Lung squamous cell carcinoma is a common type of lung cancer, causing approximately 400,000 deaths per year worldwide. Genomic alterations in squamous cell lung cancers have not been comprehensively characterized, and no molecularly targeted agents have been specifically developed for its treatment. As part of The Cancer Genome Atlas, here we profile 178 lung squamous cell carcinomas to provide a comprehensive landscape of genomic and epigenomic alterations. We show that the tumour type is characterized by complex genomic alterations, with a mean of 360 exonic mutations, 165 genomic rearrangements, and 323 segments of copy number alteration per tumour. We find statistically recurrent mutations in 11 genes, including mutation of TP53 in nearly all specimens. Previously unreported loss-of-function mutations are seen in the HLA-A class I major histocompatibility gene. Significantly altered pathways included NFE2L2 and KEAP1 in 34%, squamous differentiation genes in 44%, phosphatidylinositol-3-OH kinase pathway genes in 47%, and CDKN2A and RB1 in 72% of tumours. We identified a potential therapeutic target in most tumours, offering new avenues of investigation for the treatment of squamous cell lung cancers.

/pdf/comprehensive-genomic-characterization-of-squamous-cell-lung-21esjtw2hn.pdf

Comprehensive genomic characterization of squamous cell lung cancers

DrugBank is a richly annotated resource that combines detailed drug data with comprehensive drug target and drug action information. Since its first release in 2006, DrugBank has been widely used to facilitate in silico drug target discovery, drug design, drug docking or screening, drug metabolism prediction, drug interaction prediction and general pharmaceutical education. The latest version of DrugBank (release 2.0) has been expanded significantly over the previous release. With approximately 4900 drug entries, it now contains 60% more FDA-approved small molecule and biotech drugs including 10% more 'experimental' drugs. Significantly, more protein target data has also been added to the database, with the latest version of DrugBank containing three times as many non-redundant protein or drug target sequences as before (1565 versus 524). Each DrugCard entry now contains more than 100 data fields with half of the information being devoted to drug/chemical data and the other half devoted to pharmacological, pharmacogenomic and molecular biological data. A number of new data fields, including food-drug interactions, drug-drug interactions and experimental ADME data have been added in response to numerous user requests. DrugBank has also significantly improved the power and simplicity of its structure query and text query searches. DrugBank is available at http://www.drugbank.ca.

/pdf/drugbank-a-knowledgebase-for-drugs-drug-actions-and-drug-h5bxks5u8l.pdf

DrugBank: a knowledgebase for drugs, drug actions and drug targets

DrugBank (http://www.drugbank.ca) is a richly annotated database of drug and drug target information. It contains extensive data on the nomenclature, ontology, chemistry, structure, function, action, pharmacology, pharmacokinetics, metabolism and pharmaceutical properties of both small molecule and large molecule (biotech) drugs. It also contains comprehensive information on the target diseases, proteins, genes and organisms on which these drugs act. First released in 2006, DrugBank has become widely used by pharmacists, medicinal chemists, pharmaceutical researchers, clinicians, educators and the general public. Since its last update in 2008, DrugBank has been greatly expanded through the addition of new drugs, new targets and the inclusion of more than 40 new data fields per drug entry (a 40% increase in data ‘depth’). These data field additions include illustrated drug-action pathways, drug transporter data, drug metabolite data, pharmacogenomic data, adverse drug response data, ADMET data, pharmacokinetic data, computed property data and chemical classification data. DrugBank 3.0 also offers expanded database links, improved search tools for drug–drug and food–drug interaction, new resources for querying and viewing drug pathways and hundreds of new drug entries with detailed patent, pricing and manufacturer data. These additions have been complemented by enhancements to the quality and quantity of existing data, particularly with regard to drug target, drug description and drug action data. DrugBank 3.0 represents the result of 2 years of manual annotation work aimed at making the database much more useful for a wide range of ‘omics’ (i.e. pharmacogenomic, pharmacoproteomic, pharmacometabolomic and even pharmacoeconomic) applications.

/pdf/drugbank-3-0-a-comprehensive-resource-for-omics-research-on-4jrdtzynwv.pdf

DrugBank 3.0: a comprehensive resource for ‘Omics’ research on drugs

Many late-onset neurodegenerative diseases, including Parkinson's disease and Huntington's disease, are associated with the formation of intracellular aggregates by toxic proteins. It is therefore crucial to understand the factors that regulate the steady-state levels of these 'toxins', at both the synthetic and degradation stages. The degradation pathways acting on such aggregate-prone cytosolic proteins include the ubiquitin-proteasome system and macroautophagy. Dysfunction of the ubiquitin-proteasome or macroautophagy pathways might contribute to the pathology of various neurodegenerative conditions. However, enhancing macroautophagy with drugs such as rapamycin could offer a tractable therapeutic strategy for a number of these diseases.

The roles of intracellular protein-degradation pathways in neurodegeneration

(Macro)autophagy is a bulk degradation process that mediates the clearance of long-lived proteins and organelles. Autophagy is initiated by double-membraned structures, which engulf portions of cytoplasm. The resulting autophagosomes ultimately fuse with lysosomes, where their contents are degraded. Although the term autophagy was first used in 1963, the field has witnessed dramatic growth in the last 5 years, partly as a consequence of the discovery of key components of its cellular machinery. In this review we focus on mammalian autophagy, and we give an overview of the understanding of its machinery and the signaling cascades that regulate it. As recent studies have also shown that autophagy is critical in a range of normal human physiological processes, and defective autophagy is associated with diverse diseases, including neurodegeneration, lysosomal storage diseases, cancers, and Crohn's disease, we discuss the roles of autophagy in health and disease, while trying to critically evaluate if the coincidence between autophagy and these conditions is causal or an epiphenomenon. Finally, we consider the possibility of autophagy upregulation as a therapeutic approach for various conditions.

https://www.physiology.org/doi/pdf/10.1152/physrev.00030.2009

Regulation of Mammalian Autophagy in Physiology and Pathophysiology

Degenerative disorders of motor neurons include a range of progressive fatal diseases such as amyotrophic lateral sclerosis (ALS), spinal-bulbar muscular atrophy (SBMA), and spinal muscular atrophy (SMA). Although the causative genetic alterations are known for some cases, the molecular basis of many SMA and SBMA-like syndromes and most ALS cases is unknown. Here we show that missense point mutations in the cytoplasmic dynein heavy chain result in progressive motor neuron degeneration in heterozygous mice, and in homozygotes this is accompanied by the formation of Lewy-like inclusion bodies, thus resembling key features of human pathology. These mutations exclusively perturb neuron-specific functions of dynein.

https://science.sciencemag.org/content/sci/300/5620/808.full.pdf

Mutations in Dynein Link Motor Neuron Degeneration to Defects in Retrograde Transport

The druggable genome: an update.

Protein micro-arrays are disclosed, with methods for their design, production and automated raw data processing, quality control and evaluation, that are suitable for performing parallel miniaturized quantitative binding assays which exhibit improved performance for automated high-throughput and parallel analyses of multiple parameters. The micro-arrays and methods of the invention are particularly well adapted to immunoassay analyses in which antibodies or antigens form the micro-arrays.

Parallel miniaturized quantitative immunoassays

A method for determining the concentration/amount of analyte molecules in the sample comprises the step of: (a) adding to the sample a known concentration/amount of competitor or analogue molecules of the analyte, said competitor/analogue molecules being distinct from said analyte molecules, (b) reacting/contacting the sample of step (a) with capture molecules for the analyte and competitor molecules, (c) determining a measure for the ratio R of analyte and competitor molecules that are bound to the capture molecules, (d) determining the concentration/amount of the analyte molecules from the ratio R of step (c) and the known concentration/amount of competitor molecules in the sample of step (a).

Stefan Lampel

Papers

Mutations in Dynein Link Motor Neuron Degeneration to Defects in Retrograde Transport

The druggable genome: an update.

Parallel miniaturized quantitative immunoassays

Method for determining analyte molecules in a sample