A genome wide association study on Newfoundland colorectal cancer patients' survival outcomes

Genetic Variants as Predictors of the Success of Colorectal Cancer Treatments

BACKGROUND

Some genetic polymorphisms (SNPs) have been proposed as predictors for different colorectal cancer (CRC) outcomes. This work aims to assess their performance in our cohort and find new SNPs associated with them.

METHODS

A total of 833 CRC cases were analyzed for seven outcomes, including the use of chemotherapy, and stratified by tumor location and stage. The performance of 63 SNPs was assessed using a generalized linear model and area under the receiver operating characteristic curve, and local SNPs were detected using logistic regressions.

RESULTS

In total 26 of the SNPs showed an AUC > 0.6 and a significant association (p < 0.05) with one or more outcomes. However, clinical variables outperformed some of them, and the combination of genetic and clinical data showed better performance. In addition, 49 suggestive (p < 5 × 10-6) SNPs associated with one or more CRC outcomes were detected, and those SNPs were located at or near genes involved in biological mechanisms associated with CRC.

CONCLUSIONS

Some SNPs with clinical data can be used in our population as predictors of some CRC outcomes, and the local SNPs detected in our study could be feasible markers that need further validation as predictors.

From Omic Layers to Personalized Medicine in Colorectal Cancer: The Road Ahead

Colorectal cancer is a major health concern since it is a highly diagnosed cancer and the second cause of death among cancers. Thus, the most suitable biomarkers for its diagnosis, prognosis, and treatment have been studied to improve and personalize the prevention and clinical management of colorectal cancer. The emergence of omic techniques has provided a great opportunity to better study CRC and make personalized medicine feasible. In this review, we will try to summarize how the analysis of the omic layers can be useful for personalized medicine and the existing difficulties. We will discuss how single and multiple omic layer analyses have been used to improve the prediction of the risk of CRC and its outcomes and how to overcome the challenges in the use of omic layers in personalized medicine.

Multifactor dimensionality reduction method identifies novel SNP interactions in the WNT protein interaction networks that are associated with recurrence risk in colorectal cancer

Background

Interactions among genetic variants are rarely studied but may explain a part of the variability in patient outcomes.

Objectives

In this study, we aimed to identify 1 to 3 way interactions among SNPs from five Wnt protein interaction networks that predict the 5-year recurrence risk in a cohort of stage I-III colorectal cancer patients.

Methods

423 patients recruited to the Newfoundland Familial Colorectal Cancer Registry were included. Five Wnt family member proteins (Wnt1, Wnt2, Wnt5a, Wnt5b, and Wnt11) were selected. The BioGRID database was used to identify the proteins interacting with each of these proteins. Genotypes of the SNPs located in the interaction network genes were retrieved from a genome-wide SNP genotype data previously obtained in the patient cohort. The GMDR 0.9 program was utilized to examine 1-, 2-, and 3-SNP interactions using a 5-fold cross validation step. Top GMDR 0.9 models were assessed by permutation testing and, if significant, prognostic associations were verified by multivariable logistic regression models.

Results

GMDR 0.9 has identified novel 1, 2, and 3-way SNP interactions associated with 5-year recurrence risk in colorectal cancer. Nine of these interactions were multi loci interactions (2-way or 3-way). Identified interaction models were able to distinguish patients based on their 5-year recurrence-free status in multivariable regression models. The significance of interactions was the highest in the 3-SNP models. Several of the identified SNPs were eQTLs, indicating potential biological roles of the genes they were associated with in colorectal cancer recurrence.

Conclusions

We identified novel interacting genetic variants that associate with 5-year recurrence risk in colorectal cancer. A significant portion of the genes identified were previously linked to colorectal cancer pathogenesis or progression. These variants and genes are of interest for future functional and prognostic studies. Our results provide further evidence for the utility of GMDR models in identifying novel prognostic biomarkers and the biological importance of the Wnt pathways in colorectal cancer.

Examining SNP-SNP interactions and risk of clinical outcomes in colorectal cancer using multifactor dimensionality reduction based methods

Background: SNP interactions may explain the variable outcome risk among colorectal cancer patients. Examining SNP interactions is challenging, especially with large datasets. Multifactor Dimensionality Reduction (MDR)-based programs may address this problem.

Objectives: 1) To compare two MDR-based programs for their utility; and 2) to apply these programs to sets of MMP and VEGF-family gene SNPs in order to examine their interactions in relation to colorectal cancer survival outcomes.

Methods: This study applied two data reduction methods, Cox-MDR and GMDR 0.9, to study one to three way SNP interactions. Both programs were run using a 5-fold cross validation step and the top models were verified by permutation testing. Prognostic associations of the SNP interactions were verified using multivariable regression methods. Eight datasets, including SNPs from MMP family genes (n = 201) and seven sets of VEGF-family interaction networks (n = 1,517 SNPs) were examined.

Results: ∼90 million potential interactions were examined. Analyses in the MMP and VEGF gene family datasets found several novel 1- to 3-way SNP interactions. These interactions were able to distinguish between the patients with different outcome risks (regression p-values 0.03–2.2E-09). The strongest association was detected for a 3-way interaction including CHRM3.rs665159_EPN1.rs6509955_PTGER3.rs1327460 variants.

Conclusion: Our work demonstrates the utility of data reduction methods while identifying potential prognostic markers in colorectal cancer.

Genome-wide association study identifies tumor anatomical site-specific risk variants for colorectal cancer survival

Identification of new genetic markers may improve the prediction of colorectal cancer prognosis. Our objective was to examine genome-wide associations of germline genetic variants with disease-specific survival in an analysis of 16,964 cases of colorectal cancer. We analyzed genotype and colorectal cancer-specific survival data from a consortium of 15 studies. Approximately 7.5 million SNPs were examined under the log-additive model using Cox proportional hazards models, adjusting for clinical factors and principal components. Additionally, we ran secondary analyses stratifying by tumor site and disease stage. We used a genome-wide p-value threshold of 5 × 10-8 to assess statistical significance. No variants were statistically significantly associated with disease-specific survival in the full case analysis or in the stage-stratified analyses. Three SNPs were statistically significantly associated with disease-specific survival for cases with tumors located in the distal colon (rs698022, HR = 1.48, CI 1.30-1.69, p = 8.47 × 10-9) and the proximal colon (rs189655236, HR = 2.14, 95% CI 1.65-2.77, p = 9.19 × 10-9 and rs144717887, HR = 2.01, 95% CI 1.57-2.58, p = 3.14 × 10-8), whereas no associations were detected for rectal tumors. Findings from this large genome-wide association study highlight the potential for anatomical-site-stratified genome-wide studies to identify germline genetic risk variants associated with colorectal cancer-specific survival. Larger sample sizes and further replication efforts are needed to more fully interpret these findings.

A comprehensive analysis of SNPs and CNVs identifies novel markers associated with disease outcomes in colorectal cancer

We aimed to examine the associations of a genome-wide set of single nucleotide polymorphisms (SNPs) and 254 copy number variations (CNVs) and/or insertion/deletions (INDELs) with clinical outcomes in colorectal cancer patients (n = 505). We also aimed to investigate whether their associations changed (e.g., appeared, diminished) over time. Multivariable Cox proportional hazards and piece-wise Cox regression models were used to examine the associations. The Cancer Genome Atlas (TCGA) datasets were used for replication purposes and to examine the gene expression differences between tumor and nontumor tissue samples. A common SNP (WBP11-rs7314075) was associated with disease-specific survival with P-value of 3.2 × 10^-8 . Association of this region with disease-specific survival was also detected in the TCGA patient cohort. Two expression quantitative trait loci (eQTLs) were identified in this locus that were implicated in the regulation of ERP27 expression. Interestingly, expression levels of ERP27 and WBP11 were significantly different between colorectal tumors and nontumor tissues. Three SNPs predicted the risk of recurrent disease only after 5 years postdiagnosis. Overall, our study identified novel variants, one of which also showed an association in the TCGA dataset, but no CNVs/INDELs, that associated with outcomes in colorectal cancer. Three SNPs were candidate predictors of long-term recurrence/metastasis risk.

Interaction between GALNT12 and C1GALT1 Associates with Galactose-Deficient IgA1 and IgA Nephropathy

BACKGROUND

Galactose-deficient IgA1 plays a key role in the pathogenesis of IgA nephropathy, the most common primary GN worldwide. Although serum levels of galactose-deficient IgA1 have a strong genetic component, the genetic link between this molecule and IgA nephropathy has not yet been clearly established.

METHODS

To identify novel loci associated with galactose-deficient IgA1, we performed a quantitative genome-wide association study for serum galactose-deficient IgA1 levels, on the basis of two different genome-wide association study panels conducted in 1127 patients with IgA nephropathy. To test genetic associations with susceptibility to IgA nephropathy, we also enrolled 2352 patients with biopsy-diagnosed IgA nephropathy and 2632 healthy controls. Peripheral blood samples from 59 patients and 27 healthy controls were also collected for gene expression analysis.

RESULTS

We discovered two loci, in C1GALT1 and GALNT12, that achieved genome-wide significance, explaining about 3.7% and 3.4% of variance in serum galactose-deficient IgA1 levels, respectively. We confirmed the previously reported association of C1GALT1 with serum galactose-deficient IgA1 levels, but with a different lead single-nucleotide polymorphism (rs10238682; β=0.26, P=1.20×10^-9); the locus we identified at GALNT12 (rs7856182; β=0.73, P=2.38×10^-9) was novel. Of more interest, we found that GALNT12 exhibits genetic interactions with C1GALT1 in both galactose-deficient IgA1 levels (P=1.40×10^-2) and disease risk (P=6.55×10^-3). GALNT12 mRNA expression in patients with IgA nephropathy was significantly lower compared with healthy controls.

CONCLUSIONS

Our data identify GALNT12 as a novel gene associated with galactose-deficient IgA1 and suggest novel genetic interactions. These findings support a key role of genetically conferred dysregulation of galactose-deficient IgA1 in the development of IgA nephropathy.

An in silico approach to identify and prioritize miRNAs target sites polymorphisms in colorectal cancer and obesity

Colorectal cancer (CRC) and obesity are linked clinical entities with a series of complex processes being engaged in their development. MicroRNAs (miRNAs) participate in these processes through regulating CRC and obesity‐related genes. This study aimed to develop an in silico approach to systematically identify and prioritize miRNAs target sites polymorphisms in obesity and CRC. Data from genome‐wide association studies (GWASs) were used to retrieve CRC and obesity‐associated variants. The polymorphisms that were resided in experimentally verified or computationally predicted miRNA target sites were retrieved and prioritized using a range of bioinformatics analyses. We found 6284 CRC and 38931 obesity unique variants. For CRC 33 haplotypes variants in 134 interactions were in miRNA targetome, while for obesity we found more than 935 unique interactions. Functionally prioritized SNPs revealed that, SNPs in 153 obesity and 50 CRC unique interactions were have disruptive effects on miRNA:mRNA integration by changing on target RNA secondary structure. Structural accessibility of target sites were decreased in 418 and 103 unique interactions and increased in 516 and 79 interactions, for obesity and CRC, respectively. The miRNA:mRNA hybrid stability was increased in 127 and 17 unique interactions and decreased in 33 and 24 interactions for the effect of obesity and CRC SNPs, respectively. In this study, seven SNPs with 15 interactions and three SNPs with four interactions were prioritized for obesity and CRC, respectively. These SNPs could be used for future studies for finding potential biomarkers for diagnoses, prognosis, or treatment of CRC and obesity.

The Relationship Between Tumor-Stroma Ratio, the Immune Microenvironment, and Survival in Patients With Spinal Chordoma

BACKGROUND

Currently, little is known about the clinical relevance of tumor-stroma ratio (TSR) in chordoma and data discussing the relationship between TSR and immune status of chordoma are lacking.

OBJECTIVE

To characterize TSR distribution in spinal chordoma, and investigated its correlation with clinicopathologic or immunological features of patients and outcome.

METHODS

TSR was assessed visually on hematoxylin and eosin-stained sections from 54 tumor specimens by 2 independent pathologists. Multiplex immunofluorescence was used to quantify the expression levels of microvessel density, Ki-67, Brachyury, and tumor as well as stromal PD-L1. Tumor immunity status including the Immunoscore and densities of tumor-infiltrating lymphocytes (TILs) subtypes were obtained from our published data and reanalyzed.

RESULTS

Bland-Altman plot showed no difference between mean TSR derived from the two observers. TSR was positively associated with stromal PD-L1 expression, the Immunoscore and CD3+ as well as CD4+ TILs density, but negatively correlated with tumor microvessel density, Ki-67 index, surrounding muscle invasion by tumor and number of Foxp3+ and PD-1+ TILs. Low TSR independently predicted poor local recurrence-free survival and overall survival. Moreover, patients with low TSR and low Immunoscore chordoma phenotype were associated with the worst survival. More importantly, combined TSR and Immunoscore accurately reflected prognosis and enhanced the ability of TSR or Immunoscore alone for outcome prediction.

CONCLUSION

These data reveal the significant impact of TSR on tumor progression and immunological response of patients. Subsequent use of agents targeting the stroma compartment may be an effective strategy to treat chordoma especially in combination with immune-based drugs.

A Comprehensive Study of the Effect on Colorectal Cancer Survival of Common Germline Genetic Variation Previously Linked with Cancer Prognosis

BACKGROUND

Germline genetic variants may influence pathways of tumor progression common to multiple cancer types. Here, we investigated the association between survival after colorectal cancer diagnosis and 128 common genetic variants previously associated with prognosis in genome-wide association studies in different cancer types.

METHODS

We studied survival outcomes in a large well-documented, prospective, population-based cohort (5,675 patients with colorectal cancer) with up to 20 years' follow-up.

RESULTS

None of the 128 variants were significantly associated with overall or colorectal cancer-specific survival (P < 5 × 10-4, Bonferroni-corrected threshold). We observed suggestive evidence (P < 0.05) for eight variants (rs17026425, rs17057166, rs6854845, rs1728400, rs17693104, rs202280, rs6797464, and rs823920) in all colorectal cancer and two variants (rs17026425 and rs6854845) in rectal cancer that were concordant with previous reports.

CONCLUSIONS

Given good statistical power (>0.80 for 75% of variants), this study indicates that most previously reported variants associated with cancer survival have limited influence on colorectal cancer prognosis.

IMPACT

Although small effects cannot be excluded, clinically meaningful germline influences on patients with colorectal cancer as a group are unlikely.

The Genetics and Genomics of Asthma

Asthma is a common, clinically heterogeneous disease with strong evidence of heritability. Progress in defining the genetic underpinnings of asthma, however, has been slow and hampered by issues of inconsistency. Recent advances in the tools available for analysis-assaying transcription, sequence variation, and epigenetic marks on a genome-wide scale-have substantially altered this landscape. Applications of such approaches are consistent with heterogeneity at the level of causation and specify patterns of commonality with a wide range of alternative disease traits. Looking beyond the individual as the unit of study, advances in technology have also fostered comprehensive analysis of the human microbiome and its varied roles in health and disease. In this article, we consider the implications of these technological advances for our current understanding of the genetics and genomics of asthma.

The SNP of rs6854845 suppresses transcription via the DNA looping structure alteration of super-enhancer in colon cells

Single-nucleotide polymorphisms (SNPs) identified by Genome-Wide Association Studies (GWASs) have been determined to closely connect with multiple diseases. Previous studies revealed one underlying mechanism that SNPs located within the regulatory elements could affect the encoding gene expression through long-range regulation. SNP rs6854845 was suggested to be a risk of colon cancer in human population. Nevertheless, the underlying molecular mechanism for colon carcinogenesis remains largely unknown. In present study, rs6854845 with G > T mutation in situ in FHC, HCT-116 and SW-480 cells were generated by Crispr/Cas9. The nearby chromatin organization was investigated by chromatin conformation capture (3C). And the expression of coding gene regulated by super-enhancer (SE) was detected by real-time PCR. We observed a significantly different pattern of the genome organization upon rs6854845 generation in colon epithelial cells but not in colon cancer cells. Moreover, we observed the shifted enrichment of H3K4me1 and H3K27ac at the SE (chr4:75.7M-76.0 M) where rs6854845 located. Furthermore, we observed that the transcription of the gene clusters regulated by SE were affected by rs6854845 in colon cells. Overall, our results demonstrated that SNP rs6854845 located in SE could destroy the long-range chromosomal interaction between SE and target gene clusters thereby affecting the transcription of these genes.

A genome-wide association study identifies single nucleotide polymorphisms associated with time-to-metastasis in colorectal cancer

Background

Differentiating between cancer patients who will experience metastasis within a short time and who will be long-term survivors without metastasis is a critical aim in healthcare. The microsatellite instability (MSI)-high tumor phenotype is such a differentiator in colorectal cancer, as patients with these tumors are unlikely to experience metastasis. Our aim in this study was to determine if germline genetic variations could further differentiate colorectal cancer patients based on the long-term risk and timing of metastasis.

Methods

The patient cohort consisted of 379 stage I-III Caucasian colorectal cancer patients with microsatellite stable or MSI-low tumors. We performed univariable analysis on 810,622 common single nucleotide polymorphisms (SNPs) under different genetic models. Depending on the long-term metastasis-free survival probability estimates, we applied a mixture cure model, Cox proportional hazards regression model, or log-rank test. For SNPs reaching Bonferroni-corrected significance (p < 6.2 × 10^− 8) having valid genetic models, multivariable analysis adjusting for significant baseline characteristics was conducted.

Results

After adjusting for significant baseline characteristics, specific genotypes of ten polymorphisms were significantly associated with time-to-metastasis. These polymorphisms are three intergenic SNPs, rs5749032 (p = 1.28 × 10^− 10), rs2327990 (p = 9.59 × 10^− 10), rs1145724 (p = 3 × 10^− 8), and seven SNPs within the non-coding sequences of three genes: FHIT (p = 2.59 × 10^− 9), EPHB1 (p = 8.23 × 10^− 9), and MIR7515 (p = 4.87 × 10^− 8).

Conclusions

Our results suggest novel associations of specific genotypes of SNPs with early metastasis in Caucasian colorectal cancer patients. These associations, once replicated in other patient cohorts, could assist in the development of personalized treatment strategies for colorectal cancer patients.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5346-5) contains supplementary material, which is available to authorized users.

Associations of single nucleotide polymorphisms with mucinous colorectal cancer: genome-wide common variant and gene-based rare variant analyses

Background

Colorectal cancer has significant impact on individuals and healthcare systems. Many genes have been identified to influence its pathogenesis. However, the genetic basis of mucinous tumor histology, an aggressive subtype of colorectal cancer, is currently not well-known. This study aimed to identify common and rare genetic variations that are associated with the mucinous tumor phenotype.

Methods

Genome-wide single nucleotide polymorphism (SNP) data was investigated in a colorectal cancer patient cohort (n = 505). Association analyses were performed for 729,373 common SNPs and 275,645 rare SNPs. Common SNP association analysis was performed using univariable and multivariable logistic regression under different genetic models. Rare-variant association analysis was performed using a multi-marker test.

Results

No associations reached the traditional genome-wide significance. However, promising genetic associations were identified. The identified common SNPs significantly improved the discriminatory accuracy of the model for mucinous tumor phenotype. Specifically, the area under the receiver operating characteristic curve increased from 0.703 (95% CI: 0.634–0.773) to 0.916 (95% CI: 0.873–0.960) when considering the most significant SNPs. Additionally, the rare variant analysis identified a number of genetic regions that potentially contain causal rare variants associated with the mucinous tumor phenotype.

Conclusions

This is the first study applying both common and rare variant analyses to identify genetic associations with mucinous tumor phenotype using a genome-wide genotype data. Our results suggested novel associations with mucinous tumors. Once confirmed, these results will not only help us understand the biological basis of mucinous histology, but may also help develop targeted treatment options for mucinous tumors.

Electronic supplementary material

The online version of this article (10.1186/s40364-018-0133-z) contains supplementary material, which is available to authorized users.

Two functional indel polymorphisms in the promoter region of the Brahma gene (BRM) and disease risk and progression-free survival in colorectal cancer

Background and objective

The Brahma gene (BRM) encodes a catalytic ATPase subunit of the Switch/Sucrose non-fermentable (SWI/SNF) complex, which modulates gene expression and many important cellular processes. Two indel polymorphisms in the promoter region of BRM (BRM-741 and BRM-1321) are associated with its reduced expression and the risk of susceptibility or survival outcomes in multiple solid cancers. In this study, we have examined these variants in relation to susceptibility and survival outcomes in colorectal cancer.

Methods

Genotypes were obtained using TaqMan assays in 427 cases and 408 controls. Multivariate logistic and Cox regression models were fitted to examine the associations of the BRM-741 and BRM-1321 genotypes adjusting for relevant covariates. Sub-group analyses based on tumor location and patient sex were also performed. In all analyses, indels were examined individually as well as in combination.

Results

Our results showed that there was no association between the BRM polymorphisms and the risk of colorectal cancer. However, genotype combinations of the BRM-741 and BRM-1321 variants were associated with the risk of colon cancer. Particularly, patients having at least one variant allele had increased risk of colon cancer when compared to patients with the double wild-type genotype. In the survival analyses, BRM-741 heterozygosity was associated with longer progression-free survival time in the colorectal cancer patients. A stronger association was detected in the male patients under the recessive genetic model where the homozygosity for the variant allele of BRM-741 was associated with shorter progression-free survival time.

Conclusions

Our analyses suggest that BRM-741 and BRM-1321 indels are associated with the risk of developing colon cancer and the BRM-741 indel is associated with the disease progression in colorectal cancer patients, especially in the male patients. Although our results show a different relationship between these indels and colorectal cancer compared to other cancer sites, they also suggest that BRM and its promoter variants may have biological roles in susceptibility and survival outcomes in colorectal cancers. Performing further analyses in additional and larger cohorts are needed to confirm our conclusions.

Germline INDELs and CNVs in a cohort of colorectal cancer patients: their characteristics, associations with relapse-free survival time, and potential time-varying effects on the risk of relapse

INDELs and CNVs are structural variations that may play roles in cancer susceptibility and patient outcomes. Our objectives were a) to computationally detect and examine the genome‐wide INDEL/CNV profiles in a cohort of colorectal cancer patients, and b) to examine the associations of frequent INDELs/CNVs with relapse‐free survival time. We also identified unique variants in 13 Familial Colorectal Cancer Type X (FCCX) cases. The study cohort consisted of 495 colorectal cancer patients. QuantiSNP and PennCNV algorithms were utilized to predict the INDELs/CNVs using genome‐wide signal intensity data. Duplex PCR was used to validate predictions for 10 variants. Multivariable Cox regression models were used to test the associations of 106 common variants with relapse‐free survival time. Score test and the multivariable Cox proportional hazards models with time‐varying coefficients were applied to identify the variants with time‐varying effects on the relapse‐free survival time. A total of 3486 distinct INDELs/CNVs were identified in the patient cohort. The majority of these variants were rare (83%) and deletion variants (81%). The results of the computational predictions and duplex PCR results were highly concordant (93–100%). We identified four promising variants significantly associated with relapse‐free survival time (P < 0.05) in the multivariable Cox proportional hazards regression models after adjustment for clinical factors. More importantly, two additional variants were identified to have time‐varying effects on the risk of relapse. Finally, 58 rare variants were identified unique to the FCCX cases; none of them were detected in more than one patient. This is one of the first genome‐wide analyses that identified the germline INDEL/CNV profiles in colorectal cancer patients. Our analyses identified novel variants and genes that can biologically affect the risk of relapse in colorectal cancer patients. Additionally, for the first time, we identified germline variants that can potentially be early‐relapse markers in colorectal cancer.

No associations of a set of SNPs in the Vascular Endothelial Growth Factor (VEGF) and Matrix Metalloproteinase (MMP) genes with survival of colorectal cancer patients

In this study, we aimed to investigate the associations of genetic variations within select genes functioning in angiogenesis, lymph‐angiogenesis, and metastasis pathways and the risk of outcome in colorectal cancer patients. We followed a two‐stage analysis: First, 381 polymorphisms from 30 genes (eight Vascular Endothelial Growth Factor (VEGF) and 22 Matrix Metalloproteinase [MMP] genes) were investigated in the discovery cohort (n = 505). Then, 16 polymorphisms with the lowest P‐value in this analysis were investigated in a separate replication cohort (n = 247). Genotypes were obtained using the Illumina^® HumanOmni‐1‐Quad (discovery cohort) and Sequenom MassArray^® (replication cohort) platforms. The primary outcome measure was overall survival (OS). Kaplan–Meier, univariate and multivariable Cox regression methods were used to test the associations between genotypes and OS. Four SNPs (rs12365082, rs11225389, rs11225388, and rs2846707) had the univariate analysis P < 0.05 in both the discovery and replication cohorts. These SNPs are in linkage disequilibrium with each other to varying extent and are located in the MMP8 and MMP27 genes. In the multivariable analysis adjusting for age, stage, and microsatellite instability status, three of these SNPs (rs12365082, rs11225389, rs11225388) were independent predictors of OS (P < 0.05) in the discovery cohort. However, the same analysis in the replication cohort did not yield statistically significant results. Overall, while the genetic variations in the VEGF and MMP genes are attractive candidates as prognostic markers, our study showed no evidence of associations of a large set of SNPs in these genes and overall survival of colorectal cancer patients in our study.