Abstract 2984: A comprehensive bioinformatic analysis of the representativity of 460 cancer cell lines as model systems for 88 different clinical cancer types

AbstractRepresentative in vitro model systems that accurately model response to therapy and allow the identification of new targets are important for improving our treatment of prostate cancer. Here we describe molecular characterization and drug testing in a panel of 20 prostate cancer cell lines. The cell lines cluster into distinct subsets based on RNA expression, which is largely driven by functional Androgen Receptor (AR) expression. KLK3, the AR-responsive gene that encodes prostate specific antigen, shows the greatest variability in expression across the cell line panel. Other common prostate cancer associated genes such as TMPRSS2 and ERG show similar expression patterns. Copy number analysis demonstrates that many of the most commonly gained (including regions containing TERC and MYC) and lost regions (including regions containing TP53 and PTEN) that were identified in patient samples by the TCGA are mirrored in the prostate cancer cell lines. Assessment of response to the anti-androgen enzalutamide shows a distinct separation of responders and non-responders, predominantly related to status of wild-type AR. Surprisingly, several AR-null lines responded to enzalutamide. These AR-null, enzalutamide-responsive cells were characterized by high levels of expression of glucocorticoid receptor (GR) encoded by NR3C1. Treatment of these cells with the anti-GR agent mifepristone showed that they were more sensitive to this drug than enzalutamide, as were several of the enzalutamide non-responsive lines. This is consistent with several recent reports that suggest that GR expression is an alternative signaling mechanism that can bypass AR blockade. This study reinforces the utility of large cell line panels for the study of cancer and identifies several cell lines that represent ideal models to study AR-null cells that have upregulated GR to sustain growth.

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Extracting Biological Insights from the Project Achilles Genome-Scale CRISPR Screens in Cancer Cell Lines

10.1101/720243 ◽

2019 ◽

Cited By ~ 41

Author(s):

Joshua M. Dempster ◽

Jordan Rossen ◽

Mariya Kazachkova ◽

Joshua Pan ◽

Guillaume Kugener ◽

...

Keyword(s):

Data Processing ◽

Cell Lines ◽

Cancer Cell ◽

Cancer Cell Lines ◽

Loss Of Function ◽

The Public ◽

Quality Control Metrics ◽

Cancer Types ◽

Genome Scale

AbstractOne of the main goals of the Cancer Dependency Map project is to systematically identify cancer vulnerabilities across cancer types to accelerate therapeutic discovery. Project Achilles serves this goal through the in vitro study of genetic dependencies in cancer cell lines using CRISPR/Cas9 (and, previously, RNAi) loss-of-function screens. The project is committed to the public release of its experimental results quarterly on the DepMap Portal (https://depmap.org), on a pre-publication basis. As the experiment has evolved, data processing procedures have changed. Here we present the current and projected Achilles processing pipeline, including recent improvements and the analyses that led us to adopt them, spanning data releases from early 2018 to the first quarter of 2020. Notable changes include quality control metrics, calculation of probabilities of dependency, and correction for screen quality and other biases. Developing and improving methods for extracting biologically-meaningful scores from Achilles experiments is an ongoing process, and we will continue to evaluate and revise data processing procedures to produce the best results.

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Pan-cancer single cell RNA-seq uncovers recurring programs of cellular heterogeneity

10.1101/807552 ◽

2019 ◽

Cited By ~ 4

Author(s):

Gabriela S. Kinker ◽

Alissa C. Greenwald ◽

Rotem Tal ◽

Zhanna Orlova ◽

Michael S. Cuoco ◽

...

Keyword(s):

Single Cell ◽

Cell Lines ◽

Cancer Cell ◽

Cancer Cell Lines ◽

Human Tumors ◽

Model Systems ◽

Cellular Heterogeneity ◽

Specific Cell ◽

Rna Seq ◽

Mesenchymal Transition

AbstractCultured cell lines are the workhorse of cancer research, but it is unclear to what extent they recapitulate the cellular heterogeneity observed among malignant cells in tumors, given the absence of a native tumor microenvironment. Here, we used multiplexed single cell RNA-seq to profile ~200 cancer cell lines. We uncovered expression programs that are recurrently heterogeneous within many cancer cell lines and are largely independent of observed genetic diversity. These programs of heterogeneity are associated with diverse biological processes, including cell cycle, senescence, stress and interferon responses, epithelial-to-mesenchymal transition, and protein maturation and degradation. Notably, some of these recurrent programs recapitulate those seen in human tumors, suggesting a prominent role of intrinsic plasticity in generating intra-tumoral heterogeneity. Moreover, the data allowed us to prioritize specific cell lines as model systems of cellular plasticity. We used two such models to demonstrate the dynamics, regulation and drug sensitivities associated with a cancer senescence program also observed in human tumors. Our work describes the landscape of cellular heterogeneity in diverse cancer cell lines, and identifies recurrent patterns of expression heterogeneity that are shared between tumors and specific cell lines and can thus be further explored in follow up studies.

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Newly established gastrointestinal cancer cell lines retain the genomic and immunophenotypic landscape of their parental cancers

Scientific Reports ◽

10.1038/s41598-020-74797-0 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Daniela Hirsch ◽

Steffen Seyfried ◽

Tobias Staib ◽

David Fiedler ◽

Christian Sauer ◽

...

Keyword(s):

Cell Lines ◽

Cancer Cell ◽

Molecular Mechanisms ◽

Human Cancer ◽

Cancer Cell Lines ◽

Biological Properties ◽

Model Systems ◽

Comparative Genomic ◽

Parental Tumor ◽

Tumor Entities

Abstract Human cancer cell lines are frequently used as model systems to study molecular mechanisms and genetic changes in cancer. However, the model is repeatedly criticized for its lack of proximity to original patient tumors. Therefore, understanding to what extent cell lines cultured under artificial conditions reflect the phenotypic and genomic profiles of their corresponding parental tumors is crucial when analyzing their biological properties. To directly compare molecular alterations between patient tumors and derived cell lines, we have established new cancer cell lines from four patients with gastrointestinal tumors. Tumor entities comprised esophageal cancer, colon cancer, rectal cancer and pancreatic cancer. Phenotype and genotype of both patient tumors and derived low-passage cell lines were characterized by immunohistochemistry (22 different antibodies), array-based comparative genomic hybridization and targeted next generation sequencing (48-gene panel). The immunophenotype was highly consistent between patient tumors and derived cell lines; the expression of most markers in cell lines was concordant with the respective parental tumor and characteristic for the respective tumor entities in general. The chromosomal aberration patterns of the parental tumors were largely maintained in the cell lines and the distribution of gains and losses was typical for the respective cancer entity, despite a few distinct differences. Cancer gene mutations (e.g., KRAS, TP53) and microsatellite status were also preserved in the respective cell line derivates. In conclusion, the four examined newly established cell lines exhibited a phenotype and genotype closely recapitulating their parental tumor. Hence, newly established cancer cell lines may be useful models for further pharmacogenomic studies.

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Antisense oligonucleotide delivery to cancer cell lines for the treatment of different cancer types

Artificial Cells Nanomedicine and Biotechnology ◽

10.3109/21691401.2015.1115409 ◽

2015 ◽

Vol 44 (8) ◽

pp. 1938-1948 ◽

Cited By ~ 9

Author(s):

Ebru Kilicay ◽

Ebru Erdal ◽

Baki Hazer ◽

Mustafa Türk ◽

Emir Baki Denkbas

Keyword(s):

Cell Lines ◽

Cancer Cell ◽

Antisense Oligonucleotide ◽

Cancer Cell Lines ◽

Cancer Types ◽

Oligonucleotide Delivery

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Synthesis, Antiproliferative Activity, and DNA Binding Studies of Nucleoamino Acid-Containing Pt(II) Complexes

Pharmaceuticals ◽

10.3390/ph13100284 ◽

2020 ◽

Vol 13 (10) ◽

pp. 284

Author(s):

Claudia Riccardi ◽

Domenica Capasso ◽

Angela Coppola ◽

Chiara Platella ◽

Daniela Montesarchio ◽

...

Keyword(s):

Cell Lines ◽

Cancer Cell ◽

Synergistic Effects ◽

Polyacrylamide Gel Electrophoresis ◽

Platinum Complexes ◽

Cancer Cell Lines ◽

Cd Spectroscopy ◽

Model Systems ◽

Binding Studies

We here report our studies on the reaction with the platinum(II) ion of a nucleoamino acid constituted by the l-2,3-diaminopropanoic acid linked to the thymine nucleobase through a methylenecarbonyl linker. The obtained new platinum complexes, characterized by spectroscopic and mass spectrometric techniques, were envisaged to exploit synergistic effects due to the presence of both the platinum center and the nucleoamino acid moiety. The latter can be potentially useful to protect the complexes from early deactivation, as well as to facilitate their cell internalization. The biological activity of the complexes in terms of antiproliferative effects was evaluated in vitro on different cancer cell lines and healthy cells, showing the best results on human cervical adenocarcinoma (HeLa) cells along with good selectivity for cancer over normal cells. In contrast, the metal-free nucleoamino acid did not show any cytotoxicity on both normal and cancer cell lines. Finally, the ability of the novel Pt(II) complexes to bind various DNA model systems was investigated by circular dichroism (CD) spectroscopy and polyacrylamide gel electrophoresis analyses proving that the newly obtained compounds can potentially target DNA, similarly to other well-known anticancer Pt complexes, with a peculiar G-quadruplex vs. duplex selectivity.

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Mutation Signatures Including APOBEC in Cancer Cell Lines

JNCI Cancer Spectrum ◽

10.1093/jncics/pky002 ◽

2018 ◽

Vol 2 (1) ◽

Cited By ~ 18

Author(s):

Matthew C Jarvis ◽

Diako Ebrahimi ◽

Nuri A Temiz ◽

Reuben S Harris

Keyword(s):

Cell Lines ◽

Cancer Cell ◽

Cancer Cell Lines ◽

Model Systems ◽

Single Base Substitution ◽

Base Substitution ◽

Cancer Type ◽

Primary Tumors ◽

Single Base ◽

Substitution Mutation

Abstract Background: Multiple endogenous and exogenous sources of DNA damage contribute to the overall mutation burden in cancer, with distinct and overlapping combinations contributing to each cancer type. Many mutation sources result in characteristic mutation signatures, which can be deduced from tumor genomic DNA sequences. Examples include spontaneous hydrolytic deamination of methyl-cytosine bases in CG motifs (AGEING signature) and C-to-T and C-to-G mutations in 5'-TC(A/T) motifs (APOBEC signature). Methods: The deconstructSigs R package was used to analyze single-base substitution mutation signatures in more than 1000 cancer cell lines. Two additional approaches were used to analyze the APOBEC mutation signature. Results: Most cell lines show evidence for multiple mutation signatures. For instance, the AGEING signature, which is the largest source of mutation in most primary tumors, predominates in the majority of cancer cell lines. The APOBEC mutation signature is enriched in cancer cell lines from breast, lung, head/neck, bladder, and cervical cancers, where this signature also comprises a large fraction of all mutations. Conclusions: The single-base substitution mutation signatures of cancer cell lines often reflect those of the original tumors from which they are derived. Cancer cell lines with enrichments for distinct mutation signatures such as APOBEC have the potential to become model systems for fundamental research on the underlying mechanisms and for advancing clinical strategies to exploit these processes.

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TBIO-26. NON-CANONICAL OPEN READING FRAMES ENCODE FUNCTIONAL PROTEINS ESSENTIAL FOR CANCER CELL SURVIVAL

Neuro-Oncology ◽

10.1093/neuonc/noaa222.849 ◽

2020 ◽

Vol 22 (Supplement_3) ◽

pp. iii471-iii471

Author(s):

John Prensner ◽

Oana Enache ◽

Victor Luria ◽

Karsten Krug ◽

Karl Clauser ◽

...

Keyword(s):

Cell Lines ◽

Cancer Cell ◽

Protein Translation ◽

Cancer Cell Lines ◽

Open Reading Frames ◽

Sequencing Analysis ◽

Multiple Cancer ◽

Cancer Types ◽

Non Coding Rnas ◽

Reading Frames

Abstract The brain is the foremost non-gonadal tissue for expression of non-coding RNAs of unclear function. Yet, whether such transcripts are truly non-coding or rather the source of non-canonical protein translation is unknown. Here, we used functional genomic screens to establish the cellular bioactivity of non-canonical proteins located in putative non-coding RNAs or untranslated regions of protein-coding genes. We experimentally interrogated 553 open reading frames (ORFs) identified by ribosome profiling for three major phenotypes: 257 (46%) demonstrated protein translation when ectopically expressed in HEK293T cells, 401 (73%) induced gene expression changes following ectopic expression across 4 cancer cell types, and 57 (10%) induced a viability defect when the endogenous ORF was knocked out using CRISPR/Cas9 in 8 human cancer cell lines. CRISPR tiling and start codon mutagenesis indicated that the biological impact of these non-canonical ORFs required their translation as opposed to RNA-mediated effects. We functionally characterized one of these ORFs, G029442—renamed GREP1 (Glycine-Rich Extracellular Protein-1)—as a cancer-implicated gene with high expression in multiple cancer types, such as gliomas. GREP1 knockout in >200 cancer cell lines reduced cell viability in multiple cancer types, including glioblastoma, in a cell-autonomous manner and produced cell cycle arrest via single-cell RNA sequencing. Analysis of the secretome of GREP1-expressing cells showed increased abundance of the oncogenic cytokine GDF15, and GDF15 supplementation mitigated the growth inhibitory effect of GREP1 knock-out. Taken together, these experiments suggest that the non-canonical ORFeome is surprisingly rich in biologically active proteins and potential cancer therapeutic targets deserving of further study.

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Comparing cancer cell lines and tumor samples by genomic profiles

10.1101/028159 ◽

2015 ◽

Cited By ~ 2

Author(s):

Rileen Sinha ◽

Nikolaus Schultz ◽

Chris Sander

Keyword(s):

Cell Lines ◽

Cancer Cell ◽

Cancer Cell Line ◽

Cancer Cell Lines ◽

Response To Therapy ◽

Computational Method ◽

The Cancer Genome Atlas ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Tumor Material

Cancer cell lines are often used in laboratory experiments as models of tumors, although they can have substantially different genetic and epigenetic profiles compared to tumors. We have developed a general computational method, TumorComparer, to systematically quantify similarities and differences between tumor material when detailed genetic and molecular profiles are available. The comparisons can be flexibly tailored to a particular biological question by placing a higher weight on functional alterations of interest (weighted similarity). In a first pan-cancer application, we have compared 260 cell lines from the Cancer Cell Line Encyclopaedia (CCLE) and 1914 tumors of six different cancer types from The Cancer Genome Atlas (TCGA), using weights to emphasize genomic alterations that frequently recur in tumors. We report the potential suitability of particular cell lines as tumor models and identify apparently unsuitable outlier cell lines, some of which are in wide use, for each of the six cancer types. In future, this weighted similarity method may be generalized for use in a clinical setting to compare patient profiles consisting of genomic patterns combined with clinical attributes, such as diagnosis, treatment and response to therapy.

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