scholarly journals Analysis of the Single-Cell Heterogeneity of Adenocarcinoma Cell Lines and the Investigation of Intratumor Heterogeneity Reveals the Expression of Transmembrane Protein 45A (TMEM45A) in Lung Adenocarcinoma Cancer Patients

Cancers ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 144
Author(s):  
Patrícia Neuperger ◽  
József Á. Balog ◽  
László Tiszlavicz ◽  
József Furák ◽  
Nikolett Gémes ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Single Cell ◽  
Cell Line ◽  
Cancer Patients ◽  
Cell Lines ◽  
Lung Tumor ◽  
Expression Patterns ◽  
Cell Mass ◽  
Cell Heterogeneity ◽  
Primary Lung Adenocarcinoma

Intratumoral heterogeneity (ITH) is responsible for the majority of difficulties encountered in the treatment of lung-cancer patients. Therefore, the heterogeneity of NSCLC cell lines and primary lung adenocarcinoma was investigated by single-cell mass cytometry (CyTOF). First, we studied the single-cell heterogeneity of frequent NSCLC adenocarcinoma models, such as A549, H1975, and H1650. The intra- and inter-cell-line single-cell heterogeneity is represented in the expression patterns of 13 markers—namely GLUT1, MCT4, CA9, TMEM45A, CD66, CD274 (PD-L1), CD24, CD326 (EpCAM), pan-keratin, TRA-1-60, galectin-3, galectin-1, and EGFR. The qRT-PCR and CyTOF analyses revealed that a hypoxic microenvironment and altered metabolism may influence cell-line heterogeneity. Additionally, human primary lung adenocarcinoma and non-involved healthy lung tissue biopsies were homogenized to prepare a single-cell suspension for CyTOF analysis. The CyTOF showed the ITH of human primary lung adenocarcinoma for 14 markers; particularly, the higher expressions of GLUT1, MCT4, CA9, TMEM45A, and CD66 were associated with the lung-tumor tissue. Our single-cell results are the first to demonstrate TMEM45A expression in human lung adenocarcinoma, which was verified by immunohistochemistry.

An artificial intelligent platform for live cell identification and the detection of cross-contamination (Preprint)

2019 ◽  
Author(s):  
Ruixin Wang ◽  
Dongni Wang ◽  
Dekai Kang ◽  
Xusen Guo ◽  
Chong Guo ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Cell Morphology ◽  
Single Cell Level ◽  
Cross Contamination ◽  
Cell Level ◽  
Cell Identification ◽  
Pure Cell ◽  
Microscopy Images

BACKGROUND In vitro human cell line models have been widely used for biomedical research to predict clinical response, identify novel mechanisms and drug response. However, one-fifth to one-third of cell lines have been cross-contaminated, which can seriously result in invalidated experimental results, unusable therapeutic products and waste of research funding. Cell line misidentification and cross-contamination may occur at any time, but authenticating cell lines is infrequent performed because the recommended genetic approaches are usually require extensive expertise and may take a few days. Conversely, the observation of live-cell morphology is a direct and real-time technique. OBJECTIVE The purpose of this study was to construct a novel computer vision technology based on deep convolutional neural networks (CNN) for “cell face” recognition. This was aimed to improve cell identification efficiency and reduce the occurrence of cell-line cross contamination. METHODS Unstained optical microscopy images of cell lines were obtained for model training (about 334 thousand patch images), and testing (about 153 thousand patch images). The AI system first trained to recognize the pure cell morphology. In order to find the most appropriate CNN model，we explored the key image features in cell morphology classification tasks using the classical CNN model-Alexnet. After that, a preferred fine-grained recognition model BCNN was used for the cell type identification (seven classifications). Next, we simulated the situation of cell cross-contamination and mixed the cells in pairs at different ratios. The detection of the cross-contamination was divided into two levels, whether the cells are mixed and what the contaminating cell is. The specificity, sensitivity, and accuracy of the model were tested separately by external validation. Finally, the segmentation model DialedNet was used to present the classification results at the single cell level. RESULTS The cell texture and density were the influencing factors that can be better recognized by the bilinear convolutional neural network (BCNN) comparing to AlexNet. The BCNN achieved 99.5% accuracy in identifying seven pure cell lines and 86.3% accuracy for detecting cross-contamination (mixing two of the seven cell lines). DilatedNet was applied to the semantic segment for analyzing in single-cell level and achieved an accuracy of 98.2%. CONCLUSIONS This study successfully demonstrated that cell lines can be morphologically identified using deep learning models. Only light-microscopy images and no reagents are required, enabling most labs to routinely perform cell identification tests.

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.

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.

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.

scholarly journals Comprehensive Analysis of SWI/SNF Inactivation in Lung Adenocarcinoma Cell Models

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3712
Author(s):  
Paola Peinado ◽  
Alvaro Andrades ◽  
Marta Cuadros ◽  
Maria Isabel Rodriguez ◽  
Isabel F. Coira ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Line ◽  
Genetic Alterations ◽  
Cell Models ◽  
Functional Studies ◽  
Cellular Models ◽  
Mutational Status

Mammalian SWI/SNF (SWitch/Sucrose Non-Fermentable) complexes are ATP-dependent chromatin remodelers whose subunits have emerged among the most frequently mutated genes in cancer. Studying SWI/SNF function in cancer cell line models has unveiled vulnerabilities in SWI/SNF-mutant tumors that can lead to the discovery of new therapeutic drugs. However, choosing an appropriate cancer cell line model for SWI/SNF functional studies can be challenging because SWI/SNF subunits are frequently altered in cancer by various mechanisms, including genetic alterations and post-transcriptional mechanisms. In this work, we combined genomic, transcriptomic, and proteomic approaches to study the mutational status and the expression levels of the SWI/SNF subunits in a panel of 38 lung adenocarcinoma (LUAD) cell lines. We found that the SWI/SNF complex was mutated in more than 76% of our LUAD cell lines and there was a high variability in the expression of the different SWI/SNF subunits. These results underline the importance of the SWI/SNF complex as a tumor suppressor in LUAD and the difficulties in defining altered and unaltered cell models for the SWI/SNF complex. These findings will assist researchers in choosing the most suitable cellular models for their studies of SWI/SNF to bring all of its potential to the development of novel therapeutic applications.

scholarly journals Domain-invariant features for mechanism of action prediction in a multi-cell-line drug screen

2019 ◽  
Vol 36 (5) ◽  
pp. 1607-1613 ◽  
Author(s):  
Joseph C Boyd ◽  
Alice Pinheiro ◽  
Elaine Del Nery ◽  
Fabien Reyal ◽  
Thomas Walter
Keyword(s):  
Drug Discovery ◽  
Single Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Mechanism Of Action ◽  
Molecular Subtype ◽  
Supplementary Information ◽  
Breast Cancer Cell Lines ◽  
Molecular Heterogeneity ◽  
Drug Mechanism

Abstract Motivation High-content screening is an important tool in drug discovery and characterization. Often, high-content drug screens are performed on one single-cell line. Yet, a single-cell line cannot be thought of as a perfect disease model. Many diseases feature an important molecular heterogeneity. Consequently, a drug may be effective against one molecular subtype of a disease, but less so against another. To characterize drugs with respect to their effect not only on one cell line but on a panel of cell lines is therefore a promising strategy to streamline the drug discovery process. Results The contribution of this article is 2-fold. First, we investigate whether we can predict drug mechanism of action (MOA) at the molecular level without optimization of the MOA classes to the screen specificities. To this end, we benchmark a set of algorithms within a conventional pipeline, and evaluate their MOA prediction performance according to a statistically rigorous framework. Second, we extend this conventional pipeline to the simultaneous analysis of multiple cell lines, each manifesting potentially different morphological baselines. For this, we propose multi-task autoencoders, including a domain-adaptive model used to construct domain-invariant feature representations across cell lines. We apply these methods to a pilot screen of two triple negative breast cancer cell lines as models for two different molecular subtypes of the disease. Availability and implementation https://github.com/jcboyd/multi-cell-line or https://zenodo.org/record/2677923. Supplementary information Supplementary data are available at Bioinformatics online.

Analysis of Mitosis In Acute Myeloid Leukemia Using Live-Cell Imaging.

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 3363-3363
Author(s):  
Dominik Schnerch ◽  
Julia Felthaus ◽  
Lara Mentlein ◽  
Monika Engelhardt ◽  
Ralph M. Waesch
Keyword(s):  
Single Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Genetic Instability ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Cyclin B ◽  
Single Cell Level ◽  
Cell Level ◽  
Mitotic Control

Abstract Abstract 3363 Proper mitotic control is a prerequisite to guarantee the equal distribution of the genetic material onto the two developing daughter cells. A mitotic key regulator is cyclin B. High levels of cyclin B facilitate entry into mitosis whereas its controlled degradation coordinates chromosome separation and cytokinesis. The latter events are coordinated by the anaphase- promoting complex / cyclosome (APC/C), a ubiquitin ligase that couples ubiquitin chains to cyclin B, mediating its proteasomal degradation. The regulation of the APC/C-activity by complex protein networks, such as the spindle assembly checkpoint, therefore presents the basis for an accurate mitosis. Mitotic errors give rise to daughter cells with an aberrant set of chromosomes and contribute to genetic instability. Genetic instability is a hallmark of cancer cells and plays an important role in the onset and progression of acute myeloid leukemia (AML). In rare cases, de novo AMLs present with multiple cytogenetic aberrations (complex karyotype). However, a larger number of patients develop karyotype deviations in the course of the disease, sometimes even under therapy, which comes along with an adverse prognosis. Understanding the biology that drives the gain and loss of genetic material therefore bears the potential of identifying new therapeutic targets. We compared a number of lymphoblastic and myeloid cell lines and found AML cell lines to be deficient in arresting at metaphase in the presence of the microtubule-disrupting agent nocodazole. Cyclin B was expressed at much lower levels in the AML cell line Kasumi-1 and did not accumulate following spindle disruption as observed in the lymphoblastic cell line DG-75. We could show that Kasumi-1 cells, when challenged with nocodazole, were not capable of properly maintaining chromatid-cohesion and underwent premature sister chromatid separation. These findings suggest that mitotic control mechanisms do not work tightly enough in AML cells to prevent chromosome separation in the presence of spindle disruption. We applied live-cell imaging to exactly characterize mitotic timing in Kasumi-1 cells at a single cell level. The expression of a GFP-tagged derivative of histone H2 served to visualize the nuclear envelope breakdown and anaphase onset. Detection of the latter events allowed the faithful measurement of mitotic timing. We could find a significant shortening of mitosis in Kasumi-1 cells as compared to the lymphoblastic cell line DG-75. In both AML cell lines and primary AML blasts we identified the spindle assembly checkpoint components BubR1 and Bub1 to be downregulated. Interestingly, re-expression of BubR1 in Kasumi-1 cells led to a significant stabilization of cyclin B on western blots. To address the question whether an increased expression of cyclin B leads to a more pronounced mitotic delay in the presence of spindle-disruption in AML cells is subject of current experiments. It was reported that different cell types can escape from a mitotic block as a consequence of cyclin B degradation. In the literature, this phenomenon was referred to as mitotic slippage and is known to drive genetic instability. To monitor cyclin B turnover and localization at a single cell level, we generated a chimeric cyclin B-molecule, SNAP-cyclin B, which can couple to a suitable fluorochrome in a self-labeling reaction after addition to the growth medium. In this system, the fluorescence intensity reflects the amount of chimeric cyclin B and allows the monitoring of APC/C-dependent proteolysis. In our current approaches we aim at studying cyclin B-turnover at a single cell level in AML cell lines as well as primary leukemia cells by using live-cell imaging before and after BubR1- and Bub1-rescue. An aberrant cell cycle control is found in most human malignancies and might be an important driving force in leukemogenesis. We hypothesize that BubR1, in concert with different other regulators, might lead to inaccuracies in mitotic control. This hypothesis is underlined by the shortened time to anaphase in Kasumi-1 cells and a decreased expression of cyclin B, both of which are characteristics of BubR1-depletion. Mitotic regulators are already targets in AML therapy and a deeper understanding of mitotic processes in AML might lead to improved approaches. Disclosures: No relevant conflicts of interest to declare.

Expression level of ACE2 in lung adenocarcinoma.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e21022-e21022
Author(s):  
Danni Liu ◽  
Tianhao Mu ◽  
Shifu Chen
Keyword(s):  
Lung Adenocarcinoma ◽  
Lung Tumor ◽  
Expression Level ◽  
Normal Lung ◽  
Primary Lung Adenocarcinoma ◽  
Significant Difference ◽  
And Gender ◽  
Novel Coronavirus ◽  
Public Datasets ◽  
Ethnicity And Gender

e21022 Background: 2019-nCoV, a novel coronavirus (2019-nCoV), has infected tens of thousands of people in Wuhan, Hubei Province, China. This new coronavirus has led to hundreds of deaths, and especially threatened people with underlying diseases. ACE2 was reported as the 2019-nCoV putative receptor. The expression abundance of ACE2 may cause different disease progressions. Here, we evaluated the expression profile of ACE2 from 283 samples in lung adenocarcinoma . Methods: 283 samples from the public datasets (GEO: GSE31210 and GEO: GSE2109) were grouped by tissue, ethnicity and gender. The data was normalized by the RMA algorithm. Student 's t-test was used to compare the expression of ACE2 in different groups . Results: The expression level of ACE2 of primary lung tumor was significantly higher than normal lung tissue ( p < 0.0001). ACE2 was significantly differential-expressed between Asian and Caucasian lung adenocarcinoma patients ( p < 0.0001). However, no significant difference of the expression of ACE2 was observed by gender ( p = 0.33). Conclusions: ACE2 was highly expressed in primary lung adenocarcinoma , compared with normal lung tissues. The expression level of ACE2 was higher in Asian lung adenocarcinoma patients than Caucasian’s. These conclusions imply that Asian people with lung adenocarcinoma may be more vulnerable to 2019-nCoV.

scholarly journals A Case of Paraneoplastic Remitting Seronegative Symmetrical Synovitis with Pitting Edema Syndrome Improved by Chemotherapy

2017 ◽  
Vol 10 (3) ◽  
pp. 1131-1137 ◽  
Author(s):  
Takahiko Sakamoto ◽  
Shuji Ota ◽  
Terunobu Haruyama ◽  
Masashi Ishihara ◽  
Maika Natsume ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Lung Tumor ◽  
Laboratory Data ◽  
Acute Onset ◽  
Imaging Data ◽  
Primary Lung Adenocarcinoma ◽  
Rs3pe Syndrome ◽  
Hands And Feet ◽  
Endothelial Growth Factor ◽  
Pitting Edema

The patient was a 69-year-old male who had started experiencing acute-onset pain in both shoulder joints and edema of both hands and feet. His symptoms progressively worsened within 1 month. Laboratory data indicated elevated CRP and erythrocyte sedimentation rate despite the normal range of antinuclear antibodies and rheumatoid factor and normal organ function. Furthermore, imaging data of the hand indicated synovitis without bone erosions. Meanwhile, chest CT revealed a lung tumor, leading to a diagnosis of primary lung adenocarcinoma with EGFR mutation (cT2aN3M0, stage IIIB). Based on these findings, he was diagnosed as suffering from paraneoplastic remitting seronegative symmetrical synovitis with pitting edema (RS3PE) syndrome. Thereafter, his symptoms disappeared as the tumor size was rapidly decreased by gefitinib therapy for lung adenocarcinoma. Currently, RS3PE syndrome can be classified as a vascular endothelial growth factor (VEGF)-associated disorder. Given that his symptoms improved by chemotherapy, the present case further supported the possible hypothesis that paraneoplastic RS3PE syndrome might be caused by tumor-induced VEGF. Therefore, the present case suggested that the symptoms of acute-onset joint pain accompanied by pitting edema in elderly patients should be considered suspicious for a malignant tumor, thereby warranting a detailed full-body examination.

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