Genetic and Chemical Modifiers of EGFR Dependence in Non-Small Cell Lung Cancer

The term `oncogene addiction' has been used to describe the phenomenon whereby tumor cells exhibit singular reliance on an oncogene or oncogenic pathway for their survival, despite the accumulation of multiple genetic lesions. In non-small cell lung cancer (NSCLC), this principle is perhaps best exemplified with the finding that epidermal growth factor receptor (EGFR) mutations predict response to EGFR-targeted therapies and thus represent a dependency in the subset of tumors harboring these alterations. Yet while EGFR-mutant tumors often respond dramatically to EGFR inhibition, nearly 30% of cases are refractory to therapy at the outset, and all responsive patients ultimately develop resistance to therapy. A deeper understanding of the genetic underpinnings of EGFR dependence, and of the mechanisms by which EGFR-mutant cells can overcome addiction to EGFR, may improve clinical outcomes

Inhibitor-Sensitive FGFR1 Amplification in Human Non-Small Cell Lung Cancer

Background Squamous cell lung carcinomas account for approximately 25% of new lung carcinoma cases and 40,000 deaths per year in the United States. Although there are multiple genomically targeted therapies for lung adenocarcinoma, none has yet been reported in squamous cell lung carcinoma. Methodology/Principal Findings Using SNP array analysis, we found that a region of chromosome segment 8p11-12 containing three genes–WHSC1L1, LETM2, and FGFR1–is amplified in 3% of lung adenocarcinomas and 21% of squamous cell lung carcinomas. Furthermore, we demonstrated that a non-small cell lung carcinoma cell line harboring focal amplification of FGFR1 is dependent on FGFR1 activity for cell growth, as treatment of this cell line either with FGFR1-specific shRNAs or with FGFR small molecule enzymatic inhibitors leads to cell growth inhibition. Conclusions/Significance These studies show that FGFR1 amplification is common in squamous cell lung cancer, and that FGFR1 may represent a promising therapeutic target in non-small cell lung cancer.Novartis Pharmaceuticals CorporationAmerican Lung AssociationUniting Against Lung CancerSara Thomas Monopoli FundSeaman FoundationIndia. Dept. of BiotechnologyNational Lung Cancer Partnershi

Validation of Chordoma Cell Lines

<p>A) Proliferation rates of chordoma cell lines. U-CH2, MUG-Chor1, and JHC7 cells were seeded at a density of 20K cells, and cell number was measured at the indicated intervals for 16 days. Data represent the mean ± SD of 3 replicates. The experiment using JHC7 cells was performed at a different time than the remaining cell lines. B) Comparison of chordoma cell viability in IMDM/RPMI versus DMEM growth media. U-CH2, MUG-Chor1, and U-CH1 cells were grown using either IMDM/RPMI (4:1) + 10% FBS + DMSO (1:1000) media; or DMEM + 10% FBS + DMSO (1:1000) media for 72h. Cell viability was measured using CellTiter-Glo. Data are expressed as percent viability relative to IMDM/RPMI-treated cells and represent the mean ± SD of 24 replicates. ***0.0001 < P < 0.001; ****P < 0.0001 (two-tailed, unpaired t-tests). C) Chordoma cell lines express brachyury. JHC7, MUG-Chor1 (MUG), U-CH2, and U-CH1 chordoma cells and 293T human embryonic kidney cells were immunoblotted for brachyury expression.</p

A pan-cancer analysis of transcriptome changes associated with somatic mutations in U2AF1 reveals commonly altered splicing events.

Although recurrent somatic mutations in the splicing factor U2AF1 (also known as U2AF35) have been identified in multiple cancer types, the effects of these mutations on the cancer transcriptome have yet to be fully elucidated. Here, we identified splicing alterations associated with U2AF1 mutations across distinct cancers using DNA and RNA sequencing data from The Cancer Genome Atlas (TCGA). Using RNA-Seq data from 182 lung adenocarcinomas and 167 acute myeloid leukemias (AML), in which U2AF1 is somatically mutated in 3-4% of cases, we identified 131 and 369 splicing alterations, respectively, that were significantly associated with U2AF1 mutation. Of these, 30 splicing alterations were statistically significant in both lung adenocarcinoma and AML, including three genes in the Cancer Gene Census, CTNNB1, CHCHD7, and PICALM. Cell line experiments expressing U2AF1 S34F in HeLa cells and in 293T cells provide further support that these altered splicing events are caused by U2AF1 mutation. Consistent with the function of U2AF1 in 3' splice site recognition, we found that S34F/Y mutations cause preferences for CAG over UAG 3' splice site sequences. This report demonstrates consistent effects of U2AF1 mutation on splicing in distinct cancer cell types

Mapping the landscape of genetic dependencies in chordoma

Cancer cells possess unique molecular features that can confer an increased dependence on specific genes. Here, the authors use CRISPR-Cas9 screens to identify selectively essential genes and therapeutic targets in chordoma

Targeted brachyury degradation disrupts a highly specific autoregulatory program controlling chordoma cell identity

© 2020 The Authors Sheppard et al. map the brachyury regulatory landscape in chordoma and explore its targeting using transcriptional CDK inhibition and targeted brachyury degradation. Brachyury is a highly selective transcriptional regulator of chordoma identity, and they confirm that brachyury targeting is a promising therapeutic strategy

Perspectives of Big Data Quality in Smart Service Ecosystems (Quality of Design and Quality of Conformance)

Despite the increasing importance of data and information quality, current research related to Big Data quality is still limited. It is particularly unknown how to apply previous data quality models to Big Data. In this paper we review Big Data quality research from several perspectives and apply a known quality model with its elements of conformance to specification and design in the context of Big Data. Furthermore, we extend this model and demonstrate it utility by analyzing the impact of three Big Data characteristics such as volume, velocity and variety in the context of smart cities. This paper intends to build a foundation for further empirical research to understand Big Data quality and its implications in the design and execution of smart service ecosystems

<i>CTNNB1</i> 3′ UTR splicing associated with <i>U2AF1</i> S34F/Y mutation in lung adenocarcinoma and AML.

<p>“Percent spliced in” (PSI) values of the proximal 3′ splice site of the <i>CTNNB1</i> 3′ UTR splice event in (<b>A</b>) lung adenocarcinoma and (<b>B</b>) AML. (<b>C</b>) RNA-Seq read coverage of the 3′ UTR event in HeLa cells with two <i>U2AF1</i> non-induced controls, induction of <i>U2AF1</i> wild-type, and induction of <i>U2AF1</i> S34F.</p