Folate intake and colorectal cancer risk according to genetic subtypes defined by targeted tumor sequencing.

BACKGROUND: Folate is involved in multiple genetic, epigenetic, and metabolic processes, and inadequate folate intake has been associated with an increased risk of cancer. OBJECTIVE: We examined whether folate intake is differentially associated with colorectal cancer (CRC) risk according to somatic mutations in genes linked to CRC using targeted sequencing. DESIGN: Participants within 2 large CRC consortia with available information on dietary folate, supplemental folic acid, and total folate intake were included. Colorectal tumor samples from cases were sequenced for the presence of nonsilent mutations in 105 genes and 6 signaling pathways (IGF2/PI3K, MMR, RTK/RAS, TGF-ß, WNT, and TP53/ATM). Multinomial logistic regression models were analyzed comparing mutated/nonmutated CRC cases to controls to compute multivariable-adjusted odds ratios (ORs) with 95% confidence interval (CI). Heterogeneity of associations of mutated compared with nonmutated CRC cases was tested in case-only analyses using logistic regression. Analyses were performed separately in hypermutated and nonhypermutated tumors, because they exhibit different clinical behaviors. RESULTS: We included 4339 CRC cases (702 hypermutated tumors, 16.2%) and 11,767 controls. Total folate intake was inversely associated with CRC risk (OR = 0.93; 95% CI: 0.90, 0.96). Among hypermutated tumors, 12 genes (AXIN2, B2M, BCOR, CHD1, DOCK3, FBLN2, MAP3K21, POLD1, RYR1, TET2, UTP20, and ZNF521) showed nominal statistical significance (P < 0.05) for heterogeneity by mutation status, but none remained significant after multiple testing correction. Among these genetic subtypes, the associations between folate variables and CRC were mostly inverse or toward the null, except for tumors mutated for DOCK3 (supplemental folic acid), CHD1 (total folate), and ZNF521 (dietary folate) that showed positive associations. We did not observe differential associations in analyses among nonhypermutated tumors, or according to the signaling pathways. CONCLUSIONS: Folate intake was not differentially associated with CRC risk according to mutations in the genes explored. The nominally significant differential mutation effects observed in a few genes warrants further investigation.

Body size and risk of colorectal cancer molecular defined subtypes and pathways: Mendelian randomization analyses.

BACKGROUND: Obesity has been positively associated with most molecular subtypes of colorectal cancer (CRC); however, the magnitude and the causality of these associations is uncertain. METHODS: We used Mendelian randomization (MR) to examine potential causal relationships between body size traits (body mass index [BMI], waist circumference, and body fat percentage) with risks of Jass classification types and individual subtypes of CRC (microsatellite instability [MSI] status, CpG island methylator phenotype [CIMP] status, BRAF and KRAS mutations). Summary data on tumour markers were obtained from two genetic consortia (CCFR, GECCO). FINDINGS: A 1-standard deviation (SD:5.1 kg/m2) increment in BMI levels was found to increase risks of Jass type 1MSI-high,CIMP-high,BRAF-mutated,KRAS-wildtype (odds ratio [OR]: 2.14, 95% confidence interval [CI]: 1.46, 3.13; p-value = 9 × 10-5) and Jass type 2non-MSI-high,CIMP-high,BRAF-mutated,KRAS-wildtype CRC (OR: 2.20, 95% CI: 1.26, 3.86; p-value = 0.005). The magnitude of these associations was stronger compared with Jass type 4non-MSI-high,CIMP-low/negative,BRAF-wildtype,KRAS-wildtype CRC (p-differences: 0.03 and 0.04, respectively). A 1-SD (SD:13.4 cm) increment in waist circumference increased risk of Jass type 3non-MSI-high,CIMP-low/negative,BRAF-wildtype,KRAS-mutated (OR 1.73, 95% CI: 1.34, 2.25; p-value = 9 × 10-5) that was stronger compared with Jass type 4 CRC (p-difference: 0.03). A higher body fat percentage (SD:8.5%) increased risk of Jass type 1 CRC (OR: 2.59, 95% CI: 1.49, 4.48; p-value = 0.001), which was greater than Jass type 4 CRC (p-difference: 0.03). INTERPRETATION: Body size was more strongly linked to the serrated (Jass types 1 and 2) and alternate (Jass type 3) pathways of colorectal carcinogenesis in comparison to the traditional pathway (Jass type 4). FUNDING: Cancer Research UK, National Institute for Health Research, Medical Research Council, National Institutes of Health, National Cancer Institute, American Institute for Cancer Research, Brigham and Women's Hospital, Prevent Cancer Foundation, Victorian Cancer Agency, Swedish Research Council, Swedish Cancer Society, Region Västerbotten, Knut and Alice Wallenberg Foundation, Lion's Cancer Research Foundation, Insamlingsstiftelsen, Umeå University. Full funding details are provided in acknowledgements.

Epidemiologic Factors in Relation to Colorectal Cancer Risk and Survival by Genotoxic Colibactin Mutational Signature.

BACKGROUND: The genotoxin colibactin causes a tumor single-base substitution (SBS) mutational signature, SBS88. It is unknown whether epidemiologic factors' association with colorectal cancer risk and survival differs by SBS88. METHODS: Within the Genetic Epidemiology of Colorectal Cancer Consortium and Colon Cancer Family Registry, we measured SBS88 in 4,308 microsatellite stable/microsatellite instability low tumors. Associations of epidemiologic factors with colorectal cancer risk by SBS88 were assessed using multinomial regression (N = 4,308 cases, 14,192 controls; cohort-only cases N = 1,911), and with colorectal cancer-specific survival using Cox proportional hazards regression (N = 3,465 cases). RESULTS: 392 (9%) tumors were SBS88 positive. Among all cases, the highest quartile of fruit intake was associated with lower risk of SBS88-positive colorectal cancer than SBS88-negative colorectal cancer [odds ratio (OR) = 0.53, 95% confidence interval (CI) 0.37-0.76; OR = 0.75, 95% CI 0.66-0.85, respectively, Pheterogeneity = 0.047]. Among cohort studies, associations of body mass index (BMI), alcohol, and fruit intake with colorectal cancer risk differed by SBS88. BMI ≥30 kg/m2 was associated with worse colorectal cancer-specific survival among those SBS88-positive [hazard ratio (HR) = 3.40, 95% CI 1.47-7.84], but not among those SBS88-negative (HR = 0.97, 95% CI 0.78-1.21, Pheterogeneity = 0.066). CONCLUSIONS: Most epidemiologic factors did not differ by SBS88 for colorectal cancer risk or survival. Higher BMI may be associated with worse colorectal cancer-specific survival among those SBS88-positive; however, validation is needed in samples with whole-genome or whole-exome sequencing available. IMPACT: This study highlights the importance of identification of tumor phenotypes related to colorectal cancer and understanding potential heterogeneity for risk and survival.

Genotoxic colibactin mutational signature in colorectal cancer is associated with clinicopathological features, specific genomic alterations and better survival.

Background and Aims: The microbiome has long been suspected of a role in colorectal cancer (CRC) tumorigenesis. The mutational signature SBS88 mechanistically links CRC development with the strain of Escherichia coli harboring the pks island that produces the genotoxin colibactin, but the genomic, pathological and survival characteristics associated with SBS88-positive tumors are unknown. Methods: SBS88-positive CRCs were identified from targeted sequencing data from 5,292 CRCs from 17 studies and tested for their association with clinico-pathological features, oncogenic pathways, genomic characteristics and survival. Results: In total, 7.5% (398/5,292) of the CRCs were SBS88-positive, of which 98.7% (392/398) were microsatellite stable/microsatellite instability low (MSS/MSI-L), compared with 80% (3916/4894) of SBS88 negative tumors (p=1.5x10-28). Analysis of MSS/MSI-L CRCs demonstrated that SBS88 positive CRCs were associated with the distal colon (OR=1.84, 95% CI=1.40-2.42, p=1x10-5) and rectum (OR=1.90, 95% CI=1.44-2.51, p=6x10-6) tumor sites compared with the proximal colon. The top seven recurrent somatic mutations associated with SBS88-positive CRCs demonstrated mutational contexts associated with colibactin-induced DNA damage, the strongest of which was the APC:c.835-8A>G mutation (OR=65.5, 95%CI=39.0-110.0, p=3x10-80). Large copy number alterations (CNAs) including CNA loss on 14q and gains on 13q, 16q and 20p were significantly enriched in SBS88-positive CRCs. SBS88-positive CRCs were associated with better CRC-specific survival (p=0.007; hazard ratio of 0.69, 95% CI=0.52-0.90) when stratified by age, sex, study, and by stage. Conclusion: SBS88-positivity, a biomarker of colibactin-induced DNA damage, can identify a novel subtype of CRC characterized by recurrent somatic mutations, copy number alterations and better survival. These findings provide new insights for treatment and prevention strategies for this subtype of CRC.

A High-Throughput Workflow for FFPE Tissue Proteomics.

Laser capture microdissection (LCM) has become an indispensable tool for mass spectrometry-based proteomic analysis of specific regions obtained from formalin-fixed paraffin-embedded (FFPE) tissue samples in both clinical and research settings. Low protein yields from LCM samples along with laborious sample processing steps present challenges for proteomic analysis without sacrificing protein and peptide recovery. Automation of sample preparation workflows is still under development, especially for samples such as laser-capture microdissected tissues. Here, we present a simplified and rapid workflow using adaptive focused acoustics (AFA) technology for sample processing for high-throughput FFPE-based proteomics. We evaluated three different workflows: standard extraction method followed by overnight trypsin digestion, AFA-assisted extraction and overnight trypsin digestion, and AFA-assisted extraction simultaneously performed with trypsin digestion. The use of AFA-based ultrasonication enables automated sample processing for high-throughput proteomic analysis of LCM-FFPE tissues in 96-well and 384-well formats. Further, accelerated trypsin digestion combined with AFA dramatically reduced the overall processing times. LC-MS/MS analysis revealed a slightly higher number of protein and peptide identifications in AFA accelerated workflows compared to standard and AFA overnight workflows. Further, we did not observe any difference in the proportion of peptides identified with missed cleavages or deamidated peptides across the three different workflows. Overall, our results demonstrate that the workflow described in this study enables rapid and high-throughput sample processing with greatly reduced sample handling, which is amenable to automation.

Body mass index and molecular subtypes of colorectal cancer.

BACKGROUND: Obesity is an established risk factor for colorectal cancer (CRC), but the evidence for the association is inconsistent across molecular subtypes of the disease. METHODS: We pooled data on body mass index (BMI), tumor microsatellite instability status, CpG island methylator phenotype status, BRAF and KRAS mutations, and Jass classification types for 11 872 CRC cases and 11 013 controls from 11 observational studies. We used multinomial logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusted for covariables. RESULTS: Higher BMI was associated with increased CRC risk (OR per 5 kg/m2 = 1.18, 95% CI = 1.15 to 1.22). The positive association was stronger for men than women but similar across tumor subtypes defined by individual molecular markers. In analyses by Jass type, higher BMI was associated with elevated CRC risk for types 1-4 cases but not for type 5 CRC cases (considered familial-like/Lynch syndrome microsatellite instability-H, CpG island methylator phenotype-low or negative, BRAF-wild type, KRAS-wild type, OR = 1.04, 95% CI = 0.90 to 1.20). This pattern of associations for BMI and Jass types was consistent by sex and design of contributing studies (cohort or case-control). CONCLUSIONS: In contrast to previous reports with fewer study participants, we found limited evidence of heterogeneity for the association between BMI and CRC risk according to molecular subtype, suggesting that obesity influences nearly all major pathways involved in colorectal carcinogenesis. The null association observed for the Jass type 5 suggests that BMI is not a risk factor for the development of CRC for individuals with Lynch syndrome.

Identifying colorectal cancer caused by biallelic MUTYH pathogenic variants using tumor mutational signatures.

Carriers of germline biallelic pathogenic variants in the MUTYH gene have a high risk of colorectal cancer. We test 5649 colorectal cancers to evaluate the discriminatory potential of a tumor mutational signature specific to MUTYH for identifying biallelic carriers and classifying variants of uncertain clinical significance (VUS). Using a tumor and matched germline targeted multi-gene panel approach, our classifier identifies all biallelic MUTYH carriers and all known non-carriers in an independent test set of 3019 colorectal cancers (accuracy = 100% (95% confidence interval 99.87-100%)). All monoallelic MUTYH carriers are classified with the non-MUTYH carriers. The classifier provides evidence for a pathogenic classification for two VUS and a benign classification for five VUS. Somatic hotspot mutations KRAS p.G12C and PIK3CA p.Q546K are associated with colorectal cancers from biallelic MUTYH carriers compared with non-carriers (p = 2 × 10-23 and p = 6 × 10-11, respectively). Here, we demonstrate the potential application of mutational signatures to tumor sequencing workflows to improve the identification of biallelic MUTYH carriers.

A microRNA Transcriptome-wide Association Study of Prostate Cancer Risk.

Large genome-wide association studies have identified hundreds of single-nucleotide polymorphisms associated with increased risk of prostate cancer (PrCa), and many of these risk loci is presumed to confer regulatory effects on gene expression. While eQTL studies of long RNAs has yielded many potential risk genes, the relationship between PrCa risk genetics and microRNA expression dysregulation is understudied. We performed an microRNA transcriptome-wide association study of PrCa risk using small RNA sequencing and genome-wide genotyping data from N = 441 normal prostate epithelium tissue samples along with N = 411 prostate adenocarcinoma tumor samples from the Cancer Genome Atlas (TCGA). Genetically regulated expression prediction models were trained for all expressed microRNAs using the FUSION TWAS software. TWAS for PrCa risk was performed with both sets of models using single-SNP summary statistics from the recent PRACTICAL consortium PrCa case-control OncoArray GWAS meta-analysis. A total of 613 and 571 distinct expressed microRNAs were identified in the normal and tumor tissue datasets, respectively (overlap: 480). Among these, 79 (13%) normal tissue microRNAs demonstrated significant cis-heritability (median cis-h2 = 0.15, range: 0.03-0.79) for model training. Similar results were obtained from TCGA tumor samples, with 48 (9%) microRNA expression models successfully trained (median cis-h2 = 0.14, range: 0.06-0.60). Using normal tissue models, we identified two significant TWAS microRNA associations with PrCa risk: over-expression of mir-941 family microRNAs (PTWAS = 2.9E-04) and reduced expression of miR-3617-5p (PTWAS = 1.0E-03). The TCGA tumor TWAS also identified a significant association with miR-941 overexpression (PTWAS = 9.7E-04). Subsequent finemapping of the TWAS results using a multi-tissue database indicated limited evidence of causal status for each microRNA with PrCa risk (posterior inclusion probabilities <0.05). Future work will examine downstream regulatory effects of microRNA dysregulation as well as microRNA-mediated risk mechanisms via competing endogenous RNA relationships.

Diabetes mellitus in relation to colorectal tumor molecular subtypes: A pooled analysis of more than 9000 cases.

Diabetes is an established risk factor for colorectal cancer. However, colorectal cancer is a heterogeneous disease and it is not well understood whether diabetes is more strongly associated with some tumor molecular subtypes than others. A better understanding of the association between diabetes and colorectal cancer according to molecular subtypes could provide important insights into the biology of this association. We used data on lifestyle and clinical characteristics from the Colorectal Cancer Family Registry (CCFR) and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), including 9756 colorectal cancer cases (with tumor marker data) and 9985 controls, to evaluate associations between reported diabetes and risk of colorectal cancer according to molecular subtypes. Tumor markers included BRAF and KRAS mutations, microsatellite instability and CpG island methylator phenotype. In the multinomial logistic regression model, comparing colorectal cancer cases to cancer-free controls, diabetes was positively associated with colorectal cancer regardless of subtype. The highest OR estimate was found for BRAF-mutated colorectal cancer, n = 1086 (ORfully adj : 1.67, 95% confidence intervals [CI]: 1.36-2.05), with an attenuated association observed between diabetes and colorectal cancer without BRAF-mutations, n = 7959 (ORfully adj : 1.33, 95% CI: 1.19-1.48). In the case only analysis, BRAF-mutation was differentially associated with diabetes (Pdifference  = .03). For the other markers, associations with diabetes were similar across tumor subtypes. In conclusion, our study confirms the established association between diabetes and colorectal cancer risk, and suggests that it particularly increases the risk of BRAF-mutated tumors.

Landscape of somatic single nucleotide variants and indels in colorectal cancer and impact on survival.

Colorectal cancer (CRC) is a biologically heterogeneous disease. To characterize its mutational profile, we conduct targeted sequencing of 205 genes for 2,105 CRC cases with survival data. Our data shows several findings in addition to enhancing the existing knowledge of CRC. We identify PRKCI, SPZ1, MUTYH, MAP2K4, FETUB, and TGFBR2 as additional genes significantly mutated in CRC. We find that among hypermutated tumors, an increased mutation burden is associated with improved CRC-specific survival (HR = 0.42, 95% CI: 0.21-0.82). Mutations in TP53 are associated with poorer CRC-specific survival, which is most pronounced in cases carrying TP53 mutations with predicted 0% transcriptional activity (HR = 1.53, 95% CI: 1.21-1.94). Furthermore, we observe differences in mutational frequency of several genes and pathways by tumor location, stage, and sex. Overall, this large study provides deep insights into somatic mutations in CRC, and their potential relationships with survival and tumor features.

An expanded variant list and assembly annotation identifies multiple novel coding and noncoding genes for prostate cancer risk using a normal prostate tissue eQTL data set.

Prostate cancer (PrCa) is highly heritable; 284 variants have been identified to date that are associated with increased prostate cancer risk, yet few genes contributing to its development are known. Expression quantitative trait loci (eQTL) studies link variants with affected genes, helping to determine how these variants might regulate gene expression and may influence prostate cancer risk. In the current study, we performed eQTL analysis on 471 normal prostate epithelium samples and 249 PrCa-risk variants in 196 risk loci, utilizing RNA sequencing transcriptome data based on ENSEMBL gene definition and genome-wide variant data. We identified a total of 213 genes associated with known PrCa-risk variants, including 141 protein-coding genes, 16 lncRNAs, and 56 other non-coding RNA species with differential expression. Compared to our previous analysis, where RefSeq was used for gene annotation, we identified an additional 130 expressed genes associated with known PrCa-risk variants. We detected an eQTL signal for more than half (n = 102, 52%) of the 196 loci tested; 52 (51%) of which were a Group 1 signal, indicating high linkage disequilibrium (LD) between the peak eQTL variant and the PrCa-risk variant (r2>0.5) and may help explain how risk variants influence the development of prostate cancer.

Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers.

BACKGROUND: Links between colorectal cancer (CRC) and the gut microbiome have been established, but the specific microbial species and their role in carcinogenesis remain an active area of inquiry. Our understanding would be enhanced by better accounting for tumor subtype, microbial community interactions, metabolism, and ecology. METHODS: We collected paired colon tumor and normal-adjacent tissue and mucosa samples from 83 individuals who underwent partial or total colectomies for CRC. Mismatch repair (MMR) status was determined in each tumor sample and classified as either deficient MMR (dMMR) or proficient MMR (pMMR) tumor subtypes. Samples underwent 16S rRNA gene sequencing and a subset of samples from 50 individuals were submitted for targeted metabolomic analysis to quantify amino acids and short-chain fatty acids. A PERMANOVA was used to identify the biological variables that explained variance within the microbial communities. dMMR and pMMR microbial communities were then analyzed separately using a generalized linear mixed effects model that accounted for MMR status, sample location, intra-subject variability, and read depth. Genome-scale metabolic models were then used to generate microbial interaction networks for dMMR and pMMR microbial communities. We assessed global network properties as well as the metabolic influence of each microbe within the dMMR and pMMR networks. RESULTS: We demonstrate distinct roles for microbes in dMMR and pMMR CRC. Bacteroides fragilis and sulfidogenic Fusobacterium nucleatum were significantly enriched in dMMR CRC, but not pMMR CRC. These findings were further supported by metabolic modeling and metabolomics indicating suppression of B. fragilis in pMMR CRC and increased production of amino acid proxies for hydrogen sulfide in dMMR CRC. CONCLUSIONS: Integrating tumor biology and microbial ecology highlighted distinct microbial, metabolic, and ecological properties unique to dMMR and pMMR CRC. This approach could critically improve our ability to define, predict, prevent, and treat colorectal cancers.

DNA mismatch repair protein deficient non-neoplastic colonic crypts: a novel indicator of Lynch syndrome.

Lynch syndrome is the most common form of hereditary colorectal carcinoma. However, establishing the diagnosis of Lynch syndrome is challenging, and ancillary studies that distinguish between sporadic DNA mismatch repair (MMR) protein deficiency and Lynch syndrome are needed, particularly when germline mutation studies are inconclusive. The aim of this study was to determine if MMR protein-deficient non-neoplastic intestinal crypts can help distinguish between patients with and without Lynch syndrome. We evaluated the expression of MMR proteins in non-neoplastic intestinal mucosa obtained from colorectal surgical resection specimens from patients with Lynch syndrome-associated colorectal carcinoma (n = 52) and patients with colorectal carcinoma without evidence of Lynch syndrome (n = 70), including sporadic MMR protein-deficient colorectal carcinoma (n = 30), MMR protein proficient colorectal carcinoma (n = 30), and "Lynch-like" syndrome (n = 10). MMR protein-deficient non-neoplastic colonic crypts were identified in 19 of 122 (16%) patients. MMR protein-deficient colonic crypts were identified in 18 of 52 (35%) patients with Lynch syndrome compared to only 1 of 70 (1%) patients without Lynch syndrome (p < 0.001). This one patient had "Lynch-like" syndrome and harbored two MSH2-deficient non-neoplastic colonic crypts. MMR protein-deficient non-neoplastic colonic crypts were not identified in patients with sporadic MMR protein-deficient or MMR protein proficient colorectal carcinoma. Our findings suggest that MMR protein-deficient colonic crypts are a novel indicator of Lynch syndrome, and evaluation for MMR protein-deficient crypts may be a helpful addition to Lynch syndrome diagnostics.

High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing.

Functional characterization of disease-causing variants at risk loci has been a significant challenge. Here we report a high-throughput single-nucleotide polymorphisms sequencing (SNPs-seq) technology to simultaneously screen hundreds to thousands of SNPs for their allele-dependent protein-binding differences. This technology takes advantage of higher retention rate of protein-bound DNA oligos in protein purification column to quantitatively sequence these SNP-containing oligos. We apply this technology to test prostate cancer-risk loci and observe differential allelic protein binding in a significant number of selected SNPs. We also test a unique application of self-transcribing active regulatory region sequencing (STARR-seq) in characterizing allele-dependent transcriptional regulation and provide detailed functional analysis at two risk loci (RGS17 and ASCL2). Together, we introduce a powerful high-throughput pipeline for large-scale screening of functional SNPs at disease risk loci.

Targeted sequencing of 36 known or putative colorectal cancer susceptibility genes.

BACKGROUND: Mutations in several genes predispose to colorectal cancer. Genetic testing for hereditary colorectal cancer syndromes was previously limited to single gene tests; thus, only a very limited number of genes were tested, and rarely those infrequently mutated in colorectal cancer. Next-generation sequencing technologies have made it possible to sequencing panels of genes known and suspected to influence colorectal cancer susceptibility. METHODS: Targeted sequencing of 36 known or putative CRC susceptibility genes was conducted for 1231 CRC cases from five subsets: (1) Familial Colorectal Cancer Type X (n = 153); (2) CRC unselected by tumor immunohistochemical or microsatellite stability testing (n = 548); (3) young onset (age <50 years) (n = 333); (4) proficient mismatch repair (MMR) in cases diagnosed at ≥50 years (n = 68); and (5) deficient MMR CRCs with no germline mutations in MLH1, MSH2, MSH6, or PMS2 (n = 129). Ninety-three unaffected controls were also sequenced. RESULTS: Overall, 29 nonsense, 43 frame-shift, 13 splice site, six initiator codon variants, one stop codon, 12 exonic deletions, 658 missense, and 17 indels were identified. Missense variants were reviewed by genetic counselors to determine pathogenicity; 13 were pathogenic, 61 were not pathogenic, and 584 were variants of uncertain significance. Overall, we identified 92 cases with pathogenic mutations in APC,MLH1,MSH2,MSH6, or multiple pathogenic MUTYH mutations (7.5%). Four cases with intact MMR protein expression by immunohistochemistry carried pathogenic MMR mutations. CONCLUSIONS: Results across case subsets may help prioritize genes for inclusion in clinical gene panel tests and underscore the issue of variants of uncertain significance both in well-characterized genes and those for which limited experience has accumulated.

FIRE: functional inference of genetic variants that regulate gene expression.

MOTIVATION: Interpreting genetic variation in noncoding regions of the genome is an important challenge for personal genome analysis. One mechanism by which noncoding single nucleotide variants (SNVs) influence downstream phenotypes is through the regulation of gene expression. Methods to predict whether or not individual SNVs are likely to regulate gene expression would aid interpretation of variants of unknown significance identified in whole-genome sequencing studies. RESULTS: We developed FIRE (Functional Inference of Regulators of Expression), a tool to score both noncoding and coding SNVs based on their potential to regulate the expression levels of nearby genes. FIRE consists of 23 random forests trained to recognize SNVs in cis-expression quantitative trait loci (cis-eQTLs) using a set of 92 genomic annotations as predictive features. FIRE scores discriminate cis-eQTL SNVs from non-eQTL SNVs in the training set with a cross-validated area under the receiver operating characteristic curve (AUC) of 0.807, and discriminate cis-eQTL SNVs shared across six populations of different ancestry from non-eQTL SNVs with an AUC of 0.939. FIRE scores are also predictive of cis-eQTL SNVs across a variety of tissue types. AVAILABILITY AND IMPLEMENTATION: FIRE scores for genome-wide SNVs in hg19/GRCh37 are available for download at https://sites.google.com/site/fireregulatoryvariation/. CONTACT: nilah@stanford.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mapping Complex Traits in a Diversity Outbred F1 Mouse Population Identifies Germline Modifiers of Metastasis in Human Prostate Cancer.

It is unclear how standing genetic variation affects the prognosis of prostate cancer patients. To provide one controlled answer to this problem, we crossed a dominant, penetrant mouse model of prostate cancer to Diversity Outbred mice, a collection of animals that carries over 40 million SNPs. Integration of disease phenotype and SNP variation data in 493 F1 males identified a metastasis modifier locus on Chromosome 8 (LOD = 8.42); further analysis identified the genes Rwdd4, Cenpu, and Casp3 as functional effectors of this locus. Accordingly, analysis of over 5,300 prostate cancer patient samples revealed correlations between the presence of genetic variants at these loci, their expression levels, cancer aggressiveness, and patient survival. We also observed that ectopic overexpression of RWDD4 and CENPU increased the aggressiveness of two human prostate cancer cell lines. In aggregate, our approach demonstrates how well-characterized genetic variation in mice can be harnessed in conjunction with systems genetics approaches to identify and characterize germline modifiers of human disease processes.

Tumor Budding in Colorectal Carcinoma: Confirmation of Prognostic Significance and Histologic Cutoff in a Population-based Cohort.

Tumor budding in colorectal carcinoma has been associated with poor outcome in multiple studies, but the absence of an established histologic cutoff for "high" tumor budding, heterogeneity in study populations, and varying methods for assessing tumor budding have hindered widespread incorporation of this parameter in clinical reports. We used an established scoring system in a population-based cohort to determine a histologic cutoff for "high" tumor budding and confirm its prognostic significance. We retrieved hematoxylin and eosin-stained sections from 553 incident colorectal carcinoma cases. Each case was previously characterized for select molecular alterations and survival data. Interobserver agreement was assessed between 2 gastrointestinal pathologists and a group of 4 general surgical pathologists. High budding (≥ 10 tumor buds in a ×20 objective field) was present in 32% of cases, low budding in 46%, and no budding in 22%. High tumor budding was associated with advanced pathologic stage (P < 0.001), microsatellite stability (P = 0.005), KRAS mutation (P = 0.010), and on multivariate analysis with a > 2 times risk of cancer-specific death (hazard ratio = 2.57 [1.27, 5.19]). After multivariate adjustment, by penalized smoothing splines, we found increasing tumor bud counts from 5 upward to be associated with an increasingly shortened cancer-specific survival. By this method, a tumor bud count of 10 corresponded to approximately 2.5 times risk of cancer-specific death. The interobserver agreement was good with weighted κ of 0.70 for 2 gastrointestinal pathologists over 121 random cases and 0.72 between all 6 pathologists for 20 random cases. Using an established method to assess budding on routine histologic stains, we have shown that a cutoff of 10 for high tumor budding is independently associated with a significantly worse prognosis. The reproducibility data provide support for the routine widespread implementation of tumor budding in clinical reports.

A large multiethnic genome-wide association study of prostate cancer identifies novel risk variants and substantial ethnic differences.

UNLABELLED: A genome-wide association study (GWAS) of prostate cancer in Kaiser Permanente health plan members (7,783 cases, 38,595 controls; 80.3% non-Hispanic white, 4.9% African-American, 7.0% East Asian, and 7.8% Latino) revealed a new independent risk indel rs4646284 at the previously identified locus 6q25.3 that replicated in PEGASUS (N = 7,539) and the Multiethnic Cohort (N = 4,679) with an overall P = 1.0 × 10(-19) (OR, 1.18). Across the 6q25.3 locus, rs4646284 exhibited the strongest association with expression of SLC22A1 (P = 1.3 × 10(-23)) and SLC22A3 (P = 3.2 × 10(-52)). At the known 19q13.33 locus, rs2659124 (P = 1.3 × 10(-13); OR, 1.18) nominally replicated in PEGASUS. A risk score of 105 known risk SNPs was strongly associated with prostate cancer (P < 1.0 × 10(-8)). Comparing the highest to lowest risk score deciles, the OR was 6.22 for non-Hispanic whites, 5.82 for Latinos, 3.77 for African-Americans, and 3.38 for East Asians. In non-Hispanic whites, the 105 risk SNPs explained approximately 7.6% of disease heritability. The entire GWAS array explained approximately 33.4% of heritability, with a 4.3-fold enrichment within DNaseI hypersensitivity sites (P = 0.004). SIGNIFICANCE: Taken together, our findings of independent risk variants, ethnic variation in existing SNP replication, and remaining unexplained heritability have important implications for further clarifying the genetic risk of prostate cancer. Our findings also suggest that there may be much promise in evaluating understudied variation, such as indels and ethnically diverse populations.

Comprehensively evaluating cis-regulatory variation in the human prostate transcriptome by using gene-level allele-specific expression.

The identification of cis-acting regulatory variation in primary tissues has the potential to elucidate the genetic basis of complex traits and further our understanding of transcriptomic diversity across cell types. Expression quantitative trait locus (eQTL) association analysis using RNA sequencing (RNA-seq) data can improve upon the detection of cis-acting regulatory variation by leveraging allele-specific expression (ASE) patterns in association analysis. Here, we present a comprehensive evaluation of cis-acting eQTLs by analyzing RNA-seq gene-expression data and genome-wide high-density genotypes from 471 samples of normal primary prostate tissue. Using statistical models that integrate ASE information, we identified extensive cis-eQTLs across the prostate transcriptome and found that approximately 70% of expressed genes corresponded to a significant eQTL at a gene-level false-discovery rate of 0.05. Overall, cis-eQTLs were heavily concentrated near the transcription start and stop sites of affected genes, and effects were negatively correlated with distance. We identified multiple instances of cis-acting co-regulation by using phased genotype data and discovered 233 SNPs as the most strongly associated eQTLs for more than one gene. We also noted significant enrichment (25/50, p = 2E-5) of previously reported prostate cancer risk SNPs in prostate eQTLs. Our results illustrate the benefit of assessing ASE data in cis-eQTL analyses by showing better reproducibility of prior eQTL findings than of eQTL mapping based on total expression alone. Altogether, our analysis provides extensive functional context of thousands of SNPs in prostate tissue, and these results will be of critical value in guiding studies examining disease of the human prostate.