonn, University Hospital Bonn, Bonn, Germany</p> <p>12. Department of Urology, University Hospital Bonn, Bonn, Germany</p> <p>13. Istituto Nazionale Tumori-IRCCS-Fondazione G. Pascale, Napoli, Italy</p> <p>14. Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland</p> <p>15. Department of Medical Immunology, Institute of Health Sciences, Bursa Uludag University, Bursa, Turkey</p> <p>16. Skin Cancer Center, Department of Dermatology, University Hospital Tübingen, Tübingen, Germany</p> <p>17. iFIT Cluster of Excellence (EXC 2180), University of Tübingen, Tübingen, Germany</p> <p>18. Department of Medical Genetics, Life Sciences Institute, University of British Columbia, Vancouver, Canada</p> <p>19. Sackler Faculty of Medicine, Tel-Aviv University, Israel</p> <p>20. Department of Oncology, Kantonsspital St. Gallen, St.Gallen, Switzerland</p> <p>21. Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland</p> <p>22. Universitäts-Hautklinik, University of Tübingen, Tübingen, Germany</p> <p> </p> <p> </p>
Single cell data from Imaging Mass Cytometry of mouse lung tumours treated with KRAS-G12C and immune checkpoint inhibitors (Dataset 3)
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Immune Checkpoint Inhibitor, Nivolumab, Combined with Chemotherapy Improved the Survival of Unresectable Ad-vanced and Metastatic Esophageal Squamous Cell Carcinoma: a real world experience
<p><strong>Figure S1 the detail of treatments.</strong> Blue arrow means this patient was still alive at the latest date of follow up. Hollow circle means this patient die. The others were lose follow up at the latest date of follow up.</p> <p><strong>Figure S2 progression free survival (PFS) of patients received immunotherapy, including 5 nivolumab and chemotherapy and 1 dual immune check point inhibitor, on different PD-L1 tumor cells (TC) expression.</strong> (A) divided by PD-L1 TC <1% or ≧1%. (B)divided by PD-L1 TC <10% or ≧10%.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.