C0c94bc5-7b70-475d-b53d-0b3c9c01e805 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001008418 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control.
CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients.
This dataset contains the ADT/SPEX data for each sample.
Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.
| EGAD00001008419 | EGA
Project description:FFPE skin biopsy samples from patients with CTCL, dermatitis, or healthy controls were profiled by NanoString gene expression analysis A classifier was constructed that was able to identify mycosis fungoides (MF) samples from dermatitis and healthy controls.
2020-06-16 | GSE143382 | GEO
Project description:Genome wide genomic DNA profiling with the HumanMethylation450 BeadChip (450k) of skin samples. The skin tissue DNA was derived from a peri-umbilical punch biopsy (adipose tissue was removed from the biopsy before freezing) from 322 healthy female twins of the TwinsUK cohort. Family structure is present in this data. If the samples are related they will share a similar Relatedness identification ID either monozygotic_twinpair_* or dizygotic_twinpair_*
2017-01-04 | GSE90124 | GEO
Project description:Background: Atopic eczema (AE) is a common chronic inflammatory skin disorder. In order to dissect the genetic background several linkage and genetic association studies have been performed. Yet very little is known about specific genes involved in this complex skin disease, and the underlying molecular mechanisms are not fully understood. Results: We used human DNA microarrays to identify a molecular picture of the programmed responses of the human genome to AE. The transcriptional program was analyzed in skin biopsy samples from lesional and patch-tested skin from AE patients sensitized to Malassezia sympodialis (M. sympodialis), and corresponding biopsies from healthy individuals. The most notable feature of the global gene-expression pattern observed in AE skin was a reciprocal expression of induced inflammatory genes and repressed lipid metabolism genes. The overall transcriptional response in M. sympodialis patch-tested AE skin was similar to the gene-expression signature identified in lesional AE skin. In the constellation of genes differentially expressed in AE skin compared to healthy control skin, we have identified several potential susceptibility genes that may play a critical role in the pathological condition of AE. Many of these genes, including genes with a role in immune responses, lipid homeostasis, and epidermal differentiation, are localized on chromosomal regions previously linked to AE. Conclusion: Through genome-wide expression profiling, we were able to discover a distinct reciprocal expression pattern of induced inflammatory genes and repressed lipid metabolism genes in skin from AE patients. We found a significant enrichment of differentially expressed genes in AE with cytobands associated to the disease, and furthermore new chromosomal regions were found that could potentially guide future region-specific linkage mapping in AE. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: Skin biopsies from normal ('normal') and lesional and patch-tested ('leisonal') skin from Atopic eczema patients sensitized to Malassezia sympodialis Organism Part: location of skin biopsy Keywords: disease state analysis Computed
2010-06-24 | E-GEOD-12511 | biostudies-arrayexpress
Project description:Background: Atopic eczema (AE) is a common chronic inflammatory skin disorder. In order to dissect the genetic background several linkage and genetic association studies have been performed. Yet very little is known about specific genes involved in this complex skin disease, and the underlying molecular mechanisms are not fully understood. Results: We used human DNA microarrays to identify a molecular picture of the programmed responses of the human genome to AE. The transcriptional program was analyzed in skin biopsy samples from lesional and patch-tested skin from AE patients sensitized to Malassezia sympodialis (M. sympodialis), and corresponding biopsies from healthy individuals. The most notable feature of the global gene-expression pattern observed in AE skin was a reciprocal expression of induced inflammatory genes and repressed lipid metabolism genes. The overall transcriptional response in M. sympodialis patch-tested AE skin was similar to the gene-expression signature identified in lesional AE skin. In the constellation of genes differentially expressed in AE skin compared to healthy control skin, we have identified several potential susceptibility genes that may play a critical role in the pathological condition of AE. Many of these genes, including genes with a role in immune responses, lipid homeostasis, and epidermal differentiation, are localized on chromosomal regions previously linked to AE. Conclusion: Through genome-wide expression profiling, we were able to discover a distinct reciprocal expression pattern of induced inflammatory genes and repressed lipid metabolism genes in skin from AE patients. We found a significant enrichment of differentially expressed genes in AE with cytobands associated to the disease, and furthermore new chromosomal regions were found that could potentially guide future region-specific linkage mapping in AE. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: Skin biopsies from normal ('normal') and lesional and patch-tested ('leisonal') skin from Atopic eczema patients sensitized to Malassezia sympodialis Organism Part: location of skin biopsy Keywords: disease state analysis
2008-12-17 | GSE12511 | GEO
Project description:Immunotherapies, including immune checkpoint inhibitors (ICI), have revolutionized the treatment of many cancers, producing significant improvements in survival in patients with many different cancers. However, the intended anti-tumor effects also result in a unique form of autoimmunity, known as immune-related adverse events (irAEs), which have emerged as a limiting factor for many immunotherapies. Cutaneous irAEs (cirAEs), the most frequently occurring ICI–related toxicities, have been associated with improved efficacy and survival but, in their severe forms, require systemic steroids and have in cases led to premature ICI discontinuation and fatality. There is a need for both robust biomarkers and adequate models that effectively predict which patients who develop irAEs may have improved outcomes. Using a microfluidic droplet technology that generates "mini" patient-derived organoids called MicroOrganoSpheres (MOSTM), we successfully generated skin MOS from skin biopsy samples in both healthy skin and tumor-involved skin that sustain the original patient skin immune microenvironment over three weeks. Using this model, we assessed skin cell toxicity and cytokine release in response to ICI and targeted therapies. Clinical responses were largely consistent with the skin and tumor MOS assay readouts, indicating that MOS recapitulates the potential association between skin irAEs and efficacy. Matched pairs of patient melanoma and skin MOS showed good concordance with patient outcome indicating that MOS recapitulates the potential association between skin irAEs and efficacy. Enrichment of genes associated with atopic dermatitis, vitiligo, and psoriatic dermatitis were observed in MOS generated from skin of an ICI-sensitive patient compared to the MOS generated from skin of an ICI-resistant patient. These results indicated that the skin MOS platform can potentially predict the dermatological toxicity of ICI. As the MOS assay can be completed within 12 days after biopsy acquisition, this novel technology may enable personalized medicine approaches by prediction of cirAEs and efficacy for individual patients.
2023-03-31 | GSE226869 | GEO
Project description:Tissue dissociation, mechanical and/or enzymatic, is a method of disaggregating 3D connective tissue to release cells for downstream single cell analysis. Without proper controls for tissue dissociation experiments, potential artifacts can be mistaken for baseline tissue data. We hypothesized that enzymatic (collagenase/hyaluronidase) compared to mechanical dissociation leads to dissociated related artifacts not found in endogenous tumor tissue. To distinguish artifacts between enzymatic and mechanical dissociation, we compared separate enzymatic and mechanical dissociated samples with baseline samples from healthy and tumor patient whole blood, melanoma and head and neck squamous cell carcinoma (HNSCC) tumor tissues in flow cytometry, RNA sequencing and CODEX experiments. In bulk sorted tumor tissue, there is a significant difference between enzymatic and mechanical digested samples in cell stress, heat shock proteins and cell death related genes. These genes were also significantly upregulated in enzymatic over mechanical samples in the single cell RNA sequencing HNSCC tissue data. Fibroblasts and CD39+CD103+ CD8 T cells from tumor tissue, appear to require enzymatic digestion for efficient release from tissue compared to the mechanical digested samples. CD39+CD103+ CD8 tumor infiltrating lymphocytes (TILs) show different phenotypes depending on dissociation technique and tumor tissue. In tumor tissue, CD3+CD8+CD69+ T cells and gene expression were elevated in the enzymatic samples over the mechanical and baseline frozen tissue. Tissue dissociation techniques and tissue analysis from downstream applications have the potential for dissociation related artifacts that can mislead both protein and RNA sequencing data analysis in cancer research.
2023-09-19 | GSE243359 | GEO
Project description:Tissue dissociation, mechanical and/or enzymatic, is a method of disaggregating 3D connective tissue to release cells for downstream single cell analysis. Without proper controls for tissue dissociation experiments, potential artifacts can be mistaken for baseline tissue data. We hypothesized that enzymatic (collagenase/hyaluronidase) compared to mechanical dissociation leads to dissociated related artifacts not found in endogenous tumor tissue. To distinguish artifacts between enzymatic and mechanical dissociation, we compared separate enzymatic and mechanical dissociated samples with baseline samples from healthy and tumor patient whole blood, melanoma and head and neck squamous cell carcinoma (HNSCC) tumor tissues in flow cytometry, RNA sequencing and CODEX experiments. In bulk sorted tumor tissue, there is a significant difference between enzymatic and mechanical digested samples in cell stress, heat shock proteins and cell death related genes. These genes were also significantly upregulated in enzymatic over mechanical samples in the single cell RNA sequencing HNSCC tissue data. Fibroblasts and CD39+CD103+ CD8 T cells from tumor tissue, appear to require enzymatic digestion for efficient release from tissue compared to the mechanical digested samples. CD39+CD103+ CD8 tumor infiltrating lymphocytes (TILs) show different phenotypes depending on dissociation technique and tumor tissue. In tumor tissue, CD3+CD8+CD69+ T cells and gene expression were elevated in the enzymatic samples over the mechanical and baseline frozen tissue. Tissue dissociation techniques and tissue analysis from downstream applications have the potential for dissociation related artifacts that can mislead both protein and RNA sequencing data analysis in cancer research.
2023-09-19 | GSE243360 | GEO
Project description:The identification of novel tumor-specific markers may improve understanding of melanoma progression and prognostic accuracy. Whole genome expression profiling of 46 primary melanomas, 12 metastases, and 16 normal skin samples using Affymetrix U133 PLUS 2.0 array generated gene lists including both known and new melanoma genes. The molecular genetic alterations contributing to the pathogenesis of melanoma are incompletely defined and few independent prognostic features have been identified beyond the pathologic characteristics of the primary tumor. Early stage melanoma is frequently curable, in contrast to the inferior prognosis of melanomas with regional lymph nodes involvement and the incurability of distant metastatic disease. The identification of novel tumor-specific markers may improve our understanding of melanoma progression and prognostic accuracy. To find differentially expressed genes that can distinguish melanoma from normal tissue, we performed a whole genome expression profiling of 46 primary melanoma samples, 12 regional or distant metastases, and 16 normal skin samples using Affymetrix U133 2.0 Plus array. Our study generated lists of differentially expressed genes in melanoma and identified novel prognostic marker HMGA2. It is a novel, highly overexpressed melanoma gene associated with poor prognosis. The overexpression of HMGA2 is strongly associated with regional and distant metastases and serves as an independent predictor of disease-free survival and overall survival in melanoma. Melanoma samples were obtained through an IRB-approved protocol using informed consent at the University of Michigan Multidisciplinary Melanoma Clinic. A portion of pigmented lesions clinically suspicious for melanoma and known melanoma were sampled by punch biopsy at the time of excision. The punch biopsy was bisected; half was sent to for clinical diagnosis and the other half along with adjacent normal skin when available immediately snap-frozen in liquid nitrogen. Snap-frozen tissue was embedded in OCT (TissueTek) followed by frozen sectioning and H&E slide preparation. The slides were evaluated by dermatopathologist who identified areas with greater than 70% tumor cellularity, which were sampled for RNA extraction. Primary melanomas and melanoma metastases were derived from different patients. Metastatic samples included lymph nodes (n=8), subcutaneous soft tissue (n=2), spleen (n=1), and small intestine (n=1).
2012-06-07 | E-GEOD-15605 | biostudies-arrayexpress
Project description:To acquire a better understanding of the molecular pathogenesis of HS, we performed mRNA microarray studies to compare gene expression in lesional skin to healthy skin of HS patients. A significant difference was observed in mRNA expression between lesional and clinically healthy skin of HS patients. Skin biopsy samples (n=30, LS: lesion, NL: non-lesion) were collected at baseline from patients with hidradenitis for RNA extraction and microarray analysis.
2016-01-11 | E-GEOD-72702 | biostudies-arrayexpress