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242 results for “immune response to cancer;”
Human lung cancer harbors spatially-organized stem-immunity hubs that associate with response to immunotherapy
<p>Data associated with Chen, Nieman, Spurrell et al "Human lung cancer harbors spatially-organized stem-immunity hubs that associate with response to immunotherapy" Nature Immunology, 2024. </p> <p>(1) Multiplex RNA scope. Processed cell-level data from 3 datasets, separated into manually selected "Stem Immunity" regions and "Tumor" regions, in separate files. </p> <p>(2) GeoMx. Unprocessed GeoMex data, with standard fields provided by Nanostring software. </p> <p>(3) MERFISH. Transcript-level information, including CellPose and Baysor segmentation. </p> <p>(4) Co-registered multispectral RNA and protein images. Processed cell-level data from 46 patients. Patient-level meta data information is available in supplementary table 1, tab B_Patient_Metadata. Fluorophore channel information is Figure 1a. </p> <p>Paper: <a title="https://secure-web.cisco.com/1OQRHTBMPf1SngM0FLdNuKQOPPx7fLOR87kGiirhnF_e0M74duym9zratwJMs0WJXqHJPAlkZoWXBoHafhJ72n9s0edU76bj8nCUblNWpOnoK6c8KGEQgcNuk8OuBqXAooW9yoh6etJ0bq6VGDmoFd95MrgMob6is1GxcOWx-XK996d_j8QDVu1rptbeyI8n08UfqmHA3n0A0P37k_-DYUWMh7VFNSmbLGzVqGG2n-czoFN3vL5JrMDPRvo0LDGJs96rzB6zYiaLdk6UgYXXc6eUV6FI64MTxmuXCbEmVRqONrjLdyG6HJULOrJLmKURM/https%3A%2F%2Fwww.nature.com%2Farticles%2Fs41590-024-01792-2" href="https://secure-web.cisco.com/1OQRHTBMPf1SngM0FLdNuKQOPPx7fLOR87kGiirhnF_e0M74duym9zratwJMs0WJXqHJPAlkZoWXBoHafhJ72n9s0edU76bj8nCUblNWpOnoK6c8KGEQgcNuk8OuBqXAooW9yoh6etJ0bq6VGDmoFd95MrgMob6is1GxcOWx-XK996d_j8QDVu1rptbeyI8n08UfqmHA3n0A0P37k_-DYUWMh7VFNSmbLGzVqGG2n-czoFN3vL5JrMDPRvo0LDGJs96rzB6zYiaLdk6UgYXXc6eUV6FI64MTxmuXCbEmVRqONrjLdyG6HJULOrJLmKURM/https%3A%2F%2Fwww.nature.com%2Farticles%2Fs41590-024-01792-2">https://www.nature.com/articles/s41590-024-01792-2</a></p>
Conserved angio-immune subtypes of the cancer microenvironment predict response to immune checkpoint blockade therapy
<p>Immune checkpoint blockade (ICB) therapy has revolutionized cancer treatment. However, only a fraction of the patients respond to ICB therapy. Accurate prediction of patients to likely respond to ICB would maximize the efficacy of ICB therapy. The tumor microenvironment (TME) dictates tumor progression and therapy outcome. Here, we classify the TME by analyzing the transcriptome from 11,069 cancer patients based on angiogenesis and T-cell activity. We find three distinct angio-immune TME subtypes conserved across 30 non-hematological cancers. There is a clear inverse relationship between angiogenesis and anti-tumor immunity in TME. Remarkably, patients displaying TME with low angiogenesis with strong anti-tumor immunity show the most significant responses to ICB therapy in four cancers. Re-evaluation of the renal cell carcinoma clinical trials provides compelling evidence that the baseline angio-immune state is robustly predictive of ICB responses. This study offers a rationale for incorporating baseline angio-immune scores for future ICB treatment strategies.</p>
Conserved angio-immune subtypes of the cancer microenvironment predict response to immune checkpoint blockade therapy
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Response to immune checkpoint blockade improved in pre-clinical model of breast cancer after bariatric surgery
<p>Bariatric surgery is becoming more prevalent as a sustainable weight loss approach, with vertical sleeve gastrectomy (VSG) being the first line of surgical intervention. We and others have shown that obesity exacerbates tumor growth while diet-induced weight loss impairs obesity-driven progression. It remains unknown how bariatric surgery-induced weight loss impacts cancer progression or alters responses to therapy. Using a pre-clinical model of diet induced obesity followed by VSG or diet-induced weight loss, breast cancer progression and immune checkpoint blockade therapy was investigated. Weight loss by bariatric surgery or weight matched dietary intervention before tumor engraftment protected against obesity-exacerbated tumor progression. However, VSG was not as effective as dietary intervention in reducing tumor burden despite achieving similar extent of weight and adiposity loss. Circulating leptin did not associate with changes in tumor burden. Uniquely, tumors in mice that received VSG displayed elevated inflammation and checkpoint ligand PD-L1. Further, mice that received VSG had reduced tumor infiltrating T lymphocytes suggesting an ineffective anti-tumor microenvironment. VSG-associated elevation of PD-L1 prompted us to next investigate the efficacy of immune checkpoint inhibitors in lean, obese, and formerly obese mice that lost weight by VSG or weight matched controls. While obese mice were resistant to immunotherapy, anti-PD-L1 potently impaired tumor progression after VSG through improved anti-tumor immunity. Thus, in formerly obese mice, surgical weight loss followed by immunotherapy reduced breast cancer burden. Further studies are necessary to determine how bariatric surgery sensitizes tumors to immune checkpoint inhibition.</p>
STRIDE - STimulating Immune Response In aDvanced brEast Cancer
ClinicalTrials.gov study NCT00925548. IPD Sharing: Not stated. Countries: 12. Publications: 1.
Typhoid Vaccine in Testing Response to Immune Stress in Patients With Stage I-IIIA Breast Cancer
ClinicalTrials.gov study NCT02415387. IPD Sharing: NO. Countries: 1. Publications: 1.
Response to immune checkpoint blockade improved in pre-clinical model of breast cancer after bariatric surgery
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Blood memory CD8 T cell phenotypes in lung cancer patients predict immune checkpoint treatment responses
<p>Rscript for figure generation and data analysis:</p> <p>GenerateFigures.R</p> <p> </p> <p>Seurat objects containing processed data after quality control:</p> <p><a href="../api/records/10867209/draft/files/NCCS_For_Zenodo.RDS/content" target="_blank" rel="noopener noreferrer">NCCS_For_Zenodo.RDS</a> - NCCS discovery cohort.</p> <p><a href="../api/records/10867209/draft/files/Pavia_For_Zenodo.RDS/content" target="_blank" rel="noopener noreferrer">Pavia_For_Zenodo.RDS</a> - Pavia validation cohort.</p> <p> </p> <p>RDS files containing DEGs or differentially abundant surface markers:</p> <p>TestResults2Groups.rds - Cell type specific LTR vs Non Responder DEG </p> <p>TestResults2GroupsADT.rds - Cell type specific LTR vs Non Responder differential surface markers</p> <p>TestResults2GroupsLungOnly.rds - Cell type specific LTR vs Non Responder DEG on lung samples only</p> <p>TestResults2GroupsLungOnlyADT.rds - Cell type specific LTR vs Non Responder differential surface markers on lung samples only</p> <p>TestResults3Groups.rds - Cell type specific LTR vs R vs Non Responder differential DEG</p> <p>TestResults3GroupsGeneralADT.rds - Across cell type LTR vs R vs Non Responder differential surface markers</p> <p>TestResults2GroupsGeneralRNA.rds - Across cell type LTR vs Non Responder DEG </p> <p>TestResults2GroupsGeneralADT.rds - Across cell type LTR vs Non Responder differential surface markers</p> <p>TestResults2GroupsLungOnlyGeneralRNA.rds - Across cell type LTR vs Non Responder DEG on lung samples only</p> <p>TestResults2GroupsLungOnlyGeneralADT.rds - Across cell type LTR vs Non Responder differential surface markers on lung samples only</p> <p>TestResults3GroupsGeneralRNA.rds - Across cell type LTR vs R vs Non Responder differential DEG</p> <p>TestResults3GroupsGeneralADT.rds - Across cell type LTR vs R vs Non Responder differential surface markers</p> <p> </p> <p>Logistic regression models trained on the NCCS discovery cohort:</p> <p>PerCellPredictions <CellType> * - Celltype specific models predicting either LTR, R or control group trained on all NCCS samples</p> <p>PerCellPredictions_2Groups_LungOnly <CellType> * - Celltype specific models predicting either LTR or NonResponder group, trained on lung samples only.</p> <p>PerCellPredictions_2Groups_<CellType> * - Celltype specific models predicting either LTR or NonResponder trained on all NCCS samples</p>
Prospective Biobanking Study in Cancer Patients Aiming at Better Understand the Link Between the Molecular Alterations of the Tumor Itself, Its Microenvironment and Immune Response (SCANDARE)
ClinicalTrials.gov study NCT03017573. IPD Sharing: YES. Countries: 1. Publications: 1.
The Resistance and Immune Response to Palbociclib in Breast Cancer
ClinicalTrials.gov study NCT03401359. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Evaluation of the Role of Immune Checkpoints in Response to Breast Cancer Neoadjuvant Therapy
ClinicalTrials.gov study NCT05519397. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
IMmune Proteomics to Predict NeoAdjuvant Chemotherapy and ImmunoTherapy Response in Gastric Cancer
ClinicalTrials.gov study NCT06662110. IPD Sharing: NO. Countries: 1. Publications: 1.
Evaluation of ENPP1 Expression and Immune Response in Bladder Cancer Patients
ClinicalTrials.gov study NCT06657755. IPD Sharing: NO. Countries: 1. Publications: 4.
Study of the Response to a Neoadjuvant Chemotherapy Based on the Antitumor Immune Response in Localized Breast Cancer
ClinicalTrials.gov study NCT01440413. IPD Sharing: Not stated. Countries: 1. Publications: 24.
Immune Response in Lung Cancer
ClinicalTrials.gov study NCT01955343. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Immune Checkpoints in Predicting Response to Neoadjuvant Therapy in Rectal Cancer
ClinicalTrials.gov study NCT05457075. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
A Prospective Study of Monitoring Immune Response in Locally Advanced Cervix Cancer
ClinicalTrials.gov study NCT03559803. IPD Sharing: UNDECIDED. Countries: 1. Publications: 10.
The CCANED-CIPHER Study: Early Cancer Detection and Treatment Response Monitoring Using AI-Based Platelet and Immune Cell Transcriptomic Profiling
ClinicalTrials.gov study NCT06717295. IPD Sharing: UNDECIDED. Countries: 3. Publications: 29.
Anesthetic Technique on Immune Response in Colorectal Cancer
ClinicalTrials.gov study NCT01902849. IPD Sharing: Not stated. Countries: 1. Publications: 2.
The Immune Response of Breast Cancer Patients Treated With Levobupivacaine Using Paravertebral or Superficial Chest Blocks
ClinicalTrials.gov study NCT05816538. IPD Sharing: NO. Countries: 1. Publications: 21.
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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.