Performance of a Shotgun Prediction Model for Colorectal Cancer When Using 16S rRNA Sequencing Data.

Colorectal cancer (CRC), the third most common cancer globally, has shown links to disturbed gut microbiota. While significant efforts have been made to establish a microbial signature indicative of CRC using shotgun metagenomic sequencing, the challenge lies in validating this signature with 16S ribosomal RNA (16S) gene sequencing. The primary obstacle is reconciling the differing outputs of these two methodologies, which often lead to divergent statistical models and conclusions. In this study, we introduce an algorithm designed to bridge this gap by mapping shotgun-derived taxa to their 16S counterparts. This mapping enables us to assess the predictive performance of a shotgun-based microbiome signature using 16S data. Our results demonstrate a reduction in performance when applying the 16S-mapped taxa in the shotgun prediction model, though it retains statistical significance. This suggests that while an exact match between shotgun and 16S data may not yet be feasible, our approach provides a viable method for comparative analysis and validation in the context of CRC-associated microbiome research.

Determining the optimal interval between neoadjuvant radiochemotherapy and surgery in rectal cancer: a retrospective cohort study.

INTRODUCTION: In locally advanced rectal cancer, the optimal interval between completion of neoadjuvant radiochemotherapy (RT-ChT) and surgical resection remains unclear due to contradictory data on the benefits of extending this interval. Therefore, the aim of this retrospective study was to determine the impact of this interval on outcomes in patients treated for rectal cancer at our center. METHODS: We retrospectively reviewed 382 consecutive patients treated for stage II/III rectal cancer between October 1, 2012, and December 31, 2017. We evaluated four different cut-off points (56, 63, 70, and 77 days) to determine which had the greatest impact on treatment outcomes. RESULTS: The median time between completion of RT-ChT and surgery was 67.2 days (range, 28-294). Intervals > 8 weeks (56 days) were associated with worse therapeutic outcomes. Specifically, an interval ≥ 77 days was associated with a significant decrease in overall survival (OS; 84% vs. 70%; p = 0.004), which is why we selected this interval for the comparative analysis. Several outcome variables were significantly better in the short interval (< 77 days) group, including margin involvement (5.2% vs. 13.9%; p = 0.01), sphincter preservation (78% vs. 59.3%; p = 0.003), and distant dissemination (22.6% vs. 32.5%; p = 0.04). No significant between-group differences were found in complete/nearly complete response rates (19.2% vs. 24.4%; p = 0.3). Time to surgery was statistically significant on both the univariate and multivariate analyses. CONCLUSIONS: Our findings suggest that surgery should not be delayed more than 8 weeks (56 days) after neoadjuvant treatment. An interval > 8 weeks should only be considered in patients who demonstrate a good response to neoadjuvant RT-ChT.

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.

Lymphocytic infiltration in stage II microsatellite stable colorectal tumors: A retrospective prognosis biomarker analysis.

BACKGROUND: Identifying stage II patients with colorectal cancer (CRC) at higher risk of progression is a clinical priority in order to optimize the advantages of adjuvant chemotherapy while avoiding unnecessary toxicity. Recently, the intensity and the quality of the host immune response in the tumor microenvironment have been reported to have an important role in tumorigenesis and an inverse association with tumor progression. This association is well established in microsatellite instable CRC. In this work, we aim to assess the usefulness of measures of T-cell infiltration as prognostic biomarkers in 640 stage II, CRC tumors, 582 of them confirmed microsatellite stable. METHODS AND FINDINGS: We measured both the quantity and clonality index of T cells by means of T-cell receptor (TCR) immunosequencing in a discovery dataset (95 patients with colon cancer diagnosed at stage II and microsatellite stable, median age 67, 30% women) and replicated the results in 3 additional series of stage II patients from 2 countries. Series 1 and 2 were recruited in Barcelona, Spain and included 112 fresh frozen (FF, median age 69, 44% women) and 163 formalin-fixed paraffin-embedded (FFPE, median age 67, 39% women) samples, respectively. Series 3 included 270 FFPE samples from patients recruited in Haifa, Northern Israel, as part of a large case-control study of CRC (median age 73, 46% women). Median follow-up time was 81.1 months. Cox regression models were fitted to evaluate the prognostic value of T-cell abundance and Simpson clonality of TCR variants adjusting by sex, age, tumor location, and stage (IIA and IIB). In the discovery dataset, higher TCR abundance was associated with better prognosis (hazard ratio [HR] for ≥Q1 = 0.25, 95% CI 0.10-0.63, P = 0.003). A functional analysis of gene expression on these tumors revealed enrichment in pathways related to immune response. Higher values of clonality index (lower diversity) were not associated with worse disease-free survival, though the HR for ≥Q3 was 2.32 (95% CI 0.90-5.97, P = 0.08). These results were replicated in an independent FF dataset (TCR abundance: HR = 0.30, 95% CI 0.12-0.72, P = 0.007; clonality: HR = 3.32, 95% CI 1.38-7.94, P = 0.007). Also, the association with prognosis was tested in 2 independent FFPE datasets. The same association was observed with TCR abundance (HR = 0.41, 95% CI 0.18-0.93, P = 0.03 and HR = 0.56, 95% CI 0.31-1, P = 0.042, respectively, for each FFPE dataset). However, the clonality index was associated with prognosis only in the FFPE dataset from Israel (HR = 2.45, 95% CI 1.39-4.32, P = 0.002). Finally, a combined analysis combining all microsatellite stable (MSS) samples demonstrated a clear prognosis value both for TCR abundance (HR = 0.39, 95% CI 0.26-0.57, P = 1.3e-06) and the clonality index (HR = 2.13, 95% CI 1.44-3.15, P = 0.0002). These associations were also observed when variables were considered continuous in the models (HR per log2 of TCR abundance = 0.85, 95% CI 0.78-0.93, P = 0.0002; HR per log2 or clonality index = 1.16, 95% CI 1.03-1.31, P = 0.016). LIMITATIONS: This is a retrospective study, and samples had been preserved with different methods. Validation series lack complete information about microsatellite instability (MSI) status and pathology assessment. The Molecular Epidemiology of Colorectal Cancer (MECC) study had information about overall survival instead of progression-free survival. CONCLUSION: Results from this study demonstrate that tumor lymphocytes, assessed by TCR repertoire quantification based on a sequencing method, are an independent prognostic factor in microsatellite stable stage II CRC.

Risk of colorectal cancer in users of bisphosphonates: analysis of population-based electronic health records.

The use of bisphosphonates has been associated with a decrease in the risk of colorectal cancer (CRC) in observational studies, but with controversial results and difficult to interpret because of routine concomitant use of calcium and vitamin D. We aimed to assess the association between CRC risk and outpatient exposure to antiosteoporotic drugs using a large cohort with prescription data in Catalonia. A case-control study was performed using the Information System for Development of Primary Care Research (SIDIAP) which is a primary care medical record database that has linked data on reimbursed medication. The study included 25,836 cases with an incident diagnosis of CRC between 2010 and 2015 and 129,117 matched controls by age (± 5 years), sex and healthcare region. A multivariable model was built adjusting for known risk factors and comorbidities that were significantly associated to CRC in the dataset, and a propensity score for bisphosphonates. Tests for interaction for multiple drug use and stratified analysis for tumour location were prospectively planned. Overall 18,230 individuals (11.5%) were users of bisphosphonates. A significant but modest protective effect on CRC was observed for bisphosphonates (OR 0.95, 95% CI 0.91-0.99), that was no longer significant when adjusted for calcium and vitamin D (OR 0.98, 95% CI 0.93-1.03). Bisphosphonates, however, showed a dose-response effect with duration of use even when adjusted for calcium and vitamin D (OR for use > 40 months: 0.90, 95% CI 0.81-1.00, P value for trend: 0.018). The use of bisphosphonates was associated with a modest decrease in the risk of CRC, but this effect was essentially explained by concomitant use of calcium or vitamin D. The observed protective effect was stronger for long durations of use, which deserves further study.

Comprehensive analysis of copy number aberrations in microsatellite stable colon cancer in view of stromal component.

BACKGROUND: Somatic copy number aberrations (CNAs) are common acquired changes in cancer cells having an important role in the progression of colon cancer (colorectal cancer, CRC). This study aimed to perform a characterisation of CNA and their impact in gene expression. METHODS: Copy number aberrations were inferred from SNP array data in a series of 99 CRC. Copy number aberration events were calculated and used to assess the association between copy number dosage, clinical and molecular characteristics of the tumours, and gene expression changes. All analyses were adjusted for the quantity of stroma in each sample, which was inferred from gene expression data. RESULTS: High heterogeneity among samples was observed; the proportion of altered genome ranged between 0.04 and 26.6%. Recurrent CNA regions with gains were frequent in chromosomes 7p, 8q, 13q, and 20, whereas 8p, 17p, and 18 cumulated losses. A significant positive correlation was observed between the number of somatic mutations and total CNA (Spearman's r=0.42, P=0.006). Approximately 37% of genes located in CNA regions changed their level of expression and the average partial correlation (adjusted for stromal content) with copy number was 0.54 (interquartile range 0.20 to 0.81). Altered genes showed enrichment in pathways relevant for CRC. Tumours classified as CMS2 and CMS4 by the consensus molecular subtyping showed higher frequency of CNA. Losses of one small region in 1p36.33, with gene CDK11B, were associated with poor prognosis. More than 66% of the recurrent CNA were validated in the The Cancer Genome Atlas (TCGA) data when analysed with the same procedure. Furthermore, 79% of the genes with altered expression in our data were validated in the TCGA. CONCLUSIONS: Although CNA are frequent events in microsatellite stable CRC, few focal recurrent regions were found. These aberrations have strong effects on gene expression and contribute to deregulate relevant cancer pathways. Owing to the diploid nature of stromal cells, it is important to consider the purity of tumour samples to accurately calculate CNA events in CRC.

Germline Mutations in FAN1 Cause Hereditary Colorectal Cancer by Impairing DNA Repair.

Identification of genes associated with hereditary cancers facilitates management of patients with family histories of cancer. We performed exome sequencing of DNA from 3 individuals from a family with colorectal cancer who met the Amsterdam criteria for risk of hereditary nonpolyposis colorectal cancer. These individuals had mismatch repair-proficient tumors and each carried nonsense variant in the FANCD2/FANCI-associated nuclease 1 gene (FAN1), which encodes a nuclease involved in DNA inter-strand cross-link repair. We sequenced FAN1 in 176 additional families with histories of colorectal cancer and performed in vitro functional analyses of the mutant forms of FAN1 identified. We detected FAN1 mutations in approximately 3% of families who met the Amsterdam criteria and had mismatch repair-proficient cancers with no previously associated mutations. These findings link colorectal cancer predisposition to the Fanconi anemia DNA repair pathway, supporting the connection between genome integrity and cancer risk.

Identification of candidate susceptibility genes for colorectal cancer through eQTL analysis.

In this study, we aim to identify the genes responsible for colorectal cancer risk behind the loci identified in genome-wide association studies (GWAS). These genes may be candidate targets for developing new strategies for prevention or therapy. We analyzed the association of genotypes for 26 GWAS single nucleotide polymorphisms (SNPs) with the expression of genes within a 2 Mb region (cis-eQTLs). Affymetrix Human Genome U219 expression arrays were used to assess gene expression in two series of samples, one of healthy colonic mucosa (n = 47) and other of normal mucosa adjacent to colon cancer (n = 97, total 144). Paired tumor tissues (n = 97) were also analyzed but did not provide additional findings. Partial Pearson correlation (r), adjusted for sample type, was used for the analysis. We have found Bonferroni-significant cis-eQTLs in three loci: rs3802842 in 11q23.1 associated to C11orf53, COLCA1 (C11orf92) and COLCA2 (C11orf93; r = 0.60); rs7136702 in 12q13.12 associated to DIP2B (r = 0.63) and rs5934683 in Xp22.3 associated to SHROOM2 and GPR143 (r = 0.47). For loci in chromosomes 11 and 12, we have found other SNPs in linkage disequilibrium that are more strongly associated with the expression of the identified genes and are better functional candidates: rs7130173 for 11q23.1 (r = 0.66) and rs61927768 for 12q13.12 (r = 0.86). These SNPs are located in DNA regions that may harbor enhancers or transcription factor binding sites. The analysis of trans-eQTLs has identified additional genes in these loci that may have common regulatory mechanisms as shown by the analysis of protein-protein interaction networks.

Aberrant gene expression in mucosa adjacent to tumor reveals a molecular crosstalk in colon cancer.

BACKGROUND: A colorectal tumor is not an isolated entity growing in a restricted location of the body. The patient's gut environment constitutes the framework where the tumor evolves and this relationship promotes and includes a complex and tight correlation of the tumor with inflammation, blood vessels formation, nutrition, and gut microbiome composition. The tumor influence in the environment could both promote an anti-tumor or a pro-tumor response. METHODS: A set of 98 paired adjacent mucosa and tumor tissues from colorectal cancer (CRC) patients and 50 colon mucosa from healthy donors (246 samples in total) were included in this work. RNA extracted from each sample was hybridized in Affymetrix chips Human Genome U219. Functional relationships between genes were inferred by means of systems biology using both transcriptional regulation networks (ARACNe algorithm) and protein-protein interaction networks (BIANA software). RESULTS: Here we report a transcriptomic analysis revealing a number of genes activated in adjacent mucosa from CRC patients, not activated in mucosa from healthy donors. A functional analysis of these genes suggested that this active reaction of the adjacent mucosa was related to the presence of the tumor. Transcriptional and protein-interaction networks were used to further elucidate this response of normal gut in front of the tumor, revealing a crosstalk between proteins secreted by the tumor and receptors activated in the adjacent colon tissue; and vice versa. Remarkably, Slit family of proteins activated ROBO receptors in tumor whereas tumor-secreted proteins transduced a cellular signal finally activating AP-1 in adjacent tissue. CONCLUSIONS: The systems-level approach provides new insights into the micro-ecology of colorectal tumorogenesis. Disrupting this intricate molecular network of cell-cell communication and pro-inflammatory microenvironment could be a therapeutic target in CRC patients.

Large differences in global transcriptional regulatory programs of normal and tumor colon cells.

BACKGROUND: Dysregulation of transcriptional programs leads to cell malfunctioning and can have an impact in cancer development. Our study aims to characterize global differences between transcriptional regulatory programs of normal and tumor cells of the colon. METHODS: Affymetrix Human Genome U219 expression arrays were used to assess gene expression in 100 samples of colon tumor and their paired adjacent normal mucosa. Transcriptional networks were reconstructed using ARACNe algorithm using 1,000 bootstrap replicates consolidated into a consensus network. Networks were compared regarding topology parameters and identified well-connected clusters. Functional enrichment was performed with SIGORA method. ENCODE ChIP-Seq data curated in the hmChIP database was used for in silico validation of the most prominent transcription factors. RESULTS: The normal network contained 1,177 transcription factors, 5,466 target genes and 61,226 transcriptional interactions. A large loss of transcriptional interactions in the tumor network was observed (11,585; 81% reduction), which also contained fewer transcription factors (621; 47% reduction) and target genes (2,190; 60% reduction) than the normal network. Gene silencing was not a main determinant of this loss of regulatory activity, since the average gene expression was essentially conserved. Also, 91 transcription factors increased their connectivity in the tumor network. These genes revealed a tumor-specific emergent transcriptional regulatory program with significant functional enrichment related to colorectal cancer pathway. In addition, the analysis of clusters again identified subnetworks in the tumors enriched for cancer related pathways (immune response, Wnt signaling, DNA replication, cell adherence, apoptosis, DNA repair, among others). Also multiple metabolism pathways show differential clustering between the tumor and normal network. CONCLUSIONS: These findings will allow a better understanding of the transcriptional regulatory programs altered in colon cancer and could be an invaluable methodology to identify potential hubs with a relevant role in the field of cancer diagnosis, prognosis and therapy.

Interplay between BRCA1 and RHAMM regulates epithelial apicobasal polarization and may influence risk of breast cancer.

Differentiated mammary epithelium shows apicobasal polarity, and loss of tissue organization is an early hallmark of breast carcinogenesis. In BRCA1 mutation carriers, accumulation of stem and progenitor cells in normal breast tissue and increased risk of developing tumors of basal-like type suggest that BRCA1 regulates stem/progenitor cell proliferation and differentiation. However, the function of BRCA1 in this process and its link to carcinogenesis remain unknown. Here we depict a molecular mechanism involving BRCA1 and RHAMM that regulates apicobasal polarity and, when perturbed, may increase risk of breast cancer. Starting from complementary genetic analyses across families and populations, we identified common genetic variation at the low-penetrance susceptibility HMMR locus (encoding for RHAMM) that modifies breast cancer risk among BRCA1, but probably not BRCA2, mutation carriers: n = 7,584, weighted hazard ratio ((w)HR) = 1.09 (95% CI 1.02-1.16), p(trend) = 0.017; and n = 3,965, (w)HR = 1.04 (95% CI 0.94-1.16), p(trend) = 0.43; respectively. Subsequently, studies of MCF10A apicobasal polarization revealed a central role for BRCA1 and RHAMM, together with AURKA and TPX2, in essential reorganization of microtubules. Mechanistically, reorganization is facilitated by BRCA1 and impaired by AURKA, which is regulated by negative feedback involving RHAMM and TPX2. Taken together, our data provide fundamental insight into apicobasal polarization through BRCA1 function, which may explain the expanded cell subsets and characteristic tumor type accompanying BRCA1 mutation, while also linking this process to sporadic breast cancer through perturbation of HMMR/RHAMM.

Serum 25-hydroxyvitamin D3 levels and vitamin D receptor variants in melanoma patients from the Mediterranean area of Barcelona.

BACKGROUND: Serum 25-hydroxyvitamin D3 (Vitamin D) insufficiency and single-nucleotide polymorphisms (SNPs) on its receptor, Vitamin D receptor (VDR), have been reported to be involved in melanoma susceptibility in populations mostly from northern countries. OBJECTIVE: To investigate 25-hydroxyvitamin D3 levels and VDR SNPs in melanoma patients from sunny area of Barcelona, two studies were carried out. The first study evaluated the levels of Vitamin D at time of melanoma diagnosis and the second one analyzed the association between VDR genetic variants and risk of having a high nevus number, the strongest phenotypic risk factor for melanoma. METHODS: The levels of 25-hydroxyvitamin D3 in 81 melanoma patients at diagnosis were measured. In a second group of melanoma patients, including 150 with low and 113 with high nevus number, 11 VDR SNPs were analyzed for their association with nevus number. RESULTS: In the first study, 68% of patients had insufficient levels of 25-hydroxyvitamin D3 (<25 ng/ml). Autumn-winter months and fair phototype were associated with 25-hydroxyvitamin D3 insufficiency; after multivariate analysis, season of sampling remained the only independent predictor of 25-hydroxyvitamin D3 levels. In the second study, VDR variant rs2189480 (P = 0.006) was associated with risk of high nevus number whereas rs2239179 (P = 0.044) and rs7975128 (P = 0.0005) were protective against high nevus number. After Bonferroni adjustment only rs7975128 remained significant. In stratified analysis, SNP rs7975128 was found protective against multiple melanomas (P = 0.021). CONCLUSION: This study showed that even in Barcelona, a sunny Mediterranean area, 25-hydroxyvitamin D3 levels were sub-optimal in the majority of melanoma patients at diagnosis. The involvement of VDR in nevi and, in turn, in melanoma susceptibility has also been suggested. Larger studies are needed to confirm our findings.

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.

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.

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.

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.

Allele-specific expression of APC in adenomatous polyposis families.

BACKGROUND & AIMS: Germline mutations in the APC gene cause of most cases of familial adenomatous polyposis (FAP) and a lesser proportion of attenuated FAP (AFAP). Systematic analysis of APC at the RNA level could provide insight into the pathogenicity of identified mutations and the molecular basis of FAP/AFAP in families without identifiable mutations. Here, we analyzed the prevalence of imbalances in the allelic expression of APC in polyposis families with germline mutations in the gene and without detectable mutations in APC and/or MUTYH. METHODS: Allele-specific expression (ASE) was determined by single nucleotide primer extension using an exon 11 polymorphism as an allele-specific marker. In total, 52 APC-mutation-positive (36 families) and 24 APC/MUTYH-mutation-negative (23 families) informative patients were analyzed. Seventy-six controls also were included. RESULTS: Of the APC-mutation-positive families, most of those in whom the mutation was located before the last exon of the gene (12 of 14) had ASE imbalance, which is consistent with a mechanism of nonsense-mediated decay. Of the APC/MUTYH-mutation-negative families, 2 (9%) had ASE imbalance, which might cause the disease. Normal allele expression was restored shortly after lymphocytes were cultured with puromycin, supporting a 'nonsense-mediated' hypothesis. CONCLUSIONS: ASE analysis might be used to determine the pathogenesis of some cases of FAP and AFAP in which APC mutations are not found. ASE also might be used to prioritize the order in which different areas of APC are tested. RNA-level studies are important for the molecular diagnosis of FAP.

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.

Chondroitin Sulphate and Glucosamine Use Depend on Nonsteroidal Anti-inflammatory Drug Use to Modify the Risk for Colorectal Cancer.

BACKGROUND: A safe and effective colorectal cancer chemoprevention agent remains to be discovered. There is little evidence regarding the protective effect of chondroitin sulphate and glucosamine on colorectal cancer. We aimed to assess the association between colorectal cancer risk and the use of chondroitin sulphate and glucosamine using a large cohort with dispensed data. METHODS: We performed a population-based case-control study in Catalonia using primary care reimbursed medication records (SIDIAP database). The study included 25,811 cases with an incident diagnosis of colorectal cancer and 129,117 matched controls between 2010 and 2015. RESULTS: The prevalence of ever use was 9.0% (n = 13,878) for chondroitin sulphate, 7.3% (n = 11,374) for glucosamine, and 35% for regular use of nonsteroidal anti-inflammatory drugs (NSAID; n = 45,774). A decreased risk of colorectal cancer was observed among chondroitin sulphate use [OR: 0.96; 95% confidence interval (CI), 0.91-1.01], glucosamine use (OR: 0.92; 95% CI, 0.87-0.97), and concurrent use of chondroitin sulphate and glucosamine (OR: 0.83; 95% CI, 0.70-0.98). Especially for glucosamine, there was a dose-response association regarding duration and cumulative dose. The analysis stratified by simultaneous use with other NSAIDs showed that these drugs used without other NSAIDs do not reduce risk (OR: 1.06; 95% CI, 0.74-1.51). However, they may have a synergistic protective effect when used with other NSAIDs (OR: 0.80; 95% CI, 0.72-0.88). CONCLUSIONS: This study does not provide strong support for an independent protective association of chondroitin sulphate or glucosamine on colorectal cancer risk in our population. However, these drugs may have a synergistic beneficial effect among NSAID users. IMPACT: Chondroitin sulphate or glucosamine may contribute to the protective effect of NSAID use in colorectal cancer.

Gut microbiome diversity detected by high-coverage 16S and shotgun sequencing of paired stool and colon sample.

The gut microbiome has a fundamental role in human health and disease. However, studying the complex structure and function of the gut microbiome using next generation sequencing is challenging and prone to reproducibility problems. Here, we obtained cross-sectional colon biopsies and faecal samples from nine participants in our COLSCREEN study and sequenced them in high coverage using Illumina pair-end shotgun (for faecal samples) and IonTorrent 16S (for paired feces and colon biopsies) technologies. The metagenomes consisted of between 47 and 92 million reads per sample and the targeted sequencing covered more than 300 k reads per sample across seven hypervariable regions of the 16S gene. Our data is freely available and coupled with code for the presented metagenomic analysis using up-to-date bioinformatics algorithms. These results will add up to the informed insights into designing comprehensive microbiome analysis and also provide data for further testing for unambiguous gut microbiome analysis.