Tumor type and single-cell/mesothelial-like cell pattern of breast carcinoma metastases in pleural and peritoneal effusions

2010 ◽  
Vol 40 (4) ◽  
pp. 311-315 ◽  
Author(s):  
Tatjana Antic ◽  
Yun Gong ◽  
Nour Sneige
Keyword(s):  
Breast Carcinoma ◽  
Single Cell ◽  
Tumor Type ◽  
Cell Pattern

4 Molecularly guided multiplexed digital spatial analysis reveals differential gene expression profiles in the WNT-β-catenin pathway between melanoma and prostate tumors

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A4-A4
Author(s):  
Anushka Dikshit ◽  
Dan Zollinger ◽  
Karen Nguyen ◽  
Jill McKay-Fleisch ◽  
Kit Fuhrman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Molecule ◽  
Spatial Information ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Fluorescence Assay ◽  
Differentially Expressed ◽  
Tumor Type ◽  
Prostate Tumors

BackgroundThe canonical WNT-β-catenin signaling pathway is vital for development and tissue homeostasis but becomes strongly tumorigenic when dysregulated. and alter the transcriptional signature of a cell to promote malignant transformation. However, thorough characterization of these transcriptomic signatures has been challenging because traditional methods lack either spatial information, multiplexing, or sensitivity/specificity. To overcome these challenges, we developed a novel workflow combining the single molecule and single cell visualization capabilities of the RNAscope in situ hybridization (ISH) assay with the highly multiplexed spatial profiling capabilities of the GeoMx™ Digital Spatial Profiler (DSP) RNA assays. Using these methods, we sought to spatially profile and compare gene expression signatures of tumor niches with high and low CTNNB1 expression.MethodsAfter screening 120 tumor cores from multiple tumors for CTNNB1 expression by the RNAscope assay, we identified melanoma as the tumor type with the highest CTNNB1 expression while prostate tumors had the lowest expression. Using the RNAscope Multiplex Fluorescence assay we selected regions of high CTNNB1 expression within 3 melanoma tumors as well as regions with low CTNNB1 expression within 3 prostate tumors. These selected regions of interest (ROIs) were then transcriptionally profiled using the GeoMx DSP RNA assay for a set of 78 genes relevant in immuno-oncology. Target genes that were differentially expressed were further visualized and spatially assessed using the RNAscope Multiplex Fluorescence assay to confirm GeoMx DSP data with single cell resolution.ResultsThe GeoMx DSP analysis comparing the melanoma and prostate tumors revealed that they had significantly different gene expression profiles and many of these genes showed concordance with CTNNB1 expression. Furthermore, immunoregulatory targets such as ICOSLG, CTLA4, PDCD1 and ARG1, also demonstrated significant correlation with CTNNB1 expression. On validating selected targets using the RNAscope assay, we could distinctly visualize that they were not only highly expressed in melanoma compared to the prostate tumor, but their expression levels changed proportionally to that of CTNNB1 within the same tumors suggesting that these differentially expressed genes may be regulated by the WNT-β-catenin pathway.ConclusionsIn summary, by combining the RNAscope ISH assay and the GeoMx DSP RNA assay into one joint workflow we transcriptionally profiled regions of high and low CTNNB1 expression within melanoma and prostate tumors and identified genes potentially regulated by the WNT- β-catenin pathway. This novel workflow can be fully automated and is well suited for interrogating the tumor and stroma and their interactions.GeoMx Assays are for RESEARCH ONLY, not for diagnostics.

The Multiple Faces of Carcinoid Tumor: Performance Characteristics of Low-Grade Neuroendocrine Carcinoma Metastatic to the Liver in an Educational Interlaboratory Slide Comparison Program

2011 ◽  
Vol 135 (3) ◽  
pp. 354-360
Author(s):  
Amy C Clayton ◽  
Patricia G Wasserman ◽  
Rhona J Souers ◽  
Beth Anne Chmara ◽  
Andrew Renshaw ◽  
...  
Keyword(s):  
Single Cell ◽  
Neuroendocrine Carcinoma ◽  
Benign Neoplasm ◽  
Poor Performance ◽  
Specific Reference ◽  
Low Grade ◽  
Cell Pattern ◽  
Not Otherwise Specified ◽  
Glass Slides ◽  
Large Clusters

Abstract Context.—Cytologic features of low-grade neuroendocrine carcinoma are well described in primary sites. There are fewer reports of the cytologic features specific to metastatic liver lesions or the frequency of misdiagnosis. Objective.—To identify discriminating cytologic features and characterize the rate of misdiagnosis of low-grade neuroendocrine tumors metastatic to the liver in an educational interlaboratory slide comparison program. Design.—Glass slides with the specific reference diagnosis of metastatic low-grade neuroendocrine tumor involving liver were circulated to 175 laboratories, with 575 participant responses in the College of American Pathologists Interlaboratory Comparison Program in Nongynecologic Cytology. Eight specific cytologic features were assessed to identify predictors of poor performance (>10% misdiagnosis). Results.—There was an exact match diagnosis in 496 of 575 responses (86%); 555 of 575 responses (96.5%) were correctly identified as malignant. Incorrect responses included adenocarcinoma (27), hepatocellular neoplasm (21), small cell carcinoma (11), benign neoplasm not otherwise specified (6), benign liver (3) and inflammation (3). Three features were significantly associated with the misdiagnosis of adenocarcinoma: presence of large clusters (P  =  .02), lack of single-cell pattern (P  =  .02), and lack of stripped nuclei (P  =  .01). Conclusion.—Participants often recognize metastatic low-grade neuroendocrine carcinoma in an educational glass-slide program. Adenocarcinoma was the most common incorrect diagnosis, especially in the presence of large cellular clusters or absence of a single-cell pattern or stripped nuclei.

scholarly journals The cytomorphologic spectrum of small-cell carcinoma and large-cell neuroendocrine carcinoma in body cavity effusions: A study of 68 cases

CytoJournal ◽  
2011 ◽  
Vol 8 ◽  
pp. 18 ◽  
Author(s):  
Walid E. Khalbuss ◽  
Huaitao Yang ◽  
Qian Lian ◽  
Abdelmonem Elhosseiny ◽  
Liron Pantanowitz ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Single Cell ◽  
Small Cell Carcinoma ◽  
Neuroendocrine Carcinoma ◽  
Large Cell ◽  
Body Cavity ◽  
Small Cell ◽  
Cell Clusters ◽  
Cell Pattern ◽  
Ancillary Studies

Background: Small-cell carcinoma (SCC) and large-cell neuroendocrine carcinoma (LCNEC) are uncommon in serous body cavity effusions. The purpose of this study is to examine the cytomorphological spectrum of SCC and LCNEC in body cavity serous fluids. Materials and Methods: We have 68 cases from 53 patients who had metastatic SCC or LCNEC diagnoses. All cytology slides and the available clinical data, histological follow-up, and ancillary studies were reviewed. Results: A total of 68 cases (60 pleural, 5 peritoneal, and 3 pericardial effusions) from 53 patients with an average age of 73 years (age range 43-92 years) were reported as diagnostic or suspicious of SCC (52 cases) or LCNEC (16 cases). The primary site was lung in 56 cases, pancreas in 6 cases, and 2 cases each from cervix, colon, and the head and neck region. Of the 68 cases, 48 cases had no history of malignancy of the same type. Ancillary studies were used in 46 cases (68%) including flow cytometric studies in 5 cases. There were three predominant cytomorphological patterns observed including small-cell clusters with prominent nuclear molding (33 cases, 49%), large-cell clusters mimicking non-small-cell carcinoma (18 cases, 26%), and single-cell pattern mimicking lymphoma (17 cases, 25%). Significant apoptosis was seen in 22 cases (33%) and marked tumor cell cannibalism was seen in 11 cases (16%). Nucleoli were prominent in 16 cases (24%). The most frequent neuroendocrine markers performed were synaptophysin and chromogranin. Conclusions: The most common cytomorphologic patterns seen in body cavity effusions of SCC and LCNEC were small-cell clusters with nuclear molding. However, in 51% of the cases either a predominant single-cell pattern mimicking lymphoma or large-cell clusters mimicking non-small carcinoma were noted. In our experience, effusions were the first manifestation of disease in the majority of patients diagnosed with neuroendocrine carcinoma. Therefore, familiarity with the cytomorphological spectrum of neuroendocrine carcinomas in fluid cytology may help in rapidly establishing an accurate diagnosis and in directing appropriate management.

IMMU-51. SINGLE-CELL ANALYSIS OF TUMOR-ASSOCIATED MICROGLIA AND MACROPHAGES FROM HUMAN GLIOBLASTOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi104-vi104
Author(s):  
Atul Anand ◽  
Rikke Sick Andersen ◽  
Mark Burton ◽  
Dylan Scott Lykke Harwood ◽  
Frantz Rom Poulsen ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Primary Brain Tumor ◽  
Tumor Type ◽  
Cell Analysis ◽  
Data Set ◽  
Human Glioblastoma ◽  
Glioblastoma Patient ◽  
Single Cell Rna Sequencing ◽  
Therapeutic Problem

Abstract Patients with glioblastoma, the most frequent and malignant primary brain tumor type, have a poor prognosis with a median survival of 14 months. A major therapeutic problem is chemoresistance. In surgically removed glioblastoma tissue, tumor-associated microglia and macrophages (TAMs) constitute up to 30 % of the total cells. TAMs are capable of secreting cytokines, chemokines and growth factors, thereby influencing the tumor microenvironment. However, the existence of different TAM subtypes and their role in glioblastoma is not fully comprehended and rarely considered therapeutically. This could explain why many glioblastoma clinical trials fail despite of promising preclinical results. This project aims to interrogate the existence and characteristics of different TAM subtypes in human glioblastoma biopsies in order to identify novel subpopulations and therapeutic targets. To study the heterogeneity in TAMs, CD11b+ cells were isolated from glioblastoma patient′s tissue, and single-cell RNA sequencing was performed using the 10X Genomics Chromium platform for single-cell generation and an Illumina NovaSeq6000 system for sequencing. We have sequenced TAMs from three glioblastomas and CD11b+ cells from brain tissue adjacent to two brain metastases samples. In the filtered data set of almost 71,000 CD11b+ cells, we were able to identify recently described TAM populations, such as an interferon-induced, a phagocytic, a hypoxic and a proliferating subset. Interestingly, we also discovered potential novel TAM subsets, such as a pro-angiogenic subset. We have detected a TAM population which is more complex than the established M1 and M2 phenotypes, constituting novel TAM subsets. We are currently investigating these findings to validate specific markers associated with these subpopulations, and for the identification of novel clinically relevant targets.

Morpheaform Basal Cell Carcinomas With Areas of Predominantly Single-Cell Pattern of Infiltration

2016 ◽  
Vol 38 (10) ◽  
pp. 744-750 ◽  
Author(s):  
Ellen East ◽  
Douglas R. Fullen ◽  
David Arps ◽  
Rajiv M. Patel ◽  
Nallasivam Palanisamy ◽  
...  
Keyword(s):  
Single Cell ◽  
Basal Cell ◽  
Cell Pattern ◽  
Basal Cell Carcinomas

scholarly journals Single cell derived mRNA signals across human kidney tumors

2020 ◽  
Author(s):  
Matthew D Young ◽  
Thomas J Mitchell ◽  
Lars Custers ◽  
Thanasis Margaritis ◽  
Francisco Morales ◽  
...  
Keyword(s):  
Single Cell ◽  
Human Cancer ◽  
Human Kidney ◽  
Cell Types ◽  
Renal Tumors ◽  
Tumor Type ◽  
Kidney Tumors ◽  
Cell Renal Cell Carcinoma ◽  
Cellular Origin ◽  
Normal Tissues

AbstractThe cellular transcriptome may provide clues into the differentiation state and origin of human cancer, as tumor cells may retain patterns of gene expression similar to the cell they derive from. Here, we studied the differentiation state and cellular origin of human kidney tumors, by assessing mRNA signals in 1,300 childhood and adult renal tumors, spanning seven different tumor types. Using single cell mRNA reference maps of normal tissues generated by the Human Cell Atlas project, we measured the abundance of reference “cellular signals” in each tumor. Quantifying global differentiation states, we found that, irrespective of tumor type, childhood tumors exhibited fetal cellular signals, thus replacing the long-held presumption of “fetalness” with a precise, quantitative readout of immaturity. By contrast, in adult cancers our assessment refuted the suggestion of dedifferentiation towards a fetal state in the overwhelming majority of cases, with the exception of lethal variants of clear cell renal cell carcinoma. Examining the specific cellular phenotype of each tumor type revealed an intimate connection between the different mesenchymal populations of the developing kidney and childhood renal tumors, whereas adult tumors mostly represented specific mature tubular cell types. RNA signals of each tumor type were remarkably uniform and specific, indicating a possible therapeutic and diagnostic utility. We demonstrated this utility with a case study of a cryptic renal tumor. Whilst not classifiable by clinical pathological work-up, mRNA signals revealed the diagnosis. Our findings provide a cellular definition of human renal tumors through an approach that is broadly applicable to human cancer.

scholarly journals Single cell pattern formation and transient cytoskeletal arrays

2014 ◽  
Vol 26 ◽  
pp. 51-59 ◽  
Author(s):  
William M Bement ◽  
George von Dassow
Keyword(s):  
Pattern Formation ◽  
Single Cell ◽  
Cell Pattern

scholarly journals Pan-Cancer and Single-Cell modelling of genomic alterations through gene expression

2018 ◽  
Author(s):  
Daniele Mercatelli ◽  
Forest Ray ◽  
Federico M. Giorgi
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Prediction Models ◽  
Human Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Copy Number Variations ◽  
Tumor Type ◽  
Genomic Alterations ◽  
Pan Cancer

AbstractCancer is a disease often characterized by the presence of multiple genomic alterations, which trigger altered transcriptional patterns and gene expression, which in turn sustain the processes of tumorigenesis, tumor progression and tumor maintenance. The links between genomic alterations and gene expression profiles can be utilized as the basis to build specific molecular tumorigenic relationships. In this study we perform pan-cancer predictions of the presence of single somatic mutations and copy number variations using machine learning approaches on gene expression profiles. We show that gene expression can be used to predict genomic alterations in every tumor type, where some alterations are more predictable than others. We propose gene aggregation as a tool to improve the accuracy of alteration prediction models from gene expression profiles. Ultimately, we show how this principle can be beneficial in intrinsically noisy datasets, such as those based on single cell sequencing.Author SummaryIn this article we show that transcript abundance can be used to predict the presence or absence of the majority of genomic alterations present in human cancer. We also show how these predictions can be improved by aggregating genes into small networks to counteract the effects of transcript measurement noise.

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