scholarly journals Morphological features of single cells enable accurate automated classification of cancer from non-cancer cell lines

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zeynab Mousavikhamene ◽  
Daniel J. Sykora ◽  
Milan Mrksich ◽  
Neda Bagheri
Keyword(s):  
Cell Lines ◽  
Microcontact Printing ◽  
Single Cells ◽  
Response Prediction ◽  
Extraction Methods ◽  
Automated Classification ◽  
Assembled Monolayers ◽  
Detection And Diagnosis ◽  
Key Barrier ◽  
Supervised Feature Extraction

AbstractAccurate cancer detection and diagnosis is of utmost importance for reliable drug-response prediction. Successful cancer characterization relies on both genetic analysis and histological scans from tumor biopsies. It is known that the cytoskeleton is significantly altered in cancer, as cellular structure dynamically remodels to promote proliferation, migration, and metastasis. We exploited these structural differences with supervised feature extraction methods to introduce an algorithm that could distinguish cancer from non-cancer cells presented in high-resolution, single cell images. In this paper, we successfully identified the features with the most discriminatory power to successfully predict cell type with as few as 100 cells per cell line. This trait overcomes a key barrier of machine learning methodologies: insufficient data. Furthermore, normalizing cell shape via microcontact printing on self-assembled monolayers enabled better discrimination of cell lines with difficult-to-distinguish phenotypes. Classification accuracy remained robust as we tested dissimilar cell lines across various tissue origins, which supports the generalizability of our algorithm.

scholarly journals Multiplexed profiling of single-cell extracellular vesicles secretion

2019 ◽  
Vol 116 (13) ◽  
pp. 5979-5984 ◽  
Author(s):  
Yahui Ji ◽  
Dongyuan Qi ◽  
Linmei Li ◽  
Haoran Su ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Extracellular Vesicles ◽  
Single Cell Analysis ◽  
Comprehensive Evaluation ◽  
Single Cells ◽  
Deep Understanding ◽  
Principal Component ◽  
Cell Heterogeneity ◽  
Indispensable Tool

Extracellular vesicles (EVs) are important intercellular mediators regulating health and diseases. Conventional methods for EV surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EV secretion. Herein, by using spatially patterned antibody barcodes, we realized multiplexed profiling of single-cell EV secretion from more than 1,000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to a deep understanding of previously undifferentiated single-cell heterogeneity underlying EV secretion. Notably, we observed that the decrement of certain EV phenotypes (e.g.,CD63+EV) was associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EV secretion and cytokines secretion simultaneously from the same single cells to investigate the multidimensional spectrum of cellular communications, from which we resolved tiered functional subgroups with distinct secretion profiles by visualized clustering and principal component analysis. In particular, we found that different cell subgroups dominated EV secretion and cytokine secretion. The technology introduced here enables a comprehensive evaluation of EV secretion heterogeneity at single-cell level, which may become an indispensable tool to complement current single-cell analysis and EV research.

Microcontact Printing of Lipophilic Self-Assembled Monolayers for the Attachment of Biomimetic Lipid Bilayers to Surfaces

1999 ◽  
Vol 121 (22) ◽  
pp. 5274-5280 ◽  
Author(s):  
A. Toby A. Jenkins ◽  
Neville Boden ◽  
Richard. J. Bushby ◽  
Stephen. D. Evans ◽  
Peter. F. Knowles ◽  
...  
Keyword(s):  
Lipid Bilayers ◽  
Microcontact Printing ◽  
Self Assembled Monolayers ◽  
Assembled Monolayers ◽  
Self Assembled

scholarly journals Multiplexed Profiling of Single-cell Extracellular Vesicles Secretion

2018 ◽  
Author(s):  
Yahui Ji ◽  
Dongyuan Qi ◽  
Linmei Li ◽  
Haoran Su ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Extracellular Vesicles ◽  
Single Cells ◽  
Cell Communication ◽  
Deep Understanding ◽  
Surface Markers ◽  
Cell Heterogeneity ◽  
Health And Disease ◽  
Cytokines Secretion

AbstractExtracellular vesicles (EVs) are important intercellular mediators regulating health and disease. Conventional EVs surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EVs secretion. Herein, by using spatially patterned antibodies barcode, we realized multiplexed profiling of single-cell EVs secretion from more than 1000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to deep understanding of previously undifferentiated single cell heterogeneity underlying EVs secretion. Notably, we observed the decrement of certain EV phenotypes (e.g. CD63+EVs) were associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EVs secretion and cytokines secretion simultaneously from the same single cells to investigate multidimensional spectrum of intercellular communications, from which we resolved three functional subgroups with distinct secretion profiles by visualized clustering. In particular, we found EVs secretion and cytokines secretion were generally dominated by different cell subgroups. The technology introduced here enables comprehensive evaluation of EVs secretion heterogeneity at single cell level, which may become an indispensable tool to complement current single cell analysis and EV research.SignificanceExtracellular vesicles (EVs) are cell derived nano-sized particles medicating cell-cell communication and transferring biology information molecules like nucleic acids to regulate human health and disease. Conventional methods for EV surface markers profiling can’t tell the differences in the quantity and phenotypes of EVs secretion between cells. To address this need, we developed a platform for profiling an array of surface markers on EVs from large numbers of single cells, enabling more comprehensive monitoring of cellular communications. Single cell EVs secretion assay led to previously unobserved cell heterogeneity underlying EVs secretion, which might open up new avenues for studying cell communication and cell microenvironment in both basic and clinical research.

Isolation of single cells from adherent cell lines using Smart Aliquotor CE v1 (protocols.io.bhjmj4k6)

protocols.io ◽  
2020 ◽  
Author(s):  
Lucy Kimbley ◽  
Rachel Parker ◽  
Maaike Sybil ◽  
John Holloway ◽  
Emily Swindle ◽  
...  
Keyword(s):  
Cell Lines ◽  
Single Cells ◽  
Adherent Cell

scholarly journals Joint single cell DNA-seq and RNA-seq of gastric cancer cell lines reveals rules of in vitro evolution

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Noemi Andor ◽  
Billy T Lau ◽  
Claudia Catalanotti ◽  
Anuja Sathe ◽  
Matthew Kubit ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Single Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Gastric Cancer Cell ◽  
Phenotypic Diversity ◽  
Single Cells ◽  
Cancer Cell Lines ◽  
Gastric Cancer Cell Lines

Abstract Cancer cell lines are not homogeneous nor are they static in their genetic state and biological properties. Genetic, transcriptional and phenotypic diversity within cell lines contributes to the lack of experimental reproducibility frequently observed in tissue-culture-based studies. While cancer cell line heterogeneity has been generally recognized, there are no studies which quantify the number of clones that coexist within cell lines and their distinguishing characteristics. We used a single-cell DNA sequencing approach to characterize the cellular diversity within nine gastric cancer cell lines and integrated this information with single-cell RNA sequencing. Overall, we sequenced the genomes of 8824 cells, identifying between 2 and 12 clones per cell line. Using the transcriptomes of more than 28 000 single cells from the same cell lines, we independently corroborated 88% of the clonal structure determined from single cell DNA analysis. For one of these cell lines, we identified cell surface markers that distinguished two subpopulations and used flow cytometry to sort these two clones. We identified substantial proportions of replicating cells in each cell line, assigned these cells to subclones detected among the G0/G1 population and used the proportion of replicating cells per subclone as a surrogate of each subclone's growth rate.

Realizing high aspect ratio silver micro and nanostructures by microcontact printing of alkyl thiol self-assembled monolayers

MRS Advances ◽  
2019 ◽  
Vol 4 (44-45) ◽  
pp. 2441-2451
Author(s):  
Amare Benor ◽  
Asman Tamang ◽  
Veit Wagner ◽  
Alberto Salleo ◽  
Dietmar Knipp
Keyword(s):  
Aspect Ratio ◽  
Noble Metal ◽  
Microcontact Printing ◽  
Self Assembled Monolayers ◽  
Head Group ◽  
Material System ◽  
Printing Process ◽  
Aspect Ratios ◽  
Assembled Monolayers ◽  
Self Assembled

ABSTRACTThe patterning of gold and silver micro and nanostructures on rigid and flexible substrates is investigated by microcontact printed thiol based self-assembled monolayers. The aspect ratio of the noble metal micro and nanostructures is determined by interaction of the -SH head group of the CH3(CH2)19SH molecules and the surface of the noble metal. Silver micro and nanostructures with >10 times higher aspect ratios can be realized in comparison to commonly realized gold micro and nanostructures. The printing process is described, and the etching process is characterized in terms of etching window and etching selectivity. Potential electronic and photonic applications of the micro and nanostructures are discussed taking the boundary conditions of the printing process and the selected material system into consideration.

Patterning of Surface Chemistry and Topography for Biological Applications

1998 ◽  
Vol 4 (S2) ◽  
pp. 888-889
Author(s):  
H. G. Craighead ◽  
R. C. Davis ◽  
M. Foquet ◽  
M. Isaacson ◽  
C. James ◽  
...  
Keyword(s):  
Microcontact Printing ◽  
Biological Systems ◽  
Inorganic Materials ◽  
Self Assembled Monolayers ◽  
Chemical Patterning ◽  
Critical Function ◽  
Assembled Monolayers ◽  
Cell Surface Interactions ◽  
Mechanical Devices ◽  
Glass Surfaces

The technologies of nanofabrication as applied to inorganic materials and substrates are advanced and continue to develop. These sophisticated processes enable the formation of complex electronic, optical and mechanical devices with feature sizes down to tens of nanometers. Adaptation of these types of processes to surface chemical patterning and topographical patterning provides a new set of experimental tools for investigating biological systems and realizing sensors and devices that require the interaction of biological systems and fluids with inorganic materials and surfaces.In this talk we discuss methods of pattering self assembled monolayers, proteins and antibodies on silicon and glass surfaces by lithography and microcontact printing. This is of utility in a variety of experiments in cell-surface interactions and in sensor devices. In certain types of devices the manipulation of fluids and sieving of molecules is a critical function such as in DNA sequencing6 by electrophoretic separation.

scholarly journals Phosphotyrosine-based Phosphoproteomics for Target Identification and Drug Response Prediction in AML Cell Lines

2020 ◽  
Vol 19 (5) ◽  
pp. 884-899 ◽  
Author(s):  
Carolien van Alphen ◽  
Jacqueline Cloos ◽  
Robin Beekhof ◽  
David G. J. Cucchi ◽  
Sander R. Piersma ◽  
...  
Keyword(s):  
Cell Lines ◽  
Tyrosine Kinases ◽  
Kinase Inhibitor ◽  
Target Identification ◽  
Response Prediction ◽  
Clinical Samples ◽  
Label Free ◽  
Poor Treatment ◽  
Poor Treatment Outcome ◽  
The Individual

Acute myeloid leukemia (AML) is a clonal disorder arising from hematopoietic myeloid progenitors. Aberrantly activated tyrosine kinases (TK) are involved in leukemogenesis and are associated with poor treatment outcome. Kinase inhibitor (KI) treatment has shown promise in improving patient outcome in AML. However, inhibitor selection for patients is suboptimal.In a preclinical effort to address KI selection, we analyzed a panel of 16 AML cell lines using phosphotyrosine (pY) enrichment-based, label-free phosphoproteomics. The Integrative Inferred Kinase Activity (INKA) algorithm was used to identify hyperphosphorylated, active kinases as candidates for KI treatment, and efficacy of selected KIs was tested.Heterogeneous signaling was observed with between 241 and 2764 phosphopeptides detected per cell line. Of 4853 identified phosphopeptides with 4229 phosphosites, 4459 phosphopeptides (4430 pY) were linked to 3605 class I sites (3525 pY). INKA analysis in single cell lines successfully pinpointed driver kinases (PDGFRA, JAK2, KIT and FLT3) corresponding with activating mutations present in these cell lines. Furthermore, potential receptor tyrosine kinase (RTK) drivers, undetected by standard molecular analyses, were identified in four cell lines (FGFR1 in KG-1 and KG-1a, PDGFRA in Kasumi-3, and FLT3 in MM6). These cell lines proved highly sensitive to specific KIs. Six AML cell lines without a clear RTK driver showed evidence of MAPK1/3 activation, indicative of the presence of activating upstream RAS mutations. Importantly, FLT3 phosphorylation was demonstrated in two clinical AML samples with a FLT3 internal tandem duplication (ITD) mutation.Our data show the potential of pY-phosphoproteomics and INKA analysis to provide insight in AML TK signaling and identify hyperactive kinases as potential targets for treatment in AML cell lines. These results warrant future investigation of clinical samples to further our understanding of TK phosphorylation in relation to clinical response in the individual patient.

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