Variants within the SP110 nuclear body protein modify risk of canine degenerative myelopathy.

Canine degenerative myelopathy (DM) is a naturally occurring neurodegenerative disease with similarities to some forms of amyotrophic lateral sclerosis (ALS). Most dogs that develop DM are homozygous for a common superoxide dismutase 1 gene (SOD1) mutation. However, not all dogs homozygous for this mutation develop disease. We performed a genome-wide association analysis in the Pembroke Welsh Corgi (PWC) breed comparing DM-affected and -unaffected dogs homozygous for the SOD1 mutation. The analysis revealed a modifier locus on canine chromosome 25. A haplotype within the SP110 nuclear body protein (SP110) was present in 40% of affected compared with 4% of unaffected dogs (P = 1.5 × 10(-5)), and was associated with increased probability of developing DM (P = 4.8 × 10(-6)) and earlier onset of disease (P = 1.7 × 10(-5)). SP110 is a nuclear body protein involved in the regulation of gene transcription. Our findings suggest that variations in SP110-mediated gene transcription may underlie, at least in part, the variability in risk for developing DM among PWCs that are homozygous for the disease-related SOD1 mutation. Further studies are warranted to clarify the effect of this modifier across dog breeds.

Pathway analysis of cervical cancer genome-wide association study highlights the MHC region and pathways involved in response to infection.

Cervical cancer is caused by infection with human papillomavirus (HPV). A genome-wide association study (GWAS) has identified several susceptibility loci for cervical cancer, but they explain only a small fraction of cervical cancer heritability. Other variants with weaker effect may be missed due to the stringent significance threshold. To identify important pathways in cervical carcinogenesis, we performed a two-stage pathway analysis in two independent GWASs in the Swedish population, using the single-nucleotide polymorphism (SNP) ratio test. The 565 predefined pathways from Kyoto Encyclopedia of Genes and Genomes and BioCarta databases were systematically evaluated in the discovery stage (1034 cases and 3948 controls with 632,668 SNPs) and the suggestive pathways were further validated in the replication stage (616 cases and 506 controls with 341,358 SNPs). We found 12 pathways that were significant in both stages, and these were further validated using set-based analysis. For 10 of these pathways, the effect was mainly due to genetic variation within the major histocompatibility complex (MHC) region. In addition, we identified a set of novel candidate genes outside the MHC region in the pathways denoted 'Staphylococcus aureus infection' and 'herpes simplex infection' that influenced susceptibility to cervical cancer (empirical P = 4.99 × 10(-5) and 4.99 × 10(-5) in the discovery study; empirical P = 8.98 × 10(-5) and 0.009 in the replication study, respectively). Staphylococcus aureus infection may evoke an inflammatory response that inadvertently enhances malignant progression caused by HPV infection, and Herpes simplex virus-2 infection may act in conjunction with HPV infection to increase the risk of cervical carcinoma development. These findings provide new insights into the etiology of cervical cancer.

Identification of two novel mammographic density loci at 6Q25.1.

INTRODUCTION: Mammographic density (MD) is a strong heritable and intermediate phenotype for breast cancer, but much of its genetic variation remains unexplained. We performed a large-scale genetic association study including 8,419 women of European ancestry to identify MD loci. METHODS: Participants of three Swedish studies were genotyped on a custom Illumina iSelect genotyping array and percent and absolute mammographic density were ascertained using semiautomated and fully automated methods from film and digital mammograms. Linear regression analysis was used to test for SNP-MD associations, adjusting for age, body mass index, menopausal status and six principal components. Meta-analyses were performed by combining P values taking sample size, study-specific inflation factor and direction of effect into account. RESULTS: Genome-wide significant associations were observed for two previously identified loci: ZNF365 (rs10995194, P = 2.3 × 10(-8) for percent MD and P = 8.7 × 10(-9) for absolute MD) and AREG (rs10034692, P = 6.7 × 10(-9) for absolute MD). In addition, we found evidence of association for two variants at 6q25.1, both of which are known breast cancer susceptibility loci: rs9485370 in the TAB2 gene (P = 4.8 × 10(-9) for percent MD and P = 2.5 × 10(-8) for absolute MD) and rs60705924 in the CCDC170/ESR1 region (P = 2.2 × 10(-8) for absolute MD). Both regions have been implicated in estrogen receptor signaling with TAB2 being a potential regulator of tamoxifen response. CONCLUSIONS: We identified two novel MD loci at 6q25.1. These findings underscore the importance of 6q25.1 as a susceptibility region and provide more insight into the mechanisms through which MD influences breast cancer risk.

Large-scale proteomics reveals precise biomarkers for detection of ovarian cancer in symptomatic women.

Ovarian cancer is the 8th most common cancer among women and has a 5-year survival of only 30-50%. While the survival is close to 90% for stage I tumours it is only 20% for stage IV. Current biomarkers are not sensitive nor specific enough, and novel biomarkers are urgently needed. We used the Explore PEA technology for large-scale analysis of 2943 plasma proteins to search for new biomarkers using two independent clinical cohorts. The discovery analysis using the first cohort identified 296 proteins that had significantly different levels in malign tumours as compared to benign and for 269 (91%) of these, the association was replicated in the second cohort. Multivariate modelling, including all proteins independent of their association in the univariate analysis, identified a model for separating benign conditions from malign tumours (stage I-IV) consisting of three proteins; WFDC2, KRT19 and RBFOX3. This model achieved an AUC of 0.92 in the replication cohort and a sensitivity and specificity of 0.93 and 0.77 at a cut-off developed in the discovery cohort. There was no statistical difference of the performance in the replication cohort compared to the discovery cohort. WFDC2 and KRT19 have previously been associated with ovarian cancer but RBFOX3 has not previously been identified as a potential biomarker. Our results demonstrate the ability of using high-throughput precision proteomics for identification of novel plasma protein biomarker for ovarian cancer detection.

Toward ovarian cancer screening with protein biomarkers using dried, self-sampled cervico-vaginal fluid.

Early detection is key for increased survival in ovarian cancer, but no general screening program exists today due to lack of biomarkers and overall cost versus benefit over traditional clinical methods. Here, we used dried cervico-vaginal fluid (CVF) as sampling matrix coupled with mass spectrometry for detection of protein biomarkers. We find that self-collected CVF on paper cards yields robust results and is suitable for high-throughput proteomics. Artificial intelligence-based methods were used to identify an 11-protein panel that separates cases from controls. In validation data, the panel achieved a sensitivity of 0.97 (95% CI 0.91-1.00) at a specificity of 0.67 (0.40-0.87). Analyses of samples collected prior to development of symptoms indicate that the panel is informative also of future risk of disease. Dried CVF is used in cervical cancer screening, and our results opens the possibility for a screening program also for ovarian cancer, based on self-collected CVF samples.

Adiposity and sex-specific cancer risk.

Obesity is associated with several types of cancer and fat distribution, which differs dramatically between sexes, has been suggested to be an independent risk factor. However, sex-specific effects on cancer risk have rarely been studied. Here we estimate the effects of fat accumulation and distribution on cancer risk in females and males. We performed a prospective study in 442,519 UK Biobank participants, for 19 cancer types and additional histological subtypes, with a mean follow-up time of 13.4 years. Cox proportional hazard models were used to estimate the effect of 14 different adiposity phenotypes on cancer rates, and a 5% false discovery rate was considered statistically significant. Adiposity-related traits are associated with all but three cancer types, and fat accumulation is associated with a larger number of cancers compared to fat distribution. In addition, fat accumulation or distribution exhibit differential effects between sexes on colorectal, esophageal, and liver cancer.

Contribution of TMC6 and TMC8 (EVER1 and EVER2) variants to cervical cancer susceptibility.

Cervical cancer (CxCa) is caused by persistent human papillomavirus (HPV) infection; genetic predisposition is also suspected to play a role. Our study is a targeted candidate gene follow-up based on: (i) strong clinical evidence demonstrating that mutations in the TMC6 and TMC8 (EVER1 and EVER2) genes associate with the HPV-associated disease epidermodysplasia verruciformis (EV) and (ii) recent epidemiological data suggesting a genetic susceptibility conferred by polymorphisms in such genes for skin and CxCa. Clarifying the association of the TMC6/8 genes with risk of CxCa will help in understanding why some HPV-infected women develop persistent infection, cervical lesions and eventually cancer while others do not. Twenty-two single nucleotide polymorphisms (SNPs) harboring the TMC6/8 genes were genotyped in 2,989 cases with cervical intraepithelial neoplasia grade III or invasive CxCa and 2,281 controls from the Swedish population. Association was evaluated in logistic regression models. Two SNPs displayed association with cervical disease: rs2290907 [odds ratio (OR)(GGvsAA) = 0.6, 95% confidence interval (95% CI): 0.3-0.9, p = 0.02)] and rs16970849 (OR(AGvsGG) = 0.8, 95% CI: 0.66-0.98, p = 0.03). The present data support the involvement of the TMC6/8 region in CxCa susceptibility but further analyses are needed to replicate our findings, fully characterize the region and understand the function of the genetic variants involved.

Data-driven analysis of a validated risk score for ovarian cancer identifies clinically distinct patterns during follow-up and treatment.

Background: Ovarian cancer is the eighth most common cancer among women and due to late detection prognosis is poor with an overall 5-year survival of 30-50%. Novel biomarkers are needed to reduce diagnostic surgery and enable detection of early-stage cancer by population screening. We have previously developed a risk score based on an 11-biomarker plasma protein assay to distinguish benign tumors (cysts) from malignant ovarian cancer in women with adnexal ovarian mass. Methods: Protein concentrations of 11 proteins were characterized in plasma from 1120 clinical samples with a custom version of the proximity extension assay. The performance of the assay was evaluated in terms of prediction accuracy based on receiver operating characteristics (ROC) and multiple hypothesis adjusted Fisher's Exact tests on achieved sensitivity and specificity. Results: The assay's performance is validated in two independent clinical cohorts with a sensitivity of 0.83/0.91 and specificity of 0.88/0.92. We also show that the risk score follows the clinical development and is reduced upon treatment, and increased with relapse and cancer progression. Data-driven modeling of the risk score patterns during a 2-year follow-up after diagnosis identifies four separate risk score trajectories linked to clinical development and survival. A Cox proportional hazard regression analysis of 5-year survival shows that at time of diagnosis the risk score is the second-strongest predictive variable for survival after tumor stage, whereas MUCIN-16 (CA-125) alone is not significantly predictive. Conclusion: The robust performance of the biomarker assay across clinical cohorts and the correlation with clinical development indicates its usefulness both in the diagnostic work-up of women with adnexal ovarian mass and for predicting their clinical course.

Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer.

BACKGROUND: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. METHODS: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). RESULTS: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. CONCLUSIONS: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.

Evaluation of Fanconi anaemia genes FANCA, FANCC and FANCL in cervical cancer susceptibility.

OBJECTIVE: Disrupting the function of any of the 13 Fanconi anaemia (FA) genes causes a DNA repair deficiency disorder, with patients being susceptible to a number of cancer types. Variation in the family of FA genes has been suggested to affect risk of cervical cancer. The current study evaluates the influence of three genes in the FA pathway on cervical cancer risk in Swedish women. METHODS: TagSNPs in FANCA, FANCC and FANCL were selected using the Tagger algorithm in Haploview. A total of 81 tagSNPs were genotyped in 782 cases (CIN3 or ICC) and 775 controls using the Illumina GoldenGate Assay and statistically analyzed for association with cervical cancer. RESULTS: 72 SNPs were successfully genotyped in >98% of the samples. Nominal associations were detected for FANCA rs11649196 (p=0.05) and rs4128763 in FANCC (p=0.02). The associations did not withstand correction for multiple testing. CONCLUSIONS: The current study does not support that genetic variation in FANCA, FANCC or FANCL genes affects susceptibility to cervical cancer in the Swedish population.

Genome-Wide Analyses for Osteosarcoma in Leonberger Dogs Reveal the CDKN2A/B Gene Locus as a Major Risk Locus.

Dogs represent a unique spontaneous cancer model. Osteosarcoma (OSA) is the most common primary bone tumor in dogs (OMIA 001441-9615), and strongly resembles human forms of OSA. Several large- to giant-sized dog breeds, including the Leonberger, have a greatly increased risk of developing OSA. We performed genome-wide association analysis with high-density imputed SNP genotype data from 273 Leonberger cases with a median age of 8.1 [3.1-13.5] years and 365 controls older than eight years. This analysis revealed significant associations at the CDKN2A/B gene locus on canine chromosome 11, mirroring previous findings in other dog breeds, such as the greyhound, that also show an elevated risk for OSA. Heritability (h2SNP) was determined to be 20.6% (SE = 0.08; p-value = 5.7 × 10-4) based on a breed prevalence of 20%. The 2563 SNPs across the genome accounted for nearly all the h2SNP of OSA, with 2183 SNPs of small effect, 316 SNPs of moderate effect, and 64 SNPs of large effect. As with many other cancers it is likely that regulatory, non-coding variants underlie the increased risk for cancer development. Our findings confirm a complex genetic basis of OSA, moderate heritability, and the crucial role of the CDKN2A/B locus leading to strong cancer predisposition in dogs. It will ultimately be interesting to study and compare the known genetic loci associated with canine OSA in human OSA.

Interaction of immunological genes on chromosome 2q33 and IFNG in susceptibility to cervical cancer.

OBJECTIVE: Cervical cancer is caused by persistent infection with human papillomavirus and genetic susceptibility factors may augment disease risk. The immune response consists of complex interactions and it was recently proposed that the association of combinations of genotypes at several genes should be examined. In support of this the combination CD28+17(TT)/IFNG+874(AA) was shown to increase cervical cancer risk in a Brazilian population (VB Guzman et al. New approach reveals CD28 and IFNG gene interaction in the susceptibility to cervical cancer. Hum Mol Genet 2008;17:1838-44) and our aim was to replicate this finding. METHODS: We re-examined the proposed associations by analysis of polymorphisms at CD28, IFNG, TNF, PDCD1, ICOS and CTLA4 in 1306 Swedish cases and 811 controls. RESULTS: Logistic regression analysis detected association at single SNP level for CD28+17 (p=0.01), IFNG+874 (p=0.02), and PDCD1+7785 (p=0.04). The two locus combination CD28+17(TT)/IFNG+874(AA) (OR=0.76 (0.60-0.96, empirical p=0.03) and the three-locus combination CD28+17(TT)/IFNG+874(AA)/ICOS+1564(TT) (OR=0.65(0.49-0.87), empirical p=0.006) were associated with decreased risk. The strongest association was detected for the combination CTLA4-319 (CC)/IFNG (AA) (OR=0.67(0.53-0.84), empirical p=0.0007). CONCLUSION: The observation that these combinations of loci are associated in different populations supports their importance in cervical cancer development although the opposite directions of the effect call for clarification. The polymorphisms studied might not be the functional variants per se, but linked to those exerting a functional effect. The opposite associations in the two populations could then be explained by differences in linkage disequilibrium and population structure.

Temporal trends over 3 decades and intrafamilial clustering of HPV types in Swedish patients with cervical cancer in situ.

Information on HPV type distribution in cervical cancer in situ in different populations is needed for evaluation of prophylactic vaccination programs targeting HPV 16 and 18. In our study, the HPV type prevalence in 1,079 Swedish women from multicase families diagnosed with cervical cancer in situ 1965-1993 was investigated using real-time PCR and archival tissue material. HPV type information was obtained for 974 samples. Among these, HPV 16 (61%) was the dominant type followed by HPV 33/52/58 (24%), HPV 31 (13%) and HPV 18/45 (12%). The detected prevalence of HPV 16 among cancer in situ decreased by 13% over the study period while the group of low frequency high-risk types increased. Related women were not prone to infection by the same type. These data suggest that the prevalence of individual HPV types has changed over time in Swedish patients with cervical cancer in situ. Large-scale studies of pathology biobank materials will enable further insight into the temporal changes of individual HPV types, as baseline information to properly evaluate the effect of vaccine programs. The findings also indicate that genetic susceptibility to cervical cancer operates through general and not type specific susceptibility to HPV infection.

Polymorphisms in 9q32 and TSCOT are linked to cervical cancer in affected sib-pairs with high mean age at diagnosis.

Cervical cancer is a multifactorial disease influenced by both environmental and genetic factors. We have previously found linkage to 9q32 in a genomewide scan of affected sib-pairs (ASPs) with cervical cancer and to the thymic stromal co-transporter (TSCOT), a candidate gene in this region. Here we examined the contribution of 9q32 and TSCOT to cervical cancer susceptibility using at larger material of 641 ASPs, 278 of which were included in the earlier genome-scan. Since heritable forms of cancer frequently show stronger genetic effects in families with early onset of disease, we stratified the ASPs into two groups based on mean age at diagnosis (MAAD) within sib-pairs. Surprisingly, ASPs with high MAAD (30.5-47.5 years) showed increased sharing at all microsatellite markers at 9q31.1-33.1 and linkage signals of up to MLS = 2.74 for TSCOT SNPs, while ASPs with low MAAD (19-30 years) showed no deviation from random genetic sharing (MLS = 0.00). The difference in allelic sharing between the two MAAD strata was significant (P < 0.005) and is not likely to be explained by the HLA haplotype, a previously known genetic susceptibility factor for cervical cancer. Our results indicate locus heterogeneity in the susceptibility to cervical cancer between the two strata, with polymorphisms in the 9q32 region mainly showing an effect in women with high MAAD.

Variants of chemokine receptor 2 and interleukin 4 receptor, but not interleukin 10 or Fas ligand, increase risk of cervical cancer.

Cervical cancer is caused by persistent infection of oncogenic human papillomavirus (HPV). Most infected women clear the virus without developing cervical lesions and it is likely that immunological host factors affect susceptibility to cervical cancer. The impact of the human leukocyte antigen (HLA) locus on the risk of cervical cancer is established and several other genes involved in immunological pathways have been suggested as biologically plausible candidates. The aim of this study was to examine the potential role of polymorphisms in 4 candidate genes by analysis of 1,306 familial cervical cancer cases and 288 controls. The following genes and polymorphisms were studied: Chemokine receptor 2 (CCR-2) V64I; Interleukin 4 receptor alpha (IL-4R) I75V, S503P and Q576R; Interleukin 10 (IL-10) -592; and Fas ligand (FasL) -844. The CCR-2 64I variant was associated with decreased risk of cervical cancer; homozygote carriers of the 64I variant had an odds ratio of 0.31 (0.12-0.77). This association was detected in both carriers and noncarriers of the HLA DQB1*0602 cervical cancer risk allele. The IL-4R 75V variant was associated with increased risk of cervical tumors, cases homozygote for 75V had an odds ratio of 1.91 (1.27-2.86) with a tendency that the association was stronger in noncarriers of the DQB1*0602 allele. We did not find any association for IL-10 -592, or FasL -844, previously reported to be associated with cervical cancer in the Dutch and Chinese populations, respectively.

Molecular Differences between Screen-Detected and Interval Breast Cancers Are Largely Explained by PAM50 Subtypes.

Purpose: Interval breast cancer is of clinical interest, as it exhibits an aggressive phenotype and evades detection by screening mammography. A comprehensive picture of somatic changes that drive tumors to become symptomatic in the screening interval can improve understanding of the biology underlying these aggressive tumors.Experimental Design: Initiated in April 2013, Clinical Sequencing of Cancer in Sweden (Clinseq) is a scientific and clinical platform for the genomic profiling of cancer. The breast cancer pilot study consisted of women diagnosed with breast cancer between 2001 and 2012 in the Stockholm/Gotland regions. A subset of 307 breast tumors was successfully sequenced, of which 113 were screen-detected and 60 were interval cancers. We applied targeted deep sequencing of cancer-related genes; low-pass, whole-genome sequencing; and RNA sequencing technology to characterize somatic differences in the genomic and transcriptomic architecture by interval cancer status. Mammographic density and PAM50 molecular subtypes were considered.Results: In the univariate analyses, TP53, PPP1R3A, and KMT2B were significantly more frequently mutated in interval cancers than in screen-detected cancers. Acquired somatic copy number aberrations with a frequency difference of at least 15% between the two groups included gains in 17q23-q25.3 and losses in 16q24.2. Gene expression analysis identified 447 significantly differentially expressed genes, of which 120 were replicated in an independent microarray dataset. After adjusting for PAM50, most differences were no longer significant.Conclusions: Molecular differences by interval cancer status were observed, but they were largely explained by PAM50 subtypes. This work offers new insights into the biological differences between the two tumor groups. Clin Cancer Res; 23(10); 2584-92. ©2016 AACR.

E-Science technologies in a workflow for personalized medicine using cancer screening as a case study.

OBJECTIVE: We provide an e-Science perspective on the workflow from risk factor discovery and classification of disease to evaluation of personalized intervention programs. As case studies, we use personalized prostate and breast cancer screenings. MATERIALS AND METHODS: We describe an e-Science initiative in Sweden, e-Science for Cancer Prevention and Control (eCPC), which supports biomarker discovery and offers decision support for personalized intervention strategies. The generic eCPC contribution is a workflow with 4 nodes applied iteratively, and the concept of e-Science signifies systematic use of tools from the mathematical, statistical, data, and computer sciences. RESULTS: The eCPC workflow is illustrated through 2 case studies. For prostate cancer, an in-house personalized screening tool, the Stockholm-3 model (S3M), is presented as an alternative to prostate-specific antigen testing alone. S3M is evaluated in a trial setting and plans for rollout in the population are discussed. For breast cancer, new biomarkers based on breast density and molecular profiles are developed and the US multicenter Women Informed to Screen Depending on Measures (WISDOM) trial is referred to for evaluation. While current eCPC data management uses a traditional data warehouse model, we discuss eCPC-developed features of a coherent data integration platform. DISCUSSION AND CONCLUSION: E-Science tools are a key part of an evidence-based process for personalized medicine. This paper provides a structured workflow from data and models to evaluation of new personalized intervention strategies. The importance of multidisciplinary collaboration is emphasized. Importantly, the generic concepts of the suggested eCPC workflow are transferrable to other disease domains, although each disease will require tailored solutions.

Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers.

Sequencing-based breast cancer diagnostics have the potential to replace routine biomarkers and provide molecular characterization that enable personalized precision medicine. Here we investigate the concordance between sequencing-based and routine diagnostic biomarkers and to what extent tumor sequencing contributes clinically actionable information. We applied DNA- and RNA-sequencing to characterize tumors from 307 breast cancer patients with replication in up to 739 patients. We developed models to predict status of routine biomarkers (ER, HER2,Ki-67, histological grade) from sequencing data. Non-routine biomarkers, including mutations in BRCA1, BRCA2 and ERBB2(HER2), and additional clinically actionable somatic alterations were also investigated. Concordance with routine diagnostic biomarkers was high for ER status (AUC = 0.95;AUC(replication) = 0.97) and HER2 status (AUC = 0.97;AUC(replication) = 0.92). The transcriptomic grade model enabled classification of histological grade 1 and histological grade 3 tumors with high accuracy (AUC = 0.98;AUC(replication) = 0.94). Clinically actionable mutations in BRCA1, BRCA2 and ERBB2(HER2) were detected in 5.5% of patients, while 53% had genomic alterations matching ongoing or concluded breast cancer studies. Sequencing-based molecular profiling can be applied as an alternative to histopathology to determine ER and HER2 status, in addition to providing improved tumor grading and clinically actionable mutations and molecular subtypes. Our results suggest that sequencing-based breast cancer diagnostics in a near future can replace routine biomarkers.

The dog as a genetic model for immunoglobulin A (IgA) deficiency: identification of several breeds with low serum IgA concentrations.

Immunoglobulin A (IgA) serves as the basis of the secretory immune system by protecting the lining of mucosal sites from pathogens. In both humans and dogs, IgA deficiency (IgAD) is associated with recurrent infections of mucosal sites and immune-mediated diseases. Low concentrations of serum IgA have previously been reported to occur in a number of dog breeds but no generally accepted cut-off value has been established for canine IgAD. The current study represents the largest screening to date of IgA in dogs in terms of both number of dogs (n=1267) and number of breeds studied (n=22). Serum IgA concentrations were quantified by using capture ELISA and were found to vary widely between breeds. We also found IgA to be positively correlated with age (p<0.0001). Apart from the two breeds previously reported as predisposed to low IgA (Shar-Pei and German shepherd), we identified six additional breeds in which ≥ 10% of all tested dogs had very low (<0.07 g/l) IgA concentrations (Hovawart, Norwegian elkhound, Nova Scotia duck tolling retriever, Bullterrier, Golden retriever and Labrador retriever). In addition, we discovered low IgA concentrations to be significantly associated with canine atopic dermatitis (CAD, p<0.0001) and pancreatic acinar atrophy (PAA, p=0.04) in German shepherds.

TGFß receptor 1: an immune susceptibility gene in HPV-associated cancer.

Only a minority of those exposed to human papillomavirus (HPV) develop HPV-related cervical and oropharyngeal cancer. Because host immunity affects infection and progression to cancer, we tested the hypothesis that genetic variation in immune-related genes is a determinant of susceptibility to oropharyngeal cancer and other HPV-associated cancers by performing a multitier integrative computational analysis with oropharyngeal cancer data from a head and neck cancer genome-wide association study (GWAS). Independent analyses, including single-gene, gene-interconnectivity, protein-protein interaction, gene expression, and pathway analysis, identified immune genes and pathways significantly associated with oropharyngeal cancer. TGFßR1, which intersected all tiers of analysis and thus selected for validation, replicated significantly in the head and neck cancer GWAS limited to HPV-seropositive cases and an independent cervical cancer GWAS. The TGFßR1 containing p38-MAPK pathway was significantly associated with oropharyngeal cancer and cervical cancer, and TGFßR1 was overexpressed in oropharyngeal cancer, cervical cancer, and HPV(+) head and neck cancer tumors. These concordant analyses implicate TGFßR1 signaling as a process dysregulated across HPV-related cancers. This study demonstrates that genetic variation in immune-related genes is associated with susceptibility to oropharyngeal cancer and implicates TGFßR1/TGFß signaling in the development of both oropharyngeal cancer and cervical cancer. Better understanding of the immunogenetic basis of susceptibility to HPV-associated cancers may provide insight into host/virus interactions and immune processes dysregulated in the minority of HPV-exposed individuals who progress to cancer.