Risk Model for Colorectal Cancer in Spanish Population Using Environmental and Genetic Factors: Results from the MCC-Spain study

Predictive Score for Advanced Colorectal Neoplasia Based on Cardiovascular and Colorectal Cancer Risk Factors

Background and Aims: Cardiovascular disease and colorectal cancer (CRC) are significant health problems and share some risk factors. The aim of our study was to develop and validate a predictive score for advanced colorectal neoplasia (CRN) based on risk factors for cardiovascular disease and CRC. Materials and Methods: A cross-sectional study comprising a derivation cohort and an external validation cohort of 1049 and 308 patients, respectively. A prediction score for advanced CRN (CRNAS: Colorectal Neoplasia Advanced Score) was developed from a logistic regression model, comprising sex, age, first-degree family history for CRC, systolic and diastolic blood pressure, total cholesterol, HDL cholesterol, body mass index, diabetes, smoking, and antihypertensive treatment. Other cardiovascular risk scores (Framingham-Wilson, REGICOR, SCORE, and FRESCO) were also used to predict the risk of advanced CRN. The discriminatory capacity of each score was evaluated using the area under the curve (AUC). Results: CRN were found in 379 subjects from the derivation cohort (36%), including 228 patients (22%) with an advanced CRN. Male sex, age, diabetes, and smoking were identified as independent risk factors for advanced CRN. The newly created score (CRNAS) showed an AUC of 0.68 (95% CI: 0.64-0.73) for advanced CRN, which was better than cardiovascular risk scores (p < 0.001). In the validation cohort, the AUC of CRNAS for advanced CRN was 0.67 (95% CI: 0.57-0.76). Conclusions: The newly validated CRNAS has a better discriminatory capacity to predict advanced CRN than cardiovascular scores. It may be useful for selecting candidates for screening colonoscopy, especially in those with cardiovascular risk factors.

High polygenic risk score is a risk factor associated with colorectal cancer based on data from the UK Biobank

Colorectal cancer (CRC) is a common cancer among both men and women and is one of the leading causes of cancer death worldwide. It is important to identify risk factors that may be used to help reduce morbidity and mortality of the disease. We used a case-control study design to explore the association between CRC, polygenic risk scores (PRS), and other factors. We extracted data about 2,585 CRC cases and 9,362 controls from the UK Biobank, calculated the PRS for these cases and controls based on 140 single nucleotide polymorphisms, and performed logistic regression analyses for the 11,947 cases and controls, for an older group (ages 50+), and for a younger group (younger than 50). Five significant risk factors were identified when all 11,947 cases and controls were considered. These factors were, in descending order of the values of the adjusted odds ratios (aOR), high PRS (aOR: 2.70, CI: 2.27-3.19), male sex (aOR: 1.52, CI: 1.39-1.66), unemployment (aOR: 1.47, CI: 1.17-1.85), family history of CRC (aOR: 1.44, CI: 1.28-1.62), and age (aOR: 1.01, CI: 1.01-1.02). These five risk factors also remained significant in the older group. For the younger group, only high PRS (aOR: 2.87, CI: 1.65-5.00) and family history of CRC (aOR: 1.73, CI: 1.12-2.67) were significant risk factors. These findings indicate that genetic risk for the disease is a significant risk factor for CRC even after adjusting for family history. Additional studies are needed to examine this association using larger samples and different population groups.

Epidemiological Situation of High-Prevalence Non-Communicable Diseases in Spain: A Systematic Review

High-prevalence non-communicable diseases (HNCDs) are an ongoing global public health problem, posing a risk to the continuity of the 2030 Agenda for Sustainable Development. The aim of this study is to describe the current situation in Spain regarding certain HNCDs, namely, ischaemic heart disease, type 2 diabetes mellitus and colorectal cancer, including their prevalence and incidence in recent years. A systematic review was conducted between October 2022 and February 2023 using the MEDLINE, ProQuest and Scopus databases. After an exhaustive search, a total of thirty-four articles were included, comprising fourteen articles on colorectal cancer, seven on ischaemic heart disease and thirteen on diabetes mellitus type 2. The main topics included risk factors, lifestyles, mortality and incidence, the importance of screening and patient empowerment. On analysing each disease, it can be gleaned that risk factors and lifestyle impact the incidence, prevalence and mortality of the diseases studied. In addition, responsible human behaviour, associated with lifestyle factors, is related to the occurrence of these three diseases.

Validation of a Genetic-Enhanced Risk Prediction Model for Colorectal Cancer in a Large Community-Based Cohort

BACKGROUND

Polygenic risk scores (PRS) which summarize individuals' genetic risk profile may enhance targeted colorectal cancer screening. A critical step towards clinical implementation is rigorous external validations in large community-based cohorts. This study externally validated a PRS-enhanced colorectal cancer risk model comprising 140 known colorectal cancer loci to provide a comprehensive assessment on prediction performance.

METHODS

The model was developed using 20,338 individuals and externally validated in a community-based cohort (n = 85,221). We validated predicted 5-year absolute colorectal cancer risk, including calibration using expected-to-observed case ratios (E/O) and calibration plots, and discriminatory accuracy using time-dependent AUC. The PRS-related improvement in AUC, sensitivity and specificity were assessed in individuals of age 45 to 74 years (screening-eligible age group) and 40 to 49 years with no endoscopy history (younger-age group).

RESULTS

In European-ancestral individuals, the predicted 5-year risk calibrated well [E/O = 1.01; 95% confidence interval (CI), 0.91-1.13] and had high discriminatory accuracy (AUC = 0.73; 95% CI, 0.71-0.76). Adding the PRS to a model with age, sex, family and endoscopy history improved the 5-year AUC by 0.06 (P < 0.001) and 0.14 (P = 0.05) in the screening-eligible age and younger-age groups, respectively. Using a risk-threshold of 5-year SEER colorectal cancer incidence rate at age 50 years, adding the PRS had a similar sensitivity but improved the specificity by 11% (P < 0.001) in the screening-eligible age group. In the younger-age group it improved the sensitivity by 27% (P = 0.04) with similar specificity.

CONCLUSIONS

The proposed PRS-enhanced model provides a well-calibrated 5-year colorectal cancer risk prediction and improves discriminatory accuracy in the external cohort.

IMPACT

The proposed model has potential utility in risk-stratified colorectal cancer prevention.

The current state of genetic risk models for the development of kidney cancer: a review and validation

OBJECTIVE

To review the current state of genetic risk models for predicting the development of kidney cancer, by identifying and comparing the performance of published models.

METHODS

Risk models were identified from a recent systematic review and the Cancer-PRS web directory. A narrative synthesis of the models, previous validation studies and related genome-wide association studies (GWAS) was carried out. The discrimination and calibration of the identified models was then assessed and compared in the UK Biobank (UKB) cohort (cases, 452; controls, 487 925).

RESULTS

A total of 39 genetic models predicting the development of kidney cancer were identified and 31 were validated in the UKB. Several of the genetic-only models (seven of 25) and most of the mixed genetic-phenotypic models (five of six) had some discriminatory ability (area under the receiver operating characteristic curve >0.5) in this cohort. In general, models containing a larger number of genetic variants identified in GWAS performed better than models containing a small number of variants associated with known causal pathways. However, the performance of the included models was consistently poorer than genetic risk models for other cancers.

CONCLUSIONS

Although there is potential for genetic models to identify those at highest risk of developing kidney cancer, their performance is poorer than the best genetic risk models for other cancers. This may be due to the comparatively small number of genetic variants associated with kidney cancer identified in GWAS to date. The development of improved genetic risk models for kidney cancer is dependent on the identification of more variants associated with this disease. Whether these will have utility within future kidney cancer screening pathways is yet to determined.

Performance of the Use of Genetic Information to Assess the Risk of Colorectal Cancer in the Basque Population

Although the genetic contribution to colorectal cancer (CRC) has been studied in various populations, studies on the applicability of available genetic information in the Basque population are scarce. In total, 835 CRC cases and 940 controls from the Basque population were genotyped and genome-wide association studies were carried out. Mendelian Randomization analyses were used to discover the effect of modifiable risk factors and microbiota on CRC. In total, 25 polygenic risk score models were evaluated to assess their performance in CRC risk calculation. Moreover, 492 inflammatory bowel disease cases were used to assess whether that genetic information would not confuse both conditions. Five suggestive (p < 5 × 10−6) loci were associated with CRC risk, where genes previously associated with CRC were located (e.g., ABCA12, ATIC or ERBB4). Moreover, the analyses of CRC locations detected additional genes consistent with the biology of CRC. The possible contribution of cholesterol, BMI, Firmicutes and Cyanobacteria to CRC risk was detected by Mendelian Randomization. Finally, although polygenic risk score models showed variable performance, the best model performed correctly regardless of the location and did not misclassify inflammatory bowel disease cases. Our results are consistent with CRC biology and genetic risk models and could be applied to assess CRC risk in the Basque population.

Assessment of a Serum Microrna Risk Score for Colorectal Cancer among Participants of Screening Colonoscopy at Various Stages of Colorectal Carcinogenesis

We recently derived and validated a serum-based microRNA risk score (miR-score) which predicted colorectal cancer (CRC) occurrence with very high accuracy within 14 years of follow-up in a large population-based cohort. Here, we aimed to assess and compare the distribution of the miR-score among participants of screening colonoscopy at various stages of colorectal carcinogenesis. MicroRNAs (miRNAs) were profiled by quantitative-real-time-polymerase-chain-reaction in the serum samples of screening colonoscopy participants with CRC (n = 52), advanced colorectal adenoma (AA, n = 100), non-advanced colorectal adenoma (NAA, n = 88), and participants free of colorectal neoplasms (n = 173). The mean values of the miR-score were compared between groups by the Mann–Whitney U test. The associations of the miR-score with risk for colorectal neoplasms were evaluated using logistic regression analyses. MicroRNA risk scores were significantly higher among participants with AA than among those with NAA (p = 0.027) and those with CRC (p = 0.014), whereas no statistically significant difference was seen between those with NAA and those with no colorectal neoplasms (p = 0.127). When comparing adjacent groups, miR-scores were inversely associated with CRC versus AA and positively associated with AA versus NAA [odds ratio (OR), 0.37 (95% confidence interval (CI), 0.16–0.86) and OR, 2.22 (95% CI, 1.06–4.64) for the top versus bottom tertiles, respectively]. Our results are consistent with the hypothesis that a high miR-score may be indicative of an increased CRC risk by an increased tendency of progression from non-advanced to advanced colorectal neoplasms, along with a change of the miR-patterns after CRC manifestation.

Predictive Value of Genetic Risk Scores in the Development of Colorectal Adenomas

INTRODUCTION

Unlike colorectal cancer (CRC), few studies have explored the predictive value of genetic risk scores (GRS) in the development of colorectal adenomas (CRA), either alone or in combination with other demographic and clinical factors.

METHODS

In this study, genomic DNA from 613 Spanish Caucasian patients with CRA and 829 polyp-free individuals was genotyped for 88 single-nucleotide polymorphisms (SNPs) associated with CRC risk using the MassArray™ (Sequenom) platform. After applying a multivariate logistic regression model, five SNPs were selected to calculate the GRS. Regression models adjusted by sex, age, family history of CRC, chronic use of NSAIDs, low-dose ASA, and consumption of tobacco were built in order to study the association between GRS and CRA risk. We evaluated the discriminatory capacity using the area under the receiver operating characteristic curve (AUC). The interactions between demographic information and GRS were also analyzed.

RESULTS

Significant associations between high GRS values and risk of CRA for analyzed models were observed. In particular, patients with higher GRS values had 2.3-2.6-fold increase in risk of CRA compared to patients with middle values. Combining sex and age with the GRS significantly increased the discriminatory accuracy of the univariate model with GRS alone. The best model achieved an AUC value of 0.665 (95% CI: 0.63-0.69). The GRS showed a different behavior depending on sex and age.

CONCLUSION

Our findings showed that, besides sex and age, GRS is an important risk factor for development of CRA and may be useful for CRC risk stratification and adaptation of 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.

Caracterización del cáncer colorrectal en pacientes atendidos en un centro médico del caribe colombiano

Introducción. A nivel mundial el cáncer colorrectal es la tercera causa de malignidad y la segunda causa de mortalidad por cáncer. En Colombia, tiene una prevalencia de 8,3 % dentro de las patologías neoplásicas, ubicándolo en el tercer lugar, después del cáncer de próstata y de mama, lo que lo cataloga como un problema de salud pública, por lo que es de gran importancia mantener datos actualizados acerca de su perfil epidemiológico. Métodos. Se realizó un estudio transversal en pacientes con cáncer colorrectal atendidos en el Hospital Universitario del Caribe, Cartagena, Colombia, durante el periodo 2015-2019. Se analizaron las variables sociodemográficas, clínicas, patológicas e histológicas. Resultados. Se encontraron un total de 268 pacientes atendidos por cáncer colorrectal, con predominio femenino en el (54,5 %) de los casos, y edad promedio de 62 años; con comorbilidades en 48,8 % y sintomatología de dolor abdominal en 56,7 %. El adenocarcinoma se encontró en el 82,1 % de los casos y la intervención más realizada fue la hemicolectomía derecha. Conclusión. El perfil epidemiológico del cáncer colorrectal encontrado en este estudio concuerda con los hallazgos de la literatura médica mundial, comprometiendo especialmente mujeres en nuestra institución.

Interplay between Genome, Metabolome and Microbiome in Colorectal Cancer

Simple Summary

The development of colorectal cancer (CRC) is influenced by the environment, genetics and microbiota. Microbiome and metabolome analyses allowed for the finding of factors and markers associated with adenoma and CRC risk, but the interaction of host genomics with those omic layers remains unclear. Thus, our aim is to add host genome information to find new factors and markers associated with adenoma and CRC risk or to propose biological mechanisms involved in the risk. We found interactions between different omic layers that could be biologically relevant, and the three layers gave complementary information to predict adenoma and CRC risk. Our findings will help to find new markers for adenoma and CRC risk and to analyze biological mechanisms involved in adenoma and CRC development.

Abstract

Background: Colorectal cancer (CRC), a major health concern, is developed depending on environmental, genetic and microbial factors. The microbiome and metabolome have been analyzed to study their role in CRC. However, the interplay of host genetics with those layers in CRC remains unclear. Methods: 120 individuals were sequenced and association analyses were carried out for adenoma and CRC risk, and for selected components of the microbiome and metabolome. The epistasis between genes located in cholesterol pathways was analyzed; modifiable risk factors were studied using Mendelian randomization; and the three omic layers were used to integrate their data and to build risk prediction models. Results: We detected genetic variants that were associated to components of metabolome or microbiome and adenoma or CRC risk (e.g., in LINC01605, PROKR2 and CCSER1 genes). In addition, we found interactions between genes of cholesterol metabolism, and HDL cholesterol levels affected adenoma (p = 0.0448) and CRC (p = 0.0148) risk. The combination of the three omic layers to build risk prediction models reached high AUC values (>0.91). Conclusions: The use of the three omic layers allowed for the finding of biological mechanisms related to the development of adenoma and CRC, and each layer provided complementary information to build risk prediction models.

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 (OR_D10vsD1 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.

Evaluation of Feature Selection Techniques for Breast Cancer Risk Prediction

This study evaluates several feature ranking techniques together with some classifiers based on machine learning to identify relevant factors regarding the probability of contracting breast cancer and improve the performance of risk prediction models for breast cancer in a healthy population. The dataset with 919 cases and 946 controls comes from the MCC-Spain study and includes only environmental and genetic features. Breast cancer is a major public health problem. Our aim is to analyze which factors in the cancer risk prediction model are the most important for breast cancer prediction. Likewise, quantifying the stability of feature selection methods becomes essential before trying to gain insight into the data. This paper assesses several feature selection algorithms in terms of performance for a set of predictive models. Furthermore, their robustness is quantified to analyze both the similarity between the feature selection rankings and their own stability. The ranking provided by the SVM-RFE approach leads to the best performance in terms of the area under the ROC curve (AUC) metric. Top-47 ranked features obtained with this approach fed to the Logistic Regression classifier achieve an AUC = 0.616. This means an improvement of 5.8% in comparison with the full feature set. Furthermore, the SVM-RFE ranking technique turned out to be highly stable (as well as Random Forest), whereas relief and the wrapper approaches are quite unstable. This study demonstrates that the stability and performance of the model should be studied together as Random Forest and SVM-RFE turned out to be the most stable algorithms, but in terms of model performance SVM-RFE outperforms Random Forest.

A microRNA panel compared to environmental and polygenic scores for colorectal cancer risk prediction

Circulating microRNAs (miRNAs) could improve colorectal cancer (CRC) risk prediction. Here, we derive a blood-based miRNA panel and evaluate its ability to predict CRC occurrence in a population-based cohort of adults aged 50-75 years. Forty-one miRNAs are preselected from independent studies and measured by quantitative-real-time-polymerase-chain-reaction in serum collected at baseline of 198 participants who develop CRC during 14 years of follow-up and 178 randomly selected controls. A 7-miRNA score is derived by logistic regression. Its predictive ability, quantified by the optimism-corrected area-under-the-receiver-operating-characteristic-curve (AUC) using .632+ bootstrap is 0.794. Predictive ability is compared to that of an environmental risk score (ERS) based on known risk factors and a polygenic risk score (PRS) based on 140 previously identified single-nucleotide-polymorphisms. In participants with all scores available, optimism-corrected-AUC is 0.802 for the 7-miRNA score, while AUC (95% CI) is 0.557 (0.498-0.616) for the ERS and 0.622 (0.564-0.681) for the PRS.

[Family history of first degree as a risk factor for colorectal cancer]

OBJECTIVE

To evaluate the association between first-degree family history and colorectal cancer (CRC).

METHOD

We analyzed data from 2857 controls and 1360 CRC cases, collected in the MCC-Spain project. The adjusted odds ratio (OR) and 95% confidence interval (95% CI) of association with the family history of CRC was estimated by non-conditional logistic regression.

RESULTS

First-degree relatives doubled the risk of CRC (OR: 2.19; 95% CI: 1.80-2.66), increasing in those with two or more (OR: 4.22; 95% CI: 2.29-7.78) and in those whose relatives were diagnosed before 50 years (OR: 3.24; 95% CI: 1.52-6.91). Regarding the association of the family history with the location, no significant differences were observed between colon and rectum, but there were in the relation of these with the age of diagnosis, having more relatives those diagnosed before 50 years (OR: 4.79; 95% CI: 2.65-8.65).

CONCLUSIONS

First-degree relatives of CRC increase the chances of developing this tumor, they also increase when the relative is diagnosed at an early age. Therefore, it must be a target population on which to carry out prevention measures.

Assessing Individual Risk for High-Risk Early Colorectal Neoplasm for Pre-Selection of Screening in Shanghai, China: A Population-Based Nested Case-Control Study

Objective

To identify people with high-risk early colorectal neoplasm is highly desirable for pre-selection in colorectal cancer (CRC) screening in low-resource countries. We aim to build and validate a risk-based model so as to improve compliance and increase the benefits of screening.

Patients and Methods

Using data from the Shanghai CRC screening cohort, we conducted a population-based nested case–control study to build a risk-based model. Cases of early colorectal neoplasm were extracted as colorectal adenomas and stage 0-I CRC. Each case was matched with five individuals without neoplasm (controls) by the screening site and year of enrollment. Cases and controls were then randomly divided into two groups, with two thirds for building the risk prediction model and the other one third for model validation. Known risk factors were included for risk prediction models using logistic regressions. The area under the receiver operating characteristic curve (AUC) and Hosmer–Lemeshow chi-square statistics were used to evaluate model discrimination and calibration. The predicted individual risk probability was calculated under the risk regression equation.

Results

The model incorporating age, sex, family history and lifestyle factors including body mass index (BMI), smoking status, alcohol, regular moderate-to-intensity physical activity showed good calibration and discrimination. When the risk cutoff threshold was defined as 17%, the sensitivity and specificity of the model were 63.99% and 53.82%, respectively. The validation data analysis also showed well discrimination.

Conclusion

A risk prediction model combining personal and lifestyle factors was developed and validated for high-risk early colorectal neoplasm among the Chinese population. This risk-based model could improve the pre-selection for screening and contribute a lot to efficient population-based screening in low-resource countries.

Individual and Joint Associations of Genetic Risk and Healthy Lifestyle Score with Colorectal Neoplasms Among Participants of Screening Colonoscopy

Genetic and lifestyle factors contribute to colorectal cancer risk. We investigated their individual and joint associations with various stages of colorectal carcinogenesis. We assessed associations of a polygenic risk score (PRS) and a healthy lifestyle score (HLS) with presence of nonadvanced adenomas and advanced neoplasms among 2,585 participants of screening colonoscopy from Germany. The PRS and HLS individually showed only weak associations with presence of nonadvanced adenomas; stronger associations were observed with advanced neoplasms (ORs, 95% CI, for highest vs. lowest risk tertile: PRS 2.27, 1.78-2.88; HLS 1.96, 1.53-2.51). The PRS was associated with higher odds of advanced neoplasms among carriers of any neoplasms (1.65, 1.23-2.22). Subjects in the highest risk tertile (vs. lowest tertile) of both scores had higher risks for nonadvanced adenomas (1.77, 1.09-2.86), for advanced neoplasms (3.95, 2.53-6.16) and, among carriers of any neoplasms, for advanced versus nonadvanced neoplasms (2.26, 1.31-3.92). Both scores were individually associated with increased risk of nonadvanced adenomas and, much more pronounced, advanced neoplasms. The similarly strong association in relative terms across all levels of genetic risk implies that a healthy lifestyle may be particularly beneficial in those at highest genetic risk, given that the same relative risk reduction in this group would imply a stronger absolute risk reduction. Genetic factors may be of particular relevance for the transition of nonadvanced to advanced adenomas. PREVENTION RELEVANCE: Genetic factors have strong impact on the risk of colorectal neoplasms, which may be reduced by healthy lifestyle. Similarly strong associations in relative terms across all levels of genetic risk imply that a healthy lifestyle may be beneficial due to higher absolute risk reduction in those at highest genetic risk.

Performance of common genetic variants in risk prediction for colorectal cancer in Chinese: A two-stage and multicenter study

The efficacy of susceptible variants derived from genome-wide association studies (GWAs) optimizing discriminatory accuracy of colorectal cancer (CRC) in Chinese remains unclear. In the present validation study, we assessed 75 recently identified variants from GWAs. A risk predictive model combining 19 variants using the least absolute shrinkage and selection operator (LASSO) statistics offered certain clinical advantages. This model demonstrated an area under the receiver operating characteristic (AUC) of 0.61 during training analysis and yielded robust AUCs from 0.59 to 0.61 during validation analysis in three independent centers. The individuals carrying the highest quartile of risk score revealed over 2-fold risks of CRC (ranging from 2.12 to 2.90) compared with those who presented the lowest quartile of risk score. This genetic model offered the possibility of partitioning risk within the average risk population, which might serve as a first step toward developing individualized CRC prevention strategies in China.

Association between physical activity and digestive-system cancer: An updated systematic review and meta-analysis

BACKGROUND

Physical activity (PA) may have an impact on digestive-system cancer (DSC) by improving insulin sensitivity and anticancer immune function and by reducing the exposure of the digestive tract to carcinogens by stimulating gastrointestinal motility, thus reducing transit time. The current study aimed to determine the effect of PA on different types of DSC via a systematic review and meta-analysis.

METHODS

In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched for relevant studies in PubMed, Embase, Web of Science, Cochrane Library, and China National Knowledge Infrastructure. Using a random effects model, the relationship between PA and different types of DSC was analyzed.

RESULTS

The data used for meta-analysis were derived from 161 risk estimates in 47 studies involving 5,797,768 participants and 55,162 cases. We assessed the pooled associations between high vs. low PA levels and the risk of DSC (risk ratio (RR)  = 0.82, 95% confidence interval (95%CI): 0.79-0.85), colon cancer (RR = 0.81, 95%CI: 0.76-0.87), rectal cancer (RR = 0.88, 95%CI: 0.80-0.98), colorectal cancer (RR = 0.77, 95%CI: 0.69-0.85), gallbladder cancer (RR = 0.79, 95%CI: 0.64-0.98), gastric cancer (RR = 0.83, 95%CI: 0.76-0.91), liver cancer (RR = 0.73, 0.60-0.89), oropharyngeal cancer (RR = 0.79, 95%CI: 0.72-0.87), and pancreatic cancer (RR = 0.85, 95%CI: 0.78-0.93). The findings were comparable between case-control studies (RR = 0.73, 95%CI: 0.68-0.78) and prospective cohort studies (RR = 0.88, 95%CI: 0.80-0.91). The meta-analysis of 9 studies reporting low, moderate, and high PA levels, with 17 risk estimates, showed that compared to low PA, moderate PA may also reduce the risk of DSC (RR = 0.89, 95%CI: 0.80-1.00), while compared to moderate PA, high PA seemed to slightly increase the risk of DSC, although the results were not statistically significant (RR = 1.11, 95%CI: 0.94-1.32). In addition, limited evidence from 5 studies suggested that meeting the international PA guidelines might not significantly reduce the risk of DSC (RR = 0.96, 95%CI: 0.91-1.02).

CONCLUSION

Compared to previous research, this systematic review has provided more comprehensive information about the inverse relationship between PA and DSC risk. The updated evidence from the current meta-analysis indicates that a moderate-to-high PA level is a common protective factor that can significantly lower the overall risk of DSC. However, the reduction rate for specific cancers may vary. In addition, limited evidence suggests that meeting the international PA guidelines might not significantly reduce the risk of DSC. Thus, future studies must be conducted to determine the optimal dosage, frequency, intensity, and duration of PA required to reduce DSC risk effectively.

Identification of intestinal flora-related key genes and therapeutic drugs in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a multifactorial tumor and a leading cause of cancer-specific deaths worldwide. Recent research has shown that the alteration of intestinal flora contributes to the development of CRC. However, the molecular mechanism by which intestinal flora influences the pathogenesis of CRC remains unclear. This study aims to explore the key genes underlying the effect of intestinal flora on CRC and therapeutic drugs for CRC.

METHODS

Intestinal flora-related genes were determined using text mining. Based on The Cancer Genome Atlas database, differentially expressed genes (DEGs) between CRC and normal samples were identified with the limma package of the R software. Then, the intersection of the two gene sets was selected for enrichment analyses using the tool Database for Annotation, Visualization and Integrated Discovery. Protein interaction network analysis was performed for identifying the key genes using STRING and Cytoscape. The correlation of the key genes with overall survival of CRC patients was analyzed. Finally, the key genes were queried against the Drug-Gene Interaction database to find drug candidates for treating CRC.

RESULTS

518 genes associated with intestinal flora were determined by text mining. Based on The Cancer Genome Atlas database, we identified 48 DEGs associated with intestinal flora, including 25 up-regulated and 23 down-regulated DEGs in CRC. The enrichment analyses indicated that the selected genes were mainly involved in cell-cell signaling, immune response, cytokine-cytokine receptor interaction, and JAK-STAT signaling pathway. The protein-protein interaction network was constructed with 13 nodes and 35 edges. Moreover, 8 genes in the significant cluster were considered as the key genes and chemokine (C-X-C motif) ligand 8 (CXCL8) correlated positively with the overall survival of CRC patients. Finally, a total of 24 drugs were predicted as possible drugs for CRC treatment using the Drug-Gene Interaction database.

CONCLUSIONS

These findings of this study may provide new insights into CRC pathogenesis and treatments. The prediction of drug-gene interaction is of great practical significance for exploring new drugs or novel targets for existing drugs.

Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk

Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.

The emerging field of polygenic risk scores and perspective for use in clinical care

Genetic testing is used widely for diagnostic, carrier and predictive testing in monogenic diseases. Until recently, there were no genetic testing options available for multifactorial complex diseases like heart disease, diabetes and cancer. Genome-wide association studies (GWAS) have been invaluable in identifying single-nucleotide polymorphisms (SNPs) associated with increased or decreased risk for hundreds of complex disorders. For a given disease, SNPs can be combined to generate a cumulative estimation of risk known as a polygenic risk score (PRS). After years of research, PRSs are increasingly used in clinical settings. In this article, we will review the literature on how both genome-wide and restricted PRSs are developed and the relative merit of each. The validation and evaluation of PRSs will also be discussed, including the recognition that PRS validity is intrinsically linked to the methodological and analytical approach of the foundation GWAS together with the ethnic characteristics of that cohort. Specifically, population differences may affect imputation accuracy, risk magnitude and direction. Even as PRSs are being introduced into clinical practice, there is a push to combine them with clinical and demographic risk factors to develop a holistic disease risk. The existing evidence regarding the clinical utility of PRSs is considered across four different domains: informing population screening programs, guiding therapeutic interventions, refining risk for families at high risk, and facilitating diagnosis and predicting prognostic outcomes. The evidence for clinical utility in relation to five well-studied disorders is summarized. The potential ethical, legal and social implications are also highlighted.

External Validation of Risk Prediction Models Incorporating Common Genetic Variants for Incident Colorectal Cancer Using UK Biobank

The aim of this study was to compare and externally validate risk scores developed to predict incident colorectal cancer that include common genetic variants (SNPs), with or without established lifestyle/environmental (questionnaire-based/classical/phenotypic) risk factors. We externally validated 23 risk models from a previous systematic review in 443,888 participants ages 37 to 73 from the UK Biobank cohort who had 6-year prospective follow-up, no prior history of colorectal cancer, and data for incidence of colorectal cancer through linkage to national cancer registries. There were 2,679 (0.6%) cases of incident colorectal cancer. We assessed model discrimination using the area under the operating characteristic curve (AUC) and relative risk calibration. The AUC of models including only SNPs increased with the number of included SNPs and was similar in men and women: the model by Huyghe with 120 SNPs had the highest AUC of 0.62 [95% confidence interval (CI), 0.59-0.64] in women and 0.64 (95% CI, 0.61-0.66) in men. Adding phenotypic risk factors without age improved discrimination in men but not in women. Adding phenotypic risk factors and age increased discrimination in all cases (P < 0.05), with the best performing models including SNPs, phenotypic risk factors, and age having AUCs between 0.64 and 0.67 in women and 0.67 and 0.71 in men. Relative risk calibration varied substantially across the models. Among middle-aged people in the UK, existing polygenic risk scores discriminate moderately well between those who do and do not develop colorectal cancer over 6 years. Consideration should be given to exploring the feasibility of incorporating genetic and lifestyle/environmental information in any future stratified colorectal cancer screening program.

Precision Medicine in Lifestyle Medicine: The Way of the Future?

Precision medicine has captured the imagination of the medical community with visions of therapies precisely targeted to the specific individual's genetic, biological, social, and environmental profile. However, in practice it has become synonymous with genomic medicine. As such its successes have been limited, with poor predictive or clinical value for the majority of people. It adds little to lifestyle medicine, other than in establishing why a healthy lifestyle is effective in combatting chronic disease. The challenge of lifestyle medicine remains getting people to actually adopt, sustain, and naturalize a healthy lifestyle, and this will require an approach that treats the patient as a person with individual needs and providing them with suitable types of support. The future of lifestyle medicine is holistic and person-centered rather than technological.

Performance of individual and joint risk stratification by an environmental risk score and a genetic risk score in a colorectal cancer screening setting

Early detection of colorectal neoplasms can reduce the disease burden of colorectal cancer by timely intervention of individuals at high risk. Our aim was to evaluate a joint environmental-genetic risk score as a risk stratification tool for early detection of advanced colorectal neoplasm (ACRN). Known environmental risk factors and high-risk genetic loci were summarized into risk scores for ACRN in 1014 eligible participants of a screening study. The performances of single and joint environmental-genetic scores were evaluated with estimates and 95% confidence intervals (CI) of the absolute risk, relative risk and predictive ability using the area under the curve (AUC). Individuals with higher environmental risk scores showed increasing ACRN risk, with 3.1-fold for intermediate risk and 4.8-fold for very high risk, compared to the very low environmental risk group. Similarly, individuals with higher genetic risk scores showed increasing ACRN risk, with 2.2-fold for intermediate risk and 3.5-fold for very high risk, compared to the lowest genetic risk group. Moreover, the joint environmental-genetic score improved the ACRN risk stratification and showed higher predictive values (AUC = 0.64; 95%CI = 0.60-0.67) with substantial difference (p = 0.0002) compared to the single environmental score (0.58; 0.55-0.62). The integration of environmental and genetic factors looks promising for improving targeting individuals at high-risk of colorectal neoplasm. Applications in practical screening programs require optimization with additional genetic and other biomarkers involved in colorectal carcinogenesis.

Single nucleotide polymorphisms associated with susceptibility for development of colorectal cancer: Case-control study in a Basque population

Given the significant population diversity in genetic variation, we aimed to investigate whether single nucleotide polymorphisms (SNPs) previously identified in studies of colorectal cancer (CRC) susceptibility were also relevant to the population of the Basque Country (North of Spain). We genotyped 230 CRC cases and 230 healthy controls for 48 previously reported CRC-susceptibility SNPs. Only the rs6687758 in DUPS10 exhibited a statistically significant association with CRC risk based on the crude analysis. The rs6687758 AG genotype conferred about 2.13-fold increased risk for CRC compared to the AA genotype. Moreover, we found significant associations in cases between smoking status, physical activity, and the rs6687758 SNP. The results of a Genetic Risk Score (GRS) showed that the risk alleles were more frequent in cases than controls and the score was associated with CRC in crude analysis. In conclusion, we have confirmed a CRC susceptibility locus and the existence of associations between modifiable factors and the rs6687758 SNP; moreover, the GRS was associated with CRC. However, further experimental validations are needed to establish the role of this SNP, the function of the gene identified, as well as the contribution of the interaction between environmental factors and this locusto the risk of CRC.

Assessing the performance of genome-wide association studies for predicting disease risk

To date more than 3700 genome-wide association studies (GWAS) have been published that look at the genetic contributions of single nucleotide polymorphisms (SNPs) to human conditions or human phenotypes. Through these studies many highly significant SNPs have been identified for hundreds of diseases or medical conditions. However, the extent to which GWAS-identified SNPs or combinations of SNP biomarkers can predict disease risk is not well known. One of the most commonly used approaches to assess the performance of predictive biomarkers is to determine the area under the receiver-operator characteristic curve (AUROC). We have developed an R package called G-WIZ to generate ROC curves and calculate the AUROC using summary-level GWAS data. We first tested the performance of G-WIZ by using AUROC values derived from patient-level SNP data, as well as literature-reported AUROC values. We found that G-WIZ predicts the AUROC with <3% error. Next, we used the summary level GWAS data from GWAS Central to determine the ROC curves and AUROC values for 569 different GWA studies spanning 219 different conditions. Using these data we found a small number of GWA studies with SNP-derived risk predictors that have very high AUROCs (>0.75). On the other hand, the average GWA study produces a multi-SNP risk predictor with an AUROC of 0.55. Detailed AUROC comparisons indicate that most SNP-derived risk predictions are not as good as clinically based disease risk predictors. All our calculations (ROC curves, AUROCs, explained heritability) are in a publicly accessible database called GWAS-ROCS (http://gwasrocs.ca). The G-WIZ code is freely available for download at https://github.com/jonaspatronjp/GWIZ-Rscript/.

Cohort profile: the MCC-Spain follow-up on colorectal, breast and prostate cancers: study design and initial results

PURPOSE

Since 2016, the multicase-control study in Spain (MCC-Spain) has focused towards the identification of factors associated with cancer prognosis. Inception cohorts of patients with colorectal, breast and prostate cancers were assembled using the incident cases originally recruited.

PARTICIPANTS

2140 new cases of colorectal cancer, 1732 of breast cancer and 1112 of prostate cancer were initially recruited in 12 Spanish provinces; all cancers were incident and pathologically confirmed. Follow-up was obtained for 2097 (98%), 1685 (97%) and 1055 (94.9%) patients, respectively.

FINDINGS TO DATE

Information gathered at recruitment included sociodemographic factors, medical history, lifestyle and environmental exposures. Biological samples were obtained, and 80% of patients were genotyped using a commercial exome array. The follow-up was performed by (1) reviewing medical records; (2) interviewing the patients by phone on quality of life; and (3) verifying vital status and cause of death in the Spanish National Death Index. Ninety-seven per cent of recruited patients were successfully followed up in 2017 or 2018; patient-years of follow-up were 30 914. Most colorectal cancers (52%) were at clinical stage II or lower at recruitment; 819 patients died in the follow-up and the 5-year survival was better for women (74.4%) than men (70.0%). 71% of breast cancers were diagnosed at stages I or II; 206 women with breast cancer died in the follow-up and the 5-year survival was 90.7%. 49% of prostate cancers were diagnosed at stage II and 32% at stage III; 119 patients with prostate cancer died in the follow-up and the 5-year survival was 93.7%.

FUTURE PLANS

MCC-Spain has built three prospective cohorts on highly frequent cancers across Spain, allowing to investigate socioeconomic, clinical, lifestyle, environmental and genetic variables as putative prognosis factors determining survival of patients of the three cancers and the inter-relationship of these factors.

Risk Prediction Models for Colorectal Cancer Incorporating Common Genetic Variants: A Systematic Review

Colorectal cancer screening reduces colorectal cancer incidence and mortality. Risk models based on phenotypic variables have relatively good discrimination in external validation and may improve efficiency of screening. Models incorporating genetic variables may perform better. In this review, we updated our previous review by searching Medline and EMBASE from the end date of that review (January 2014) to February 2019 to identify models incorporating at least one SNP and applicable to asymptomatic individuals in the general population. We identified 23 new models, giving a total of 29. Of those in which the SNP selection was on the basis of published genome-wide association studies, in external or split-sample validation the AUROC was 0.56 to 0.57 for models that included SNPs alone, 0.61 to 0.63 for SNPs in combination with other risk factors, and 0.56 to 0.70 when age was included. Calibration was only reported for four. The addition of SNPs to other risk factors increases discrimination by 0.01 to 0.06. Public health modeling studies suggest that, if determined by risk models, the range of starting ages for screening would be several years greater than using family history alone. Further validation and calibration studies are needed alongside modeling studies to assess the population-level impact of introducing genetic risk-based screening programs.

Quantitative risk of positive family history in developing colorectal cancer: A meta-analysis

BACKGROUND

Positive family history is a risk factor for development of colorectal cancer. Despite numerous studies on the topic, the absolute risk in patients with a positive family history remains unclear and therefore studies are lacking to validate non-invasive screening methods in individuals with positive family history.

AIM

To quantify the risk of colorectal cancer in individuals with a positive family history.

METHODS

A comprehensive electronic literature search was performed using PubMed from January 1955 until November 2017, EMBASE from 1947 until 2018, and Cochrane Library without date restrictions. Two independent reviewers conducted study selection, data extraction and quality assessment. A meta-analysis of Mantel-Haenzel relative risks was performed using the random effects model. Newcastle-Ottawa scale was used to score the quality of selected papers. Funnel plot and Egger’s regression test was performed to detect publication bias. Subgroup analysis was performed comparing Asian and non-Asian studies. Sensitivity analyses were performed to rule out the effect of the timing of the study, overall quality, the main outcome and the effect of each individual study in overall result.

RESULTS

Forty-six out of 3390 studies, including 906981 patients were included in the final analysis. 41 of the included studies were case-control and 5 were cohort. A positive family history of colorectal cancer in first-degree relatives was associated with significantly increased risk of colorectal cancer with a relative risk of 1.87 (95%CI: 1.68-2.09; P < 0.00001). Cochrane Q test was significant (P < 0.00001, I² = 90%). Egger’s regression test showed asymmetry in the funnel plot and therefore the Trim and Fill method was used which confirmed the validity of the results. There was no difference between Asian versus non-Asian studies. Results remained robust in sensitivity analyses.

CONCLUSION

Individuals with a positive family history of colorectal cancer are 1.87 times more likely to develop colorectal cancer. Screening guidelines should pay specific attention to individuals with positive family history and further studies need to be done on validating current screening methods or developing new modalities in this high-risk population.

Determining Risk of Colorectal Cancer and Starting Age of Screening Based on Lifestyle, Environmental, and Genetic Factors

BACKGROUND & AIMS

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Role of intestinal flora in colorectal cancer from the metabolite perspective: a systematic review

Colorectal cancer is one of the most common human malignant tumors. Recent research has shown that colorectal cancer is a dysbacteriosis-induced disease; however, the role of intestinal bacteria in colorectal cancer is unclear. This review explores the role of intestinal flora in colorectal cancer. In total, 57 articles were included after identification and screening. The pertinent literature on floral metabolites in colorectal cancer from three metabolic perspectives - including carbohydrate, lipid, and amino acid metabolism - was analyzed. An association network regarding the role of intestinal flora from a metabolic perspective was constructed by analyzing the previous literature to provide direction and insight for further research on intestinal flora in colorectal cancer.

Colorectal Cancer and Alcohol Consumption-Populations to Molecules

Colorectal cancer (CRC) is a major cause of morbidity and mortality, being the third most common cancer diagnosed in both men and women in the world. Several environmental and habitual factors have been associated with the CRC risk. Alcohol intake, a common and rising habit of modern society, is one of the major risk factors for development of CRC. Here, we will summarize the evidence linking alcohol with colon carcinogenesis and possible underlying mechanisms. Some epidemiologic studies suggest that even moderate drinking increases the CRC risk. Metabolism of alcohol involves ethanol conversion to its metabolites that could exert carcinogenic effects in the colon. Production of ethanol metabolites can be affected by the colon microbiota, another recently recognized mediating factor to colon carcinogenesis. The generation of acetaldehyde and alcohol's other metabolites leads to activation of cancer promoting cascades, such as DNA-adduct formation, oxidative stress and lipid peroxidation, epigenetic alterations, epithelial barrier dysfunction, and immune modulatory effects. Not only does alcohol induce its toxic effect through carcinogenic metabolites, but alcoholics themselves are predisposed to a poor diet, low in folate and fiber, and circadian disruption, which could further augment alcohol-induced colon carcinogenesis.