Identification of intergenerational epigenetic inheritance by whole genome DNA methylation analysis in trios.

Genome-wide association studies have identified thousands of loci associated with common diseases and traits. However, a large fraction of heritability remains unexplained. Epigenetic modifications, such as the observed in DNA methylation have been proposed as a mechanism of intergenerational inheritance. To investigate the potential contribution of DNA methylation to the missing heritability, we analysed the methylomes of four healthy trios (two parents and one offspring) using whole genome bisulphite sequencing. Of the 1.5 million CpGs (19%) with over 20% variability between parents in at least one family and compatible with a Mendelian inheritance pattern, only 3488 CpGs (0.2%) lacked correlation with any SNP in the genome, marking them as potential sites for intergenerational epigenetic inheritance. These markers were distributed genome-wide, with some preference to be located in promoters. They displayed a bimodal distribution, being either fully methylated or unmethylated, and were often found at the boundaries of genomic regions with high/low GC content. This analysis provides a starting point for future investigations into the missing heritability of simple and complex traits.

Identification of a Twelve-microRNA Signature with Prognostic Value in Stage II Microsatellite Stable Colon Cancer.

We aimed to identify and validate a set of miRNAs that could serve as a prognostic signature useful to determine the recurrence risk for patients with COAD. Small RNAs from tumors of 100 stage II, untreated, MSS colon cancer patients were sequenced for the discovery step. For this purpose, we built an miRNA score using an elastic net Cox regression model based on the disease-free survival status. Patients were grouped into high or low recurrence risk categories based on the median value of the score. We then validated these results in an independent sample of stage II microsatellite stable tumor tissues, with a hazard ratio of 3.24, (CI95% = 1.05-10.0) and a 10-year area under the receiver operating characteristic curve of 0.67. Functional analysis of the miRNAs present in the signature identified key pathways in cancer progression. In conclusion, the proposed signature of 12 miRNAs can contribute to improving the prediction of disease relapse in patients with stage II MSS colorectal cancer, and might be useful in deciding which patients may benefit from adjuvant chemotherapy.

Ability of a polygenic risk score to refine colorectal cancer risk in Lynch syndrome.

BACKGROUND: Polygenic risk scores (PRSs) have been used to stratify colorectal cancer (CRC) risk in the general population, whereas its role in Lynch syndrome (LS), the most common type of hereditary CRC, is still conflicting. We aimed to assess the ability of PRS to refine CRC risk prediction in European-descendant individuals with LS. METHODS: 1465 individuals with LS (557 MLH1, 517 MSH2/EPCAM, 299 MSH6 and 92 PMS2) and 5656 CRC-free population-based controls from two independent cohorts were included. A 91-SNP PRS was applied. A Cox proportional hazard regression model with 'family' as a random effect and a logistic regression analysis, followed by a meta-analysis combining both cohorts were conducted. RESULTS: Overall, we did not observe a statistically significant association between PRS and CRC risk in the entire cohort. Nevertheless, PRS was significantly associated with a slightly increased risk of CRC or advanced adenoma (AA), in those with CRC diagnosed <50 years and in individuals with multiple CRCs or AAs diagnosed <60 years. CONCLUSION: The PRS may slightly influence CRC risk in individuals with LS in particular in more extreme phenotypes such as early-onset disease. However, the study design and recruitment strategy strongly influence the results of PRS studies. A separate analysis by genes and its combination with other genetic and non-genetic risk factors will help refine its role as a risk modifier in LS.

COLONOMICS - integrative omics data of one hundred paired normal-tumoral samples from colon cancer patients.

Colonomics is a multi-omics dataset that includes 250 samples: 50 samples from healthy colon mucosa donors and 100 paired samples from colon cancer patients (tumor/adjacent). From these samples, Colonomics project includes data from genotyping, DNA methylation, gene expression, whole exome sequencing and micro-RNAs (miRNAs) expression. It also includes data from copy number variation (CNV) from tumoral samples. In addition, clinical data from all these samples is available. The aims of the project were to explore and integrate these datasets to describe colon cancer at molecular level and to compare normal and tumoral tissues. Also, to improve screening by finding biomarkers for the diagnosis and prognosis of colon cancer. This project has its own website including four browsers allowing users to explore Colonomics datasets. Since generated data could be reuse for the scientific community for exploratory or validation purposes, here we describe omics datasets included in the Colonomics project as well as results from multi-omics layers integration.

Meta-Analysis and Validation of a Colorectal Cancer Risk Prediction Model Using Deep Sequenced Fecal Metagenomes.

The gut microbiome is a potential modifiable risk factor for colorectal cancer (CRC). We re-analyzed all eight previously published stool sequencing data and conducted an MWAS meta-analysis. We used cross-validated LASSO predictive models to identify a microbiome signature for predicting the risk of CRC and precancerous lesions. These models were validated in a new study, Colorectal Cancer Screening (COLSCREEN), including 156 participants that were recruited in a CRC screening context. The MWAS meta-analysis identified 95 bacterial species that were statistically significantly associated with CRC (FDR < 0.05). The LASSO CRC predictive model obtained an area under the receiver operating characteristic curve (aROC) of 0.81 (95%CI: 0.78−0.83) and the validation in the COLSCREEN dataset was 0.75 (95%CI: 0.66−0.84). This model selected a total of 32 species. The aROC of this CRC-trained model to predict precancerous lesions was 0.52 (95%CI: 0.41−0.63). We have identified a signature of 32 bacterial species that have a good predictive accuracy to identify CRC but not precancerous lesions, suggesting that the identified microbes that were enriched or depleted in CRC are merely a consequence of the tumor. Further studies should focus on CRC as well as precancerous lesions with the intent to implement a microbiome signature in CRC screening programs.

Evaluating the Potential of Polygenic Risk Score to Improve Colorectal Cancer Screening.

BACKGROUND: Colorectal cancer has high incidence and associated mortality worldwide. Screening programs are recommended for men and women over 50. Intermediate screens such as fecal immunochemical testing (FIT) select patients for colonoscopy with suboptimal sensitivity. Additional biomarkers could improve the current scenario. METHODS: We included 2,893 individuals with a positive FIT test. They were classified as cases when a high-risk lesion for colorectal cancer was detected after colonoscopy, whereas the control group comprised individuals with low-risk or no lesions. 65 colorectal cancer risk genetic variants were genotyped. Polygenic risk score (PRS) and additive models for risk prediction incorporating sex, age, FIT value, and PRS were generated. RESULTS: Risk score was higher in cases compared with controls [per allele OR = 1.04; 95% confidence interval (CI), 1.02-1.06; P < 0.0001]. A 2-fold increase in colorectal cancer risk was observed for subjects in the highest decile of risk alleles (≥65), compared with those in the first decile (≤54; OR = 2.22; 95% CI, 1.59-3.12; P < 0.0001). The model combining sex, age, FIT value, and PRS reached the highest accuracy for identifying patients with a high-risk lesion [cross-validated area under the ROC curve (AUROC): 0.64; 95% CI, 0.62-0.66]. CONCLUSIONS: This is the first investigation analyzing PRS in a two-step colorectal cancer screening program. PRS could improve current colorectal cancer screening, most likely for higher at-risk subgroups. However, its capacity is limited to predict colorectal cancer risk status and should be complemented by additional biomarkers. IMPACT: PRS has capacity for risk stratification of colorectal cancer suggesting its potential for optimizing screening strategies alongside with other biomarkers.

Solving the enigma of POLD1 p.V295M as a potential cause of increased cancer risk.

Germline variants that affect the proofreading activity of polymerases epsilon (POLE) and delta (POLD1) predispose to colorectal adenomas and carcinomas, among other cancers. All cancer-associated pathogenic variants reported to date consist of non-disruptive genetic changes affecting the sequence that codifies the exonuclease domain (ED). Generally, disruptive (frameshift, stop-gain) POLE and POLD1 variants and missense variants outside the ED do not predispose to cancer. However, this statement may not be true for some, very specific variants that would indirectly affect the proofreading activity of the corresponding polymerase. We evaluated, by using multiple approaches, the possibility that POLD1 c.883G>A; p.(Val295Met), -a variant located 9 amino acids upstream the ED and present in ~0.25% of hereditary cancer patients-, affects POLD1 proofreading activity. Our findings show cumulative evidence that support no alteration of the proofreading activity and lack of association with cancer. The variant is classified as likely benign according to the ACMG/AMP guidelines.

Transcriptome-Wide Association Study for Inflammatory Bowel Disease Reveals Novel Candidate Susceptibility Genes in Specific Colon Subsites and Tissue Categories.

BACKGROUND AND AIMS: Genome-wide association studies [GWAS] for inflammatory bowel disease [IBD] have identified 240 risk variants. However, the benefit of understanding the genetic architecture of IBD remains to be exploited. Transcriptome-wide association studies [TWAS] associate gene expression with genetic susceptibility to disease, providing functional insight into risk loci. In this study, we integrate relevant datasets for IBD and perform a TWAS to nominate novel genes implicated in IBD genetic susceptibility. METHODS: We applied elastic net regression to generate gene expression prediction models for the University of Barcelona and University of Virginia RNA sequencing project [BarcUVa-Seq] and correlated expression and disease association research [CEDAR] datasets. Together with Genotype-Tissue Expression project [GTEx] data, and GWAS results from about 60 000 individuals, we employed Summary-PrediXcan and Summary-MultiXcan for single and joint analyses of TWAS results, respectively. RESULTS: BarcUVa-Seq TWAS revealed 39 novel genes whose expression in the colon is associated with IBD genetic susceptibility. They included expression markers for specific colon cell types. TWAS meta-analysis including all tissues/cell types provided 186 novel candidate susceptibility genes. Additionally, we identified 78 novel susceptibility genes whose expression is associated with IBD exclusively in immune (N = 19), epithelial (N = 25), mesenchymal (N = 22) and neural (N = 12) tissue categories. Associated genes were involved in relevant molecular pathways, including pathways related to known IBD therapeutics, such as tumour necrosis factor signalling. CONCLUSION: These findings provide insight into tissue-specific molecular processes underlying IBD genetic susceptibility. Associated genes could be candidate targets for new therapeutics and should be prioritized in functional studies.

Polygenic risk score across distinct colorectal cancer screening outcomes: from premalignant polyps to colorectal cancer.

BACKGROUND: Different risk-based colorectal cancer (CRC) screening strategies, such as the use of polygenic risk scores (PRS), have been evaluated to improve effectiveness of these programs. However, few studies have previously assessed its usefulness in a fecal immunochemical test (FIT)-based screening study. METHODS: A PRS of 133 single nucleotide polymorphisms was assessed for 3619 participants: population controls, screening controls, low-risk lesions (LRL), intermediate-risk (IRL), high-risk (HRL), CRC screening program cases, and clinically diagnosed CRC cases. The PRS was compared between the subset of cases (n = 648; IRL+HRL+CRC) and controls (n = 956; controls+LRL) recruited within a FIT-based screening program. Positive predictive values (PPV), negative predictive values (NPV), and the area under the receiver operating characteristic curve (aROC) were estimated using cross-validation. RESULTS: The overall PRS range was 110-156. PRS values increased along the CRC tumorigenesis pathway (Mann-Kendall P value 0.007). Within the screening subset, the PRS ranged 110-151 and was associated with higher risk-lesions and CRC risk (ORD10vsD1 1.92, 95% CI 1.22-3.03). The cross-validated aROC of the PRS for cases and controls was 0.56 (95% CI 0.53-0.59). Discrimination was equal when restricted to positive FIT (aROC 0.56), but lower among negative FIT (aROC 0.55). The overall PPV among positive FIT was 0.48. PPV were dependent on the number of risk alleles for positive FIT (PPVp10-p90 0.48-0.57). CONCLUSIONS: PRS plays an important role along the CRC tumorigenesis pathway; however, in practice, its utility to stratify the general population or as a second test after a FIT positive result is still doubtful. Currently, PRS is not able to safely stratify the general population since the improvement on PPV values is scarce.

Non-Lynch Familial and Early-Onset Colorectal Cancer Explained by Accumulation of Low-Risk Genetic Variants.

A large proportion of familial and/or early-onset cancer patients do not carry pathogenic variants in known cancer predisposing genes. We aimed to assess the contribution of previously validated low-risk colorectal cancer (CRC) alleles to familial/early-onset CRC (fCRC) and to serrated polyposis. We estimated the association of CRC with a 92-variant-based weighted polygenic risk score (wPRS) using 417 fCRC patients, 80 serrated polyposis patients, 1077 hospital-based incident CRC patients, and 1642 controls. The mean wPRS was significantly higher in fCRC than in controls or sporadic CRC patients. fCRC patients in the highest (20th) wPRS quantile were at four-fold greater CRC risk than those in the middle quantile (10th). Compared to low-wPRS fCRC, a higher number of high-wPRS fCRC patients had developed multiple primary CRCs, had CRC family history, and were diagnosed at age ≥50. No association with wPRS was observed for serrated polyposis. In conclusion, a relevant proportion of mismatch repair (MMR)-proficient fCRC cases might be explained by the accumulation of low-risk CRC alleles. Validation in independent cohorts and development of predictive models that include polygenic risk score (PRS) data and other CRC predisposing factors will determine the implementation of PRS into genetic testing and counselling in familial and early-onset CRC.

Identifying causal models between genetically regulated methylation patterns and gene expression in healthy colon tissue.

BACKGROUND: DNA methylation is involved in the regulation of gene expression and phenotypic variation, but the inter-relationship between genetic variation, DNA methylation and gene expression remains poorly understood. Here we combine the analysis of genetic variants related to methylation markers (methylation quantitative trait loci: mQTLs) and gene expression (expression quantitative trait loci: eQTLs) with methylation markers related to gene expression (expression quantitative trait methylation: eQTMs), to provide novel insights into the genetic/epigenetic architecture of colocalizing molecular markers. RESULTS: Normal mucosa from 100 patients with colon cancer and 50 healthy donors included in the Colonomics project have been analyzed. Linear models have been used to find mQTLs and eQTMs within 1 Mb of the target gene. From 32,446 eQTLs previously detected, we found a total of 6850 SNPs, 114 CpGs and 52 genes interrelated, generating 13,987 significant combinations of co-occurring associations (meQTLs) after Bonferromi correction. Non-redundant meQTLs were 54, enriched in genes involved in metabolism of glucose and xenobiotics and immune system. SNPs in meQTLs were enriched in regulatory elements (enhancers and promoters) compared to random SNPs within 1 Mb of genes. Three colorectal cancer GWAS SNPs were related to methylation changes, and four SNPs were related to chemerin levels. Bayesian networks have been used to identify putative causal relationships among associated SNPs, CpG and gene expression triads. We identified that most of these combinations showed the canonical pathway of methylation markers causes gene expression variation (60.1%) or non-causal relationship between methylation and gene expression (33.9%); however, in up to 6% of these combinations, gene expression was causing variation in methylation markers. CONCLUSIONS: In this study we provided a characterization of the regulation between genetic variants and inter-dependent methylation markers and gene expression in a set of 150 healthy colon tissue samples. This is an important finding for the understanding of molecular susceptibility on colon-related complex diseases.

Polymorphisms within Autophagy-Related Genes Influence the Risk of Developing Colorectal Cancer: A Meta-Analysis of Four Large Cohorts.

The role of genetic variation in autophagy-related genes in modulating autophagy and cancer is poorly understood. Here, we comprehensively investigated the association of autophagy-related variants with colorectal cancer (CRC) risk and provide new insights about the molecular mechanisms underlying the associations. After meta-analysis of the genome-wide association study (GWAS) data from four independent European cohorts (8006 CRC cases and 7070 controls), two loci, DAPK2 (p = 2.19 × 10-5) and ATG5 (p = 6.28 × 10-4) were associated with the risk of CRC. Mechanistically, the DAPK2rs11631973G allele was associated with IL1 ß levels after the stimulation of peripheral blood mononuclear cells (PBMCs) with Staphylococcus aureus (p = 0.002), CD24 + CD38 + CD27 + IgM + B cell levels in blood (p = 0.0038) and serum levels of en-RAGE (p = 0.0068). ATG5rs546456T allele was associated with TNF α and IL1 ß levels after the stimulation of PBMCs with LPS (p = 0.0088 and p = 0.0076, respectively), CD14+CD16- cell levels in blood (p = 0.0068) and serum levels of CCL19 and cortisol (p = 0.0052 and p = 0.0074, respectively). Interestingly, no association with autophagy flux was observed. These results suggested an effect of the DAPK2 and ATG5 loci in the pathogenesis of CRC, likely through the modulation of host immune responses.

Genetic Effects on Transcriptome Profiles in Colon Epithelium Provide Functional Insights for Genetic Risk Loci.

BACKGROUND & AIMS: The association of genetic variation with tissue-specific gene expression and alternative splicing guides functional characterization of complex trait-associated loci and may suggest novel genes implicated in disease. Here, our aims were as follows: (1) to generate reference profiles of colon mucosa gene expression and alternative splicing and compare them across colon subsites (ascending, transverse, and descending), (2) to identify expression and splicing quantitative trait loci (QTLs), (3) to find traits for which identified QTLs contribute to single-nucleotide polymorphism (SNP)-based heritability, (4) to propose candidate effector genes, and (5) to provide a web-based visualization resource. METHODS: We collected colonic mucosal biopsy specimens from 485 healthy adults and performed bulk RNA sequencing. We performed genome-wide SNP genotyping from blood leukocytes. Statistical approaches and bioinformatics software were used for QTL identification and downstream analyses. RESULTS: We provided a complete quantification of gene expression and alternative splicing across colon subsites and described their differences. We identified thousands of expression and splicing QTLs and defined their enrichment at genome-wide regulatory regions. We found that part of the SNP-based heritability of diseases affecting colon tissue, such as colorectal cancer and inflammatory bowel disease, but also of diseases affecting other tissues, such as psychiatric conditions, can be explained by the identified QTLs. We provided candidate effector genes for multiple phenotypes. Finally, we provided the Colon Transcriptome Explorer web application. CONCLUSIONS: We provide a large characterization of gene expression and splicing across colon subsites. Our findings provide greater etiologic insight into complex traits and diseases influenced by transcriptomic changes in colon tissue.

DNA methylation events in transcription factors and gene expression changes in colon cancer.

Aim: Gain insight about the role of DNA methylation in the malignant growth of colon cancer. Patients & methods: Methylation and gene expression from 90 adjacent-tumor paired tissues and 48 healthy tissues were analyzed. Tumor genes whose change in expression was explained by changes in methylation were identified using linear models adjusted for tumor stromal content. Results: No differences in methylation were found between adjacent and healthy tissues, but clear differences were found between adjacent and tumor samples. We identified hypermethylated CpG islands located in promoter regions that drive differential gene expression of transcription factors and their target genes. Conclusion: Changes in methylation of a few genes provoke important changes in gene expression, by expanding the signal through transcription activation/repression.

Tissue and cancer-specific expression of DIEXF is epigenetically mediated by an Alu repeat.

Alu repeats constitute a major fraction of human genome and for a small subset of them a role in gene regulation has been described. The number of studies focused on the functional characterization of particular Alu elements is very limited. Most Alu elements are DNA methylated and then assumed to lie in repressed chromatin domains. We hypothesize that Alu elements with low or variable DNA methylation are candidates for a functional role. In a genome-wide study in normal and cancer tissues, we pinpointed an Alu repeat (AluSq2) with differential methylation located upstream of the promoter region of the DIEXF gene. DIEXF encodes a highly conserved factor essential for the development of zebrafish digestive tract. To characterize the contribution of the Alu element to the regulation of DIEXF we analysed the epigenetic landscapes of the gene promoter and flanking regions in different cell types and cancers. Alternate epigenetic profiles (DNA methylation and histone modifications) of the AluSq2 element were associated with DIEXF transcript diversity as well as protein levels, while the epigenetic profile of the CpG island associated with the DIEXF promoter remained unchanged. These results suggest that AluSq2 might directly contribute to the regulation of DIEXF transcription and protein expression. Moreover, AluSq2 was DNA hypomethylated in different cancer types, pointing out its putative contribution to DIEXF alteration in cancer and its potential as tumoural biomarker.

Mendelian randomization analysis rules out disylipidaemia as colorectal cancer cause.

Dyslipidemia and statin use have been associated with colorectal cancer (CRC), but prospective studies have shown mixed results. We aimed to determine whether dyslipidemia is causally linked to CRC risk using a Mendelian randomization approach and to explore the association of statins with CRC. A case-control study was performed including 1336 CRC cases and 2744 controls (MCC-Spain). Subjects were administered an epidemiological questionnaire and were genotyped with an array which included polymorphisms associated with blood lipids levels, selected to avoid pleiotropy. Four genetic lipid scores specific for triglycerides (TG), high density lipoprotein cholesterol (HDL), low density lipoprotein cholesterol (LDL), or total cholesterol (TC) were created as the count of risk alleles. The genetic lipid scores were not associated with CRC. The ORs per 10 risk alleles, were for TG 0.91 (95%CI: 0.72-1.16, p = 0.44), for HDL 1.14 (95%CI: 0.95-1.37, p = 0.16), for LDL 0.97 (95%CI: 0.81-1.16, p = 0.73), and for TC 0.98 (95%CI: 0.84-1.17, p = 0.88). The LDL and TC genetic risk scores were associated with statin use, but not the HDL or TG. Statin use, overall, was a non-significant protective factor for CRC (OR 0.84; 95%CI: 0.70-1.01, p = 0.060), but lipophilic statins were associated with a CRC risk reduction (OR 0.78; 95%CI 0.66-0.96, p = 0.018). Using the Mendelian randomization approach, our study does not support the hypothesis that lipid levels are associated with the risk of CRC. This study does not rule out, however, a possible protective effect of statins in CRC by a mechanism unrelated to lipid levels.

Low adherence to the western and high adherence to the mediterranean dietary patterns could prevent colorectal cancer.

PURPOSE: To assess if the associations found between three previously identified dietary patterns with breast, prostate and gastric cancer are also observed for colorectal cancer (CRC). METHODS: MCC-Spain is a multicase-control study that collected information of 1629 incident cases of CRC and 3509 population-based controls from 11 Spanish provinces. Western, Prudent and Mediterranean data-driven dietary patterns-derived in another Spanish case-control study-were reconstructed in MCC-Spain. Their association with CRC was assessed using mixed multivariable logistic regression models considering a possible interaction with sex. Risk by tumor site (proximal colon, distal colon, and rectum) was evaluated using multinomial regression models. RESULTS: While no effect of the Prudent pattern on CRC risk was observed, a high adherence to the Western dietary pattern was associated with increased CRC risk for both males [ORfourth(Q4) vs. first(Q1)quartile (95% CI): 1.45 (1.11;1.91)] and females [ORQ4 vs. Q1 (95% CI): 1.50 (1.07;2.09)] but seem to be confined to distal colon [ORfourth(Q4) vs. first(Q1)quartile (95% CI): 2.02 (1.44;2.84)] and rectal [ORQ4 vs. Q1 (95% CI): 1.46 (1.05;2.01)] tumors. The protective effect of the Mediterranean dietary pattern against CRC was observed for both sexes [males: ORQ4 vs. Q1 (95% CI): 0.71 (0.55;0.92); females: ORQ4 vs. Q1 (95% CI): 0.56 (0.40;0.77)] and for all cancer sites: proximal colon [ORQ4 vs. Q1 (95% CI): 0.70 (0.51;0.97)], distal colon [ORQ4 vs. Q1 (95% CI): 0.65 (0.48;0.89)], and rectum (ORQ4 vs. Q1 (95% CI): 0.60 (0.45;0.81)]. CONCLUSION: Our results are consistent with most of the associations previously found between these patterns and breast, prostate and gastric cancer risk and indicate that consuming whole fruits, vegetables, legumes, olive oil, nuts, and fish and avoiding red and processed meat, refined grains, sweets, caloric drinks, juices, convenience food, and sauces might reduce CRC risk.

Colon-specific eQTL analysis to inform on functional SNPs.

BACKGROUND: Genome-wide association studies on colorectal cancer have identified more than 60 susceptibility loci, but for most of them there is no clear knowledge of functionality or the underlying gene responsible for the risk modification. Expression quantitative trail loci (eQTL) may provide functional information for such single nucleotide polymorphisms (SNPs). METHODS: We have performed detailed eQTL analysis specific for colon tissue on a series of 97 colon tumours, their paired adjacent normal mucosa and 47 colon mucosa samples donated by healthy individuals. R package MatrixEQTL was used to search for genome-wide cis-eQTL and trans-eQTL fitting linear models adjusted for age, gender and tissue type to rank transformed expression data. RESULTS: The cis-eQTL analyses has revealed 29,073 SNP-gene associations with permutation-adjusted P-values < 0.01. These correspond to 363 unique genes. The trans-eQTL analysis identified 10,665 significant SNP-gene associations, most of them in the same chromosome, further than 1 Mb of the gene. We provide a web tool to search for specific SNPs or genes. The tool calculates Pearson or Spearman correlation, and allows to select tissue type for analysis. Data and plots can be exported. CONCLUSIONS: This resource should be useful to prioritise SNPs for further functional studies and to identify relevant genes behind identified loci.

Kallikreins Stepwise Scoring Reveals Three Subtypes of Papillary Thyroid Cancer with Prognostic Implications.

BACKGROUND: Papillary thyroid cancer (PTC) is the most common type of thyroid cancer. Unlike most cancers, its incidence has dramatically increased in the last decades mainly due to increased diagnosis of indolent PTCs. Adequate risk stratification is crucial to avoid the over-treatment of low-risk patients, as well as the under-treatment of high-risk patients, but the currently available markers are still insufficient. Kallikreins (KLKs) are emergent biomarkers in cancer, but their involvement in PTC is unknown. METHODS: This study analyzed DNA methylation (HumanMethylation arrays) and gene expression (RNA-Seq) of KLKs, BRAF and RAS mutations, and clinical data from four published thyroid cancer data sets including normal and tumor tissues (n = 73, n = 475, n = 20, and n = 82) as discovery, training, and validation series. The C4.5 classification algorithm was used to generate a decision tree. Disease-free survival was estimated using Kaplan-Meier and Cox approaches. Specific analyses were performed using real-time polymerase chain reaction and immunohistochemistry. RESULTS: The entire KLK family was deregulated in PTC, displaying a specific epigenetic and transcriptional profile strongly associated with BRAFV600E or RAS mutations. Thus, a decision-tree algorithm was developed based on three KLKs with >80% sensitivity and >95% specificity, identifying BRAF- and RAS-mutated tumors. Notably, tumors lacking these mutations were classified as BRAF- or RAS-like. Most importantly, the KLK algorithm uncovered a novel PTC subtype showing favorable prognostic features. CONCLUSIONS: The KLK algorithm could lead to a new clinically applicable strategy with important implications for the risk stratification of PTC and the management of patients.