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Transcriptome analysis in Human leprosy patients

ABSTRACT: Leprosy is classified from paucibacillary leprosy (TT and BT) to multibacillary leprosy (BB, BL, and LL). In our study, we focus on selecting or classfying the significant genes to discriminate between paucibacillary and multibacillary group and the important genes to distinguish between blood and the corresponding tissue in patients. · Human Adult Normal Skin Sample (Commercial;Cat#1234218); 6 patients of leprosy (Blood and Tissue sample (Pathologic classification: BT); 6 patients of leprosy (Blood and Tissue sample (Pathologic classification: MB)) · In blood sample, BT sample vs MB sample · In tissue sample, Normal Skin sample vs tissue BT sample or tissue MB sample · Single Color Microarray · All experiments are performed one replicate

ORGANISM(S): Homo sapiens

SUBMITTER: Tae Hoon Kim

PROVIDER: E-GEOD-24280 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Transcriptome analysis in Human leprosy patients

Project description:Leprosy is classified from paucibacillary leprosy (TT and BT) to multibacillary leprosy (BB, BL, and LL). In our study, we focus on selecting or classfying the significant genes to discriminate between paucibacillary and multibacillary group and the important genes to distinguish between blood and the corresponding tissue in patients.

2011-03-17 | GSE24280 | GEO

Genome-wide expression profiling of leprosy and granuloma annulare skin lesions

Project description:Here we report the data generated by short-read sequencing of mRNA (polyA) isolated from granuloma annulare and leprosy skin lesions. Our main aim was to identify putative mRNA biomarkers for distinguishing leprosy from other differential diagnoses. Additionally, we also explored the distinction between MB and PB by using differential expression analysis as well as training a penalized logistic regression to select important features. Our results showed that few genes are enough to differentiate leprosy lesions, including paucibacillary cases, from other morphological and histopathological similar skin diseases. Some of these genes have been replicated in a larger and more heterogeneous sample with RT-qPCR, validating their classification potential. We also suggest important novel gene candidates to improve our understanding of molecular differences between MB and PB lesions, which could either pinpoint new pathways and targets for host-based specialized adjuvant treatment for leprosy. Finally, this dataset has been used to explore the relationship between cornification and keratinocyte-related genes and TGFB-mediated epithelial-mesenchymal transition (EMT), which could indicate that in skin, M. leprae could be de-differentiating, directly or indirectly, other cell types into a progenitor/stem-like phenotype, facilitating mycobacterial survival and migration within the host. Alternatively, this could highlight which pathways are activated during granuloma formation and/or skin barrier assembly/disassembly.

2021-10-01 | E-MTAB-10318 | biostudies-arrayexpress

Gene Expression Analysis of Blood PBMC Response to Mycobacterium leprae antigens

Project description:8 leprosy patients including 4 multibacillary (MB) and 4 paucibacillary (PB), and 8 non-leprosy controls including 4 healthy house contacts (HHCs) and 4 endemic controls (ECs) were included in the study. The immune response differences between leprosy patients and controls were evaluated by analyzing the transcriptional profiles of PBMCs to M. leprae sonicate antigens by RNA-seq. The analyses revealed potential biomarkers (including mRNAs and lncRNAs) preferentially expressed in PBMCs in leprosy patients that may be useful for early diagnosis of leprosy.

2021-07-16 | GSE179987 | GEO

Integration of cell type deconvolution with immune pathways identifies gene networks of host defense and immunopathology in leprosy

Project description:Transcriptome profiles derived from the site of human disease has led to the identification of genes that contribute to pathogenesis, yet the complex mixture of cell types in these lesions has been an obstacle for defining specific mechanisms. Leprosy provides an outstanding model to study host defense and pathogenesis in a human infectious disease, given its clinical spectrum which interrelates with the host immunologic and pathologic responses. Here, we investigated gene expression profiles derived from skin lesions for each clinical subtype of leprosy, analyzing gene co-expression modules by cell type deconvolution. In lesions from tuberculoid leprosy patients, those with the self-limited form of the disease, dendritic cells were linked with MMP12 as part of a tissue remodeling network that contributes to granuloma formation. In lesions from lepromatous leprosy patients, those with disseminated disease, macrophages were linked with a gene network that programs phagocytosis. In erythema nodosum leprosum, neutrophil and endothelial cell gene networks were identified as part of the vasculitis that results in tissue injury. The present integrated computational approach provides a systems approach towards identifying cell-defined functional networks that contribute to host defense and immunopathology at the site of human infectious disease.

2016-08-30 | GSE84893 | GEO

Blood RNA signature RISK4LEP predicts leprosy years before clinical onset

Project description:Exploratory RNA expression analysis during development of leprosy allows identification of RISK4LEP, a 4-gene blood RNA signature predicting leprosy years before clinical onset.

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FOXC1 in triple negative breast cancer [ChIP-seq]

Project description:To investigate FOXC1 chromatin binding, and the effect of FOXC1 CRISPR knockout in triple negative breast cancer cell lines MDA-MB-231, MDA-MB-468, Hs578t, and Bt-549.

2024-06-14 | GSE213840 | GEO

FOXC1 in triple negative breast cancer [RNA-seq]

Project description:To investigate FOXC1 chromatin binding, and the effect of FOXC1 CRISPR knockout in triple negative breast cancer cell lines MDA-MB-231, MDA-MB-468, Hs578t, and Bt-549.

2024-06-14 | GSE213839 | GEO

MDA-MB-231 Breast Cancer Bone Tropic vs Parental Hypoxic Secretome Analysis

Project description:The project profiled the expression patterns in hypoxia induced secretomes between MDA-MB-231 parental and MDA-MB-231 Bone Tropic (BT) breast cancer cell lines which have been previously generated by Massague and colleagues (Kang et al. Cancer Cell 2003).

2017-03-29 | MSV000080797 | MassIVE

MDA-MB-231 Breast Cancer Bone Tropic vs Parental Hypoxic Secretome Analysis

2015-05-28 | PXD000397 | Pride

Transcription profiling by array of human breast cancer cell line BT-474 with annexin A1 over-expression or silenced with siRNA to demonstrate design of multi-condition experiments

Project description:Multiple-condition experiment was desinged to be any number of conditions in an experiment without replicate observations for microarray and used to identify genes differentially expressed between different pairs of conditions (treatments).<br> In this study we used breast cancer stable cell lines for overexpressing and silencing annexin A1 (ANXA1), which belongs to a family of -dependent phospholipid binding proteins and are preferentially located on the cytosolic face of the plasma membrane. Cell lines overexpressing ANXA1 (MDA_MB-453/cDNA) were generated by introducing retroviral vectors containing ANXA1 cDNA (pBabe/ANXA1 cDNA) into breast cancer cell line MDA-MB-453 (a low expressor of ANXA1). Breast cancer cell line BT-474, a high expressor of ANXA1, was infected with ANXA1 siRNA-plasmid viruses to knockdown ANAXAI expressor (BT-474/siRNA) where nucleotides corresponding to siRNA were synthesized and ligated into the pLNCX retroviral vector [35,36]. We also used a pLNCX/U6 empty vector to infect BT-474 and obtained an empty vector expressor. Therefore, 5 breast cancer cell lines (MDA_MB-453, MDA_MB-453/cDNA, BT-474, BT-474/siRNA, and BT-474/U6) are attributed to two genotypes: MDA_MB-453 and BT-474. MCE was performed for microarray analysis with these 5 breast cancer cell lines, that is, only one sample was drawn from each breast cancer cell line.

2010-06-26 | E-MEXP-2775 | biostudies-arrayexpress

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