scholarly journals Histopathology and Genetic Biomarkers of Choroidal Melanoma

2020 ◽  
Vol 10 (22) ◽  
pp. 8081 ◽  
Author(s):  
Giuseppe Broggi ◽  
Andrea Russo ◽  
Michele Reibaldi ◽  
Daniela Russo ◽  
Silvia Varricchio ◽  
...  
Keyword(s):  
Choroidal Melanoma ◽  
Malignant Neoplasm ◽  
Cell Types ◽  
Epithelioid Cell ◽  
Tnm Staging ◽  
Cell Type ◽  
Mixed Cell ◽  
Histological Variants ◽  
Genetic Features ◽  
S 100

Choroidal melanoma (CM), despite its rarity, is the most frequent intraocular malignancy. Over time, several histological variants of CM have been distinguished, including spindle A and B cell, fascicular, epithelioid and necrotic type. However, they have been progressively abandoned as having no prognostic value and currently, the American Joint Committee of Cancer (AJCC) classification identifies three CM cell types: spindle, epithelioid and mixed cell type. Other rare histological variants of CM include: (i) diffuse melanoma; (ii) clear cell; and (iii) balloon cell melanoma. Immunohistochemically, CMs are stained with Human Melanoma Black 45 (HMB45) antigen, S-100 protein, Melan-A (also known as melanoma antigen recognized by T cells 1/MART-1), melanocyte inducing transcription factor (MITF), tyrosinase, vimentin, and Sex determining region Y-Box 10 (SOX10). Several genetic and histopathological prognostic factors of CM have been reported in the literature, including epithelioid cell type, TNM staging, extraocular extension, monosomy 3 and 6p gain and loss of BAP-1 gene. The aim of this review was to summarize the histopathological, immunohistochemical and genetic features of CM, establishing “the state of the art” and providing colleagues with practical tools to promptly deal with patients affected by this rare malignant neoplasm.

Clinicopathological Features and Gene Mutation Analysis of Gastrointestinal Stromal Tumors: A Series of 58 Patients

2021 ◽  
Author(s):  
hao cheng ◽  
Tian Qiu ◽  
Su-sheng Shi
Keyword(s):  
Spindle Cell ◽  
Cell Types ◽  
Epithelioid Cell ◽  
Wild Type ◽  
Cell Type ◽  
Mixed Cell ◽  
Stromal Tumors ◽  
Exon 11 ◽  
Mutant Forms ◽  
Spindle Cell Type

Abstract 【Background】In gastrointestinal stromal tumors (GISTs), mutually exclusive gain-of-function mutations of KIT and PDGFRA are associated with different mutation-dependent clinical behavior. The study aims to analyze the characteristics of the clinicopathology and genotypes in GISTs in China.【Methods】All adult patients with GIST located in the stomach or small intestine who underwent surgical resections in the Cancer Hospital, Chinese Academy of Medical Sciences from January 2009 to January 2019 without prior Imatinib(Glivec) treatment were included. Specimens were collected for histopathological examination, and mutations in c-kit and PDGFRα genes were analyzed by PCR and the next generation sequencing(NGS). The clinicopathological characteristics of each gene were also analyzed.【Results】A total of 58 GIST patients was included in the study. Among the genotypes, there were 51(87.9%) c-kit mutations, five(8.6%) PDGFRα mutations, and two(3.4%) wild-type mutations. Among the cell types, there were 40 cases(69.0%) of spindle cell type, three cases(5.2%) of epithelioid cell type, and three cases(5.2%) of mixed cell type. Among the four mutant forms of c-kit exon-11, the most common were point mutation in 16 cases(38.1%), deletion mutation in 13 cases(31.0%), insertion mutation in four cases(9.5%), and mixed mutation in nine cases(21.4%). According to the National Institutes of Health(NIH) risk grade, there were three cases(5.2%) with very-low risk, nine cases(15.5%) with low risk, 19 cases(32.8%) with medium risk, and 23 cases(39.7%) with high risk. There were significant differences in cell types among different gene types(P = 0.022) and significant differences in tumor risk among different mutant forms of c-kit gene exon-11(P = 0.039).【Conclusion】In c-kit mutations, spindle cell type was significantly more than epithelioid cell type and mixed cell type. In PDGFRα mutations, spindle cell type and mixed cell type were prevalent. In wild type, spindle cell type and epithelioid cell type were significantly common. A high risk of deletion mutation and mixed mutation is expected in the c-kit exon-11 mutation form, while the intermediate risk of point and insertion mutations are common.

scholarly journals DNA Methylation Profiles of Purified Cell Types in Bronchoalveolar Lavage: Applications for Mixed Cell Paediatric Pulmonary Studies

2021 ◽  
Vol 12 ◽  
Author(s):  
Shivanthan Shanthikumar ◽  
Melanie R. Neeland ◽  
Richard Saffery ◽  
Sarath C. Ranganathan ◽  
Alicia Oshlack ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bronchoalveolar Lavage ◽  
Association Studies ◽  
Cell Types ◽  
Alveolar Epithelial Cells ◽  
Cell Type ◽  
Mixed Cell ◽  
Alveolar Epithelial ◽  
Cell Type Composition ◽  
Type Composition

In epigenome-wide association studies analysing DNA methylation from samples containing multiple cell types, it is essential to adjust the analysis for cell type composition. One well established strategy for achieving this is reference-based cell type deconvolution, which relies on knowledge of the DNA methylation profiles of purified constituent cell types. These are then used to estimate the cell type proportions of each sample, which can then be incorporated to adjust the association analysis. Bronchoalveolar lavage is commonly used to sample the lung in clinical practice and contains a mixture of different cell types that can vary in proportion across samples, affecting the overall methylation profile. A current barrier to the use of bronchoalveolar lavage in DNA methylation-based research is the lack of reference DNA methylation profiles for each of the constituent cell types, thus making reference-based cell composition estimation difficult. Herein, we use bronchoalveolar lavage samples collected from children with cystic fibrosis to define DNA methylation profiles for the four most common and clinically relevant cell types: alveolar macrophages, granulocytes, lymphocytes and alveolar epithelial cells. We then demonstrate the use of these methylation profiles in conjunction with an established reference-based methylation deconvolution method to estimate the cell type composition of two different tissue types; a publicly available dataset derived from artificial blood-based cell mixtures and further bronchoalveolar lavage samples. The reference DNA methylation profiles developed in this work can be used for future reference-based cell type composition estimation of bronchoalveolar lavage. This will facilitate the use of this tissue in studies examining the role of DNA methylation in lung health and disease.

scholarly journals DPre: computational identification of differentiation bias and genes underlying cell type conversions

2019 ◽  
Author(s):  
Simon Steffens ◽  
Xiuling Fu ◽  
Fangfang He ◽  
Yuhao Li ◽  
Isaac A Babarinde ◽  
...  
Keyword(s):  
Ectopic Expression ◽  
Large Cell ◽  
Cell Types ◽  
Supplementary Information ◽  
Computational Techniques ◽  
Cell Type ◽  
Mixed Cell ◽  
Directional Bias ◽  
Differentiated Cells

Abstract Summary Cells are generally resistant to cell type conversions, but can be converted by the application of growth factors, chemical inhibitors and ectopic expression of genes. However, it remains difficult to accurately identify the destination cell type or differentiation bias when these techniques are used to alter cell type. Consequently, there is demand for computational techniques that can help researchers understand both the cell type and differentiation bias. While advanced tools identifying cell types exist for single cell data and the deconvolution of mixed cell populations, the problem of exploring partially differentiated cells of indeterminate transcriptional identity has not been addressed. To fill this gap, we developed driver-predictor, which relies on scoring per gene transcriptional similarity between RNA-Seq datasets to reveal directional bias of differentiation. By comparing against large cell type transcriptome libraries or a desired target expression profile, the tool enables the user to visualize both the changes in transcriptional identity as well as the genes accounting for the cell type changes. This software will be a powerful tool for researchers to explore in vitro experiments that involve cell type conversions. Availability and implementation Source code is open source under the MIT license and is freely available on https://github.com/LoaloaF/DPre. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Virtual methylome dissection facilitated by single-cell analyses

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Liduo Yin ◽  
Yanting Luo ◽  
Xiguang Xu ◽  
Shiyu Wen ◽  
Xiaowei Wu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Nonnegative Matrix ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Cell Type ◽  
Mixed Cell ◽  
Numerous Cell ◽  
Cell Type Specific ◽  
Methylation Patterns

Abstract Background Numerous cell types can be identified within plant tissues and animal organs, and the epigenetic modifications underlying such enormous cellular heterogeneity are just beginning to be understood. It remains a challenge to infer cellular composition using DNA methylomes generated for mixed cell populations. Here, we propose a semi-reference-free procedure to perform virtual methylome dissection using the nonnegative matrix factorization (NMF) algorithm. Results In the pipeline that we implemented to predict cell-subtype percentages, putative cell-type-specific methylated (pCSM) loci were first determined according to their DNA methylation patterns in bulk methylomes and clustered into groups based on their correlations in methylation profiles. A representative set of pCSM loci was then chosen to decompose target methylomes into multiple latent DNA methylation components (LMCs). To test the performance of this pipeline, we made use of single-cell brain methylomes to create synthetic methylomes of known cell composition. Compared with highly variable CpG sites, pCSM loci achieved a higher prediction accuracy in the virtual methylome dissection of synthetic methylomes. In addition, pCSM loci were shown to be good predictors of the cell type of the sorted brain cells. The software package developed in this study is available in the GitHub repository (https://github.com/Gavin-Yinld). Conclusions We anticipate that the pipeline implemented in this study will be an innovative and valuable tool for the decoding of cellular heterogeneity.

scholarly journals Cellular deconvolution of GTEx tissues powers eQTL studies to discover thousands of novel disease and cell-type associated regulatory variants

2019 ◽  
Author(s):  
Margaret K. R. Donovan ◽  
Agnieszka D’Antonio-Chronowska ◽  
Matteo D’Antonio ◽  
Kelly A. Frazer
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Expression Profiles ◽  
Malignant Neoplasm ◽  
Cell Types ◽  
Mouse Cell ◽  
Tissue Type ◽  
Cell Type ◽  
Signature Genes ◽  
Different Cell Types

AbstractThe Genotype-Tissue Expression (GTEx) resource has contributed a wealth of novel insights into the regulatory impact of genetic variation on gene expression across human tissues, however thus far has not been utilized to study how variation acts at the resolution of the different cell types composing the tissues. To address this gap, using liver and skin as a proof-of-concept tissues, we show that readily available signature genes based on expression profiles of mouse cell types can be used to deconvolute the cellular composition of human GTEx tissues. We then deconvoluted 6,829 bulk RNA-seq samples corresponding to 28 GTEx tissues and show that we are able to quantify cellular heterogeneity, determining both the different cell types present in each of the tissues and how their proportions vary between samples of the same tissue type. Conducting eQTL analyses for GTEx liver and skin samples using cell type composition estimates as interaction terms, we identified thousands of novel genetic associations that had lower effect sizes and were cell-type-associated. We further show that cell-type-associated eQTLs in skin colocalize with melanoma, malignant neoplasm, and infection signatures, indicating variants that influence gene expression in distinct skin cell types play important roles in skin traits and disease. Overall, our study provides a framework to estimate the relative fractions of different cell types in GTEx tissues using signature genes from mouse cell types and functionally characterize human genetic variation that impacts gene expression in a cell-type-specific manner.

Correlation of Heterogeneity for Chromosome 3 Copy Number with Cell Type in Choroidal Melanoma of Mixed-Cell Type

2006 ◽  
Vol 47 (12) ◽  
pp. 5177 ◽  
Author(s):  
Teresa Sandinha ◽  
Maura Farquharson ◽  
Ian McKay ◽  
Fiona Roberts
Keyword(s):  
Copy Number ◽  
Choroidal Melanoma ◽  
Chromosome 3 ◽  
Cell Type ◽  
Mixed Cell

scholarly journals CyAnno: A semi-automated approach for cell type annotation of mass cytometry datasets

2020 ◽  
Author(s):  
Abhinav Kaushik ◽  
Diane Dunham ◽  
Ziyuan He ◽  
Monali Manohar ◽  
Manisha Desai ◽  
...  
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
Cell Types ◽  
Training Data ◽  
Live Cells ◽  
Cell Type ◽  
Mixed Cell ◽  
Learning Framework ◽  
Single Cell Type ◽  
Rare Cells

AbstractFor immune system monitoring in large-scale studies at the single-cell resolution using CyTOF, (semi-)automated computational methods are applied for annotating live cells of mixed cell types. Here, we show that the live cell pool can be highly enriched with undefined heterogeneous cells, i.e. ‘ungated’ cells, and that current (semi-)automated approaches ignore their modeling resulting in misclassified annotations. Therefore, we introduce ‘CyAnno’, a novel semi-automated approach for deconvoluting the unlabeled cytometry dataset based on a machine learning framework utilizing manually gated training data that allows the integrative modeling of ‘gated’ cell types and the ‘ungated’ cells. By applying this framework on several CyTOF datasets, we demonstrated that including the ‘ungated’ cells can lead to a significant increase in the prediction accuracy of the ‘gated’ cell types. CyAnno can be used to identify even a single cell type, including rare cells, with higher efficacy than current state-of-the-art semi-automated approaches.

scholarly journals A Review of Gastrointestinal Stromal Tumours- A Single Centre Experience

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Muhammad ZR ◽  
Norra H ◽  
Suhaila A ◽  
Norlelawati AT ◽  
Naznin M
Keyword(s):  
Histopathological Examination ◽  
Gastrointestinal Stromal Tumour ◽  
Risk Behaviour ◽  
Cell Types ◽  
Epithelioid Cell ◽  
Low Risk ◽  
Future Research ◽  
Mixed Cell ◽  
Common Location ◽  
Number Of Publications

Introduction: Gastrointestinal stromal tumour (GIST) is relatively rare. The clinical behaviour of GIST ranges from benign to frank sarcoma. The diagnosis is established through histopathological examination and immunohistochemistry profile. In Malaysia, the number of publications related to GIST is relatively rare. This study was therefore conducted to examine the demographic, histopathological and immunohistochemical features of GIST cases diagnosed in the Department of Pathology, Hospital Tengku Ampuan Afzan, Kuantan, Pahang from 2009 until 2014. Methods: Past histopathological records were reviewed. Demographic and histopathological and immunohistochemical data of patients diagnosed were collected. Results: There were 28 cases (14 males and 14 females) diagnosed as GIST. Mean age was 56.4 years, and the majority were above 40 years of age (85.7%). Stomach was the most common location (42.9%), followed by small intestine (28.6%). In 23 cases (82%), the tumours exhibited spindle cell morphology, while epithelioid cell and mixed cell types were seen in 3 cases (11%) and 2 cases (7%), respectively. Five cases were categorised as very low risk to low risk behaviour, while 18 cases were intermediate to high. None of the histological parameters analysed which include tumour morphology, necrosis, haemorrhage, nuclear atypia and mean number of mitoses showed significance difference between the different risk behaviour groups. Positivity with KIT (CD117), considered to be the defining immunohistochemistry feature, was negative in 2 cases. Conclusion: Although this study is a retrospective study, the findings contribute to the knowledge on GISTS in Malaysia. Future research related to GISTs in Malaysia should focus on molecular analyses for KIT and PDGFRA mutations for diagnostic confirmation especially in KIT-negative cases and also for the purpose of therapeutic response correlations.

Dendritic cells of the human epidermis: immuno-electron microscopic studies of la antigen reactivity

1978 ◽  
Vol 36 (2) ◽  
pp. 644-645
Author(s):  
G. Rowden ◽  
M. G. Lewis ◽  
T. M. Phillips
Keyword(s):  
Dendritic Cells ◽  
Langerhans Cells ◽  
Cell Types ◽  
Cell Type ◽  
Electron Microscopic ◽  
La Antigen ◽  
Microscopic Studies ◽  
A Cell ◽  
C3 Receptors ◽  
Antigen Reactivity

Langerhans cells of mammalian stratified squamous epithelial have proven to be an enigma since their discovery in 1868. These dendritic suprabasal cells have been considered as related to melanocytes either as effete cells, or as post divisional products. Although grafting experiments seemed to demonstrate the independence of the cell types, much confusion still exists. The presence in the epidermis of a cell type with morphological features seemingly shared by melanocytes and Langerhans cells has been especially troublesome. This so called "indeterminate", or " -dendritic cell" lacks both Langerhans cells granules and melanosomes, yet it is clearly not a keratinocyte. Suggestions have been made that it is related to either Langerhans cells or melanocyte. Recent studies have unequivocally demonstrated that Langerhans cells are independent cells with immune function. They display Fc and C3 receptors on their surface as well as la (immune region associated) antigens.

scholarly journals Fibroblasts Influence the Efficacy, Resistance, and Future Use of Vaccines and Immunotherapy in Cancer Treatment

Vaccines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 634
Author(s):  
Bailee H. Sliker ◽  
Paul M. Campbell
Keyword(s):  
Transforming Growth Factor ◽  
Transforming Growth Factor Β ◽  
Cell Types ◽  
Fibroblast Activation Protein ◽  
Cancer Associated Fibroblasts ◽  
Cell Type ◽  
Adaptive Immune ◽  
Adaptive Immune Cells ◽  
New Research ◽  
Tumor Types

Tumors are composed of not only epithelial cells but also many other cell types that contribute to the tumor microenvironment (TME). Within this space, cancer-associated fibroblasts (CAFs) are a prominent cell type, and these cells are connected to an increase in tumor progression as well as alteration of the immune landscape present in and around the tumor. This is accomplished in part by their ability to alter the presence of both innate and adaptive immune cells as well as the release of various chemokines and cytokines, together leading to a more immunosuppressive TME. Furthermore, new research implicates CAFs as players in immunotherapy response in many different tumor types, typically by blunting their efficacy. Fibroblast activation protein (FAP) and transforming growth factor β (TGF-β), two major CAF proteins, are associated with the outcome of different immunotherapies and, additionally, have become new targets themselves for immune-based strategies directed at CAFs. This review will focus on CAFs and how they alter the immune landscape within tumors, how this affects response to current immunotherapy treatments, and how immune-based treatments are currently being harnessed to target the CAF population itself.

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