Diet and colorectal cancer: analysis of a candidate pathway using SNPS, haplotypes, and multi-gene assessment

Thioredoxin reductase 3 suppression promotes colitis and carcinogenesis via activating pyroptosis and necrosis

BACKGROUND

Txnrd3 as selenoprotein plays key roles in antioxidant process and sperm maturation. Inflammatory bowel diseases, such as ulcerative colitis and Crohn's disease, are becoming significantly increasing disease worldwide in recent years which are proved relative to diet, especially selenium intake.

METHODS

In the present study, 8-week-old C57BL/6N male Txnrd3-/-, Txnrd3-/ + , Txnrd3 + / + mice, weight 25-30 g, were randomly chosen and each group with 30 mice. Feed 3.5% DSS drinking water and normal water continuously for 7 days. Mouse colon cancer cells (CT26) were cultured in vitro to establish Txnrd3 overexpressed/knocked-down model by cell transfection technology. Morphology and ultrastructure, calcium levels, ROS level, cell death were observed and detected in vivo and vitro.

RESULTS

In Txnrd3-/-mice, ulcerative colitis was more severe, the morphological and ultrastructural lesions were also more prominent compared with wild-type mice, accompanied by the significantly increased expression of NLRP3, Caspase1, RIPK3, and MLKL. Overexpression of Txnrd3 could lead to increased oxidative stress through intracellular calcium outflow-induced oxidative stress increase followed by necrosis and pyroptosis pathway activation and further inhibit the growth and proliferation of colon cancer cells.

CONCLUSION

Txnrd3 overexpression leads to intracellular calcium outflow and increased ROS, which eventually leads to necrosis and focal death of colon cancer cells, while causing Txnrd3-/- mice depth of the crypt deeper, weakened intestinal secretion and immune function and aggravate the occurrence of ulcerative colitis. The present study lays a foundation for the prevention and treatment of ulcerative colitis and colon carcinoma in clinic treatment.

Polymorphisms in the mTOR-PI3K-Akt pathway, energy balance-related exposures and colorectal cancer risk in the Netherlands Cohort Study

BACKGROUND

The mTOR-PI3K-Akt pathway influences cell metabolism and (malignant) cell growth. We generated sex-specific polygenic risk scores capturing natural variation in 7 out of 10 top-ranked genes in this pathway. We studied the scores directly and in interaction with energy balance-related factors (body mass index (BMI), trouser/skirt size, height, physical activity, and early life energy restriction) in relation to colorectal cancer (CRC) risk in the Netherlands Cohort Study (NLCS) (n=120,852). The NLCS has a case-cohort design and 20.3 years of follow-up. Participants completed a baseline questionnaire on diet and cancer in 1986 when 55-69 years old. ~75% of the cohort returned toenail clippings used for DNA isolation and genotyping (n subcohort=3,793, n cases=3,464). To generate the scores, the dataset was split in two and risk alleles were defined and weighted based on sex-specific associations with CRC risk in the other dataset half, because there were no SNPs in the top-ranked genes associated with CRC risk in previous genome-wide association studies at a significance level p<1*10^-5.

RESULTS

Cox regression analyses showed positive associations between the sex-specific polygenic risk scores and colon but not rectal cancer risk in men and women, with hazard ratios for continuously modeled scores close to 1.10. There was no modifying effect observed of the scores on associations between the energy balance-related factors and CRC risk. However, BMI (in men), non-occupational physical activity (in women), and height (in men and women) were associated with the risk of CRC, in particular (proximal and distal) colon cancer, in the direction as expected in the lower tertiles of the sex-specific polygenic risk scores.

CONCLUSIONS

Current data suggest that the mTOR-PI3K-Akt pathway may be involved in colon cancer development. This study thereby sheds more light on colon cancer etiology through use of genetic variation in the mTOR-PI3K-Akt pathway.

A 6 lncRNA-Based Risk Score System for Predicting the Recurrence of Colon Adenocarcinoma Patients

Colon adenocarcinoma (COAD) is a common type of colon cancer, and post-operative recurrence and metastasis may occur in COAD patients. This study is designed to build a risk score system for COAD patients. The Cancer Genome Atlas (TCGA) dataset of COAD (the training set) was downloaded, and GSE17538 and GSE39582 (the validation sets) from Gene Expression Omnibus database were obtained. The differentially expressed RNAs (DERs) were analyzed by limma package. Using survival package, the independent prognosis-associated long non-coding RNAs (lncRNAs) were selected for constructing risk score system. After the independent clinical prognostic factors were screened out using survival package, a nomogram survival model was constructed using rms package. Furthermore, competitive endogenous RNA (ceRNA) regulatory network and enrichment analyses separately were performed using Cytoscape software and DAVID tool. Totally 404 DERs between recurrence and non-recurrence groups were identified. Based on the six independent prognosis-associated lncRNAs (including H19, KCNJ2-AS1, LINC00899, LINC01503, PRKAG2-AS1, and SRRM2-AS1), the risk score system was constructed. After the independent clinical prognostic factors (Pathologic M, pathologic T, and RS model status) were identified, the nomogram survival model was built. In the ceRNA regulatory network, there were three lncRNAs, four miRNAs, and 77 mRNAs. Additionally, PPAR signaling pathway and hedgehog signaling pathway were enriched for the mRNAs in the ceRNA regulatory network. The risk score system and the nomogram survival model might be used for predicting COAD recurrence. Besides, PPAR signaling pathway and hedgehog signaling pathway might affect the recurrence of COAD patients.

Association of Selenoprotein and Selenium Pathway Genotypes with Risk of Colorectal Cancer and Interaction with Selenium Status

Selenoprotein genetic variations and suboptimal selenium (Se) levels may contribute to the risk of colorectal cancer (CRC) development. We examined the association between CRC risk and genotype for single nucleotide polymorphisms (SNPs) in selenoprotein and Se metabolic pathway genes. Illumina Goldengate assays were designed and resulted in the genotyping of 1040 variants in 154 genes from 1420 cases and 1421 controls within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Multivariable logistic regression revealed an association of 144 individual SNPs from 63 Se pathway genes with CRC risk. However, regarding the selenoprotein genes, only TXNRD1 rs11111979 retained borderline statistical significance after adjustment for correlated tests (PACT = 0.10; PACT significance threshold was P < 0.1). SNPs in Wingless/Integrated (Wnt) and Transforming growth factor (TGF) beta-signaling genes (FRZB, SMAD3, SMAD7) from pathways affected by Se intake were also associated with CRC risk after multiple testing adjustments. Interactions with Se status (using existing serum Se and Selenoprotein P data) were tested at the SNP, gene, and pathway levels. Pathway analyses using the modified Adaptive Rank Truncated Product method suggested that genes and gene x Se status interactions in antioxidant, apoptosis, and TGF-beta signaling pathways may be associated with CRC risk. This study suggests that SNPs in the Se pathway alone or in combination with suboptimal Se status may contribute to CRC development.

Stepwise approach to SNP-set analysis illustrated with the Metabochip and colorectal cancer in Japanese Americans of the Multiethnic Cohort

BACKGROUND

Common variants have explained less than the amount of heritability expected for complex diseases, which has led to interest in less-common variants and more powerful approaches to the analysis of whole-genome scans. Because of low frequency (low statistical power), less-common variants are best analyzed using SNP-set methods such as gene-set or pathway-based analyses. However, there is as yet no clear consensus regarding how to focus in on potential risk variants following set-based analyses. We used a stepwise, telescoping approach to analyze common- and rare-variant data from the Illumina Metabochip array to assess genomic association with colorectal cancer (CRC) in the Japanese sub-population of the Multiethnic Cohort (676 cases, 7180 controls). We started with pathway analysis of SNPs that are in genes and pathways having known mechanistic roles in colorectal cancer, then focused on genes within the pathways that evidenced association with CRC, and finally assessed individual SNPs within the genes that evidenced association. Pathway SNPs downloaded from the dbSNP database were cross-matched with Metabochip SNPs and analyzed using the logistic kernel machine regression approach (logistic SNP-set kernel-machine association test, or sequence kernel association test; SKAT) and related methods.

RESULTS

The TGF-β and WNT pathways were associated with all CRC, and the WNT pathway was associated with colon cancer. Individual genes demonstrating the strongest associations were TGFBR2 in the TGF-β pathway and SMAD7 (which is involved in both the TGF-β and WNT pathways). As partial validation of our approach, a known CRC risk variant in SMAD7 (in both the TGF-β and WNT pathways: rs11874392) was associated with CRC risk in our data. We also detected two novel candidate CRC risk variants (rs13075948 and rs17025857) in TGFBR2, a gene known to be associated with CRC risk.

CONCLUSIONS

A stepwise, telescoping approach identified some potentially novel risk variants associated with colorectal cancer, so it may be a useful method for following up on results of set-based SNP analyses. Further work is required to assess the statistical characteristics of the approach, and additional applications should aid in better clarifying its utility.

Genetic variants and traits related to insulin-like growth factor-I and insulin resistance and their interaction with lifestyles on postmenopausal colorectal cancer risk

Genetic variants and traits in metabolic signaling pathways may interact with lifestyle factors such as obesity, physical activity, and exogenous estrogen (E), influencing postmenopausal colorectal cancer (CRC) risk, but these interrelated pathways are not fully understood. In this case-cohort study, we examined 33 single-nucleotide polymorphisms (SNPs) in genes related to insulin-like growth factor-I (IGF-I)/ insulin resistance (IR) traits and signaling pathways, using data from 704 postmenopausal women in Women’s Health Initiative Observation ancillary studies. Stratifying by the lifestyle modifiers, we assessed the effects of IGF-I/IR traits (fasting total and free IGF-I, IGF binding protein-3, insulin, glucose, and homeostatic model assessment–insulin resistance) on CRC risk as a mediator or influencing factor. Six SNPs in the INS, IGF-I, and IGFBP3 genes were associated with CRC risk, and those associations differed between non-obese/active and obese/inactive women and between E nonusers and users. Roughly 30% of the cancer risk due to the SNP was mediated by IGF-I/IR traits. Likewise, carriers of 11 SNPs in the IRS1 and AKT1/2 genes (signaling pathway–related genetic variants) had different associations with CRC risk between strata, and the proportion of the SNP–cancer association explained by traits varied from 30% to 50%. Our findings suggest that IGF-I/IR genetic variants interact with obesity, physical activity, and exogenous E, altering postmenopausal CRC risk, through IGF-I/IR traits, but also through different pathways. Unraveling gene–phenotype–lifestyle interactions will provide data on potential genetic targets in clinical trials for cancer prevention and intervention strategies to reduce CRC risk.

Effect of genetic variants and traits related to glucose metabolism and their interaction with obesity on breast and colorectal cancer risk among postmenopausal women

BACKGROUND

Impaired glucose metabolism-related genetic variants and traits likely interact with obesity and related lifestyle factors, influencing postmenopausal breast and colorectal cancer (CRC), but their interconnected pathways are not fully understood. By stratifying via obesity and lifestyles, we partitioned the total effect of glucose metabolism genetic variants on cancer risk into two putative mechanisms: 1) indirect (risk-associated glucose metabolism genetic variants mediated by glucose metabolism traits) and 2) direct (risk-associated glucose metabolism genetic variants through pathways other than glucose metabolism traits) effects.

METHOD

Using 16 single-nucleotide polymorphisms (SNPs) associated with glucose metabolism and data from 5379 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies, we retrospectively assessed the indirect and direct effects of glucose metabolism-traits (fasting glucose, insulin, and homeostatic model assessment-insulin resistance [HOMA-IR]) using two quantitative tests.

RESULTS

Several SNPs were associated with breast cancer and CRC risk, and these SNP-cancer associations differed between non-obese and obese women. In both strata, the direct effect of cancer risk associated with the SNP accounted for the majority of the total effect for most SNPs, with roughly 10% of cancer risk due to the SNP that was from an indirect effect mediated by glucose metabolism traits. No apparent differences in the indirect (glucose metabolism-mediated) effects were seen between non-obese and obese women. It is notable that among obese women, 50% of cancer risk was mediated via glucose metabolism trait, owing to two SNPs: in breast cancer, in relation to GCKR through glucose, and in CRC, in relation to DGKB/TMEM195 through HOMA-IR.

CONCLUSIONS

Our findings suggest that glucose metabolism genetic variants interact with obesity, resulting in altered cancer risk through pathways other than those mediated by glucose metabolism traits.

Sirolimus and Everolimus Pathway: Reviewing Candidate Genes Influencing Their Intracellular Effects

Sirolimus (SRL) and everolimus (EVR) are mammalian targets of rapamycin inhibitors (mTOR-I) largely employed in renal transplantation and oncology as immunosuppressive/antiproliferative agents. SRL was the first mTOR-I produced by the bacterium Streptomyces hygroscopicus and approved for several medical purposes. EVR, derived from SRL, contains a 2-hydroxy-ethyl chain in the 40th position that makes the drug more hydrophilic than SRL and increases oral bioavailability. Their main mechanism of action is the inhibition of the mTOR complex 1 and the regulation of factors involved in a several crucial cellular functions including: protein synthesis, regulation of angiogenesis, lipid biosynthesis, mitochondrial biogenesis and function, cell cycle, and autophagy. Most of the proteins/enzymes belonging to the aforementioned biological processes are encoded by numerous and tightly regulated genes. However, at the moment, the polygenic influence on SRL/EVR cellular effects is still not completely defined, and its comprehension represents a key challenge for researchers. Therefore, to obtain a complete picture of the cellular network connected to SRL/EVR, we decided to review major evidences available in the literature regarding the genetic influence on mTOR-I biology/pharmacology and to build, for the first time, a useful and specific “SRL/EVR genes-focused pathway”, possibly employable as a starting point for future in-depth research projects.

Gene-diet interactions and their impact on colorectal cancer risk

A number of studies have evaluated the role of gene-diet interaction in the etiology of colorectal cancer (CRC). Historically, these studies focused on established dietary risk factors and genes involved in their metabolism. However, results from these candidate gene studies were inconsistent, possibly due to multiple testing and publication bias. In recent years, genome-wide association studies have identified a number of CRC susceptibility loci, and subsequent meta-analyses have observed limited evidence that diet may modify the risk associated with these susceptibility loci. Statistical techniques have been recently developed to evaluate the presence of interaction across the entire genome; results from these genome-wide studies have demonstrated limited evidence of interaction and have failed to replicate results from candidate gene studies and those using established susceptibility loci. However, larger sample sizes are likely needed to elucidate modest or weak interaction in genome-wide studies of gene-diet interaction.

Epidemiological transition of colorectal cancer in developing countries: Environmental factors, molecular pathways, and opportunities for prevention

Colorectal cancer (CRC) is one of the leading causes of cancer and cancer-related mortality worldwide. The disease has been traditionally a major health problem in industrial countries, however the CRC rates are increasing in the developing countries that are undergoing economic growth. Several environmental risk factors, mainly changes in diet and life style, have been suggested to underlie the rise of CRC in these populations. Diet and lifestyle impinge on nuclear receptors, on the intestinal microbiota and on crucial molecular pathways that are implicated in intestinal carcinogenesis. In this respect, the epidemiological transition in several regions of the world offers a unique opportunity to better understand CRC carcinogenesis by studying the disease phenotypes and their environmental and molecular associations in different populations. The data from these studies may have important implications for the global prevention and treatment of CRC.

Association of mTOR polymorphisms with cancer risk and clinical outcomes: a meta-analysis

Genetic polymorphisms in mTOR gene may be associated with cancer risk and clinical outcomes of cancer patients by affecting mTOR gene expression or its activation. However, inconsistent results have been reported. The aim of this study is to systematically evaluate the association between mTOR polymorphisms (rs2295080, rs2536 and rs11121704) and cancer risk as well as clinical outcome by a meta-analysis. We identified 10 eligible studies and extracted data by two investigators. Based on dominant and recessive models, odds ratio (ORs) and 95% confidence intervals (CIs) were calculated by using Stata, version 11 to evaluate the association strength. Our meta-analysis results showed that the wild genotype TT of rs2295080 polymorphism was associated with increased cancer risk under dominant model (OR = 1.24, 95%CI: 1.12–1.36, p<0.0005) in Chinese but not with clinical outcome parameters, while the TT genotype of rs11121704 was associated with poor clinical outcome parameters (OR = 1.53, 95%CI: 1.01–2.32, p = 0.044), such as death, metastasis and resistance to chemotherapy. However, rs2536 may not influence cancer susceptibility. In conclusion, this meta-analysis indicated the common polymorphisms in mTOR gene might be genetic risk factors for the carcinogenesis and clinical outcomes of cancer patients. However, further investigation on large population and different ethnicities are warranted.