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4,330 results for “Melanoma”
Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma
<p>Code and data for manuscript "Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma"</p>
B-cell receptor data from intratumoural B cells in melanoma patients
<p>This record contains data used in the Crescioli et al. analysis of B-cell response in melanoma, specifically analysis concerning high-throughput BCR repertoire.</p> <p>Files:</p> <p>"Visium_all_Aug22_comboDatBoth.txt": IMGT/HighV-Quest output of the high-throughput intratumoural BCR repertoire from n=5 melanoma tumours. In tab-separated text file format.</p> <p>"HV_EB_COV_MEL_comb_Oct22.RDS": A R data object (readable into R with "readRDS(...)") containing combined data from the melanoma (MEL) data with analogous high-throughput BCR repertoire data from healthy volunteers (HV), Ebola convalescent patients (EB) and hospitalised COVID-19 patients (COV). HV, EB and COV data are taken from <a href="https://dx.doi.org/10.5281/zenodo.5146019">https://dx.doi.org/10.5281/zenodo.5146019</a>. Here the sequences are filtered to contain only unique combinations of isotype and IMGT-numbered V-domain DNA sequence (to remove redundancies due to e.g. capturing BCR transcripts from plasma cells).</p> <p>"BM_Master_Light_Useasreftrue_140325_withPepStats_8.csv". IMGT/HighV-Quest output of the Bone Marrow light chain repertoire data. <a href="https://doi.org/10.3389/fimmu.2016.00388">Published in Townsend et al. Front Immunol 7:388 (2016)</a>. Used here for the comparison of gene conversion frequencies against the melanoma light chain repertoire.</p> <p>"BM_Master_Light_Useasreftrue_140325_withPepStats_8_Vgapped.fasta". The IMGT-gapped V-gene sequence from the Townsend et al. (see above) Bone Marrow light chain repertoire data. This is the raw input to BrepConvert. Provided here for this dataset; same sequences for the melanoma/healthy data are already in the RDS object ("HV_EB_COV_MEL_comb_Oct22.RDS").</p> <p>"2_IMGT-gapped-nt-sequences_visa.txt", "2_IMGT-gapped-nt-sequences_visb.txt": Raw output of IMGT/HighV-Quest containing IMGT-gapped nucleotide sequences. These files were parsed to extract the IMGT-gapped V-gene sequence for BrepConvert analysis.</p> <p>"BrepConvert.zip": BrepConvert gene conversion analysis results for Healthy and Melanoma repertoires.</p> <p>See code in <a href="https://github.com/josef0731/melanoma-ig">https://github.com/josef0731/melanoma-ig</a> for ways to use these input files for reproducing the analyses.</p> <p> </p>
A 3-dimensional histology computer model of malignant melanoma
<p>This dataset contains 66 slices of a human melanoma cut in sequential order and the reconstructed model stored in the NIfTI file format. The model can be viewed in the web browser by accessing https://dbo-dkfz.github.io/niivue-ui-fork/ and opening the downloaded file.</p>
MITF/miR-579-3p novel regulatory axis controls BRAF-mutated melanoma decision between cell senescence or progression upon exposure to MAPK inhibitors.
<p><strong>Abstract</strong></p> <p>Therapy of metastatic melanoma has improved dramatically over the last years thanks to the development of targeted therapies (MAPK inhibitors) and immunotherapies. However, drug resistance continues to be a major limitation to the efficacy of these therapies. Our research group has provided robust evidence as to the involvement of a set of microRNAs in the development of resistance to target therapy in BRAF-mutated melanoma cell lines. Among them, a pivotal role is played by miR-579-3p, whose role as oncosuppressor was discovered by our group some years ago. Here we show that miR-579-3p and the microphthalmia-associated transcription factor (MITF) influence reciprocally their expression through positive feedback regulatory loops. In particular we show that miR-579-3p is specifically deregulated in BRAF-mutant melanomas and that its expression levels mirror those of MITF. Luciferase and ChIP studies show that MITF is a positive regulator of miR-579-3p, which is located in the intron 11 of the human gene ZFR (Zink-finger recombinase) and is co-transcribed with its host gene. Moreover, miR-579-3p, by targeting BRAF is able to stabilize MITF protein thus inducing its own transcription. As a consequence, upon exposure to MAPK inhibitors or, alternatively upon miR-579-3p transfection, the activation of this newly uncovered miR-579-3p/MITF axis induces a potent block of proliferation and senescence of BRAF-mutant melanoma cells. Moreover, the long term development of resistance to MAPKi is able to select cells characterized by the loss of both miR-579-3p and MITF and the same down-regulation is also present in patients relapsing after targeted therapies treatments. Altogether these findings suggest that miR-579-3p/MITF interplay potentially governs the balance between proliferation, senescence and resistance to target therapies in BRAF-mutant melanomas.</p> <p><strong>KEYWORDS: </strong></p> <p><strong>Acknowledgements</strong></p> <p>This study was supported by Italian Association for Cancer Research (AIRC) grants IG19865 to G. Ciliberto and IG24451 to R. Mancini and by the Lazio Innova grants 2018 n. 85-2017-13750 and 2020 n. A0375-2020-36657 to R. Mancini and by Italian Minister of Health grant PRIN 2017 (Prot. 2017HWTP2K) to G. Ciliberto and R. Mancini, by Italian Minister of Health through “Ricerca Corrente” grant L2/1 to P.A. Ascierto. The study was also supported by Lega Italiana per la Lotta ai Tumori (LILT) grant n. 2021U0001637 to L. Fattore. We thank all patients who donated samples for this research.</p>
Immune Landscape and Gene Function Analysis of Uveal Melanoma Based on Focal Adhesion-Related Gene Typing
<p><strong>Figure legend</strong><strong>s</strong></p> <p><strong>Figure 1 Identification of focal adhesion gene clusters and immune analysis</strong></p> <p>(A) Relative changes in the area under the CDF curve. (B) Consensus clustering results, K=3. (C) Survival curves of different clusters. (D) ssGSEA heatmap showing differences in immune infiltration between clusters. (E) Expression levels of immune checkpoints in different clusters. (F) Violin plots of immune scores, stromal scores, ESTIMATE scores, and tumor purity scores.</p> <p> </p> <p><strong>Figure 2 GSEA pathway enrichment analysis</strong></p> <p> </p> <p><strong>Figure 3 PPI network related to DEGs between cluster 2 and clusters 1 and 3 and HUB gene selection</strong></p> <p>(A) Selection of DEGs between cluster 2 and clusters 1 and 3. (B) PPI network of DEGs between clusters. (C) Intersection analysis of the top 20 HUB genes in the PPI network using five algorithms.</p> <p> </p> <p><strong>Figure 4 Functional analysis of HUB genes in the interaction network and construction of co-expression network</strong></p> <p>(A) Heatmap showing the expression of HUB genes in cluster 2 and clusters 1 and 3. (B) GO functional enrichment analysis of HUB genes. (C) KEGG pathway enrichment analysis of HUB genes. (D) Construction of the co-expression network of HUB genes and their co-expressed genes.</p> <p> </p> <p><strong>Figure 5 Survival curves of patients corresponding to HUB genes at high and low expression levels</strong></p> <p> </p> <p><strong>Figure 6 Exploration of the correlation between HUB genes and drug sensitivity through CellMiner database</strong></p> <p> </p>
Data for: A cell surface-binding antibody atlas nominates a MUC18-directed antibody-drug conjugate for targeting melanoma
<p><span>Recent advances in targeted therapy and immunotherapy have substantially improved the treatment of melanoma. However, therapeutic strategies are still needed for unresponsive or treatment-relapsed melanoma patients. To discover antibody-drug conjugate (ADC)-tractable cell surface targets for melanoma, we developed an atlas of melanoma cell surface binding antibodies (pAbs) using a proteome-scale antibody array platform (PETAL). Target identification of pAbs led to development of melanoma cell killing ADCs against LGR6, TRPM1, ASAP1, and MUC18, among others. MUC18 was overexpressed in both tumor cells and tumor-infiltrating blood vessels across major melanoma subtypes, making it a potential dual-compartment and universal melanoma therapeutic target. AMT-253, an MUC18-directed ADC based on topoisomerase I inhibitor exatecan and a self-immolative T moiety, had a higher therapeutic index compared to its microtubule inhibitor-based counterpart and favorable pharmacokinetics and tolerability in monkeys. AMT-253 exhibited MUC18-specific cytotoxicity through DNA damage and apoptosis and a strong bystander killing effect, leading to potent antitumor activities against melanoma cell line and patient-derived xenograft models. Tumor vasculature-targeting by a mouse MUC18-specific antibody-T1000-exatecan conjugate inhibited tumor growth in human melanoma xenografts. Combination therapy of AMT-253 with an anti-angiogenic agent generated higher efficacy than single agent in a mucosal melanoma model. Beyond melanoma, AMT-253 was also efficacious in a wide range of MUC18-expressing solid tumors. Efficient target/antibody discovery in combination with the T moiety-exatecan linker-payload exemplified here may facilitate discovery of new ADC to improve cancer treatment</span><span>.</span></p>
Single-arm Trial to Evaluate the Role of the Immune Response to Talimogene Laherparepvec in Unresected Melanoma
ClinicalTrials.gov study NCT02366195. IPD Sharing: YES. Countries: 13. Publications: 1.
Sargramostim, Vaccine Therapy, or Sargramostim and Vaccine Therapy in Preventing Disease Recurrence in Patients With Melanoma That Has Been Removed By Surgery
ClinicalTrials.gov study NCT01989572. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Study of Lifileucel (LN-144), Autologous Tumor Infiltrating Lymphocytes, in the Treatment of Patients With Metastatic Melanoma
ClinicalTrials.gov study NCT02360579. IPD Sharing: NO. Countries: 8. Publications: 4.
A Study of IO102/IO103, Nivolumab, and Relatlimab in People With Melanoma
ClinicalTrials.gov study NCT05912244. IPD Sharing: YES. Countries: 1. Publications: 2.
BO-112 With Pembrolizumab in Unresectable Malignant Melanoma
ClinicalTrials.gov study NCT04570332. IPD Sharing: NO. Countries: 2. Publications: 1.
Trial of Lymphoseek in Intraoperative Localization of Lymph Nodes in Breast Cancer and Melanoma
ClinicalTrials.gov study NCT00671918. IPD Sharing: Not stated. Countries: 2. Publications: 48.
A Study of Tilsotolimod in Combo With Ipilimumab vs Ipilimumab Alone in Subjects With Anti-PD-1 Refractory Melanoma
ClinicalTrials.gov study NCT03445533. IPD Sharing: NO. Countries: 11. Publications: 1.
Ipilimumab and All-Trans Retinoic Acid Combination Treatment of Advanced Melanoma
ClinicalTrials.gov study NCT02403778. IPD Sharing: NO. Countries: 1. Publications: 1.
PH 1 Biomarker Study of Nivolumab and Ipilimumab and Nivolumab in Combination With Ipilimumab in Advanced Melanoma
ClinicalTrials.gov study NCT01621490. IPD Sharing: Not stated. Countries: 3. Publications: 3.
Study Comparing Combination of LGX818 Plus MEK162 Versus Vemurafenib and LGX818 Monotherapy in BRAF Mutant Melanoma
ClinicalTrials.gov study NCT01909453. IPD Sharing: YES. Countries: 29. Publications: 9.
Imatinib Mesylate in Treating Patients With Stage III or Stage IV Melanoma That Cannot Be Removed by Surgery
ClinicalTrials.gov study NCT00470470. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Study to Evaluate the Safety/ Efficacy of T-VEC in Japanese Subjects With Unresectable Stage IIIB-IV Malignant Melanoma
ClinicalTrials.gov study NCT03064763. IPD Sharing: YES. Countries: 1. Publications: 1.
A Study of Vemurafenib (RO5185426) in Comparison With Dacarbazine in Previously Untreated Patients With Metastatic Melanoma (BRIM 3)
ClinicalTrials.gov study NCT01006980. IPD Sharing: Not stated. Countries: 12. Publications: 8.
Melanoma Perception and Health Literacy in People of Color
ClinicalTrials.gov study NCT02437305. IPD Sharing: Not stated. Countries: 1. Publications: 6.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.