Guidelines for initiating colorectal cancer (CRC) screening are based on family history but do not consider lifestyle, environmental, or genetic risk factors. We developed models to determine risk of ...CRC, based on lifestyle and environmental factors and genetic variants, and to identify an optimal age to begin screening.
We collected data from 9748 CRC cases and 10,590 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colorectal Transdisciplinary study, from 1992 through 2005. Half of the participants were used to develop the risk determination model and the other half were used to evaluate the discriminatory accuracy (validation set). Models of CRC risk were created based on family history, 19 lifestyle and environmental factors (E-score), and 63 CRC-associated single-nucleotide polymorphisms identified in genome-wide association studies (G-score). We evaluated the discriminatory accuracy of the models by calculating area under the receiver operating characteristic curve values, adjusting for study, age, and endoscopy history for the validation set. We used the models to project the 10-year absolute risk of CRC for a given risk profile and recommend ages to begin screening in comparison to CRC risk for an average individual at 50 years of age, using external population incidence rates for non-Hispanic whites from the Surveillance, Epidemiology, and End Results program registry.
In our models, E-score and G-score each determined risk of CRC with greater accuracy than family history. A model that combined both scores and family history estimated CRC risk with an area under the receiver operating characteristic curve value of 0.63 (95% confidence interval, 0.62–0.64) for men and 0.62 (95% confidence interval, 0.61–0.63) for women; area under the receiver operating characteristic curve values based on only family history ranged from 0.53 to 0.54 and those based only E-score or G-score ranged from 0.59 to 0.60. Although screening is recommended to begin at age 50 years for individuals with no family history of CRC, starting ages calculated based on combined E-score and G-score differed by 12 years for men and 14 for women, for individuals with the highest vs the lowest 10% of risk.
We used data from 2 large international consortia to develop CRC risk calculation models that included genetic and environmental factors along with family history. These determine risk of CRC and starting ages for screening with greater accuracy than the family history only model, which is based on the current screening guideline. These scoring systems might serve as a first step toward developing individualized CRC prevention strategies.
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MicroRNAs (miRNAs) have been implicated in colorectal cancer (CRC) development and associated with prognostic indicators such as disease stage and survival. Prognostic associations are often based on ...few individuals and imprecise. In this study, we utilize population‐based data from 1,141 CRC cases to replicate previously reported associations between 121 miRNAs and disease stage and survival. The Agilent Human miRNA Microarray V19.0 was used to generate miRNA data following a stringent quality control protocol. Assessment of survival was done using Cox Proportional Hazard models adjusting for age, disease stage and tumor molecular phenotype. Five miRNAs were associated with more advanced disease stage; hsa‐miR‐145‐5p and hsa‐miR‐31‐5p showed increased expression with more advanced tumor stage, while hsa‐miR‐200b‐3p, hsa‐miR‐215 and hsa‐miR‐451a had decreased expression with more advanced tumors. Thirteen miRNAs were associated with CRC mortality among individuals diagnosed with colon cancer while 14 were associated with CRC mortality after a diagnosis with rectal cancer. Strongest associations were observed for those miRNAs that were expressed in a small subset of tumors. Most notable associations were for hsa‐miR‐145‐3p hazard ratio (HR) 2.94, 95% confidence interval (CI) 1.54, 5.61, and hsa‐miR‐9‐3p (HR 10.28, 95% CI 1.31, 80.84) with colon cancer and hsa‐miR‐335‐5p (HR 0.17, 95% CI 0.05, 0.54) for rectal cancer. hsa‐miR‐374a‐5p, hsa‐miR‐570‐3p and hsa‐miR‐18a‐5p significantly reduced the hazard of dying for all cases, regardless of tumor site. Our findings illustrate the need for a large sample to evaluate the association of miRNAs with survival and disease stage in order to determine associations by tumor site.
What's new?
MicroRNAs (miRNAs) are promising prognostic biomarkers in colorectal cancer, but more work is needed to identify clinically meaningful stage‐ and survival‐specific associations. The present study attempted to identify those associations for 121 miRNAs using population‐based data for more than 1,140 colorectal cancer patients. Microarray and statistical analyses uncovered five miRNAs associated specifically with more advanced colorectal cancer. Another 25 miRNAs were linked to mortality for either colon cancer or rectal cancer. The large number of patients and the incorporation of data on tumor molecular phenotype facilitated the detection of associations for miRNAs infrequently expressed in the study population.
Background & Aims:
The concept of a CpG island methylator phenotype (CIMP), especially in microsatellite stable colon cancer, is not accepted universally. We therefore evaluated a large ...population-based sample of individuals with colon cancer and used univariate and multivariate analyses of CIMP with clinicopathologic variables and tumor mutations to determine the biologic relevance of this phenotype.
Methods:
A total of 864 tumors from individuals with colon cancer from Utah and Northern California were evaluated by methylation-specific polymerase chain reaction of CpG islands in
hMLH1, methylated in tumors (MINT) 1, MINT 2, MINT 31, and
CDKN2A (p16). CIMP high was defined as methylation at 2 or more of these loci. The
BRAF V600E mutation was determined by sequencing. Microsatellite instability had been determined previously.
Results:
In a multivariate analysis of microsatellite stable tumors, CIMP high was related significantly to the V600E
BRAF mutation (odds ratio, 39.52; 95% confidence interval, 11.44–136.56),
KRAS2 mutations (odds ratio, 2.22; 95% confidence interval, 1.48–3.34), older age (
P trend = .03), and increased stage (
P trend = .03), and these tumors were less likely to be located in the distal colon (odds ratio, .42; 95% confidence interval, .27–.65). CIMP-high unstable tumors also were more likely to have the V600E
BRAF mutation, be located proximally, and occur in older individuals (in univariate analyses). However, CIMP-high unstable tumors were significantly more likely than their stable counterparts to be
KRAS2 wild type,
TP53 wild type, poorly differentiated, proximally located, occur at lower stages, and have the
BRAF V600E mutation (64.1% vs 17.6%).
Conclusions:
The evaluation of a large, population-based sample strongly supports the biologic relevance of CIMP in colon cancer. However, the presence or absence of microsatellite instability has a major effect on the expression of this phenotype.
We examined expression of genes in the p53-signaling pathway. We determine if genes that have significantly different expression in carcinoma tissue compared to normal mucosa also have significantly ...differentially expressed miRNAs. We utilize a sample of 217 CRC cases.
We focused on fold change (FC) > 1.50 or <0.67 for genes and miRNAs, that were statistically significant after adjustment for multiple comparisons. We evaluated the linear association between the differential expression of miRNA and mRNA. miRNA:mRNA seed-region matches also were determined.
Eleven dysregulated genes were associated with 37 dysregulated miRNAs; all were down-stream from the TP53 gene. MiR-150-5p (HR = 0.82) and miR-196b-5p (HR 0.73) significantly reduced the likelihood of dying from CRC when miRNA expression increased in rectal tumors.
Our data suggest that activation of p53 from cellular stress, could target downstream genes that in turn could influence cell cycle arrest, apoptosis, and angiogenesis through mRNA:miRNA interactions.
Tumor suppressor genes (TSGs) and oncogenes (OG) are involved in carcinogenesis. MiRNAs also contribute to cellular pathways leading to cancer. We use data from 217 colorectal cancer (CRC) cases to ...evaluate differences in TSGs and OGs expression between paired CRC and normal mucosa and evaluate how TSGs and OGs are associated with miRNAs. Gene expression data from RNA‐Seq and miRNA expression data from Agilent Human miRNA Microarray V19.0 were used. We focus on genes most strongly associated with CRC (fold change (FC) of ≥1.5 or ≤0.67) that were statistically significant after adjustment for multiple comparisons. Of the 74 TSGs evaluated, 22 were associated with carcinoma/normal mucosa differential expression. Ten TSGs were up‐regulated (FAM123B, RB1, TP53, RUNX1, MSH2, BRCA1, BRCA2, SOX9, NPM1, and RNF43); six TSGs were down‐regulated (PAX5, IZKF1, GATA3, PRDM1, TET2, and CYLD); four were associated with MSI tumors (MLH1, PTCH1, and CEBPA down‐regulated and MSH6 up‐regulated); and two were associated with MSS tumors (PHF6 and ASXL1 up‐regulated). Thirteen of these TSGs were associated with 44 miRNAs. Twenty‐seven of the 59 OGs evaluated were dysregulated: 14 down‐regulated (KLF4, BCL2, SSETBP1, FGFR2, TSHR, MPL, KIT, PDGFRA, GNA11, GATA2, FGFR3, AR, CSF1R, and JAK3), seven up‐regulated (DNMT1, EZH2, PTPN11, SKP2, CCND1, MET, and MYC); three down‐regulated for MSI (FLT3, CARD11, and ALK); two up‐regulated for MSI (IDH2 and HRAS); and one up‐regulated with MSS tumors (CTNNB1). These findings suggest possible co‐regulatory function between TSGs, OGs, and miRNAs, involving both direct and indirect associations that operate through feedback and feedforward loops.
Apoptosis is genetically regulated and involves intrinsic and extrinsic pathways. We examined 133 genes within these pathways to identify whether they are expressed differently in colorectal ...carcinoma (CRC) and normal tissue (N = 217) and if they are associated with similar differential miRNA expression. Gene expression data (RNA-Seq) and miRNA expression data (Agilent Human miRNA Microarray V19.0) were generated. We focused on dysregulated genes with a fold change (FC) of > 1.50 or < 0.67, that were significant after adjustment for multiple comparisons. miRNA:mRNA seed-region matches were determined. Twenty-three genes were significantly downregulated (FC < 0.67) and 18 were significantly upregulated (FC > 1.50). Of these 41 genes, 11 were significantly associated with miRNA differential expression.
BIRC5
had the greatest number of miRNA associations (14) and the most miRNAs with a seed-region match (10). Four of these matches, miR-145-5p, miR-150-5p, miR-195-5p, and miR-650, had a negative beta coefficient.
CSF2RB
was associated with ten total miRNAs (five with a seed-region match, and one miRNA, miR-92a-3p, with a negative beta coefficient). Of the three miRNAs associated with
CTSS
, miR-20b-5p, and miR-501-3p, had a seed-region match and a negative beta coefficient between miRNA:mRNA pairs. Several miRNAs that were associated with dysregulated gene expression, seed-region matches, and negative beta coefficients also were associated with CRC-specific survival. Our data suggest that miRNAs could influence several apoptosis-related genes.
BIRC5, CTSS
, and
CSF2R
all had seed-region matches with miRNAs that would favor apoptosis. Our study identifies several miRNA associated with apoptosis-related genes, that if validated, could be important therapeutic targets.
Given the high incidence of colorectal cancer (CRC), and the availability of procedures that can detect disease and remove precancerous lesions, there is a need for a model that estimates the ...probability of developing CRC across various age intervals and risk factor profiles.
The development of separate CRC absolute risk models for men and women included estimating relative risks and attributable risk parameters from population-based case-control data separately for proximal, distal, and rectal cancer and combining these estimates with baseline age-specific cancer hazard rates based on Surveillance, Epidemiology, and End Results (SEER) incidence rates and competing mortality risks.
For men, the model included a cancer-negative sigmoidoscopy/colonoscopy in the last 10 years, polyp history in the last 10 years, history of CRC in first-degree relatives, aspirin and nonsteroidal anti-inflammatory drug (NSAID) use, cigarette smoking, body mass index (BMI), current leisure-time vigorous activity, and vegetable consumption. For women, the model included sigmoidoscopy/colonoscopy, polyp history, history of CRC in first-degree relatives, aspirin and NSAID use, BMI, leisure-time vigorous activity, vegetable consumption, hormone-replacement therapy (HRT), and estrogen exposure on the basis of menopausal status. For men and women, relative risks differed slightly by tumor site. A validation study in independent data indicates that the models for men and women are well calibrated.
We developed absolute risk prediction models for CRC from population-based data, and a simple questionnaire suitable for self-administration. This model is potentially useful for counseling, for designing research intervention studies, and for other applications.
A sizable fraction of colorectal cancer (CRC) is expected to be explained by heritable factors, with heritability estimates ranging from 12 to 35% twin and family studies. Genome-wide association ...studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) associated with CRC risk. Although it has been shown that these CRC susceptibility SNPs only explain a small proportion of the genetic risk, it is not clear how much of the heritability these SNPs explain and how much is left to be detected by other, yet to be identified, common SNPs. Therefore, we estimated the heritability of CRC under different scenarios using Genome-Wide Complex Trait Analysis in the Genetics and Epidemiology of Colorectal Cancer Consortium including 8025 cases and 10 814 controls. We estimated that the heritability explained by known common CRC SNPs identified in GWAS was 0.65% (95% CI:0.3-1%; P = 1.11 × 10-16), whereas the heritability explained by all common SNPs was at least 7.42% (95% CI: 4.71-10.12%; P = 8.13 × 10(-8)), suggesting that many common variants associated with CRC risk remain to be detected. Comparing the heritability explained by the common variants with that from twin and family studies, a fraction of the heritability may be explained by other genetic variants, such as rare variants. In addition, our analysis showed that the gene × smoking interaction explained a significant proportion of the CRC variance (P = 1.26 × 10(-2)). In summary, our results suggest that known CRC SNPs only explain a small proportion of the heritability and more common SNPs have yet to be identified.
Dietary patterns have been used to summarize diet consumption and to evaluate how diet is associated with diseases in epidemiological research. However, there are many issues surrounding both the use ...and interpretation of dietary patterns. These issues include how to collect, summarize, and create dietary patterns, as well as how to interpret the results. Because labels are given arbitrarily to dietary patterns to help characterize the pattern in a meaningful way, it is often not clear from the literature as to the consistency of results among studies. Additionally, the utilization of dietary patterns as a tool for public health messages is a topic that is unresolved. These issues are discussed in this paper.
Identification of causal microRNAs (miRNAs) in colorectal cancer (CRC) is elusive, due to our lack of understanding of how specific miRNAs affect biological pathways and outcomes. An miRNA can ...regulate many mRNAs and an mRNA can be associated with many miRNAs; appreciation of these complex networks in which miRNAs operate is necessary to transition from identifying dysregulated miRNAs to identifying individual miRNAs or groups of miRNAs that are suitable for therapeutic purposes. The aim of the paper is to compile results from a population-based study (
= 1,954 cases with matched carcinoma/normal tissue) of miRNAs in CRC. The information gained allows for cohesive and comprehensive insight into miRNAs and CRC in terms of function and impact. Comparison of miRNA expression with mRNA expression from nine signaling pathways in carcinogenic processes allowed us to identify miRNA targets within a biological context. MiRNAs that directly influence mRNA expression may be effective biomarkers or therapeutic targets.
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