Modeling the prevention of colorectal cancer from the combined impact of host and behavioral risk factors

Construction of an immune gene expression meta signature to assess the prognostic risk of colorectal cancer patients

Despite recent advancements in colorectal cancer (CRC) treatment, particularly with the introduction of immunotherapy and checkpoint inhibitors, the efficacy of these therapies remains limited to a subset of patients. To address this challenge, our study aimed to develop a prognostic biomarker based on immune-related genes to predict better outcomes in CRC patients and aid in treatment decision-making. We comprehensively analysed immune gene expression signatures associated with CRC prognosis to construct an immune meta-signature with prognostic potential. Utilising data from The Cancer Genome Atlas (TCGA), we employed Cox regression to identify immune-related genes with prognostic significance from multiple studies. Subsequently, we compared the expression levels of immune genes, levels of immune cell infiltration, and various immune-related molecules between high-risk and low-risk patient groups. Functional analysis using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses provided insights into the biological pathways associated with the identified prognostic genes. Finally, we validated our findings using a separate CRC cohort from the Gene Expression Omnibus (GEO). Integration of the prognostic genes revealed significant disparities in survival outcomes. Differential expression analysis identified a set of immune-associated genes, which were further refined using LASSO penalisation and Cox regression. Univariate Cox regression analyses confirmed the autonomy of the gene signature as a prognostic indicator for CRC patient survival. Our risk prediction model effectively stratified CRC patients based on their prognosis, with the high-risk group showing enrichment in pro-oncogenic terms and pathways. Immune infiltration analysis revealed an augmented presence of certain immunosuppressive subsets in the high-risk group. Finally, we validated the performance of our prognostic model by applying the risk score equation to a different CRC patient dataset, confirming its prognostic potential in this new cohort. Overall, our study presents a novel immune-related gene signature with promising implications for predicting cancer progression and prognosis, thereby enabling more personalised management strategies for CRC patients.

Colorectal cancer mortality trend analysis in Montenegro from 1990 to 2018

Colorectal cancer (CRC) is the second leading cause of cancer-related death in Europe. This study aimed to investigate CRC mortality trends in Montenegro from 1990 to 2018 and critically review the impact of preventive activities on cancer suppression in this country. We used the national CRC mortality data categorized by sex and age. Mortality rates were age-standardized according to the World Standard Population. The trends were described using regression techniques. In the period from 1990 to 2018, there was a significant increase in CRC mortality (P < .05). The death rates and the number of deaths from CRC were constantly increasing for both the overall level and gender, with the mean annual percentage change for the rates respectively average annual percent change (95% confidence interval-CI): 2.6% (1.9-3.2), 2.6% (1.8-3.5); 2.3% (1.3-3.3), and for the number of cases, respectively: 4.2% (3.5-4.9), 4.3% (3.3-5.3), 4.3% (3.2-5.5). The most affected age groups were 65 to 74 years (33%), followed by those aged 75 to 84 years (25%) and the age group 55 to 64 (22%). In Montenegro, CRC mortality trends are increasing among both men and women over the age of 45. Additional research on the risk factors and mechanisms that contribute to the unfavorable trends in CRC mortality in Montenegro is necessary.

Downregulated expression of plakophilin-2 gene in patients with colon adenocarcinoma predicts an unfavorable prognosis and immune infiltrate

BACKGROUND

Plakophilin 2 gene (PKP2) has been revealed to be differentially expressed in various cancer types and is correlated with prognosis. However, the role of PKP2 in colon adenocarcinoma remains indistinct.

METHODS

Differences in transcriptional expression of PKP2 between colon adenocarcinoma tissues and normal adjacent tissues were acquired from the publicly available dataset-the Cancer Genome Atlas. A receiver operating curve (ROC) was constructed to differentiate colon adenocarcinoma tissues from adjacent normal tissues. The Kaplan-Meier plot method was performed to evaluate the effect of PKP2 on survival. The correlation between mRNA expression of PKP2 and immune infiltrating was determined by the Tumor Immune Estimation Resource and Tumor-Immune System Interaction databases.

RESULTS

The expression of PKP2 in colon adenocarcinoma tissues was significantly downregulated compared with corresponding adjacent normal tissues. Decreased PKP2 mRNA expression was associated with lymph node metastases and advanced pathological stage. The ROC curve analysis indicated that with a cutoff value of 6.034, the sensitivity and specificity for PKP2 differentiating the colon adenocarcinoma tissues from the adjacent normal tissues were 90.2 and 66.5% respectively. Kaplan-Meier plot survival analysis revealed that colon adenocarcinoma patients with low-PKP2 had a worse prognosis than those with high-PKP2 (68.2 vs. 101.4 months, p = 0.028). Correlation analysis showed that mRNA expression of PKP2 was correlative with immune infiltrates.

CONCLUSIONS

Downregulated PKP2 is significantly correlated with unfavorable immune infiltrating and survival in colon adenocarcinoma. This research indicates that PKP2 can be selected as a novel biomarker of potential immunotherapy targets and unfavorable prognosis in colon adenocarcinoma.

Clinically relevant combined effect of polygenic background, rare pathogenic germline variants, and family history on colorectal cancer incidence

BACKGROUND AND AIMS

Summarised in polygenic risk scores (PRS), the effect of common, low penetrant genetic variants associated with colorectal cancer (CRC), can be used for risk stratification.

METHODS

To assess the combined impact of the PRS and other main factors on CRC risk, 163,516 individuals from the UK Biobank were stratified as follows: 1. carriers status for germline pathogenic variants (PV) in CRC susceptibility genes (APC, MLH1, MSH2, MSH6, PMS2), 2. low (< 20%), intermediate (20-80%), or high PRS (> 80%), and 3. family history (FH) of CRC. Multivariable logistic regression and Cox proportional hazards models were applied to compare odds ratios and to compute the lifetime incidence, respectively.

RESULTS

Depending on the PRS, the CRC lifetime incidence for non-carriers ranges between 6 and 22%, compared to 40% and 74% for carriers. A suspicious FH is associated with a further increase of the cumulative incidence reaching 26% for non-carriers and 98% for carriers. In non-carriers without FH, but high PRS, the CRC risk is doubled, whereas a low PRS even in the context of a FH results in a decreased risk. The full model including PRS, carrier status, and FH improved the area under the curve in risk prediction (0.704).

CONCLUSION

The findings demonstrate that CRC risks are strongly influenced by the PRS for both a sporadic and monogenic background. FH, PV, and common variants complementary contribute to CRC risk. The implementation of PRS in routine care will likely improve personalized risk stratification, which will in turn guide tailored preventive surveillance strategies in high, intermediate, and low risk groups.

Identification and validation of an inflammation-related lncRNAs signature for improving outcomes of patients in colorectal cancer

Background: Colorectal cancer is the fourth most deadly cancer worldwide. Although current treatment regimens have prolonged the survival of patients, the prognosis is still unsatisfactory. Inflammation and lncRNAs are closely related to tumor occurrence and development in CRC. Therefore, it is necessary to establish a new prognostic signature based on inflammation-related lncRNAs to improve the prognosis of patients with CRC. Methods: LASSO-penalized Cox analysis was performed to construct a prognostic signature. Kaplan-Meier curves were used for survival analysis and ROC curves were used to measure the performance of the signature. Functional enrichment analysis was conducted to reveal the biological significance of the signature. The R package "maftool" and GISTIC2.0 algorithm were performed for analysis and visualization of genomic variations. The R package "pRRophetic", CMap analysis and submap analysis were performed to predict response to chemotherapy and immunotherapy. Results: An effective and independent prognostic signature, IRLncSig, was constructed based on sixteen inflammation-related lncRNAs. The IRLncSig was proved to be an independent prognostic indicator in CRC and was superior to clinical variables and the other four published signatures. The nomograms were constructed based on inflammation-related lncRNAs and detected by calibration curves. All samples were classified into two groups according to the median value, and we found frequent mutations of the TP53 gene in the high-risk group. We also found some significantly amplificated regions in the high-risk group, 8q24.3, 20q12, 8q22.3, and 20q13.2, which may regulate the inflammatory activity of cancer cells in CRC. Finally, we identified chemotherapeutic agents for high-risk patients and found that these patients were more likely to respond to immunotherapy, especially anti-CTLA4 therapy. Conclusion: In short, we constructed a new signature based on sixteen inflammation-related lncRNAs to improve the outcomes of patients in CRC. Our findings have proved that the IRLncSig can be used as an effective and independent marker for predicting the survival of patients with CRC.

Clinical implications of genetic testing in familial intermediate and late-onset colorectal cancer

The genetic background of familial, late-onset colorectal cancer (CRC) (i.e., onset > age 50 years) has not been studied as thoroughly as other subgroups of familial CRC, and the proportion of families with a germline genetic predisposition to CRC remains to be defined. To define the contribution of known or suggested CRC predisposition genes to familial late-onset CRC, we analyzed 32 well-established or candidate CRC predisposition genes in 75 families with late-onset CRC. We identified pathogenic or likely pathogenic variants in five patients in MSH6 (n = 1), MUTYH (monoallelic; n = 2) and NTHL1 (monoallelic; n = 2). In addition, we identified a number of variants of unknown significance in particular in the lower penetrant Lynch syndrome-associated mismatch repair (MMR) gene MSH6 (n = 6). In conclusion, screening using a comprehensive cancer gene panel in families with accumulation of late-onset CRC appears not to have a significant clinical value due to the low level of high-risk pathogenic variants detected. Our data suggest that only patients with abnormal MMR immunohistochemistry (IHC) or microsatellite instability (MSI) analyses, suggestive of Lynch syndrome, or a family history indicating another cancer predisposition syndrome should be prioritized for such genetic evaluations. Variants in MSH6 and MUTYH have previously been proposed to be involved in digenic or oligogenic hereditary predisposition to CRC. Accumulation of variants in MSH6 and monoallelic, pathogenic variants in MUTYH in our study indicates that digenic or oligogenic inheritance might be involved in late-onset CRC and warrants further studies of complex types of inheritance.

Global, regional, and national burden of colorectal cancer and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND

Colorectal cancer is the third leading cause of cancer deaths worldwide. Given the recent increasing trends in colorectal cancer incidence globally, up-to-date information on the colorectal cancer burden could guide screening, early detection, and treatment strategies, and help effectively allocate resources. We examined the temporal patterns of the global, regional, and national burden of colorectal cancer and its risk factors in 204 countries and territories across the past three decades.

METHODS

Estimates of incidence, mortality, and disability-adjusted life years (DALYs) for colorectal cancer were generated as a part of the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019 by age, sex, and geographical location for the period 1990-2019. Mortality estimates were produced using the cause of death ensemble model. We also calculated DALYs attributable to risk factors that had evidence of causation with colorectal cancer.

FINDINGS

Globally, between 1990 and 2019, colorectal cancer incident cases more than doubled, from 842 098 (95% uncertainty interval [UI] 810 408-868 574) to 2·17 million (2·00-2·34), and deaths increased from 518 126 (493 682-537 877) to 1·09 million (1·02-1·15). The global age-standardised incidence rate increased from 22·2 (95% UI 21·3-23·0) per 100 000 to 26·7 (24·6-28·9) per 100 000, whereas the age-standardised mortality rate decreased from 14·3 (13·5-14·9) per 100 000 to 13·7 (12·6-14·5) per 100 000 and the age-standardised DALY rate decreased from 308·5 (294·7-320·7) per 100 000 to 295·5 (275·2-313·0) per 100 000 from 1990 through 2019. Taiwan (province of China; 62·0 [48·9-80·0] per 100 000), Monaco (60·7 [48·5-73·6] per 100 000), and Andorra (56·6 [42·8-71·9] per 100 000) had the highest age-standardised incidence rates, while Greenland (31·4 [26·0-37·1] per 100 000), Brunei (30·3 [26·6-34·1] per 100 000), and Hungary (28·6 [23·6-34·0] per 100 000) had the highest age-standardised mortality rates. From 1990 through 2019, a substantial rise in incidence rates was observed in younger adults (age <50 years), particularly in high Socio-demographic Index (SDI) countries. Globally, a diet low in milk (15·6%), smoking (13·3%), a diet low in calcium (12·9%), and alcohol use (9·9%) were the main contributors to colorectal cancer DALYs in 2019.

INTERPRETATION

The increase in incidence rates in people younger than 50 years requires vigilance from researchers, clinicians, and policy makers and a possible reconsideration of screening guidelines. The fast-rising burden in low SDI and middle SDI countries in Asia and Africa calls for colorectal cancer prevention approaches, greater awareness, and cost-effective screening and therapeutic options in these regions.

FUNDING

Bill & Melinda Gates Foundation.

Establishment and experimental validation of an immune miRNA signature for assessing prognosis and immune landscape of patients with colorectal cancer

As essential regulators of gene expression, miRNAs are engaged in the initiation and progression of colorectal cancer (CRC), including antitumour immune response. In this study, we proposed an integrated algorithm, ImmuMiRNA, for identifying miRNA modulators of immune‐associated pathways. Based on these immune‐associated miRNAs, we applied the LASSO algorithm to develop a reliable and individualized signature for evaluating overall survival (OS) and inflammatory landscape of CRC patients. An external public data set and qRT‐PCR data from 40 samples were further utilized to validate this signature. As a result, an immune‐associated miRNA prognostic signature (IAMIPS) consisting of three miRNAs (miR‐194‐3P, miR‐216a‐5p and miR‐3677‐3p) was established and validated. Patients in the high‐risk group possessed worse OS. After stratification for clinical factors, the signature remained a powerful independent predictor for OS. IAMIPS displayed much better accuracy than the traditional clinical stage in assessing the prognosis of CRC. Further analysis revealed that patients in the high‐risk group were characterized by inflammatory response, abundance immune cell infiltration, and higher immune checkpoint profiles and tumour mutation burden (TMB). In conclusion, the IAMIPS is highly predictive of OS in patients with CRC, which may serve as a powerful prognostic tool to further optimize immunotherapies for cancer.

Identification of Vitamin D-related gene signature to predict colorectal cancer prognosis

Colorectal cancer (CRC) is one of the most common malignant carcinomas worldwide with poor prognosis, imposing an increasingly heavy burden on patients. Previous experiments and epidemiological studies have shown that vitamin D and vitamin D-related genes play a vital role in CRC. Therefore, we aimed to construct a vitamin D-related gene signature to predict prognosis in CRC. The CRC data from The Cancer Genome Atlas (TCGA) was performed as the training set. A total of 173 vitamin D-related genes in the TCGA CRC dataset were screened, and 17 genes associated with CRC prognosis were identified from them. Then, a vitamin D-related gene signature consisting of those 17 genes was established by univariate and multivariate Cox analyses. Moreover, four external datasets (GSE17536, GSE103479, GSE39582, and GSE17537) were used as testing set to validate the stability of this signature. The high-risk group presented a significantly poorer overall survival than low-risk group in both of training set and testing sets. Besides, the areas under the curve (AUCs) for signature on OS in training set at 1, 3, and 5 years were 0.710, 0.708, 0.710 respectively. The AUCs of the ROC curve in GSE17536 for 1, 3, and 5 years were 0.649, 0.654, and 0.694. These results indicated the vitamin D-related gene signature model could effectively predict the survival status of CRC patients. This vitamin D-related gene signature was also correlated with TNM stage in CRC clinical parameters, and the higher risk score from this model was companied with higher clinical stage. Furthermore, the high accuracy of this prognostic signature was validated and confirmed by nomogram model. In conclusion, we have proposed a novel vitamin D-related gene model to predict the prognosis of CRC, which will help provide new therapeutic targets and act as potential prognostic biomarkers for CRC.

The Emerging Landscape of Long Non-Coding RNAs in Colorectal Cancer Metastasis

Colorectal cancer (CRC) is one of the most common gastrointestinal cancers, with extremely high rates of morbidity and mortality. The main cause of death in CRC is distant metastasis; it affects patient prognosis and survival and is one of the key challenges in the treatment of CRC. Long non-coding RNAs (lncRNAs) are a group of non-coding RNA molecules with more than 200 nucleotides. Abnormal lncRNA expression is closely related to the occurrence and progression of several diseases, including cancer. Recent studies have shown that numerous lncRNAs play pivotal roles in the CRC metastasis, and reversing the expression of these lncRNAs through artificial means can reduce the malignant phenotype of metastatic CRC to some extent. This review summarizes the major mechanisms of lncRNAs in CRC metastasis and proposes lncRNAs as potential therapeutic targets for CRC and molecular markers for early diagnosis.

A prospective study of the associations among fine particulate matter, genetic variants, and the risk of colorectal cancer

BACKGROUND

Fine particulate matter (PM_2.5) is suspected to increase the risk of colorectal cancer, but the mechanism remains unknown. We aimed to investigate the association between PM_2.5 exposure, genetic variants and colorectal cancer risk in the Prostate, Lung, Colon and Ovarian (PLCO) Cancer Screening trial.

METHODS

We included a prospective cohort of 139,534 cancer-free individuals from 10 United States research centers with over ten years of follow-up. We used a Cox regression model to assess the association between PM_2.5 exposure and colorectal cancer incidence by calculating the hazard ratio (HR) and 95% confidence interval (CI) with adjustment for potential confounders. The polygenic risk score (PRS) and genome-wide interaction analysis (GWIA) were used to evaluate the multiplicative interaction between PM_2.5 exposure and genetic variants in regard to colorectal cancer risk.

RESULTS

After a median of 10.43 years of follow-up, 1,666 participants had been diagnosed with colorectal cancer. PM_2.5 exposure was significantly associated with an increased risk of colorectal cancer (HR = 1.27; 95% CI = 1.17-1.37 per 5 μg/m³ increase). Five independent susceptibility loci reached statistical significance at P < 1.22 × 10^-8 in the interaction analysis. Furthermore, a joint interaction was observed between PM_2.5 exposure and the PRS based on these five loci with colorectal cancer risk (P = 3.11 × 10^-29). The Gene Ontology analysis showed that the vascular endothelial growth factor (VEGF) receptor signaling pathway was involved in the biological process of colorectal cancer.

CONCLUSIONS

Our large-scale analysis has shown for the first time that long-term PM_2.5 exposure potential increases colorectal cancer risk, which might be modified by genetic variants.

Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients

BACKGROUND

Despite recent advance in immune therapy, great heterogeneity exists in the outcomes of colorectal cancer (CRC) patients. In this study, we aimed to analyze the immune-related gene (IRG) expression profiles from three independent public databases and develop an effective signature to forecast patient's prognosis.

METHODS

IRGs were collected from the ImmPort database. The CRC dataset from The Cancer Genome Atlas (TCGA) database was used to identify a prognostic gene signature, which was verified in another two CRC datasets from the Gene Expression Omnibus (GEO). Gene function enrichment analysis was conducted. A prognostic nomogram was built incorporating the IRG signature with clinical risk factors.

RESULTS

The three datasets had 487, 579, and 224 patients, respectively. A prognostic six-gene-signature (CCL22, LIMK1, MAPKAPK3, FLOT1, GPRC5B, and IL20RB) was developed through feature selection that showed good differentiation between the low- and high-risk groups in the training set (p < 0.001), which was later confirmed in the two validation groups (log-rank p < 0.05). The signature outperformed tumor TNM staging for survival prediction. GO and KEGG functional annotation analysis suggested that the signature was significantly enriched in metabolic processes and regulation of immunity (p < 0.05). When combined with clinical risk factors, the model showed robust prediction capability.

CONCLUSION

The immune-related six-gene signature is a reliable prognostic indicator for CRC patients and could provide insight for personalized cancer management.

Ultra-Processed Food Intake and Smoking Interact in Relation with Colorectal Adenomas

Smoking and ultra-processed foods (UPFs), a substantial part of the western diet, have been suggested to have a potential carcinogenic effect, though epidemiologic data are lacking. We aimed to examine the association between high UPF intake and colorectal adenomas, and to test the interaction with smoking. In a case-control study among consecutive subjects undergoing colonoscopy in a tertiary center during 2010–2015, UPF intake and smoking were compared between cases with colorectal adenomas and controls. Within 652 participants (cases, n = 294 and controls, n = 358), high UPF intake (defined as percent of kcal from UPF above the study sample upper tertile) was positively associated with adenomas (Odds ratio (OR) = 1.75, 95% Confidence interval (CI) 1.14–2.68), advanced and proximal adenomas (OR = 2.17, 1.29–3.65 and OR = 2.38, 1.37–4.11) among the whole study sample; and with adenomas (OR = 3.54, 1.90–6.61), non-advanced adenomas (OR = 2.60, 1.20–5.63), advanced adenomas (OR = 4.76, 2.20–10.30), proximal adenomas (OR = 6.23, 2.67–14.52), and distal adenomas (OR = 2.49, 1.21–5.13) among smokers. Additionally, a dose-dependent association was observed between tertiles of UPF intake and adenomas only among smokers (p for trend < 0.001). A significant interaction between smoking and high UPF intake was detected (p for interaction = 0.004). High intake of UPFs is strongly and independently associated with colorectal adenomas, especially advanced and proximal adenoma, and interacts with smoking. Results highlight smokers as more susceptible to the negative health effects of UPF consumption on colorectal neoplasia.

The Impact of a Comprehensive Risk Prediction Model for Colorectal Cancer on a Population Screening Program

BACKGROUND

In many countries, population colorectal cancer (CRC) screening is based on age and family history, though more precise risk prediction could better target screening. We examined the impact of a CRC risk prediction model (incorporating age, sex, lifestyle, genomic, and family history factors) to target screening under several feasible screening scenarios.

METHODS

We estimated the model's predicted CRC risk distribution in the Australian population. Predicted CRC risks were categorized into screening recommendations under 3 proposed scenarios to compare with current recommendations: 1) highly tailored, 2) 3 risk categories, and 3) 4 sex-specific risk categories. Under each scenario, for 35- to 74-year-olds, we calculated the number of CRC screens by immunochemical fecal occult blood testing (iFOBT) and colonoscopy and the proportion of predicted CRCs over 10 years in each screening group.

RESULTS

Currently, 1.1% of 35- to 74-year-olds are recommended screening colonoscopy and 56.2% iFOBT, and 5.7% and 83.2% of CRCs over 10 years were predicted to occur in these groups, respectively. For the scenarios, 1) colonoscopy was recommended to 8.1% and iFOBT to 37.5%, with 36.1% and 50.1% of CRCs in each group; 2) colonoscopy was recommended to 2.4% and iFOBT to 56.0%, with 13.2% and 76.9% of cancers in each group; and 3) colonoscopy was recommended to 5.0% and iFOBT to 54.2%, with 24.5% and 66.5% of cancers in each group.

CONCLUSIONS

A highly tailored CRC screening scenario results in many fewer screens but more cancers in those unscreened. Category-based scenarios may provide a good balance between number of screens and cancers detected and are simpler to implement.

Integrated analysis identifies an immune-based prognostic signature for the mesenchymal identity in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) has been divided into 4 consensus molecular subtypes (CMSs), of which CMS4 has the mesenchymal identity and the highest relapse rate. Our goal is to develop a prognostic signature by integrating the immune system and mesenchymal modalities involved in CMS4.

METHODS

The gene expression profiles collected from 5 public datasets were applied to this study, including 1280 samples totally. Network analysis was applied to integrate the mesenchymal modalities and immune signature to establish an immune-based prognostic signature for CRC (IPSCRC).

RESULTS

We identified 6 immune genes as key factors of CMS4 and established the IPSCRC. The IPSCRC could significantly divide patients into high- and low- risk groups in terms of relapse-free survival (RFS) and overall survival (OS) and in discovery (RFS: P < .0001) and 4 independent validation sets (RFS range: P = .01 to <.0001; OS range: P = .02-.0004). After stage stratification, the IPSCRC could still distinguish poor prognosis patients in discovery (RFS: P = .04) and validation cohorts (RFS range: P = .04-.007) within stage II in terms of RFS. Further, in multivariate analysis, the IPSCRC remained an independent predictor of prognosis. Moreover, Macrophage M2 was significantly enriched in the high-risk group, while plasma cells enriched in the low-risk group.

CONCLUSION

We propose an immune-based signature identified by network analysis, which is a promising prognostic biomarker and help for the selection of CRC patients who might benefit from more rigorous therapies. Further prospective studies are warranted to test and validate its efficiency for clinical application.

Assessing thyroid cancer risk using polygenic risk scores

Genome-wide association studies (GWASs) have identified at least 10 single-nucleotide polymorphisms (SNPs) associated with papillary thyroid cancer (PTC) risk. Most of these SNPs are common variants with small to moderate effect sizes. Here we assessed the combined genetic effects of these variants on PTC risk by using summarized GWAS results to build polygenic risk score (PRS) models in three PTC study groups from Ohio (1,544 patients and 1,593 controls), Iceland (723 patients and 129,556 controls), and the United Kingdom (534 patients and 407,945 controls). A PRS based on the 10 established PTC SNPs showed a stronger predictive power compared with the clinical factors model, with a minimum increase of area under the receiver-operating curve of 5.4 percentage points (P ≤ 1.0 × 10^-9). Adding an extended PRS based on 592,475 common variants did not significantly improve the prediction power compared with the 10-SNP model, suggesting that most of the remaining undiscovered genetic risk in thyroid cancer is due to rare, moderate- to high-penetrance variants rather than to common low-penetrance variants. Based on the 10-SNP PRS, individuals in the top decile group of PRSs have a close to sevenfold greater risk (95% CI, 5.4-8.8) compared with the bottom decile group. In conclusion, PRSs based on a small number of common germline variants emphasize the importance of heritable low-penetrance markers in PTC.

Metabolic models predict bacterial passengers in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a complex multifactorial disease. Increasing evidence suggests that the microbiome is involved in different stages of CRC initiation and progression. Beyond specific pro-oncogenic mechanisms found in pathogens, metagenomic studies indicate the existence of a microbiome signature, where particular bacterial taxa are enriched in the metagenomes of CRC patients. Here, we investigate to what extent the abundance of bacterial taxa in CRC metagenomes can be explained by the growth advantage resulting from the presence of specific CRC metabolites in the tumor microenvironment.

METHODS

We composed lists of metabolites and bacteria that are enriched on CRC samples by reviewing metabolomics experimental literature and integrating data from metagenomic case-control studies. We computationally evaluated the growth effect of CRC enriched metabolites on over 1500 genome-based metabolic models of human microbiome bacteria. We integrated the metabolomics data and the mechanistic models by using scores that quantify the response of bacterial biomass production to CRC-enriched metabolites and used these scores to rank bacteria as potential CRC passengers.

RESULTS

We found that metabolic networks of bacteria that are significantly enriched in CRC metagenomic samples either depend on metabolites that are more abundant in CRC samples or specifically benefit from these metabolites for biomass production. This suggests that metabolic alterations in the cancer environment are a major component shaping the CRC microbiome.

CONCLUSION

Here, we show with in sillico models that supplementing the intestinal environment with CRC metabolites specifically predicts the outgrowth of CRC-associated bacteria. We thus mechanistically explain why a range of CRC passenger bacteria are associated with CRC, enhancing our understanding of this disease. Our methods are applicable to other microbial communities, since it allows the systematic investigation of how shifts in the microbiome can be explained from changes in the metabolome.

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.

Ability of known susceptibility SNPs to predict colorectal cancer risk for persons with and without a family history

Before SNP-based risk can be incorporated in colorectal cancer (CRC) screening, the ability of these SNPs to estimate CRC risk for persons with and without a family history of CRC, and the screening implications need to be determined. We estimated the association with CRC of a 45 SNP-based risk using 1181 cases and 999 controls, and its correlation with CRC risk predicted from detailed family history. We estimated the predicted change in the distribution across predefined risk categories, and implications for recommended screening commencement age, from adding SNP-based risk to family history. The inter-quintile risk ratio for colorectal cancer risk of the SNP-based risk was 3.28 (95% CI 2.54-4.22). SNP-based and family history-based risks were not correlated (r = 0.02). For persons with no first-degree relatives with CRC, screening could commence 4 years earlier for women (5 years for men) in the highest quintile of SNP-based risk. For persons with two first-degree relatives with CRC, screening could commence 16 years earlier for men and women in the highest quintile, and 7 years earlier for the lowest quintile. This 45 SNP panel in conjunction with family history, can identify people who could benefit from earlier screening. Risk reclassification by 45 SNPs could inform targeted screening for CRC prevention, particularly in clinical genetics settings when mutations in high-risk genes cannot be identified. Yet to be determined is cost-effectiveness, resources requirements, community, patient and clinician acceptance, and feasibility with potentially ethical, legal and insurance implications.

Talin1 knockdown prohibits the proliferation and migration of colorectal cancer cells via the EMT signaling pathway

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second highest cause of cancer-associated death worldwide. Talin1 activates integrins, which mediate cell adhesion, proliferation, tumorigenesis and metastasis. The aim of the present study was to determine talin1 expression levels in colorectal cancer (CRC) and investigate the role of talin1 in CRC proliferation and invasion in vitro and in vivo. Talin1 protein expression levels were detected in human CRC and adjacent normal tissues by immunohistochemistry. Talin1 short hairpin RNA and control vectors were designed and stably transfected into HCT116 CRC cells. Cell proliferation was determined by MTT assay. Cell migratory and invasive capabilities were detected by wound-healing and Matrigel invasion assays. The expression of proteins in the epithelial-to-mesenchymal transition signaling pathway was determined by western blotting and reverse transcription-quantitative PCR. The effect of talin1 on tumor growth was explored in vivo using BALB/c nude mice. Immunohistochemical analysis of CRC and adjacent normal tissue revealed that talin1 expression was upregulated in CRC. Talin1 knockdown significantly reduced the proliferation, migration and invasive ability of HCT116 cells compared with the control. Protein levels of phosphorylated STAT3 and vimentin were significantly lower in talin1-knockdown HCT116 cell lines compared with the control, whereas protein levels of E-cadherin were increased. Interleukin-6 mRNA levels were significantly increased in patients' blood samples compared with blood samples from healthy controls, as well as in CRC compared with adjacent normal tissue. In vivo experiments demonstrated that talin1 knockdown reduced CRC tumor growth and weight in nude mice. In conclusion, Talin1 knockdown may prevent the proliferation and migration of CRC cells by downregulating various factors involved in the epithelial-to-mesenchymal transition process, such as phosphorylated STAT3 and vimentin; therefore, talin1 may provide a novel therapeutic target for CRC.

Development and validation of an immune-related gene pairs signature in colorectal cancer

Although the outcome of colorectal cancer (CRC) patients has improved significantly with the recent implementation of annual screening programs, reliable prognostic biomarkers are still needed due to the disease heterogeneity. Increasing pieces of evidence revealed an association between immune signature and CRC prognosis. Thus, we aim to build a robust immune-related gene pairs (IRGPs) signature that can estimate prognosis for CRC. Gene expression profiles and clinical information of CRC patients were collected from six public cohorts, divided into training cohort (n = 565) and five independent validation cohorts (n = 572, 290, 90 177 and 68, respectively). Within 1534 immune genes, a 19 IRGPs signature consisting of 36 unique genes was constructed which was significantly associated with the survival. In the validation cohorts, the IRGPs signature significantly stratified patients into high- vs low-risk groups in terms of prognosis across and within subpopulations with early stages disease and was prognostic in univariate and multivariate analyses. Several biological processes, including response to bacterium, were enriched among genes in the IRGPs signature. Macrophage M2 and mast cells were significantly higher in the high-risk risk group compared with the low-risk group. The IRGPs signature achieved a higher accuracy than commercialized multigene signatures for estimation of survival. When integrated with clinical factors such as sex and stage, the composite clinical and IRGPs signature showed improved prognostic accuracy relative to IRGPs signatures alone. In short, we developed a robust IRGPs signature for estimating prognosis in CRC, including early-stage disease, providing new insights into the identification of CRC patients with a high risk of mortality.

Systematic evaluation of cancer-specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts

BACKGROUND

Genetic risk score (GRS) is an odds ratio (OR)-weighted and population-standardized method for measuring cumulative effect of multiple risk-associated single nucleotide polymorphisms (SNPs). We hypothesize that GRS is a valid tool for risk assessment of most common cancers.

METHODS

Utilizing genotype and phenotype data from The Cancer Genome Atlas (TCGA) and Electronic Medical Records and Genomics (eMERGE), we tested 11 cancer-specific GRSs (bladder, breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, prostate, renal, and thyroid cancer) for association with the respective cancer type. Cancer-specific GRSs were calculated, for the first time in these cohorts, based on previously published risk-associated SNPs using the Caucasian subjects in these two cohorts.

RESULTS

Mean cancer-specific GRS in the population controls of eMERGE approximated the expected value of 1.00 (between 0.98 and 1.02) for all 11 types of cancer. Mean cancer-specific GRS was consistently higher in respective cancer patients than controls for all 11 types of cancer (P < 0.05). When subjects were categorized into low-, average-, and high-risk groups based on cancer-specific GRS (<0.5, 0.5-1.5, and >1.5, respectively), significant dose-response associations of higher cancer-specific GRS with higher OR of respective type of cancer were found for nine types of cancer (P_-trend  < 0.05). More than 64% subjects in the population controls of eMERGE can be classified as high risk for at least one type of these cancers.

CONCLUSION

Validity of GRS for predicting cancer risk is demonstrated for most types of cancer. If confirmed in larger studies, cancer-specific GRS may have the potential for developing personalized cancer screening strategy.

Large-Scale Genome-Wide Association Study of East Asians Identifies Loci Associated With Risk for Colorectal Cancer

BACKGROUND & AIMS

Genome-wide association studies (GWASs) have associated approximately 50 loci with risk of colorectal cancer (CRC)-nearly one third of these loci were initially associated with CRC in studies conducted in East Asian populations. We conducted a GWAS of East Asians to identify CRC risk loci and evaluate the generalizability of findings from GWASs of European populations to Asian populations.

METHODS

We analyzed genetic data from 22,775 patients with CRC (cases) and 47,731 individuals without cancer (controls) from 14 studies in the Asia Colorectal Cancer Consortium. First, we performed a meta-analysis of 7 GWASs (10,625 cases and 34,595 controls) and identified 46,554 promising risk variants for replication by adding them to the Multi-Ethnic Global Array (MEGA) for genotype analysis in 6445 cases and 7175 controls. These data were analyzed, along with data from an additional 5705 cases and 5961 controls genotyped using the OncoArray. We also obtained data from 57,976 cases and 67,242 controls of European descent. Variants at identified risk loci were functionally annotated and evaluated in correlation with gene expression levels.

RESULTS

A meta-analyses of all samples from people of Asian descent identified 13 loci and 1 new variant at a known locus (10q24.2) associated with risk of CRC at the genome-wide significance level of P < 5 × 10-8. We did not perform experiments to replicate these associations in additional individuals of Asian ancestry. However, the lead risk variant in 6 of these loci was also significantly associated with risk of CRC in European descendants. A strong association (44%-75% increase in risk per allele) was found for 2 low-frequency variants: rs201395236 at 1q44 (minor allele frequency, 1.34%) and rs77969132 at 12p11.21 (minor allele frequency, 1.53%). For 8 of the 13 associated loci, the variants with the highest levels of significant association were located inside or near the protein-coding genes L1TD1, EFCAB2, PPP1R21, SLCO2A1, HLA-G, NOTCH4, DENND5B, and GNAS. For other intergenic loci, we provided evidence for the possible involvement of the genes ALDH7A1, PRICKLE1, KLF5, WWOX, and GLP2R. We replicated findings for 41 of 52 previously reported risk loci.

CONCLUSIONS

We showed that most of the risk loci previously associated with CRC risk in individuals of European descent were also associated with CRC risk in East Asians. Furthermore, we identified 13 loci significantly associated with risk for CRC in Asians. Many of these loci contained genes that regulate the immune response, Wnt signaling to β-catenin, prostaglandin E2 catabolism, and cell pluripotency and proliferation. Further analyses of these genes and their variants is warranted, particularly for the 8 loci for which the lead CRC risk variants were not replicated in persons of European descent.

Gene pair based prognostic signature for colorectal colon cancer

BACKGROUND

The identification of high-risk colorectal cancer (CRC) patient is key to individualized treatment after surgery and reliable prognostic biomarkers are needed identifying high-risk CRC patients.

METHODS

We developed a gene pair based prognostic signature that could can the prognosis risk in patients with CRC. This study retrospectively analyzed 4 public CRC datasets, and 1123 patients with CRC were divided into a training cohort (n = 300) and 3 independent validation cohorts (n = 507, 226, and 90 patients).

RESULTS

A signature of 9 prognosis-related gene pairs (PRGPs) consisting of 17 unique genes was constructed. Then, a PRGP index (PRGPI) was constructed and divided patients into high- and low-risk groups according to the signature score. Patients in the high-risk group showed a poorer relapse-free survival than the low-risk group in both the training cohort [hazard ratio (HR) range, 4.6, 95% confidence interval (95% CI), 2.55-8.32; P < .0001] and meta-validation set (hazard ratio range, 4.09, 95% CI, 1.99-8.39; P < .0001). The PRGPI signature achieved a higher accuracy [mean concordance index (C-index): 0.6∼0.74] than a commercialized molecular signature (mean C-index, 0.48∼0.56) for estimation of relapse-free survival in comparable validation sets.

CONCLUSION

The gene pair based prognostic signature is a promising biomarker for estimating relapse-free survival of CRC.

Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative

Health systems are stewards of patient electronic health record (EHR) data with extraordinarily rich depth and breadth, reflecting thousands of diagnoses and exposures. Measures of genomic variation integrated with EHRs offer a potential strategy to accurately stratify patients for risk profiling and discover new relationships between diagnoses and genomes. The objective of this study was to evaluate whether polygenic risk scores (PRS) for common cancers are associated with multiple phenotypes in a phenome-wide association study (PheWAS) conducted in 28,260 unrelated, genotyped patients of recent European ancestry who consented to participate in the Michigan Genomics Initiative, a longitudinal biorepository effort within Michigan Medicine. PRS for 12 cancer traits were calculated using summary statistics from the NHGRI-EBI catalog. A total of 1,711 synthetic case-control studies was used for PheWAS analyses. There were 13,490 (47.7%) patients with at least one cancer diagnosis in this study sample. PRS exhibited strong association for several cancer traits they were designed for, including female breast cancer, prostate cancer, melanoma, basal cell carcinoma, squamous cell carcinoma, and thyroid cancer. Phenome-wide significant associations were observed between PRS and many non-cancer diagnoses. To differentiate PRS associations driven by the primary trait from associations arising through shared genetic risk profiles, the idea of "exclusion PRS PheWAS" was introduced. Further analysis of temporal order of the diagnoses improved our understanding of these secondary associations. This comprehensive PheWAS used PRS instead of a single variant.

A five-gene based risk score with high prognostic value in colorectal cancer

Colorectal cancer (CRC) is one of the most frequently occurring malignancies worldwide. The outcomes of patients with similar clinical symptoms or at similar pathological stages remain unpredictable. This inherent clinical diversity is most likely due to the genetic heterogeneity. The present study aimed to create a predicting tool to evaluate patient survival based on genetic profile. Firstly, three Gene Expression Omnibus (GEO) datasets (GSE9348, GSE44076 and GSE44861) were utilized to identify and validate differentially expressed genes (DEGs) in CRC. The GSE14333 dataset containing survival information was then introduced in order to screen and verify prognosis-associated genes. Of the 66 DEGs, the present study screened out 46 biomarkers closely associated to patient overall survival. By Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, it was demonstrated that these genes participated in multiple biological processes which were highly associated with cancer proliferation, drug-resistance and metastasis, thus further affecting patient survival. The five most important genes, MET proto-oncogene, receptor tyrosine kinase, carboxypeptidase M, serine hydroxymethyltransferase 2, guanylate cyclase activator 2B and sodium voltage-gated channel a subunit 9 were selected by a random survival forests algorithm, and were further made up to a linear risk score formula by multivariable cox regression. Finally, the present study tested and verified this risk score within three independent GEO datasets (GSE14333, GSE17536 and GSE29621), and observed that patients with a high risk score had a lower overall survival (P<0.05). Furthermore, this risk score was the most significant compared with other predicting factors including age and American Joint Committee on Cancer stage, in the model, and was able to predict patient survival independently and directly. The findings suggest that this survival associated DEGs-based risk score is a powerful and accurate prognostic tool and is promisingly implemented in a clinical setting.

Comparison of the efficiency of colorectal cancer screening programs based on age and genetic risk for reduction of colorectal cancer mortality

Given that colorectal cancer risk depends partly on inherited factors, screening program efficiency may be increased by incorporating genetic factors. We compared the efficiency of screening based on age and genetic risk in a simulated population. We simulated a population matching the size, age distribution and colorectal cancer incidence and mortality of Australia. We also simulated the distribution of genetic risk for colorectal cancer based on the expected number of inherited risk alleles of 45 single-nucleotide polymorphisms (SNPs) previously reported as associated with colorectal cancer. We compared the expected colorectal cancer deaths under three screening programs; age-based, genetic-based and combined age-based and genetic-based. The age-based program would prevent 25.4 deaths per 100 000 invited to screen, none of which would be under age 50; the genetic program would prevent 26.2 deaths per 100 000 invited to screen, 16 of which would be under age 50; and the combined program would prevent 24.4 deaths per 100 000 invited to screen, 16 of which would be under age 50. Genetic testing of 1.5 million 45-49 year olds would identify 91% of the people aged under 50 at sufficient risk to warrant screening, potentially saving 16 colorectal cancer deaths each year. Screening eligibility based on genetic risk profile for age is as efficient as eligibility based on age alone for preventing colorectal cancer mortality, but identifies an additional 7% of the population at sufficient risk to benefit from screening who would not normally be screened given they are aged under 50 years.

Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis

Molecular pathological epidemiology (MPE) is an integrative field that utilizes molecular pathology to incorporate interpersonal heterogeneity of a disease process into epidemiology. In each individual, the development and progression of a disease are determined by a unique combination of exogenous and endogenous factors, resulting in different molecular and pathological subtypes of the disease. Based on "the unique disease principle," the primary aim of MPE is to uncover an interactive relationship between a specific environmental exposure and disease subtypes in determining disease incidence and mortality. This MPE approach can provide etiologic and pathogenic insights, potentially contributing to precision medicine for personalized prevention and treatment. Although breast, prostate, lung, and colorectal cancers have been among the most commonly studied diseases, the MPE approach can be used to study any disease. In addition to molecular features, host immune status and microbiome profile likely affect a disease process, and thus serve as informative biomarkers. As such, further integration of several disciplines into MPE has been achieved (e.g., pharmaco-MPE, immuno-MPE, and microbial MPE), to provide novel insights into underlying etiologic mechanisms. With the advent of high-throughput sequencing technologies, available genomic and epigenomic data have expanded dramatically. The MPE approach can also provide a specific risk estimate for each disease subgroup, thereby enhancing the impact of genome-wide association studies on public health. In this article, we present recent progress of MPE, and discuss the importance of accounting for the disease heterogeneity in the era of big-data health science and precision medicine.