25 Jul 2021-bioRxiv (Cold Spring Harbor Laboratory)-
TL;DR: PTEN tumors are addicted to ATM to detect and repair radiation induced DNA damage, which creates an exploitable bottleneck and low concentration of ATM inhibitor is able to synergise with IR to treat PTEN-deficient tumors in genetically well-defined IR resistant lung cancer models.
Abstract: Background: Despite advances in treatment of patients with non-small cell lung cancer, carriers of certain genetic alterations are prone to failure. One such factor frequently mutated, is the tumor suppressor PTEN. These tumors are supposed to be more resistant to radiation, chemo- and immunotherapy. Methods: Using CRISPR genome editing, we deleted PTEN in a human tracheal stem cell-like cell line as well generated primary murine NSCLC, proficient or deficient for Pten, in vivo. These models were used to verify the impact of PTEN loss in vitro and in vivo by immunohistochemical staining, western blot and RNA-Sequencing. Radiation sensitivity was assessed by colony formation and growth assays. To elucidate putative treatment options, identified via the molecular characterisation, PTEN pro- and deficient cells were treated with PI3K/mTOR/DNA-PK-inhibitor PI-103 or the ATM-inhibitors KU-60019 und AZD 1390. Changes in radiation sensitivity were assessed by colony-formation assay, FACS, western-blot, phospho-proteomic mass spectrometry and ex vivo lung slice cultures. Results: We demonstrate that loss of PTEN led to altered expression of transcriptional programs which directly regulate therapy resistance, resulting in establishment of radiation resistance. While PTEN-deficient tumor cells were not dependent on DNA PK for IR resistance nor activated ATR during IR, they showed a significant dependence for the DNA damage kinase ATM. Pharmacologic inhibition of ATM, via KU-60019 and AZD1390 at non-toxic doses, restored and even synergized with IR in PTEN-deficient human and murine NSCLC cells as well in a multicellular organotypic ex vivo tumor model. Conclusion: PTEN tumors are addicted to ATM to detect and repair radiation induced DNA damage. This creates an exploitable bottleneck. At least in cellulo and ex vivo we show that low concentration of ATM inhibitor is able to synergise with IR to treat PTEN-deficient tumors in genetically well-defined IR resistant lung cancer models.
For cell 97 detachment Trypsin (Sigma Aldrich) was used.
Result files were filtered 395 for the included genes to create pathway specific visualizations.
The authors study suggests that tumors harbouring a loss of function mutation in PTEN can 930 be therapeutically addressed by irradiation in combination with ATM inhibition.
BioRxiv preprint 26 h after radiation with 8 Gy (dashed lines) or without radiation (continuous 1108 lines) (dead cells stained with trypan blue excluded from analysis).
TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
Abstract: Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).
TL;DR: The combined cancer death rate dropped continuously from 1991 to 2015 by a total of 26%, translating to approximately 2,378,600 fewer cancer deaths than would have been expected if death rates had remained at their peak.
TL;DR: The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.
Abstract: The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.
TL;DR: A practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics, which makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries.
Abstract: The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
TL;DR: The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA with a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages.
Abstract: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.
Q1. What is the role of a phosphorylated PTEN in cancer cells?
ATM-mediated PTEN phosphorylation promotes PTEN nuclear 1315 translocation and autophagy in response to DNA-damaging agents in cancer cells.
Q2. What is the % gene that is altered?
%Genetic Alteration Inframe Mutation (putative driver) Missense Mutation (putative driver) Missense Mutation (unknown significance) Truncating Mutation (putative driver) Truncating Mutation (unknown significance) Fusion Amplification (putative driver) Amplification (unknown significance) Deep Deletion (putative driver) Deep Deletion (unknown significance)mRNA High mRNA Low No alterationsProfiled in mRNA expression z-scores relative to diploidsamples (RNA Seq V2 RSEM)Yes NoPTENKRASHRASNRASEGFRBRAFPIK3CA38%26%8%16%13%23%75%Genetic
Q3. What is the genesis of 1318 murine lung cancer?
Implementation of CRISPR/Cas9 Genome Editing to Generate 1318 Murine Lung Cancer Models That Depict the Mutational Landscape of Human 1319Disease.
Q4. who is the author/funder of the preprint?
1252.CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.