Expression of the immune modulator secretory leukocyte protease inhibitor (SLPI) in colorectal cancer liver metastases and matched primary tumors is associated with a poorer prognosis

Secretory leukocyte protease inhibitor (SLPI), a pleiotropic protein expressed by healthy intestinal epithelial cells, functions as an inhibitor of NF-κB and neutrophil proteases and exerts antimicrobial activity. We previously showed SLPI suppresses intestinal epithelial chemokine production in response to microbial contact. Increased SLPI expression was recently detected in various types of carcinoma. In addition, accumulating evidence indicates SLPI expression is favorable for tumor cells. In view of these findings and the abundance of SLPI in the colonic epithelium, we hypothesized SLPI promotes colorectal cancer (CRC) growth and metastasis. Here, we aimed to establish wh

A spatiotemporal ensemble machine learning framework for generating land use/land cover time-series maps for Europe (2000–2019) based on LUCAS, CORINE and GLAD Landsat

A spatiotemporal machine learning framework for automated prediction and analysis of long-term Land Use/Land Cover dynamics is presented. The framework includes: (1) harmonization and preprocessing of spatial and spatiotemporal input datasets (GLAD Landsat, NPP/VIIRS) including five million harmonized LUCAS and CORINE Land Cover-derived training samples, (2) model building based on spatial k-fold cross-validation and hyper-parameter optimization, (3) prediction of the most probable class, class probabilities and model variance of predicted probabilities per pixel, (4) LULC change analysis on time-series of produced maps. The spatiotemporal ensemble model consists of a random forest, gradient boosted tree classifier, and an artificial neural network, with a logistic regressor as meta-learner. The results show that the most important variables for mapping LULC in Europe are: seasonal aggregates of Landsat green and near-infrared bands, multiple Landsat-derived spectral indices, long-term surface water probability, and elevation. Spatial cross-validation of the model indicates consistent performance across multiple years with overall accuracy (a weighted F1-score) of 0.49, 0.63, and 0.83 when predicting 43 (level-3), 14 (level-2), and five classes (level-1). Additional experiments show that spatiotemporal models generalize better to unknown years, outperforming single-year models on known-year classification by 2.7% and unknown-year classification by 3.5%. Results of the accuracy assessment using 48,365 independent test samples shows 87% match with the validation points. Results of time-series analysis (time-series of LULC probabilities and NDVI images) suggest forest loss in large parts of Sweden, the Alps, and Scotland. Positive and negative trends in NDVI in general match the land degradation and land restoration classes, with “urbanization” showing the most negative NDVI trend. An advantage of using spatiotemporal ML is that the fitted model can be used to predict LULC in years that were not included in its training dataset, allowing generalization to past and future periods, e.g. to predict LULC for years prior to 2000 and beyond 2020. The generated LULC time-series data stack (ODSE-LULC), including the training points, is publicly available via the ODSE Viewer. Functions used to prepare data and run modeling are available via the eumap library for Python

Development and validation of a quantitative coronary CT Angiography model for diagnosis of vessel-specific coronary ischemia

Background: Noninvasive stress testing is commonly used for detection of coronary ischemia but possesses variable accuracy and may result in excessive health care costs. Objectives: This study aimed to derive and validate an artificial intelligence-guided quantitative coronary computed tomography angiography (AI-QCT) model for the diagnosis of coronary ischemia that integrates atherosclerosis and vascular morphology measures (AI-QCTISCHEMIA) and to evaluate its prognostic utility for major adverse cardiovascular events (MACE). Methods: A post hoc analysis of the CREDENCE (Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia) and PACIFIC-1 (Comparison of Coronary Computed Tomography Angiography, Single Photon Emission Computed Tomography [SPECT], Positron Emission Tomography [PET], and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve) studies was performed. In both studies, symptomatic patients with suspected stable coronary artery disease had prospectively undergone coronary computed tomography angiography (CTA), myocardial perfusion imaging (MPI), SPECT, or PET, fractional flow reserve by CT (FFRCT), and invasive coronary angiography in conjunction with invasive FFR measurements. The AI-QCTISCHEMIA model was developed in the derivation cohort of the CREDENCE study, and its diagnostic performance for coronary ischemia (FFR ≤0.80) was evaluated in the CREDENCE validation cohort and PACIFIC-1. Its prognostic value was investigated in PACIFIC-1. Results: In CREDENCE validation (n = 305, age 64.4 ± 9.8 years, 210 [69%] male), the diagnostic performance by area under the receiver-operating characteristics curve (AUC) on per-patient level was 0.80 (95% CI: 0.75-0.85) for AI-QCTISCHEMIA, 0.69 (95% CI: 0.63-0.74; P < 0.001) for FFRCT, and 0.65 (95% CI: 0.59-0.71; P < 0.001) for MPI. In PACIFIC-1 (n = 208, age 58.1 ± 8.7 years, 132 [63%] male), the AUCs were 0.85 (95% CI: 0.79-0.91) for AI-QCTISCHEMIA, 0.78 (95% CI: 0.72-0.84; P = 0.037) for FFRCT, 0.89 (95% CI: 0.84-0.93; P = 0.262) for PET, and 0.72 (95% CI: 0.67-0.78; P < 0.001) for SPECT. Adjusted for clinical risk factors and coronary CTA-determined obstructive stenosis, a positive AI-QCTISCHEMIA test was associated with an HR of 7.6 (95% CI: 1.2-47.0; P = 0.030) for MACE. Conclusions: This newly developed coronary CTA-based ischemia model using coronary atherosclerosis and vascular morphology characteristics accurately diagnoses coronary ischemia by invasive FFR and provides robust prognostic utility for MACE beyond presence of stenosis.info:eu-repo/semantics/acceptedVersio

Consensus molecular subtype classification of colorectal adenomas

Consensus molecular subtyping is an RNA expression-based classification system for colorectal cancer (CRC). Genomic alterations accumulate during CRC pathogenesis, including the premalignant adenoma stage, leading to changes in RNA expression. Only a minority of adenomas progress to malignancies, a transition that is associated with specific DNA copy number aberrations or microsatellite instability (MSI). We aimed to investigate whether colorectal adenomas can already be stratified into consensus molecular subtype (CMS) classes, and whether specific CMS classes are related to the presence of specific DNA copy number aberrations associated with progression to malignancy. RNA sequencing was performed on 62 adenomas and 59 CRCs. MSI status was determined with polymerase chain reaction-based methodology. DNA copy number was assessed by low-coverage DNA sequencing (n = 30) or array-comparative genomic hybridisation (n = 32). Adenomas were classified into CMS classes together with CRCs from the study cohort and from The Cancer Genome Atlas (n = 556), by use of the established CMS classifier. As a result, 54 of 62 (87%) adenomas were classified according to the CMS. The CMS3 ‘metabolic subtype’, which was least common among CRCs, was most prevalent among adenomas (n = 45; 73%). One of the two adenomas showing MSI was classified as CMS1 (2%), the ‘MSI immune’ subtype. Eight adenomas (13%) were classified as the ‘canonical’ CMS2. No adenomas were classified as the ‘mesenchymal’ CMS4, consistent with the fact that adenomas lack invasion-associated stroma. The distribution of the CMS classes among adenomas was confirmed in an independent series. CMS3 was enriched with adenomas at low risk of progressing to CRC, whereas relatively more high-risk adenomas were observed in CMS2. We conclude that adenomas can be stratified into the CMS classes. Considering that CMS1 and CMS2 expression signatures may mark adenomas at increased risk of progression, the distribution of the CMS classes among adenomas is consistent with the proportion of adenomas expected to progress to CRC

Competing Isogenic Campylobacter Strains Exhibit Variable Population Structures In Vivo▿ †

Consumption of poultry contaminated with Campylobacter jejuni is a risk factor for human gastrointestinal disease. The rational development of control strategies for Campylobacter within chickens requires an understanding of the colonization process at the molecular and population levels, both within and between hosts. Experiments employing competing strains of Campylobacter have been used to investigate colonization. Implicit in these studies is the assumption that the behavior of competing strains is reproducible between experiments. Variability in the recovery of mutants from the chicken gastrointestinal tract during signature-tagged mutagenesis studies demonstrated that this is not always the case. To further investigate this phenomenon in the absence of confounding factors due to phenotypic differences between mutants, we constructed individually identifiable wild-type isogenic tagged strains (WITS) that have indistinguishable phenotypes in pure culture. By using mixtures of WITS, it is possible to monitor the relative amounts of subpopulations of essentially wild-type bacteria. Using a 2-week-old chicken model of colonization, we observed unpredictable variations in population structure both within and between experiments, even in the simplest case of two competing strains. This variation occurred both when birds were simultaneously infected with two WITS and when birds inoculated with different WITS were cohoused. We present evidence for founder effects during initial colonization with subsequent bird-to-bird transmission. We suggest that these and phenotypic variation contribute to the observed variability. These factors render simple models of colonization which do not take them into account inappropriate for Campylobacter and impact the planning and interpretation of competition experiments using this organism

Concordance of specific human papillomavirus types in sex partners is more prevalent than would be expected by chance and is associated with increased viral loads

BACKGROUND: Genital human papillomavirus (HPV) infections are generally accepted to be sexually transmitted, but studies of HPV infections in sex partners are limited. We investigated HPV type-specific concordance and viral load in 238 heterosexual couples. Women with cervical intraepithelial neoplasia were the index patients in these couples. METHODS: GP5+/6+ polymerase chain reaction (PCR), followed by reverse-line blot analysis, was used for the detection of 45 HPV types in cervical and penile scrape samples. Viral loads were subsequently determined in scrape samples positive for HPV types 16, 18, 31, and 33 by LightCycler-based real-time PCR assays. RESULTS: A total of 89.9% of the women and 72.9% of their male partners were HPV positive. Predominantly high-risk HPV types were found in persons of both sexes, but infections with multiple and non-high-risk HPV types were more common in men. Of the HPV-positive couples, 57.8% of the men had the same HPV type as their partners; this rate was significantly higher than that expected by chance (P < .001). Moreover, these HPV-concordant men had higher penile scrape viral loads than did the non-HPV-concordant men. For HPV type 16-positive women, higher cervical viral loads were predictive of presence of HPV type 16 in their sex partners. CONCLUSIONS: In sexually active couples, HPV type concordance was more prevalent than expected by chance and was associated with increased viral loads. These data provide biological support for HPV transmission between sex partners

Human papillomavirus-16 is the predominant type etiologically involved in penile squamous cell carcinoma

PURPOSE: Human papillomavirus (HPV) infections are suggested to be involved in the development of penile squamous cell carcinoma (SCC), but comprehensive studies to define the association are limited. Therefore, we performed molecular and serologic analyses for a broad spectrum of HPV types on a large series of 83 penile SCCs, and we compared serological findings to those of age-matched male controls (N = 83). METHODS: Penile SCCs were subjected to detection and typing assays for mucosal and cutaneous HPVs and to subsequent, type-specific viral load and viral gene expression assays. Sera of patients and of controls were analyzed for type-specific mucosal and cutaneous HPV L1, E6, and/or E7 antibodies using bead-based, multiplex serology. RESULTS: HPV DNA of mucosal and/or cutaneous types was found in 46 of 83 (55%) penile SCCs. HPV16 was the predominant type, appearing in 24 (52%) of 46 of penile SCCs. The majority of HPV16 DNA-positive SCCs (18 of 24; 75%) demonstrated E6 transcriptional activity and a high viral load. Additionally, HPV16 molecular findings were strongly associated with HPV16 L1-, E6-, and E7-antibody seropositivity. Furthermore, serologic case-control analyses demonstrated that, in addition to the association of HPV16 with penile SCC, seropositivity against any HPV type was significantly more common in patients compared with in controls. HPV18 and HPV6 seropositivity were associated with HPV16-negative SCCs but were not correlated to molecular findings. CONCLUSION: HPV16 is the main HPV type etiologically involved in the development of penile SCC. Although individuals who develop penile SCC show a greater prior exposure to a broad spectrum of HPV types, insufficient evidence was found to claim a role for HPV types other than HPV16 in penile carcinogenesis

Common and different genetic background for rheumatoid arthritis and coeliac disease

Contains fulltext : 81471.pdf (publisher's version ) (Closed access)Recent genome-wide association studies (GWAS) have revealed genetic risk factors in autoimmune and inflammatory disorders. Several of the associated genes and underlying pathways are shared by various autoimmune diseases. Rheumatoid arthritis (RA) and coeliac disease (CD) are two autoimmune disorders which have commonalities in their pathogenesis. We aimed to replicate known RA loci in a Dutch RA population, and to investigate whether the effect of known RA and CD risk factors generalize across the two diseases. We selected all loci associated to either RA or CD in a GWAS and confirmed in an independent cohort, with a combined P-value cut-off P < 5 x 10(-6). We genotyped 11 RA and 11 CD loci in 1368 RA patients, 795 CD patients and 1683 Dutch controls. We combined our results in a meta-analysis with UK GWAS on RA (1860 cases; 2938 controls) and CD (767 cases; 1422 controls). In the Dutch RA cohort, the PTPN22 and IL2/IL21 variants showed convincing association (P = 3.4 x 10(-12) and P = 2.8 x 10(-4), respectively). Association of RA with the known CD risk variant in the SH2B3 was also observed, predominantly in the subgroup of rheumatoid factor-positive RA patients (P = 0.0055). In a meta-analysis of Dutch and UK data sets, shared association with six loci (TNFAIP3, IL2/IL21, SH2B3, LPP, MMEL1/TNFRSF14 and PFKFB3/PRKCQ) was observed in both RA and CD cohorts. We confirmed two known loci and identified four novel ones for shared CD-RA genetic risk. Most of the shared loci further emphasize a role for adaptive and innate immunity in these diseases

Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease

Item does not contain fulltextUsing variants from the 1000 Genomes Project pilot European CEU dataset and data from additional resequencing studies, we densely genotyped 183 non-HLA risk loci previously associated with immune-mediated diseases in 12,041 individuals with celiac disease (cases) and 12,228 controls. We identified 13 new celiac disease risk loci reaching genome-wide significance, bringing the number of known loci (including the HLA locus) to 40. We found multiple independent association signals at over one-third of these loci, a finding that is attributable to a combination of common, low-frequency and rare genetic variants. Compared to previously available data such as those from HapMap3, our dense genotyping in a large sample collection provided a higher resolution of the pattern of linkage disequilibrium and suggested localization of many signals to finer scale regions. In particular, 29 of the 54 fine-mapped signals seemed to be localized to single genes and, in some instances, to gene regulatory elements. Altogether, we define the complex genetic architecture of the risk regions of and refine the risk signals for celiac disease, providing the next step toward uncovering the causal mechanisms of the disease