RESUMEN
Single nucleotide substitutions are the most common type of somatic mutations in cancer genome. The goal of this study was to use publicly available somatic mutation data to quantify negative and positive selection in individual lung tumors and test how strength of directional and absolute selection is associated with clinical features. The analysis found a significant variation in strength of selection (both negative and positive) among tumors, with median selection tending to be negative even though tumors with strong positive selection also exist. Strength of selection estimated as the density of missense mutations relative to the density of silent mutations showed only a weak correlation with tumor mutation burden. In the "all histology together" analysis we found that absolute strength of selection was strongly correlated with all clinically relevant features analyzed. In histology-stratified analysis selection was strongest in small cell lung cancer. Selection in adenocarcinoma was somewhat higher compared to squamous cell carcinoma. The study suggests that somatic mutation- based quantifying of directional and absolute selection in individual tumors can be a useful biomarker of tumor aggressiveness.
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Neoplasias Pulmonares , Mutación , Selección Genética , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patología , Biomarcadores de Tumor/genética , Mutación Missense , Carcinoma de Células Escamosas/genética , Carcinoma de Células Escamosas/patologíaRESUMEN
BACKGROUND: Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated. METHODS: The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways. RESULTS: Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified. CONCLUSIONS: Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby. PLAIN LANGUAGE SUMMARY: The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.
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Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Adulto , Humanos , Carcinoma de Pulmón de Células no Pequeñas/genética , Metilación de ADN , Neoplasias Pulmonares/genética , Estudio de Asociación del Genoma Completo , Epigénesis Genética , Biomarcadores , Islas de CpGRESUMEN
INTRODUCTION: We are conducting a multicenter study to identify classifiers predictive of disease-specific survival in patients with primary melanomas. Here we delineate the unique aspects, challenges, and best practices for optimizing a study of generally small-sized pigmented tumor samples including primary melanomas of at least 1.05mm from AJTCC TNM stage IIA-IIID patients. We also evaluated tissue-derived predictors of extracted nucleic acids' quality and success in downstream testing. This ongoing study will target 1,000 melanomas within the international InterMEL consortium. METHODS: Following a pre-established protocol, participating centers ship formalin-fixed paraffin embedded (FFPE) tissue sections to Memorial Sloan Kettering Cancer Center for the centralized handling, dermatopathology review and histology-guided coextraction of RNA and DNA. Samples are distributed for evaluation of somatic mutations using next gen sequencing (NGS) with the MSK-IMPACTTM assay, methylation-profiling (Infinium MethylationEPIC arrays), and miRNA expression (Nanostring nCounter Human v3 miRNA Expression Assay). RESULTS: Sufficient material was obtained for screening of miRNA expression in 683/685 (99%) eligible melanomas, methylation in 467 (68%), and somatic mutations in 560 (82%). In 446/685 (65%) cases, aliquots of RNA/DNA were sufficient for testing with all three platforms. Among samples evaluated by the time of this analysis, the mean NGS coverage was 249x, 59 (18.6%) samples had coverage below 100x, and 41/414 (10%) failed methylation QC due to low intensity probes or insufficient Meta-Mixed Interquartile (BMIQ)- and single sample (ss)- Noob normalizations. Six of 683 RNAs (1%) failed Nanostring QC due to the low proportion of probes above the minimum threshold. Age of the FFPE tissue blocks (p<0.001) and time elapsed from sectioning to co-extraction (p = 0.002) were associated with methylation screening failures. Melanin reduced the ability to amplify fragments of 200bp or greater (absent/lightly pigmented vs heavily pigmented, p<0.003). Conversely, heavily pigmented tumors rendered greater amounts of RNA (p<0.001), and of RNA above 200 nucleotides (p<0.001). CONCLUSION: Our experience with many archival tissues demonstrates that with careful management of tissue processing and quality control it is possible to conduct multi-omic studies in a complex multi-institutional setting for investigations involving minute quantities of FFPE tumors, as in studies of early-stage melanoma. The study describes, for the first time, the optimal strategy for obtaining archival and limited tumor tissue, the characteristics of the nucleic acids co-extracted from a unique cell lysate, and success rate in downstream applications. In addition, our findings provide an estimate of the anticipated attrition that will guide other large multicenter research and consortia.
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Melanoma , MicroARNs , Ácidos Nucleicos , Humanos , Fijación del Tejido/métodos , MicroARNs/análisis , Melanoma/genética , ADN/genética , Adhesión en Parafina/métodos , FormaldehídoRESUMEN
The X-chromosome is among the largest human chromosomes. It differs from autosomes by a number of important features including hemizygosity in males, an almost complete inactivation of one copy in females, and unique patterns of recombination. We used data from the Catalog of Published Genome Wide Association Studies to compare densities of the GWAS-detected SNPs on the X-chromosome and autosomes. The density of GWAS-detected SNPs on the X-chromosome is 6-fold lower compared to the density of the GWAS-detected SNPs on autosomes. Differences between the X-chromosome and autosomes cannot be explained by differences in the overall SNP density, lower X-chromosome coverage by genotyping platforms or low call rate of X-chromosomal SNPs. Similar differences in the density of GWAS-detected SNPs were found in female-only GWASs (e.g. ovarian cancer GWASs). We hypothesized that the lower density of GWAS-detected SNPs on the X-chromosome compared to autosomes is not a result of a methodological bias, e.g. differences in coverage or call rates, but has a real underlying biological reason-a lower density of functional SNPs on the X-chromosome versus autosomes. This hypothesis is supported by the observation that (i) the overall SNP density of X-chromosome is lower compared to the SNP density on autosomes and that (ii) the density of genic SNPs on the X-chromosome is lower compared to autosomes while densities of intergenic SNPs are similar.
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Estudio de Asociación del Genoma Completo , Cromosoma X , Masculino , Femenino , Humanos , Polimorfismo de Nucleótido Simple/genéticaRESUMEN
Differential methylation plays an important role in melanoma development and is associated with survival, progression and response to treatment. However, the mechanisms by which methylation promotes melanoma development are poorly understood. The traditional explanation of selective advantage provided by differential methylation postulates that hypermethylation of regulatory 5'-cytosine-phosphate-guanine-3' dinucleotides (CpGs) downregulates the expression of tumor suppressor genes and therefore promotes tumorigenesis. We believe that other (not necessarily alternative) explanations of the selective advantages of methylation are also possible. Here, we hypothesize that melanoma cells use methylation to shut down transcription of nonessential genes - those not required for cell survival and proliferation. Suppression of nonessential genes allows tumor cells to be more efficient in terms of energy and resource usage, providing them with a selective advantage over the tumor cells that transcribe and subsequently translate genes they do not need. We named the hypothesis the Rule Out (RO) hypothesis. The RO hypothesis predicts higher methylation of CpGs located in regulatory regions (CpG islands) of nonessential genes. It also predicts the higher methylation of regulatory CpGs linked to nonessential genes in melanomas compared to nevi and lower expression of nonessential genes in malignant (derived from melanoma) versus normal (derived from nonaffected skin) melanocytes. The analyses conducted using in-house and publicly available data found that all predictions derived from the RO hypothesis hold, providing observational support for the hypothesis.
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Melanoma , Neoplasias Cutáneas , Humanos , Melanoma/patología , Neoplasias Cutáneas/patología , Regiones Promotoras Genéticas , Metilación de ADN , Islas de CpG , Regulación Neoplásica de la Expresión Génica , Melanoma Cutáneo MalignoRESUMEN
Largely, cancer development is driven by acquisition and positive selection of somatic mutations that increase proliferation and survival of tumor cells. As a result, genes related to cancer development tend to have an excess of somatic mutations in them. An excess of missense and/or nonsense mutations in a gene is an indicator of its cancer relevance. To identify genes with an excess of potentially functional missense or nonsense mutations one needs to compare the observed and expected numbers of mutations in the gene. We estimated the expected numbers of missense and nonsense mutations in individual human genes using (i) the number of potential sites for missense and nonsense mutations in individual transcripts and (ii) histology-specific nucleotide context-dependent mutation rates. To estimate mutation rates defined as the number of mutations per site per tumor we used silent mutations reported in the Catalog Of Somatic Mutations In Cancer (COSMIC). The estimates were nucleotide context dependent. We have identified 26 genes with an excess of missense and/or nonsense mutations for lung adenocarcinoma, 18 genes for small cell lung cancer, and 26 genes for squamous cell carcinoma of the lung. These genes include known genes and novel lung cancer gene candidates.
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Codón sin Sentido , Neoplasias Pulmonares , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patología , Mutación , Mutación Missense , Nucleótidos , OncogenesRESUMEN
Genome wide association studies (GWASs) have identified tens of thousands of single nucleotide polymorphisms (SNPs) associated with human diseases and characteristics. A significant fraction of GWAS findings can be false positives. The gold standard for true positives is an independent validation. The goal of this study was to identify SNP features associated with validation success. Summary statistics from the Catalog of Published GWASs were used in the analysis. Since our goal was an analysis of reproducibility, we focused on the diseases/phenotypes targeted by at least 10 GWASs. GWASs were arranged in discovery-validation pairs based on the time of publication, with the discovery GWAS published before validation. We used four definitions of the validation success that differ by stringency. Associations of SNP features with validation success were consistent across the definitions. The strongest predictor of SNP validation was the level of statistical significance in the discovery GWAS. The magnitude of the effect size was associated with validation success in a non-linear manner. SNPs with risk allele frequencies in the range 30-70% showed a higher validation success rate compared to rarer or more common SNPs. Missense, 5'UTR, stop gained, and SNPs located in transcription factor binding sites had a higher validation success rate compared to intergenic, intronic and synonymous SNPs. There was a positive association between validation success and the level of evolutionary conservation of the sites. In addition, validation success was higher when discovery and validation GWASs targeted the same ethnicity. All predictors of validation success remained significant in a multivariate logistic regression model indicating their independent contribution. To conclude, we identified SNP features predicting validation success of GWAS hits. These features can be used to select SNPs for validation and downstream functional studies.
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Estudio de Asociación del Genoma Completo/métodos , Polimorfismo de Nucleótido Simple , Secuencia Conservada , Etnicidad/genética , Frecuencia de los Genes , Estudios de Asociación Genética/métodos , Estudios de Asociación Genética/estadística & datos numéricos , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo/estadística & datos numéricos , Humanos , Modelos Logísticos , Análisis Multivariante , Oportunidad Relativa , Grupos Raciales/genética , Reproducibilidad de los ResultadosRESUMEN
Matching of actionable tumor mutations with targeted therapy increases response rates and prolongs survival in lung cancer patients. Drug development and trials targeting genetic alterations are expanding rapidly. We describe the role of a Molecular Tumor Board (MTB) in the design of molecularly informed treatment strategies in our lung cancer patient population. Tumor DNA was sequenced using a 50-gene targeted next-generation sequencing panel. Cases were evaluated by a multidisciplinary MTB who suggested a course of treatment based on each patient's molecular findings. During a three-year period, 21 lung cancer patients were presented at the MTB. All patients lacked common activating EGFR mutations and ALK rearrangements. One patient had Stage IIIb disease; all others were Stage IV; 18 patients had received ≥1 prior line of therapy (range 0-5). Suggestions for treatment with a targeted therapy were made for 19/21 (90.5%) patients, and four patients (21%) underwent treatment with a targeted agent, two as part of a clinical trial. Identified barriers to treatment with targeted therapy included: ineligibility for clinical trials (n â= â2), lack of interest in study/distance to travel (n â= â2), lack of disease progression (n â= â2), poor performance status (n â= â5), decision to treat next with immunotherapy (n â= â3), and unknown (n â= â1). For the majority of lung cancer patients, the MTB provided recommendations based on tumor genetic profiles. Identified barriers to treatment suggest that presentation to the MTB at earlier stages of disease may increase the number of patients eligible for treatment with a genetically informed targeted agent.
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We hypothesized that human genes differ by their sensitivity to ultraviolet (UV) exposure. We used somatic mutations detected by genome-wide screens in melanoma and reported in the Catalog Of Somatic Mutations In Cancer. As a measure of UV sensitivity, we used the number of silent mutations generated by C>T transitions in pyrimidine dimers of a given transcript divided by the number of potential sites for this type of mutations in the transcript. We found that human genes varied by UV sensitivity by two orders of magnitude. We noted that the melanoma-associated tumor suppressor gene CDKN2A was among the top five most UV-sensitive genes in the human genome. Melanoma driver genes have a higher UV-sensitivity compared with other genes in the human genome. The difference was more prominent for tumor suppressors compared with oncogene. The results of this study suggest that differential sensitivity of human transcripts to UV light may explain melanoma specificity of some driver genes. Practical significance of the study relates to the fact that differences in UV sensitivity among human genes need to be taken into consideration whereas predicting melanoma-associated genes by the number of somatic mutations detected in a given gene.
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Melanoma , Neoplasias Cutáneas , Genoma Humano , Humanos , Melanoma/genética , Mutación , Oncogenes , Mutación Silenciosa , Neoplasias Cutáneas/genética , Rayos UltravioletaRESUMEN
We hypothesized that a joint analysis of cancer risk-associated single-nucleotide polymorphism (SNP) and somatic mutations in tumor samples can predict functional and potentially causal SNPs from GWASs. We used mutations reported in the Catalog of Somatic Mutations in Cancer (COSMIC). Confirmed somatic mutations were subdivided into two groups: (1) mutations reported as SNPs, which we call mutational/SNPs and (2) somatic mutations that are not reported as SNPs, which we call mutational/noSNPs. It is generally accepted that the number of times a somatic mutation is reported in COSMIC correlates with its selective advantage to tumors, with more frequently reported mutations being more functional and providing a stronger selective advantage to the tumor cell. We found that mutations reported ≥10 times in COSMIC-frequent mutational/SNPs (fmSNPs) are likely to be functional. We identified 12 cancer risk-associated SNPs reported in the Catalog of published GWASs at least 10 times as confirmed somatic mutations and therefore deemed to be functional. Additionally, we have identified 42 SNPs that are tightly linked (R2 ≥ 0.8) to SNPs reported in the Catalog of published GWASs as cancer risk associated and that are also reported as fmSNPs. As a result, 54 candidate functional/potentially causal cancer risk associated SNPs were identified. We found that fmSNPs are more likely to be located in evolutionarily conserved regions compared with cancer risk associated SNPs that are not fmSNPs. We also found that fmSNPs also underwent positive selection, which can explain why they exist as population polymorphisms.
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Predisposición Genética a la Enfermedad , Mutación de Línea Germinal , Neoplasias/epidemiología , Neoplasias/genética , Polimorfismo de Nucleótido Simple , Estudio de Asociación del Genoma Completo , Humanos , RiesgoRESUMEN
BACKGROUND: A substantial proportion of cancer driver genes (CDG) are also cancer predisposition genes. However, the associations between genetic variants in lung CDGs and the susceptibility to lung cancer have rarely been investigated. METHODS: We selected expression-related single-nucleotide polymorphisms (eSNP) and nonsynonymous variants of lung CDGs, and tested their associations with lung cancer risk in two large-scale genome-wide association studies (20,871 cases and 15,971 controls of European descent). Conditional and joint association analysis was performed to identify independent risk variants. The associations of independent risk variants with somatic alterations in lung CDGs or recurrently altered pathways were investigated using data from The Cancer Genome Atlas (TCGA) project. RESULTS: We identified seven independent SNPs in five lung CDGs that were consistently associated with lung cancer risk in discovery (P < 0.001) and validation (P < 0.05) stages. Among these loci, rs78062588 in TPM3 (1q21.3) was a new lung cancer susceptibility locus (OR = 0.86, P = 1.65 × 10-6). Subgroup analysis by histologic types further identified nine lung CDGs. Analysis of somatic alterations found that in lung adenocarcinomas, rs78062588[C] allele (TPM3 in 1q21.3) was associated with elevated somatic copy number of TPM3 (OR = 1.16, P = 0.02). In lung adenocarcinomas, rs1611182 (HLA-A in 6p22.1) was associated with truncation mutations of the transcriptional misregulation in cancer pathway (OR = 0.66, P = 1.76 × 10-3). CONCLUSIONS: Genetic variants can regulate functions of lung CDGs and influence lung cancer susceptibility. IMPACT: Our findings might help unravel biological mechanisms underlying lung cancer susceptibility.
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Predisposición Genética a la Enfermedad/genética , Variación Genética/genética , Estudio de Asociación del Genoma Completo/métodos , Neoplasias Pulmonares/genética , Estudios de Casos y Controles , Femenino , Humanos , Masculino , Persona de Mediana EdadRESUMEN
INTRODUCTION: Inherited susceptibility to lung cancer risk in never-smokers is poorly understood. The major reason for this gap in knowledge is that this disease is relatively uncommon (except in Asians), making it difficult to assemble an adequate study sample. In this study we conducted a genome-wide association study on the largest, to date, set of European-descent never-smokers with lung cancer. METHODS: We conducted a two-phase (discovery and replication) genome-wide association study in never-smokers of European descent. We further augmented the sample by performing a meta-analysis with never-smokers from the recent OncoArray study, which resulted in a total of 3636 cases and 6295 controls. We also compare our findings with those in smokers with lung cancer. RESULTS: We detected three genome-wide statistically significant single nucleotide polymorphisms rs31490 (odds ratio [OR]: 0.769, 95% confidence interval [CI]: 0.722-0.820; p value 5.31 × 10-16), rs380286 (OR: 0.770, 95% CI: 0.723-0.820; p value 4.32 × 10-16), and rs4975616 (OR: 0.778, 95% CI: 0.730-0.829; p value 1.04 × 10-14). All three mapped to Chromosome 5 CLPTM1L-TERT region, previously shown to be associated with lung cancer risk in smokers and in never-smoker Asian women, and risk of other cancers including breast, ovarian, colorectal, and prostate. CONCLUSIONS: We found that genetic susceptibility to lung cancer in never-smokers is associated to genetic variants with pan-cancer risk effects. The comparison with smokers shows that top variants previously shown to be associated with lung cancer risk only confer risk in the presence of tobacco exposure, underscoring the importance of gene-environment interactions in the etiology of this disease.
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Cromosomas Humanos Par 5 , Neoplasias Pulmonares/epidemiología , Neoplasias Pulmonares/genética , Proteínas de la Membrana/genética , Telomerasa/genética , Estudios de Casos y Controles , Europa (Continente)/epidemiología , Femenino , Predisposición Genética a la Enfermedad , Variación Genética , Estudio de Asociación del Genoma Completo/métodos , Técnicas de Genotipaje/métodos , Humanos , Persona de Mediana Edad , Polimorfismo de Nucleótido Simple , Factores de RiesgoRESUMEN
BACKGROUND: Usually, genes with a higher-than-expected number of somatic mutations in tumor samples are assumed to be cancer related. We identified genes with a fewer-than-expected number of somatic mutations - "untouchable genes". METHODS: To predict the expected number of somatic mutations, we used a linear regression model with the number of mutations in the gene as an outcome, and gene characteristics, including gene size, nucleotide composition, level of evolutionary conservation, expression level and others, as predictors. Analysis of residuals from the regression model was used to compare the observed and predicted number of mutations. RESULTS: We have identified 19 genes with a less-than-expected number of loss-off-function (nonsense, frameshift or pathogenic missense) mutations - i.e., untouchable genes. The number of silent or neutral missense mutations in untouchable genes was equal or higher than the expected number. Many mucins, including MUC16, MUC17, MUC6, MUC5AC, MUC5B, and MUC12, are untouchable. We hypothesized that untouchable mucins help tumor cells to avoid immune response by providing a protective coat that prevents direct contact between effector immune cells, e.g., cytotoxic T-cells, and tumor cells. Survival analysis of available TCGA data demonstrated that overall survival of patients with low (below the median) expression of untouchable mucins was better compared to patients with high expression of untouchable mucins. Aside from mucins, we have identified a number of other untouchable genes. CONCLUSIONS: Untouchable genes may be ideal targets for cancer treatment since suppression of untouchable genes is expected to inhibit survival of tumor cells.
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Genes Relacionados con las Neoplasias , Genoma Humano , Neoplasias/genética , Neoplasias/terapia , Codón sin Sentido/genética , Mutación del Sistema de Lectura/genética , Humanos , Modelos Lineales , Mutación con Pérdida de Función/genética , Mucinas/genética , Mutación Missense/genética , Análisis de SupervivenciaRESUMEN
Melanoma is the most aggressive type of skin cancer in the United States with an increasing incidence. Melanoma lesions often exhibit high immunogenicity, with infiltrating immune cells playing important roles in regression of tumors occurring spontaneously or caused by therapeutic treatment. Computational and experimental methods have been used to estimate the abundance of immune cells in tumors, but their applications are limited by the requirement of large gene sets or multiple antibodies. Although the prognostic role of immune cells has been appreciated, a systematic investigation of their association with clinical factors, genomic features, prognosis and treatment response in melanoma is still lacking. This study, identifies a 25-gene signature based on RNA-seq data from The Cancer Genome Atlas (TCGA)-Skin Cutaneous Melanoma (TCGA-SKCM) dataset. This signature was used to calculate sample-specific Leukocyte Infiltration Scores (LIS) in six independent melanoma microarray datasets and scores were found to vary substantially between different melanoma lesion sites and molecular subtypes. For metastatic melanoma, LIS was prognostic in all datasets with high LIS being associated with good survival. The current approach provided additional prognostic information over established clinical factors, including age, tumor stage, and gender. In addition, LIS was predictive of patient survival in stage III melanoma, and treatment efficacy of tumor-specific antigen vaccine. IMPLICATIONS: This study identifies a 25-gene signature that effectively estimates the level of immune cell infiltration in melanoma, which provides a robust biomarker for predicting patient prognosis.
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Biomarcadores de Tumor/genética , Perfilación de la Expresión Génica/métodos , Leucocitos/metabolismo , Melanoma/genética , Neoplasias Cutáneas/genética , Femenino , Humanos , Masculino , Melanoma/patología , Pronóstico , Neoplasias Cutáneas/patologíaRESUMEN
BACKGROUND: Because driver mutations provide selective advantage to the mutant clone, they tend to occur at a higher frequency in tumor samples compared to selectively neutral (passenger) mutations. However, mutation frequency alone is insufficient to identify cancer genes because mutability is influenced by many gene characteristics, such as size, nucleotide composition, etc. The goal of this study was to identify gene characteristics associated with the frequency of somatic mutations in the gene in tumor samples. RESULTS: We used data on somatic mutations detected by genome wide screens from the Catalog of Somatic Mutations in Cancer (COSMIC). Gene size, nucleotide composition, expression level of the gene, relative replication time in the cell cycle, level of evolutionary conservation and other gene characteristics (totaling 11) were used as predictors of the number of somatic mutations. We applied stepwise multiple linear regression to predict the number of mutations per gene. Because missense, nonsense, and frameshift mutations are associated with different sets of gene characteristics, they were modeled separately. Gene characteristics explain 88% of the variation in the number of missense, 40% of nonsense, and 23% of frameshift mutations. Comparisons of the observed and expected numbers of mutations identified genes with a higher than expected number of mutations- positive outliers. Many of these are known driver genes. A number of novel candidate driver genes was also identified. CONCLUSIONS: By comparing the observed and predicted number of mutations in a gene, we have identified known cancer-associated genes as well as 111 novel cancer associated genes. We also showed that adding the number of silent mutations per gene reported by genome/exome wide screens across all cancer type (COSMIC data) as a predictor substantially exceeds predicting accuracy of the most popular cancer gene predicting tool - MutsigCV.
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Codón sin Sentido , Mutación del Sistema de Lectura , Mutación Missense , Proteínas de Neoplasias/genética , Neoplasias/genética , Humanos , Tasa de MutaciónAsunto(s)
Autoinmunidad , Proteínas/metabolismo , Enfermedad Pulmonar Obstructiva Crónica/inmunología , Enfermedad Pulmonar Obstructiva Crónica/metabolismo , Humanos , Modelos Logísticos , Fenotipo , Polimorfismo de Nucleótido Simple , Proteínas/genética , Proteínas/inmunología , Enfermedad Pulmonar Obstructiva Crónica/genética , Población BlancaRESUMEN
BACKGROUND: Accurate inference of genetic ancestry is of fundamental interest to many biomedical, forensic, and anthropological research areas. Genetic ancestry memberships may relate to genetic disease risks. In a genome association study, failing to account for differences in genetic ancestry between cases and controls may also lead to false-positive results. Although a number of strategies for inferring and taking into account the confounding effects of genetic ancestry are available, applying them to large studies (tens thousands samples) is challenging. The goal of this study is to develop an approach for inferring genetic ancestry of samples with unknown ancestry among closely related populations and to provide accurate estimates of ancestry for application to large-scale studies. METHODS: In this study we developed a novel distance-based approach, Ancestry Inference using Principal component analysis and Spatial analysis (AIPS) that incorporates an Inverse Distance Weighted (IDW) interpolation method from spatial analysis to assign individuals to population memberships. RESULTS: We demonstrate the benefits of AIPS in analyzing population substructure, specifically related to the four most commonly used tools EIGENSTRAT, STRUCTURE, fastSTRUCTURE, and ADMIXTURE using genotype data from various intra-European panels and European-Americans. While the aforementioned commonly used tools performed poorly in inferring ancestry from a large number of subpopulations, AIPS accurately distinguished variations between and within subpopulations. CONCLUSIONS: Our results show that AIPS can be applied to large-scale data sets to discriminate the modest variability among intra-continental populations as well as for characterizing inter-continental variation. The method we developed will protect against spurious associations when mapping the genetic basis of a disease. Our approach is more accurate and computationally efficient method for inferring genetic ancestry in the large-scale genetic studies.
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Genética de Población/métodos , Europa (Continente) , Genoma Humano/genética , Humanos , Filogenia , Análisis de Componente PrincipalRESUMEN
Genome-wide association studies (GWASs) identified over 500 single nucleotide polymorphisms (SNPs) influencing cancer risk. It is logical to expect the cancer-associated genes to cluster in pathways directly involved in carcinogenesis, e.g. cell cycle. Nevertheless, analyses of the GWAS-detected cancer risk genes usually show no or weak enrichment by known cancer genes.We hypothesized that GWAS-detected cancer risk-associated genes function as upstream regulators of the genes directly involved in carcinogenesis. We have analyzed four common cancers: breast, colon, lung, and prostate. To identify downstream targets of GWAS-detected cancer risk genes we used MedScan, which is a text mining tool offered by PathwayStudio. We also used data on protein/protein interactions reported by BioGRID database. Among all identified targets we have selected common downstream targets. A gene was considered a common downstream target if it was a downstream target for at least three GWAS-detected genes for a given cancer type. Common downstream targets were identified separately for each cancer type. We found that common downstream targets for all four cancer types were enriched by cell cycle genes, more specifically, the genes involved in G1/S transition. Common downstream targets for bipolar disorder, Crohn's disease, and type 2 diabetes did not show G1/S transition enrichment.The results of this analysis suggest that many cancer risk genes function as upstream regulators of the genes directly involved in G1/S transition and exert their risk effects by reducing threshold for G1/S transition, elevating the background level of cell proliferation and cancer risk.
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Carcinogénesis/genética , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Proteínas de Neoplasias/genética , Neoplasias de la Mama/genética , Neoplasias de la Mama/patología , Neoplasias del Colon/genética , Neoplasias del Colon/patología , Femenino , Puntos de Control de la Fase G1 del Ciclo Celular/genética , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patología , Masculino , Polimorfismo de Nucleótido Simple/genética , Neoplasias de la Próstata/genética , Neoplasias de la Próstata/patologíaRESUMEN
BACKGROUND: In the Prostate Cancer Prevention Trial, finasteride selectively suppressed low-grade prostate cancer and significantly reduced the incidence of prostate cancer in men treated with finasteride compared with placebo. However, an apparent increase in high-grade disease was also observed among men randomized to finasteride. We aimed to determine why and hypothesized that there is a grade-dependent response to finasteride. METHODS: From 2007 to 2012, we randomized dynamically by intranet-accessible software 183 men with localized prostate cancer to receive 5mg finasteride or placebo daily in a double-blind study during the 4-6weeks preceding prostatectomy. As the primary end point, the expression of a predefined molecular signature (ERß, UBE2C, SRD5A2, and VEGF) differentiating high- and low-grade tumors in Gleason grade (GG) 3 areas of finasteride-exposed tumors from those in GG3 areas of placebo-exposed tumors, adjusted for Gleason score (GS) at prostatectomy, was compared. We also determined androgen receptor (AR) levels, Ki-67, and cleaved caspase 3 to evaluate the effects of finasteride on the expression of its downstream target, cell proliferation, and apoptosis, respectively. The expression of these markers was also compared across grades between and within treatment groups. Logistic regression was used to assess the expression of markers. FINDINGS: We found that the predetermined molecular signature did not distinguish GG3 from GG4 areas in the placebo group. However, AR expression was significantly lower in the GG4 areas of the finasteride group than in those of the placebo group. Within the finasteride group, AR expression was also lower in GG4 than in GG3 areas, but not significantly. Expression of cleaved caspase 3 was significantly increased in both GG3 and GG4 areas in the finasteride group compared to the placebo group, although it was lower in GG4 than in GG3 areas in both groups. INTERPRETATION: We showed that finasteride's effect on apoptosis and AR expression is tumor grade dependent after short-term intervention. This may explain finasteride's selective suppression of low-grade tumors observed in the PCPT.
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Finasterida/administración & dosificación , Neoplasias de la Próstata/tratamiento farmacológico , Neoplasias de la Próstata/patología , Receptores Androgénicos/metabolismo , Administración Oral , Anciano , Apoptosis , Biomarcadores de Tumor/metabolismo , Proliferación Celular/efectos de los fármacos , Método Doble Ciego , Finasterida/farmacología , Humanos , Modelos Logísticos , Masculino , Persona de Mediana Edad , Clasificación del Tumor , Neoplasias de la Próstata/metabolismo , Resultado del TratamientoRESUMEN
While robotic-assisted laparoscopic radical prostatectomy (RALRP) is an effective treatment for localized prostate cancer, the risk of complications in older patients can be a deterrent to surgery. We evaluated the rate of medical complications following RALRP in a national dataset of safety events, and assessed whether age is an independent risk factor for these complications. Retrospective analysis of patients undergoing RALRP between 2009 and 2012 in the prospectively maintained American College of Surgeons National Surgical Quality Improvement (ACS-NSQIP) database was performed. Demographic and comorbid data were collated, medical complications occurring during the 30-day post-operative period were identified. We identified age-related comorbidities, and complications associated with these comorbidities. A binary logistic regression model with age and age-related comorbidities as predictors and specific complication as outcome, was used to evaluate whether age is an independent risk factor for these complications. 12,123 patients underwent RALRP between 2009 and 2012, with a mean age of 62 (22-92). Post-operative medical complications included urinary tract infection (UTI) (1.77 %), deep venous thrombosis (DVT) (0.67 %), pulmonary embolism (PE) (0.45 %), pneumonia (PNA) (0.27 %), myocardial infarction (MI) (0.12 %), and cerebrovascular accident (CVA) (0.01 %). Nine comorbidities were positively correlated with age (p < 0.05). Four medical complications were associated with these age-related comorbidities: MI, CVA, PNA, and UTI. On multivariate analysis, age was an independent risk factor for post-operative PNA (p < 0.05), but not for MI (p = 0.09), UTI (p = 0.3) or CVA (p = 0.2). Patient age was independently associated with post-operative pneumonia only. These data suggest that RALRP can be considered as a treatment option in selected older patients with minimal increased risk for post-operative complications.