scholarly journals Identifying tumor cells at the single cell level

2021 ◽  
Author(s):  
Jan Dohmen ◽  
Artem Baranovskii ◽  
Bora Uyar ◽  
Jonathan Ronen ◽  
Vedran Franke ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Biomarker Discovery ◽  
Single Cell Analysis ◽  
High Sensitivity ◽  
Simple Problem ◽  
Cancer Therapies ◽  
Single Cell Level ◽  
Cell Level

Tumors are highly complex tissues composed of cancerous cells, surrounded by a heterogeneous cellular microenvironment. Tumor response to treatments is governed by an interaction of cancer cell intrinsic factors with external influences of the tumor microenvironment. Disentangling the heterogeneity within a tumor is a crucial step in developing and utilization of effective cancer therapies. Single cell sequencing has the potential to revolutionize personalized medicine. In cancer therapy it enables an effective characterization of the complete heterogeneity within the tumor. A governing challenge in cancer single cell analysis is cell annotation, the assignment of a particular cell type or a cell state to each sequenced cell. We propose Ikarus, a machine learning pipeline aimed at solving a perceived simple problem, distinguishing tumor cells from normal cells at the single cell level. Automatic characterization of tumor cells is a critical limiting step for a multitude of research, clinical, and commercial applications. Automatic characterization of tumor cells would expedite neoantigen prediction, automatic characterization of tumor cell states, it would greatly facilitate cancer biomarker discovery. Such a tool can be used for automatic annotation of histopathological data, profiled using multichannel immunofluorescence or spatial sequencing. We have tested ikarus on multiple single cell datasets to ascertain that it achieves high sensitivity and specificity in multiple experimental contexts.

scholarly journals Single-Cell Transcriptome Analysis as a Promising Tool to Study Pluripotent Stem Cell Reprogramming

2021 ◽  
Vol 22 (11) ◽  
pp. 5988
Author(s):  
Hyun Kyu Kim ◽  
Tae Won Ha ◽  
Man Ryul Lee
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Cell Fate ◽  
Human Cell ◽  
Transcriptome Analysis ◽  
Single Cell Analysis ◽  
Embryonic Stem ◽  
Single Cell Level ◽  
Cell Analysis ◽  
Cell Level

Cells are the basic units of all organisms and are involved in all vital activities, such as proliferation, differentiation, senescence, and apoptosis. A human body consists of more than 30 trillion cells generated through repeated division and differentiation from a single-cell fertilized egg in a highly organized programmatic fashion. Since the recent formation of the Human Cell Atlas consortium, establishing the Human Cell Atlas at the single-cell level has been an ongoing activity with the goal of understanding the mechanisms underlying diseases and vital cellular activities at the level of the single cell. In particular, transcriptome analysis of embryonic stem cells at the single-cell level is of great importance, as these cells are responsible for determining cell fate. Here, we review single-cell analysis techniques that have been actively used in recent years, introduce the single-cell analysis studies currently in progress in pluripotent stem cells and reprogramming, and forecast future studies.

scholarly journals Heterogeneity of PIK3CA mutational status at the single cell level in circulating tumor cells from metastatic breast cancer patients

2014 ◽  
Vol 9 (4) ◽  
pp. 749-757 ◽  
Author(s):  
Marta Pestrin ◽  
Francesca Salvianti ◽  
Francesca Galardi ◽  
Francesca De Luca ◽  
Natalie Turner ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Single Cell ◽  
Cancer Patients ◽  
Tumor Cells ◽  
Metastatic Breast ◽  
Single Cell Level ◽  
Breast Cancer Patients ◽  
Cell Level ◽  
Mutational Status

scholarly journals Characterization of the development of the mouse cochlear epithelium at the single cell level

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Likhitha Kolla ◽  
Michael C. Kelly ◽  
Zoe F. Mann ◽  
Alejandro Anaya-Rocha ◽  
Kathryn Ellis ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Level ◽  
Cell Level

scholarly journals Combined Molecular Genetic and Cytogenetic Analysis from Single Cells after Isothermal Whole-Genome Amplification

2011 ◽  
Vol 57 (7) ◽  
pp. 1032-1041 ◽  
Author(s):  
Thomas Kroneis ◽  
Jochen B Geigl ◽  
Amin El-Heliebi ◽  
Martina Auer ◽  
Peter Ulz ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Molecular Genetic ◽  
Target Cells ◽  
Whole Genome ◽  
Single Cell Level ◽  
Cell Level ◽  
Genome Amplification

BACKGROUND Analysis of chromosomal aberrations or single-gene disorders from rare fetal cells circulating in the blood of pregnant women requires verification of the cells' genomic identity. We have developed a method enabling multiple analyses at the single-cell level that combines verification of the genomic identity of microchimeric cells with molecular genetic and cytogenetic diagnosis. METHODS We used a model system of peripheral blood mononuclear cells spiked with a colon adenocarcinoma cell line and immunofluorescence staining for cytokeratin in combination with DNA staining with the nuclear dye TO-PRO-3 in a preliminary study to define candidate microchimeric (tumor) cells in Cytospin preparations. After laser microdissection, we performed low-volume on-chip isothermal whole-genome amplification (iWGA) of single and pooled cells. RESULTS DNA fingerprint analysis of iWGA aliquots permitted successful identification of all analyzed candidate microchimeric cell preparations (6 samples of pooled cells, 7 samples of single cells). Sequencing of 3 single-nucleotide polymorphisms was successful at the single-cell level for 20 of 32 allelic loci. Metaphase comparative genomic hybridization (mCGH) with iWGA products of single cells showed the gains and losses known to be present in the genomic DNA of the target cells. CONCLUSIONS This method may be instrumental in cell-based noninvasive prenatal diagnosis. Furthermore, the possibility to perform mCGH with amplified DNA from single cells offers a perspective for the analysis of nonmicrochimeric rare cells exhibiting genomic alterations, such as circulating tumor cells.

Detection and Quantification of Bacterial Autofluorescence at the Single-Cell Level by a Laboratory-Built High-Sensitivity Flow Cytometer

2012 ◽  
Vol 84 (3) ◽  
pp. 1526-1532 ◽  
Author(s):  
Lingling Yang ◽  
Yingxing Zhou ◽  
Shaobin Zhu ◽  
Tianxun Huang ◽  
Lina Wu ◽  
...  
Keyword(s):  
Single Cell ◽  
High Sensitivity ◽  
Flow Cytometer ◽  
Single Cell Level ◽  
Cell Level ◽  
Detection And Quantification

scholarly journals Visualizing and isolating iron-reducing microorganisms at single cell level

2020 ◽  
Author(s):  
Cuifen Gan ◽  
Rongrong Wu ◽  
Yeshen Luo ◽  
Jianhua Song ◽  
Dizhou Luo ◽  
...  
Keyword(s):  
Single Cell ◽  
Iron Reduction ◽  
High Sensitivity ◽  
Ex Situ ◽  
Single Cell Level ◽  
Cell Level ◽  
Cell Sorter ◽  
Fluorescent Intensity

AbstractIron-reducing microorganisms (FeRM) play key roles in many natural and engineering processes. Visualizing and isolating FeRM from multispecies samples are essential to understand the in-situ location and geochemical role of FeRM. Here, we visualized FeRM by a “turn-on” Fe2+-specific fluorescent chemodosimeter (FSFC) with high sensitivity, selectivity and stability. This FSFC could selectively identify and locate active FeRM from either pure culture, co-culture of different bacteria or sediment-containing samples. Fluorescent intensity of the FSFC could be used as an indicator of Fe2+ concentration in bacterial cultures. By integrating FSFC with a single cell sorter, we obtained three FSFC-labeled cells from an enriched consortia and all of them were subsequently evidenced to be capable of iron-reduction and two unlabeled cells were evidenced to have no iron-reducing capability, further confirming the feasibility of the FSFC.ImportanceVisualization and isolation of FeRM from samples containing multispecies are commonly needed by researchers from different disciplines, such as environmental microbiology, environmental sciences and geochemistry. However, no available method has been reported. In this study, we provid a solution to visualize FeRM and evaluate their activity even at single cell level. Integrating with single cell sorter, FeRM can also be isolated from samples containing multispecies. This method can be used as a powerful tool to uncover the in-situ or ex-situ role of FeRM and their interactions with ambient microbes or chemicals.

scholarly journals Cross-Tissue Characterization of Heterogeneities of Mesenchymal Stem Cells and Their Differentiation Potentials

2021 ◽  
Vol 9 ◽  
Author(s):  
Wenhong Hou ◽  
Li Duan ◽  
Changyuan Huang ◽  
Xingfu Li ◽  
Xiao Xu ◽  
...  
Keyword(s):  
Single Cell ◽  
Umbilical Cord ◽  
Stromal Cells ◽  
Tissue Characterization ◽  
Single Cell Level ◽  
Rna Seq ◽  
Cell Level ◽  
Cell Sources ◽  
Cell Subpopulations

Mesenchymal stem/stromal cells (MSCs) are promising cell sources for regenerative medicine and the treatment of autoimmune disorders. Comparing MSCs from different tissues at the single-cell level is fundamental for optimizing clinical applications. Here we analyzed single-cell RNA-seq data of MSCs from four tissues, namely umbilical cord, bone marrow, synovial tissue, and adipose tissue. We identified three major cell subpopulations, namely osteo-MSCs, chondro-MSCs, and adipo/myo-MSCs, across all MSC samples. MSCs from the umbilical cord exhibited the highest immunosuppression, potentially indicating it is the best immune modulator for autoimmune diseases. MSC subpopulations, with different subtypes and tissue sources, showed pronounced differences in differentiation potentials. After we compared the cell subpopulations and cell status pre-and-post chondrogenesis induction, osteogenesis induction, and adipogenesis induction, respectively, we found MSC subpopulations expanded and differentiated when their subtypes consist with induction directions, while the other subpopulations shrank. We identified the genes and transcription factors underlying each induction at the single-cell level and subpopulation level, providing better targets for improving induction efficiency.

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