Gene Expression Profiling of Mycosis Fungoides in Early and Tumor Stage-A Proof-of-Concept Study Using Laser Capture/Single Cell Microdissection and NanoString Analysis.
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ABSTRACT:
SUBMITTER: Lai J
PROVIDER: S-EPMC8621072 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Laser capture microdissection (LCM) allows the precise procurement of enriched cell populations from a heterogeneous tissue, or live cell culture, under direct microscopic visualization. Histologically enriched cell populations can be procured by harvesting cells of interest directly or isolating specific cells by ablating unwanted cells. The basic components of laser microdissection technology are (a) visualization of cells via light microscopy, (b) transfer of laser energy to a thermolabile polymer with either the formation of a polymer-cell composite (capture method) or transfer of laser energy via an ultraviolet laser to photovolatize a region of tissue (cutting method), and (c) removal of cells of interest from the heterogeneous tissue section. The capture and cutting methods (instruments) for laser microdissection differ in the manner by which cells of interest are removed from the heterogeneous sample. Laser energy in the capture method is infrared (810 nm), while in the cutting mode the laser is ultraviolet (355 nm). Infrared lasers melt a thermolabile polymer that adheres to the cells of interest, whereas ultraviolet lasers ablate cells for either removal of unwanted cells or excision of a defined area of cells. LCM technology is applicable to an array of applications including mass spectrometry, DNA genotyping and loss-of-heterozygosity analysis, RNA transcript profiling, cDNA library generation, proteomics discovery, and signal kinase pathway profiling. This chapter describes LCM using an Arcturus(XT) instrument for downstream protein sample analysis and using an mmi CellCut Plus® instrument for RNA analysis via NanoString technology.
| S-EPMC3766583 | biostudies-literature
Project description:MicroRNAs (miRNAs) are small RNA species that regulate gene expression post-transcriptionally and are aberrantly expressed in many malignancies including lymphoma. However, the role of miRNAs in the pathogenesis of T-cell lymphoid malignancies is poorly understood. Previously we examined the miRNA profile of Sézary syndrome (Sz), a leukemia of skin-homing memory T cells. In this study we determined the complete miRNome of mycosis fungoides (MF), the most common type of cutaneous T cell lymphoma. The miRNA profile of skin biopsies from 19 patients with tumor stage MF and 12 patients with benign inflammatory dermatoses (eczema and lichen planus) were compared by microarray analysis. We identified 49 miRNAs that are differentially expressed in tumor stage MF compared to benign inflammatory dermatoses using ANOVA analysis (P < 0.05, Benjamini-Hochberg corrected). The majority of the differentially expressed miRNAs (30/49) were up-regulated in tumor stage MF. The most significant differentially expressed were miR-155 and miR-92a (both up-regulated in tumor stage MF), while miR-93 showed the highest up-regulation in tumor stage MF with a fold difference of 5.8. Differential expression of a selection of these miRNAs was validated by miRNA-Q-PCR on additional test groups (tumors and controls). None of the miRNAs up-regulated in tumor stage MF was previously shown to be up-regulated in Sz, and only 2 of the 19 miRNAs down-regulated in tumor stage MF were also down-regulated in Sz. Taken together this report is the first describing the miRNA signature of tumor stage MF.
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Project description:Mycosis fungoides (MF) is the most common subtype of cutaneous T-cell lymphoma. Early-stage disease is characterized by superficial infiltrates of small- to medium-sized atypical epidermotropic T lymphocytes that are clonal related. Nevertheless, the percentage of atypical T cells is low with many admixed reactive immune cells. Despite earlier studies, the composition and spatial characteristics of the cutaneous lymphocytic infiltrate has been incompletely characterized. Here, we applied mass cytometry to profile the immune system in skin biopsies of patients with early-stage MF and in normal skin from healthy individuals. Single-cell suspensions were prepared and labeled with a 43-antibody panel, and data were acquired on a Helios mass cytometer. Unbiased hierarchical clustering of the data identified the major immune lineages and heterogeneity therein. This revealed patient-unique cell clusters in both the CD4+ and myeloid cell compartments but also phenotypically distinct cell clusters that were shared by most patients. To characterize the immune compartment in the tissue context, we developed a 36-antibody panel and performed imaging mass cytometry on MF skin tissue. This visualized the structure of MF skin and the distribution of CD4+ T cells, regulatory T cells, CD8+ T cells, malignant T cells, and various myeloid cell subsets. We observed clusters of CD4+ T cells and multiple types of dendritic cells (DCs) identified through differential expression of CD11c, CD1a, and CD1c in the dermis. These results indicated substantial heterogeneity in the composition of the local immune infiltrate but suggest a prominent role for clustered CD4-DC interactions in disease pathogenesis. Probably, the local inhibition of such interactions may constitute an efficient treatment modality.
| S-EPMC8997708 | biostudies-literature
Project description:Mycosis fungoides patients who develop tumors or extracutaneous involvement usually have a poor prognosis with no curative therapy available so far. In the present EORTC multicenter study, the genomic profile of 41 skin biopsies from tumor-stage mycosis fungoides was analyzed using a high-resolution oligo-array comparative genomic hybridization platform. Seventy-six percent of cases showed genomic aberrations. The most common imbalances were gains of 7q33.3q35 followed by 17q21.1, 8q24.21, 9q34qter and 10p14 and losses of 9p21.3 followed by 9q31.2, 17p13.1, 13q14.11, 6q21.3, 10p11.22, 16q23.2 and 16q24.3. Three specific chromosomal regions, 9p21.3, 8q24.21 and 10q26qter were defined as prognostic markers exhibiting a significant correlation with overall survival (P= .042, P= .017 and P= .022, respectively). Moreover, we have established two MFt genomic subgroups distinguishing a stable group (0-5 DNA aberrations) and an unstable group (> 5 DNA aberrations), showing that the genomic unstable group had a shorter overall survival (P=.05). We therefore conclude that specific chromosomal abnormalities, such as gains of 8q24.21 (MYC) and losses of 9p21.3 (CDKN2A, CDKN2B and MTAP), and 10q26qter (MGMT and EBF3) may play an important role in prognosis. In addition, we describe the MFt genomic instability profile. Forty-one MFt were studied by arrayCGH using the Human Genome CGH 44K microarrays (G4410B and G4426B, Agilent Technologies, Palo Alto, CA, USA). In each microarray experiment, DNA obtained from a 20x10 um sections snap frozen samples from tumoral MF lesions was compared with commercial pools of healthy female DNA (Promega, Madison, WI, USA).
2010-05-06 | E-GEOD-18098 | biostudies-arrayexpress
Project description:Identifying neuronal molecular markers with restricted patterns of expression is a crucial step in dissecting the numerous pathways and functions of the brain. While the dorsomedial nucleus of the hypothalamus (DMH) has been implicated in a host of physiological processes, current functional studies have been limited by the lack of molecular markers specific for DMH. Identification of such markers would facilitate the development of mouse models with DMH-specific genetic manipulations. Here we used a combination of laser-capture microdissection (LCM) and gene expression profiling to identify genes that are highly expressed within the DMH relative to adjacent hypothalamic regions. Six of the most highly expressed of these genes, Gpr50, 4930511J11Rik, Pcsk5, Grp, Sulf1, and Ror?, were further characterized by real-time polymerase chain reaction (PCR) analysis and in situ hybridization histochemistry. The genes identified in this article will provide the basis for future gene-targeted approaches for studying DMH function.
| S-EPMC3741992 | biostudies-literature
Project description:The etiology of Type 1 Diabetes (T1D) remains elusive. Enzymatically isolated and cultured (EIC) islets cannot fully reflect the natural protein composition and disease process of in vivo islets, because of the stress from isolation procedures. In order to study islet protein composition in conditions close to the natural environment, we performed proteomic analysis of EIC islets, and laser capture microdissected (LCM) human islets and acinar tissue from fresh-frozen pancreas sections of three cadaveric donors. 1104 and 706 proteins were identified from 6 islets equivalents (IEQ) of LCM islets and acinar tissue, respectively. The proteomic profiles of LCM islets were reproducible within and among cadaveric donors. The endocrine hormones were only detected in LCM islets, whereas catalytic enzymes were significantly enriched in acinar tissue. Furthermore, high overlap (984 proteins) and similar function distribution were found between LCM and EIC islets proteomes, except that EIC islets had more acinar contaminants and stress-related signal transducer activity proteins. The comparison among LCM islets, LCM acinar tissue and EIC islets proteomes indicates that LCM combined with proteomic methods enables accurate and unbiased profiling of islet proteome from frozen pancreata. This paves the way for proteomic studies on human islets during the progression of T1D.The etiological agent triggering autoimmunity against beta cells in Type 1 diabetes (T1D) remains obscure. The in vitro models available (enzymatically isolated and cultured islets, EIC islets) do not accurately reflect what happens in vivo due to lack of the natural environment where islets exist and the preparation-induced changes in cell physiology. The importance of this study is that we investigated the feasibility of laser capture microdissection (LCM) for the isolation of intact islets from frozen cadaveric pancreatic tissue sections. We compared the protein profile of LCM islets (9 replicates from 3 cadaveric donors) with that of both LCM acinar tissues (6 replicates from the same 3 cadaveric donor as LCM islets) and EIC islets (at least 4 replicates for each sample with the same islets equivalents) by using proteomics techniques with advanced instrumentation, nanoLC-Q Exactive HF Orbitrap mass spectrometry (nano LC-MS/MS). The results demonstrate that the LCM method is reliable in isolating islets with an intact environment. LCM-based islet proteomics is a feasible approach to obtain good proteome coverage for assessing the pathology of T1D using cadaveric pancreatic samples, even from very small sample amounts. Future applications of this LCM-based proteomic method may help us understand the pathogenesis of T1D and identify potential biomarkers for T1D diagnosis at an early stage.
| S-EPMC5110395 | biostudies-literature
Project description:AimTo examine the gene expression profile of gastric cancer (GC) by combination of laser capture microdissection (LCM) and microarray and to correlate the profiling with histological subtypes.MethodsUsing LCM, pure cancer cells were procured from 45 cancerous tissues. After procurement of about 5000 cells, total RNA was extracted and the quality of RNA was determined before further amplification and hybridization. One microgram of amplified RNA was converted to cDNA and hybridized to cDNA microarray.ResultsAmong 45 cases, only 21 were qualified for their RNAs. A total of 62 arrays were performed. These included 42 arrays for cancer (21 cases with dye-swab duplication) and 20 arrays for non-tumorous cells (10 cases with dye-swab duplication) with universal reference. Analyzed data showed 504 genes were differentially expressed and could distinguish cancerous and non-cancerous groups with more than 99% accuracy. Of the 504 genes, trefoil factors 1, 2, and 3 were in the list and their expression patterns were consistent with previous reports. Immunohistochemical staining of trefoil factor 1 was also consistent with the array data. Analyses of the tumor group with these 504 genes showed that there were 3 subgroups of GC that did not correspond to any current classification system, including Lauren's classification.ConclusionBy using LCM, linear amplification of RNA, and cDNA microarray, we have identified a panel of genes that have the power to discriminate between GC and non-cancer groups. The new molecular classification and the identified novel genes in gastric carcinogenesis deserve further investigations to elucidate their clinicopathological significance.
| S-EPMC4725172 | biostudies-literature
Project description:Mycosis fungoides patients who develop tumors or extracutaneous involvement usually have a poor prognosis with no curative therapy available so far. In the present EORTC multicenter study, the genomic profile of 41 skin biopsies from tumor-stage mycosis fungoides was analyzed using a high-resolution oligo-array comparative genomic hybridization platform. Seventy-six percent of cases showed genomic aberrations. The most common imbalances were gains of 7q33.3q35 followed by 17q21.1, 8q24.21, 9q34qter and 10p14 and losses of 9p21.3 followed by 9q31.2, 17p13.1, 13q14.11, 6q21.3, 10p11.22, 16q23.2 and 16q24.3. Three specific chromosomal regions, 9p21.3, 8q24.21 and 10q26qter were defined as prognostic markers exhibiting a significant correlation with overall survival (P= .042, P= .017 and P= .022, respectively). Moreover, we have established two MFt genomic subgroups distinguishing a stable group (0-5 DNA aberrations) and an unstable group (> 5 DNA aberrations), showing that the genomic unstable group had a shorter overall survival (P=.05). We therefore conclude that specific chromosomal abnormalities, such as gains of 8q24.21 (MYC) and losses of 9p21.3 (CDKN2A, CDKN2B and MTAP), and 10q26qter (MGMT and EBF3) may play an important role in prognosis. In addition, we describe the MFt genomic instability profile.
2009-09-15 | GSE18098 | GEO
Project description:Patients with mycosis fungoides (MF) developing tumors or extracutaneous lesions usually have a poor prognosis with no cure has so far been available. To identify potential novel biomarkers for MF at the tumor stage, a genomic mapping of 41 cutaneous lymphoma biopsies was used to explore for significant genes.The gene expression profiling datasets of MF were obtained from Gene Expression Omnibus database (GEO). Gene modules were simulated using Weighted Gene Co-expression Network Analysis (WGCNA) and the top soft-connected genes (hub genes) were filtrated with a threshold (0.5). Subsequently, module eigengenes were calculated and significant biological pathways were enriched based on the KEGG database.Four genetic modules were simulated with 3263 genes collected from the whole genomic profile based on cutoff values. Significant diseases genetic terminologies associated with tumor stage MF were found in black module. Subsequently, 13 hub genes including CFLAR, GCNT2, IFNG, IL17A, IL22, MIP, PLCG1, PTH, PTPN6, REG1A, SNAP25, SUPT7L, and TP63 were shown to be related to cutaneous T-cell lymphoma (CTCL) and adult T-cell lymphoma/leukemia (ATLL).In summary, in addition to the reported genes (IL17F, PLCG1, IFNG, and PTH) in CTCL/ATLL, the other high instable genes may serve as novel biomarkers for the regulation of the biological processes and molecular mechanisms of CTLT (MF/SS).
| S-EPMC6392713 | biostudies-literature
Project description:Mycosis fungoides (MF) is the most common and best studied of cutaneous T-cell lymphoma (CTCL). Three clinical cutaneous stages have been described (patch, plaque and tumor) as the disease progress developing also the disease lymph node, peripheral blood or systemic involvement in late stages. Clinical and pathologic diagnosis of early MF stages (patch and plaque) is difficult as its morphologic similarity to inflammatory dermatoses and low proportion of tumoral cells.
2018-06-21 | GSE109421 | GEO