Catalogue of Somatic Mutations in Cancer (COSMIC) (http://www.sanger.ac.uk/cosmic) is a publicly available resource providing information on somatic mutations implicated in human cancer. Release v51 (January 2011) includes data from just over 19 000 genes, 161 787 coding mutations and 5573 gene fusions, described in more than 577 000 tumour samples. COSMICMart (COSMIC BioMart) provides a flexible way to mine these data and combine somatic mutations with other biological relevant data sets. This article describes the data available in COSMIC along with examples of how to successfully mine and integrate data sets using COSMICMart.
Database URL: http://www.sanger.ac.uk/genetics/CGP/cosmic/biomart/martview/
A major focus of modern biological research is the understanding of how genomic variation relates to disease. Although there are significant ongoing efforts to capture this understanding in curated resources, much of the information remains locked in unstructured sources, in particular, the scientific literature. Thus, there have been several text mining systems developed to target extraction of mutations and other genetic variation from the literature. We have performed the first study of the use of text mining for the recovery of genetic variants curated directly from the literature. We consider two curated databases, COSMIC (Catalogue Of Somatic Mutations In Cancer) and InSiGHT (International Society for Gastro-intestinal Hereditary Tumours), that contain explicit links to the source literature for each included mutation. Our analysis shows that the recall of the mutations catalogued in the databases using a text mining tool is very low, despite the well-established good performance of the tool and even when the full text of the associated article is available for processing. We demonstrate that this discrepancy can be explained by considering the supplementary material linked to the published articles, not previously considered by text mining tools. Although it is anecdotally known that supplementary material contains ‘all of the information’, and some researchers have speculated about the role of supplementary material (Schenck et al. Extraction of genetic mutations associated with cancer from public literature. J Health Med Inform 2012;S2:2.), our analysis substantiates the significant extent to which this material is critical. Our results highlight the need for literature mining tools to consider not only the narrative content of a publication but also the full set of material related to a publication.
The catalogue of Somatic Mutations in Cancer (COSMIC) (http://www.sanger.ac.uk/cosmic/) is the largest public resource for information on somatically acquired mutations in human cancer and is available freely without restrictions. Currently (v43, August 2009), COSMIC contains details of 1.5-million experiments performed through 13 423 genes in almost 370 000 tumours, describing over 90 000 individual mutations. Data are gathered from two sources, publications in the scientific literature, (v43 contains 7797 curated articles) and the full output of the genome-wide screens from the Cancer Genome Project (CGP) at the Sanger Institute, UK. Most of the world’s literature on point mutations in human cancer has now been curated into COSMIC and while this is continually updated, a greater emphasis on curating fusion gene mutations is driving the expansion of this information; over 2700 fusion gene mutations are now described. Whole-genome sequencing screens are now identifying large numbers of genomic rearrangements in cancer and COSMIC is now displaying details of these analyses also. Examination of COSMIC’s data is primarily web-driven, focused on providing mutation range and frequency statistics based upon a choice of gene and/or cancer phenotype. Graphical views provide easily interpretable summaries of large quantities of data, and export functions can provide precise details of user-selected data.
COSMIC is currently the most comprehensive global resource for information on somatic mutations in human cancer, combining curation of the scientific literature with tumor resequencing data from the Cancer Genome Project at the Sanger Institute, U.K. Almost 4800 genes and 250000 tumors have been examined, resulting in over 50000 mutations available for investigation. This information can be accessed in a number of ways, the most convenient being the Web-based system which allows detailed data mining, presenting the results in easily interpretable formats. This unit describes the graphical system in detail, elaborating an example walkthrough and the many ways that the resulting information can be thoroughly investigated by combining data, respecializing the query, or viewing the results in different ways. Alternate protocols overview the available precompiled data files available for download.
COSMIC; cancer; somatic; mutation; database
Cutaneous malignant melanoma is the most fatal skin cancer and although improved comprehension of its pathogenic pathways allowed to realize some effective molecular targeted therapies, novel targets and drugs are still needed. Aiming to add genetic information potentially useful for novel targets discovery, we performed an extensive genomic characterization by whole-exome sequencing and SNP array profiling of six cutaneous melanoma cell lines derived from metastatic patients. We obtained a total of 3,325 novel coding single nucleotide variants, including 2,172 non-synonymous variants. We catalogued the coding mutations according to Sanger COSMIC database and to a manually curated list including genes involved in melanoma pathways identified by mining recent literature. Besides confirming the presence of known melanoma driver mutations (BRAFV600E, NRASQ61R), we identified novel mutated genes involved in signalling pathways crucial for melanoma pathogenesis and already addressed by current targeted therapies (such as MAPK and glutamate pathways). We also identified mutations in four genes (MUC19, PAICS, RBMXL1, KIF23) never reported in melanoma, which might deserve further investigations. All data are available to the entire research community in our Melanoma Exome Database (at https://22.214.171.124/MExDB/). In summary, these cell lines are valuable biological tools to improve the genetic comprehension of this complex cancer disease and to study functional relevance of individual mutational events, and these findings could provide insights potentially useful for identification of novel therapeutic targets for cutaneous malignant melanoma.
COSMIC (http://www.sanger.ac.uk/cosmic) curates comprehensive information on somatic mutations in human cancer. Release v48 (July 2010) describes over 136 000 coding mutations in almost 542 000 tumour samples; of the 18 490 genes documented, 4803 (26%) have one or more mutations. Full scientific literature curations are available on 83 major cancer genes and 49 fusion gene pairs (19 new cancer genes and 30 new fusion pairs this year) and this number is continually increasing. Key amongst these is TP53, now available through a collaboration with the IARC p53 database. In addition to data from the Cancer Genome Project (CGP) at the Sanger Institute, UK, and The Cancer Genome Atlas project (TCGA), large systematic screens are also now curated. Major website upgrades now make these data much more mineable, with many new selection filters and graphics. A Biomart is now available allowing more automated data mining and integration with other biological databases. Annotation of genomic features has become a significant focus; COSMIC has begun curating full-genome resequencing experiments, developing new web pages, export formats and graphics styles. With all genomic information recently updated to GRCh37, COSMIC integrates many diverse types of mutation information and is making much closer links with Ensembl and other data resources.
The Catalogue Of Somatic Mutations In Cancer (COSMIC) database and web site was developed to preserve somatic mutation data and share it with the community. Over the past 25 years, approximately 350 cancer genes have been identified, of which 311 are somatically mutated. COSMIC has been expanded and now holds data previously reported in the scientific literature for 28 known cancer genes. In addition, there is data from the systematic sequencing of 518 protein kinase genes. The total gene count in COSMIC stands at 538; 25 have a mutation frequency above 5% in one or more tumour type, no mutations were found in 333 genes and 180 are rarely mutated with frequencies <5% in any tumour set. The COSMIC web site has been expanded to give more views and summaries of the data and provide faster query routes and downloads. In addition, there is a new section describing mutations found through a screen of known cancer genes in 728 cancer cell lines including the NCI-60 set of cancer cell lines.
somatic; mutation; database; website
Over the past three decades, mortality from lung cancer has sharply and continuously increased in China, ascending to the first cause of death among all types of cancer. The ability to identify the actual sequence of gene mutations may help doctors determine which mutations lead to precancerous lesions and which produce invasive carcinomas, especially using next-generation sequencing (NGS) technology. In this study, we analyzed the latest lung cancer data in the COSMIC database, in order to find genomic “hotspots” that are frequently mutated in human lung cancer genomes. The results revealed that the most frequently mutated lung cancer genes are EGFR, KRAS and TP53. In recent years, EGFR and KRAS lung cancer test kits have been utilized for detecting lung cancer patients, but they presented many disadvantages, as they proved to be of low sensitivity, labor-intensive and time-consuming. In this study, we constructed a more complete catalogue of lung cancer mutation events including 145 mutated genes. With the genes of this list it may be feasible to develop a NGS kit for lung cancer mutation detection.
Lung cancer; Next-generation sequencing; Somatic mutation kit; COSMIC
With the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/.
With the advent of whole-genome analysis for profiling tumor tissue, a pressing need has emerged for principled methods of organizing the large amounts of resulting genomic information. We propose the concept of multiplicity measures on cancer and gene networks to organize the information in a clinically meaningful manner. Multiplicity applied in this context extends Fearon and Vogelstein's multi-hit genetic model of colorectal carcinoma across multiple cancers.
Using the Catalogue of Somatic Mutations in Cancer (COSMIC), we construct networks of interacting cancers and genes. Multiplicity is calculated by evaluating the number of cancers and genes linked by the measurement of a somatic mutation. The Kamada-Kawai algorithm is used to find a two-dimensional minimum energy solution with multiplicity as an input similarity measure. Cancers and genes are positioned in two dimensions according to this similarity. A third dimension is added to the network by assigning a maximal multiplicity to each cancer or gene. Hierarchical clustering within this three-dimensional network is used to identify similar clusters in somatic mutation patterns across cancer types.
The clustering of genes in a three-dimensional network reveals a similarity in acquired mutations across different cancer types. Surprisingly, the clusters separate known causal mutations. The multiplicity clustering technique identifies a set of causal genes with an area under the ROC curve of 0.84 versus 0.57 when clustering on gene mutation rate alone. The cluster multiplicity value and number of causal genes are positively correlated via Spearman's Rank Order correlation (rs(8) = 0.894, Spearman's t = 17.48, p < 0.05). A clustering analysis of cancer types segregates different types of cancer. All blood tumors cluster together, and the cluster multiplicity values differ significantly (Kruskal-Wallis, H = 16.98, df = 2, p < 0.05).
We demonstrate the principle of multiplicity for organizing somatic mutations and cancers in clinically relevant clusters. These clusters of cancers and mutations provide representations that identify segregations of cancer and genes driving cancer progression.
Objectives: US commercial airline pilots, like all flight crew, are at increased risk for specific cancers, but the relation of these outcomes to specific air cabin exposures is unclear. Flight time or block (airborne plus taxi) time often substitutes for assessment of exposure to cosmic radiation. Our objectives were to develop methods to estimate exposures to cosmic radiation and circadian disruption for a study of chromosome aberrations in pilots and to describe workplace exposures for these pilots.
Methods: Exposures were estimated for cosmic ionizing radiation and circadian disruption between August 1963 and March 2003 for 83 male pilots from a major US airline. Estimates were based on 523 387 individual flight segments in company records and pilot logbooks as well as summary records of hours flown from other sources. Exposure was estimated by calculation or imputation for all but 0.02% of the individual flight segments’ block time. Exposures were estimated from questionnaire data for a comparison group of 51 male university faculty.
Results: Pilots flew a median of 7126 flight segments and 14 959 block hours for 27.8 years. In the final study year, a hypothetical pilot incurred an estimated median effective dose of 1.92 mSv (absorbed dose, 0.85 mGy) from cosmic radiation and crossed 362 time zones. This study pilot was possibly exposed to a moderate or large solar particle event a median of 6 times or once every 3.7 years of work. Work at the study airline and military flying were the two highest sources of pilot exposure for all metrics. An index of work during the standard sleep interval (SSI travel) also suggested potential chronic sleep disturbance in some pilots. For study airline flights, median segment radiation doses, time zones crossed, and SSI travel increased markedly from the 1990s to 2003 (Ptrend < 0.0001). Dose metrics were moderately correlated with records-based duration metrics (Spearman’s r = 0.61–0.69).
Conclusions: The methods developed provided an exposure profile of this group of US airline pilots, many of whom have been exposed to increasing cosmic radiation and circadian disruption from the 1990s through 2003. This assessment is likely to decrease exposure misclassification in health studies.
circadian disruption; cosmic radiation; exposure assessment; flight crew; pilots
The massive use of Next-Generation Sequencing (NGS) technologies is uncovering an unexpected amount of variability. The functional characterization of such variability, particularly in the most common form of variation found, the Single Nucleotide Variants (SNVs), has become a priority that needs to be addressed in a systematic way. VARIANT (VARIant ANalyis Tool) reports information on the variants found that include consequence type and annotations taken from different databases and repositories (SNPs and variants from dbSNP and 1000 genomes, and disease-related variants from the Genome-Wide Association Study (GWAS) catalog, Online Mendelian Inheritance in Man (OMIM), Catalog of Somatic Mutations in Cancer (COSMIC) mutations, etc). VARIANT also produces a rich variety of annotations that include information on the regulatory (transcription factor or miRNA-binding sites, etc.) or structural roles, or on the selective pressures on the sites affected by the variation. This information allows extending the conventional reports beyond the coding regions and expands the knowledge on the contribution of non-coding or synonymous variants to the phenotype studied. Contrarily to other tools, VARIANT uses a remote database and operates through efficient RESTful Web Services that optimize search and transaction operations. In this way, local problems of installation, update or disk size limitations are overcome without the need of sacrifice speed (thousands of variants are processed per minute). VARIANT is available at: http://variant.bioinfo.cipf.es.
As large-scale re-sequencing of genomes reveals many protein mutations, especially in human cancer tissues, prediction of their likely functional impact becomes important practical goal. Here, we introduce a new functional impact score (FIS) for amino acid residue changes using evolutionary conservation patterns. The information in these patterns is derived from aligned families and sub-families of sequence homologs within and between species using combinatorial entropy formalism. The score performs well on a large set of human protein mutations in separating disease-associated variants (∼19 200), assumed to be strongly functional, from common polymorphisms (∼35 600), assumed to be weakly functional (area under the receiver operating characteristic curve of ∼0.86). In cancer, using recurrence, multiplicity and annotation for ∼10 000 mutations in the COSMIC database, the method does well in assigning higher scores to more likely functional mutations (‘drivers’). To guide experimental prioritization, we report a list of about 1000 top human cancer genes frequently mutated in one or more cancer types ranked by likely functional impact; and, an additional 1000 candidate cancer genes with rare but likely functional mutations. In addition, we estimate that at least 5% of cancer-relevant mutations involve switch of function, rather than simply loss or gain of function.
Background: Earlier studies have found increased breast cancer risk among female cabin crew. This has been suggested to reflect lifestyle factors (for example, age at first birth), other confounding factors (for example, age at menarche), or occupational factors such as exposure to cosmic radiation and circadian rhythm alterations due to repeated jet lag.
Aims: To assess the contribution of occupational versus lifestyle and other factors to breast cancer risk among cabin attendants in Finland.
Methods: A standardised self-administered questionnaire on demographic, occupational, and lifestyle factors was given to 1041 cabin attendants. A total of 27 breast cancer cases and 517 non-cases completed the questionnaire. Breast cancer diagnoses were confirmed through the Finnish Cancer Registry. Exposure to cosmic radiation was estimated based on self-reported flight history and timetables. A conditional logistic regression model was used for analysis.
Results: In the univariate analysis, family history of breast cancer (OR = 2.67, 95% CI: 1.00 to 7.08) was the strongest determinant of breast cancer. Of occupational exposures, sleep rhythm disruptions (OR = 1.72, 95% CI: 0.70 to 4.27) were positively related and disruption of menstrual cycles (OR = 0.71, 95% CI: 0.26 to 1.96) negatively related to breast cancer. However, both associations were statistically non-significant. Cumulative radiation dose (OR = 0.99, 95% CI: 0.83 to 1.19) showed no effect on breast cancer.
Conclusions: Results suggest that breast cancer risk among Finnish cabin attendants is related to well established risk factors of breast cancer, such as family history of breast cancer. There was no clear evidence that the three occupational factors studied affected breast cancer risk among Finnish flight attendants.
The richest uranium ore bodies ever discovered (Cigar Lake and McArthur River) are presently under development in northeastern Saskatchewan. This subarctic region is also home to several operating uranium mines and aboriginal communities, partly dependent upon caribou for subsistence. Because of concerns over mining impacts and the efficient transfer of airborne radionuclides through the lichen-caribou-human food chain, radionuclides were analyzed in tissues from 18 barren-ground caribou (Rangifer tarandus groenlandicus). Radionuclides included uranium (U), radium (226Ra), lead (210Pb), and polonium (210Po) from the uranium decay series; the fission product (137Cs) from fallout; and naturally occurring potassium (40K). Natural background radiation doses average 2-4 mSv/year from cosmic rays, external gamma rays, radon inhalation, and ingestion of food items. The ingestion of 210Po and 137Cs when caribou are consumed adds to these background doses. The dose increment was 0.85 mSv/year for adults who consumed 100 g of caribou meat per day and up to 1.7 mSv/year if one liver and 10 kidneys per year were also consumed. We discuss the cancer risk from these doses. Concentration ratios (CRs), relating caribou tissues to lichens or rumen (stomach) contents, were calculated to estimate food chain transfer. The CRs for caribou muscle ranged from 1 to 16% for U, 6 to 25% for 226Ra, 1 to 2% for 210Pb, 6 to 26% for 210Po, 260 to 370% for 137Cs, and 76 to 130% for 40K, with 137Cs biomagnifying by a factor of 3-4. These CRs are useful in predicting caribou meat concentrations from the lichens, measured in monitoring programs, for the future evaluation of uranium mining impacts on this critical food chain.
To assess the incidence of cancer among male airline pilots in the Nordic countries, with special reference to risk related to cosmic radiation.
Retrospective cohort study, with follow up of cancer incidence through the national cancer registries.
Denmark, Finland, Iceland, Norway, and Sweden.
10 032 male airline pilots, with an average follow up of 17 years.
Main outcome measures
Standardised incidence ratios, with expected numbers based on national cancer incidence rates; dose-response analysis using Poisson regression.
466 cases of cancer were diagnosed compared with 456 expected. The only significantly increased standardised incidence ratios were for skin cancer: melanoma 2.3 (95% confidence interval 1.7 to 3.0), non-melanoma 2.1 (1.7 to 2.8), basal cell carcinoma 2.5 (1.9 to 3.2). The relative risk of skin cancers increased with the estimated radiation dose. The relative risk of prostate cancer increased with increasing number of flight hours in long distance aircraft.
This study does not indicate a marked increase in cancer risk attributable to cosmic radiation, although some influence of cosmic radiation on skin cancer cannot be entirely excluded. The suggestion of an association between number of long distance flights (possibly related to circadian hormonal disturbances) and prostate cancer needs to be confirmed.
What is already known on this topicAirline pilots are occupationally exposed to cosmic radiation and other potentially carcinogenic elementsIn the studies published so far, dose-response patterns have not been characterisedWhat this study addsNo marked risk of cancer attributable to cosmic radiation is observed in airline pilotsA threefold excess of skin cancers is seen among pilots with longer careers, but the influence of recreational exposure to ultraviolet light cannot be quantifiedA slight increase in risk of prostate cancer with increasing number of long haul flights suggests a need for more studies on the effects of circadian hormonal disturbances
We sought to determine the frequency and clinical characteristics of patients with lung cancer harboring NRAS mutations. We used preclinical models to identify targeted therapies likely to be of benefit against NRAS mutant lung cancer cells.
Patients and Methods
We reviewed clinical data from patients whose lung cancers were identified at 6 institutions or reported in the Catalogue of Somatic Mutations in Cancer (COSMIC) to harbor NRAS mutations. 6 NRAS mutant cell lines were screened for sensitivity against inhibitors of multiple kinases (i.e. EGFR, ALK, MET, IGF-1R, BRAF, PI3K and MEK).
Among 4562 patients with lung cancers tested, NRAS mutations were present in 30 (0.7%; 95% confidence interval, 0.45% to 0.94%); 28 of these had no other driver mutations. 83% had adenocarcinoma histology with no significant differences in gender. While 95% of patients were former or current smokers, smoking-related G:C>T:A transversions were significantly less frequent in NRAS mutated lung tumors compared to KRAS-mutant NSCLCs (NRAS: 13% (4/30), KRAS: 66% (1772/2733), p<0.00000001). 5 of 6 NRAS mutant cell lines were sensitive to the MEK inhibitors, selumetinib and trametinib, but not to other inhibitors tested.
NRAS mutations define a distinct subset of lung cancers (~1%) with potential sensitivity to MEK inhibitors. While NRAS mutations are more common in current/former smokers, the types of mutations are not those classically associated with smoking.
NRAS mutation; EGFR mutation; KRAS mutation; lung cancer; non-small cell lung cancer; driver mutation; MEK inhibitor; erlotinib; gefitinib; crizotinib
Ionizing radiation long has been recognized as a cause of cancer. Among environmental cancer risks, radiation is unique in the variety of organs and tissues that it can affect. Numerous epidemiological studies with good dosimetry provide the basis for cancer risk estimation, including quantitative information derived from observed dose-response relationships. The amount of cancer attributable to ionizing radiation is difficult to estimate, but numbers such as 1 to 3% have been suggested. Some radiation-induced cancers attributable to naturally occurring exposures, such as cosmic and terrestrial radiation, are not preventable. The major natural radiation exposure, radon, can often be reduced, especially in the home, but not entirely eliminated. Medical use of radiation constitutes the other main category of exposure; because of the importance of its benefits to one's health, the appropriate prevention strategy is to simply work to minimize exposures.
Carcinogenesis induced by space radiation is considered a major risk factor in manned interplanetary and other extended missions. The models presently used to estimate the risk for cancer induction following deep space radiation exposure are based on data from A-bomb survivor cohorts and do not account for important biological differences existing between high-linear energy transfer (LET) and low-LET-induced DNA damage. High-energy and charge (HZE) radiation, the main component of galactic cosmic rays (CGR), causes highly complex DNA damage compared to low-LET radiation, which may lead to increased frequency of chromosomal rearrangements, and contribute to carcinogenic risk in astronauts. Gastrointestinal (GI) tumors are frequent in the United States, and colorectal cancer (CRC) is the third most common cancer accounting for 10% of all cancer deaths. On the basis of the aforementioned epidemiological observations and the frequency of spontaneous precancerous GI lesions in the general population, even a modest increase in incidence by space radiation exposure could have a significant effect on health risk estimates for future manned space flights. Ground-based research is necessary to reduce the uncertainties associated with projected cancer risk estimates and to gain insights into molecular mechanisms involved in space radiation-induced carcinogenesis. We investigated in vivo differential effects of γ-rays and HZE ions on intestinal tumorigenesis using two different murine models, ApcMin/+ and Apc1638 N/+. We showed that γ- and/or HZE exposure significantly enhances development and progression of intestinal tumors in a mutant-line-specific manner, and identified suitable models for in vivo studies of space radiation–induced intestinal tumorigenesis.
Apc; intestinal tumorigenesis; space radiation; risk estimates
This article reports measurements of household levels of gamma and cosmic rays at the addresses of children with cancer at the time of diagnosis and six months before, and of similar data at the addresses of control children. There is no indication of increased risk with increasing dose rates either in matched or unmatched analyses, with or without adjustment for deprivation. Sub-division by diagnostic group did not reveal any association with any specific types of malignancy. Studies of the relationship between household gamma rays and radon concentration show no evidence of any interactions.
British Journal of Cancer (2002) 86, 1727–1731. doi:10.1038/sj.bjc.6600277 www.bjcancer.com
© 2002 Cancer Research UK
childhood cancer; gamma dose rate; radon interactions; acute lymphoblastic leukaemia; non-Hodgkin's lymphoma; central nervous system tumours
Astronauts on a mission to Mars would be exposed for up to 3 years to galactic cosmic rays (GCR) — made up of high-energy protons and high charge (Z) and energy (E) (HZE) nuclei. GCR exposure rate increases about three times as spacecraft venture out of Earth orbit into deep space where protection of the Earth's magnetosphere and solid body are lost. NASA's radiation standard limits astronaut exposures to a 3% risk of exposure induced death (REID) at the upper 95% confidence interval (CI) of the risk estimate. Fatal cancer risk has been considered the dominant risk for GCR, however recent epidemiological analysis of radiation risks for circulatory diseases allow for predictions of REID for circulatory diseases to be included with cancer risk predictions for space missions. Using NASA's models of risks and uncertainties, we predicted that central estimates for radiation induced mortality and morbidity could exceed 5% and 10% with upper 95% CI near 10% and 20%, respectively for a Mars mission. Additional risks to the central nervous system (CNS) and qualitative differences in the biological effects of GCR compared to terrestrial radiation may significantly increase these estimates, and will require new knowledge to evaluate.
Cancer-associated mutations in cancer genes constitute a diverse set of mutations associated with the disease. To gain insight into features of the set, substitution, deletion and insertion mutations were analysed at the nucleotide level, from the COSMIC database. The most frequent substitutions were c→t, g→a, g→t, and the most frequent codon changes were to termination codons. Deletions more than insertions, FS (frameshift) indels more than I-F (in-frame) ones, and single-nucleotide indels, were frequent. FS indels cause loss of significant fractions of proteins. The 5′-cut in FS deletions, and 5′-ligation in FS insertions, often occur between pairs of identical bases. Interestingly, the cut-site and 3′-ligation in insertions, and 3′-cut and join-pair in deletions, were each found to be the same significantly often (p < 0.001). It is suggested that these features aid the incorporation of indel mutations. Tumor suppressors undergo larger numbers of mutations, especially disruptive ones, over the entire protein length, to inactivate two alleles. Proto-oncogenes undergo fewer, less-disruptive mutations, in selected protein regions, to activate a single allele. Finally, catalogues, in ranked order, of genes mutated in each cancer, and cancers in which each gene is mutated, were created. The study highlights the nucleotide level preferences and disruptive nature of cancer mutations.
Life is the harnessing of chemical energy in such a way that the energy-harnessing device makes a copy of itself. No energy, no evolution. The ‘modern synthesis’ of the past century explained evolution in terms of genes, but this is only part of the story. While the mechanisms of natural selection are correct, and increasingly well understood, they do little to explain the actual trajectories taken by life on Earth. From a cosmic perspective—what is the probability of life elsewhere in the Universe, and what are its probable traits?—a gene-based view of evolution says almost nothing. Irresistible geological and environmental changes affected eukaryotes and prokaryotes in very different ways, ones that do not relate to specific genes or niches. Questions such as the early emergence of life, the morphological and genomic constraints on prokaryotes, the singular origin of eukaryotes, and the unique and perplexing traits shared by all eukaryotes but not found in any prokaryote, are instead illuminated by bioenergetics. If nothing in biology makes sense except in the light of evolution, nothing in evolution makes sense except in the light of energetics. This Special Issue of Philosophical Transactions examines the interplay between energy transduction and genome function in the major transitions of evolution, with implications ranging from planetary habitability to human health. We hope that these papers will contribute to a new evolutionary synthesis of energetics and genetics.
energy flow; genomes; mitochondria; origin of life
Galactic Cosmic Radiation consisting of high-energy, high-charged (HZE) particles poses a significant threat to future astronauts in deep space. Aside from cancer, concerns have been raised about late degenerative risks, including effects on the brain. In this study we examined the effects of 56Fe particle irradiation in an APP/PS1 mouse model of Alzheimer’s disease (AD). We demonstrated 6 months after exposure to 10 and 100 cGy 56Fe radiation at 1 GeV/µ, that APP/PS1 mice show decreased cognitive abilities measured by contextual fear conditioning and novel object recognition tests. Furthermore, in male mice we saw acceleration of Aβ plaque pathology using Congo red and 6E10 staining, which was further confirmed by ELISA measures of Aβ isoforms. Increases were not due to higher levels of amyloid precursor protein (APP) or increased cleavage as measured by levels of the β C-terminal fragment of APP. Additionally, we saw no change in microglial activation levels judging by CD68 and Iba-1 immunoreactivities in and around Aβ plaques or insulin degrading enzyme, which has been shown to degrade Aβ. However, immunohistochemical analysis of ICAM-1 showed evidence of endothelial activation after 100 cGy irradiation in male mice, suggesting possible alterations in Aβ trafficking through the blood brain barrier as a possible cause of plaque increase. Overall, our results show for the first time that HZE particle radiation can increase Aβ plaque pathology in an APP/PS1 mouse model of AD.
SWAP-70 is a protein that has been suggested to be involved in regulation of actin rearrangement. Having discovered that an artificially-derived mutant of SWAP-70 can transform mouse embryo fibroblasts, we searched for naturally-occurring mutations in the SWAP-70 gene, finding listings for several on the Web at www.sanger.ac.uk/genetics/CGP/cosmic/, including three mutations found in ovarian cancers. (The number of such mutations has now reached 13 out of 228 tumors). We created expression vectors for the mutant SWAP-70 proteins and introduced these into NIH3T3 cells. The cells expressing the mutant SWAP-70 constructs exhibited faster growth than the parental or wild-type SWAP-70-expressing cells. In most instances, cells that are able to grow in soft agar will form tumors in nude mice. While SWAP-70-transformed cells grew in soft agar, they failed to form tumors in nude mice. This result implies that transformation by the SWAP-70 mutants is unique. The cells bearing the mutant SWAP-70 genes were sensitive to nutrient starvation, supporting the idea that they are transformed cells. However, they failed to pile up and demonstrated contact inhibition, unlike most normal transformed cells. Upon expression of human SWAP-70 genes, MEK1 was activated. This activation appeared to contribute to the saturation density of the cells. As SWAP-70 has been shown to be the last protein to receive signals from cytokines, it is likely that there is a putative feedback signaling pathway, and that disorder of this signaling pathway can transform cells. Accordingly, this may explain why SWAP-70-transformed cells have different characteristics than most transformed cells.