Stable Cell Lines

Our scientists have years of experience at performing gene editing with CRISPR/Cas9, from designing gRNA to transfection and single clone generation. Creative Biogene is offering a series of knockout cell lines developed by CRISPR/Cas9 system. These cell lines provide you with a convenient means to study gene functions

An Empirical-Mathematical Approach for Calibration and Fitting Cell-Electrode Electrical Models in Bioimpedance Tests

This paper proposes a new yet efficient method allowing a significant improvement in the on-line analysis of biological cell growing and evolution. The procedure is based on an empirical-mathematical approach for calibration and fitting of any cell-electrode electrical model. It is valid and can be extrapolated for any type of cellular line used in electrical cell-substrate impedance spectroscopy (ECIS) tests. Parameters of the bioimpedance model, acquired from ECIS experiments, vary for each cell line, which makes obtaining results difficult and—to some extent-renders them inaccurate. We propose a fitting method based on the cell line initial characterization,and carry out subsequent experiments with the same line to approach the percentage of well filling and the cell density (or cell number in the well). To perform our calibration technique, the so-called oscillation-based test (OBT) approach is employed for each cell density. Calibration results are validated by performing other experiments with different concentrations on the same cell line with the same measurement technique. Accordingly, a bioimpedance electrical model of each cell line is determined, which is valid for any further experiment and leading to a more precise electrical model of the electrode-cell system. Furthermore, the model parameters calculated can be also used by any other measurement techniques. Promising experimental outcomes for three different cell-lines have been achieved, supporting the usefulness of this technique

Methylation of CpG island is not a ubiquitous mechanism for the loss of oestrogen receptor in breast cancer cells.

Methylation has been shown to play an important role in the down-regulation of oestrogen receptors (ER) in breast cancer cells. One critical question that remains unclear is whether methylation can account for the loss of ER expression in cells derived from an ER-positive cell line. This laboratory has established an in vitro cell system using long-term growth of human ER-positive breast cancer cell line T47D in oestrogen-free medium. A clonal cell line, T47D:C4:2 (C4:2), has been characterized. Unlike T47D:A18 (A18), which is a T47D line maintained in oestrogen medium, C4:2 has lost the expression of ER and hormone responsiveness. DNA fingerprinting and restriction fragment length polymorphism (RFLP) analysis results confirmed that C4:2 was of the same lineage as A18. These cell lines provide an invaluable system to study the mechanism of ER expression and regulatory pathways leading to hormone-independent growth. The results here clearly demonstrate that the ER CpG island in C4:2 cells remains unmethylated. The loss of ER in the cell line must be due to mechanisms other than methylation. We also evaluated the ER CpG island in the MDA-MB-231:10A (10A) cell line, which is a clone from the MDA-MB-231 line obtained from ATCC and the DNA from the MDA-MB-231 cell line used in the original report. Unlike the cell line from the report, which showed a full methylation pattern in the island, the 10A line only showed a partial methylation pattern in the CpG island. Possible mechanisms pertaining to the heterogeneous methylation pattern of the ER CpG island in the breast cancer cells are discussed

Development and characterization of a new human hepatic cell line

The increasing demand and hampered use of primary human hepatocytes for research purposes have urged scientists to search for alternative cell sources, such as immortalized hepatic cell lines. The aim of this study was to develop a human hepatic cell line using the combined overexpression of TERT and the cell cycle regulators cyclin D1 and mutant isoform CDK4R24C. Following transduction of adult human primary hepatocytes with the selected immortalization genes, cell growth was triggered and a cell line was established. When cultured under appropriate conditions, the cell line expressed several hepatocytic markers and liver-enriched transcription factors at the transcriptional and/or translational level, secreted liver-specific proteins and showed glycogen deposition. These results suggest that the immortalization strategy applied to primary human hepatocytes could generate a novel hepatic cell line that seems to retain some key hepatic characteristics

Development and characterization of a new human hepatic cell line

The increasing demand and hampered use of primary human hepatocytes for research purposes have urged scientists to search for alternative cell sources, such as immortalized hepatic cell lines. The aim of this study was to develop a human hepatic cell line using the combined overexpression of TERT and the cell cycle regulators cyclin D1 and mutant isoform CDK4R24C. Following transduction of adult human primary hepatocytes with the selected immortalization genes, cell growth was triggered and a cell line was established. When cultured under appropriate conditions, the cell line expressed several hepatocytic markers and liver-enriched transcription factors at the transcriptional and/or translational level, secreted liver-specific proteins and showed glycogen deposition. These results suggest that the immortalization strategy applied to primary human hepatocytes could generate a novel hepatic cell line that seems to retain some key hepatic characteristics

Production of a T cell hybridoma that expresses the T cell receptor gamma/delta heterodimer.

We have produced a T cell hybridoma line by fusion of an IL-2-dependent, long-term T cell receptor (TCR) gamma/delta+ Thy-1+, bone marrow-derived, dendritic epidermal cell line to the BW5147 tumor line. The resultant hybridoma was rapidly growing, lymphokine independent, and expressed T3 in association with the TCR gamma/delta heterodimer. Several subclones of the hybridoma line produced easily detectable levels of IL-2 after stimulation by anti-T3 or Con A. The availability of these cloned cell lines should greatly facilitate further functional, biochemical, and molecular studies of the TCR delta chain

Comprehensive transcriptomic analysis of cell lines as models of primary tumors across 22 tumor types.

Cancer cell lines are a cornerstone of cancer research but previous studies have shown that not all cell lines are equal in their ability to model primary tumors. Here we present a comprehensive pan-cancer analysis utilizing transcriptomic profiles from The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia to evaluate cell lines as models of primary tumors across 22 tumor types. We perform correlation analysis and gene set enrichment analysis to understand the differences between cell lines and primary tumors. Additionally, we classify cell lines into tumor subtypes in 9 tumor types. We present our pancreatic cancer results as a case study and find that the commonly used cell line MIA PaCa-2 is transcriptionally unrepresentative of primary pancreatic adenocarcinomas. Lastly, we propose a new cell line panel, the TCGA-110-CL, for pan-cancer studies. This study provides a resource to help researchers select more representative cell line models

Cell line name recognition in support of the identification of synthetic lethality in cancer from text

Motivation: The recognition and normalization of cell line names in text is an important task in biomedical text mining research, facilitating for instance the identification of synthetically lethal genes from the literature. While several tools have previously been developed to address cell line recognition, it is unclear whether available systems can perform sufficiently well in realistic and broad-coverage applications such as extracting synthetically lethal genes from the cancer literature. In this study, we revisit the cell line name recognition task, evaluating both available systems and newly introduced methods on various resources to obtain a reliable tagger not tied to any specific subdomain. In support of this task, we introduce two text collections manually annotated for cell line names: the broad-coverage corpus Gellus and CLL, a focused target domain corpus. Results: We find that the best performance is achieved using NERsuite, a machine learning system based on Conditional Random Fields, trained on the Gellus corpus and supported with a dictionary of cell line names. The system achieves an F-score of 88.46% on the test set of Gellus and 85.98% on the independently annotated CLL corpus. It was further applied at large scale to 24 302 102 unannotated articles, resulting in the identification of 5 181 342 cell line mentions, normalized to 11 755 unique cell line database identifiers