Screening for differentially expressed genes between left- and right-sided colon carcinoma by microarray analysis

MicroRNA-34 and gastrointestinal cancers: a player with big functions

It is commonly assumed that gastrointestinal cancer is the most common form of cancer across the globe and is the leading contributor to cancer-related death. The intricate mechanisms underlying the growth of GI cancers have been identified. It is worth mentioning that both non-coding RNAs (ncRNAs) and certain types of RNA, such as circular RNAs (circRNAs), long non-coding RNAs (lncRNAs), and microRNAs (miRNAs), can have considerable impact on the development of gastrointestinal (GI) cancers. As a tumour suppressor, in the group of short non-coding regulatory RNAs is miR-34a. miR-34a silences multiple proto-oncogenes at the post-transcriptional stage by targeting them, which inhibits all physiologically relevant cell proliferation pathways. However, it has been discovered that deregulation of miR-34a plays important roles in the growth of tumors and the development of cancer, including invasion, metastasis, and the tumor-associated epithelial-mesenchymal transition (EMT). Further understanding of miR-34a's molecular pathways in cancer is also necessary for the development of precise diagnoses and effective treatments. We outlined the most recent research on miR-34a functions in GI cancers in this review. Additionally, we emphasize the significance of exosomal miR-34 in gastrointestinal cancers.

DLK2 Acts as a Potential Prognostic Biomarker for Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis

Clear cell renal cell carcinoma (ccRCC) is the most common RCC subtype with a high mortality. It has been reported that delta-like 1 homologue (DLK1) participates in the tumor microenvironmental remodeling of ccRCC, but the relationship between delta-like 2 homologue (DLK2, a DLK1 homologue) and ccRCC is still unclear. Thus, this study aims to investigate the role of DLK2 in the biological function and disease prognosis of ccRCC using bioinformatics analysis. The TNMplot database showed that DLK2 was upregulated in ccRCC tissues. From the UALCAN analysis, the overexpression of DLK2 was associated with advanced stage and high grade in ccRCC. Moreover, the Kaplan-Meier plotter (KM Plotter) database showed that DLK2 upregulation was associated with poor survival outcome in ccRCC. By the LinkedOmics analysis, DLK2 signaling may participated in the modulation of ccRCC extracellular matrix (ECM), cell metabolism, ribosome biogenesis, TGF-β signaling and Notch pathway. Besides, Tumor Immune Estimation Resource (TIMER) analysis showed that the macrophage and CD8⁺ T cell infiltrations were associated with good prognosis in ccRCC patients. Finally, DLK2 overexpression was associated with the reduced macrophage recruitments and the M1–M2 polarization of macrophage in ccRCC tissues. Together, DLK2 may acts as a novel biomarker, even therapeutic target in ccRCC. However, this study lacks experimental validation, and further studies are required to support this viewpoint.

FCGBP Is a Prognostic Biomarker and Associated With Immune Infiltration in Glioma

The Fc Fragment of IgG Binding Protein (FCGBP) has been proven to participate in intestinal tumor immunity. However, the biological role of FCGBP has remained unclear in glioma. The differential expression of FCGBP was explored by Oncomine and GEPIA databases. The effect of FCGBP on prognosis was analyzed via Kaplan–Meier plotter and GEPIA. The Tumor Immune Estimation Resource (TIMER) tool was used to determine the correlations of FCGBP expression with tumor immune infiltration. Firstly, FCGBP was highly expressed in glioma and correlated with a worse prognosis. Gene Ontology (GO) and KEGG pathway enrichment analyses revealed that the differentially expressed genes (DEGs) and co-expression genes of FCGBP were mainly involved in the immune response. Furthermore, FCGBP expression was positively associated with multiple immune cells infiltrates as well as the expression levels of multiple immune markers in glioma. FCGBP co-expression networks mostly participated in the regulation of immune response. Finally, immunohistochemistry (IHC) assays were conducted to explore the expression of FCGBP, PD-L1, CCL2 and CD8 in glioma and correlations between them. We found that PDL1 and FCGBP were synchronously upregulated in glioma tissues. These findings revealed a new mechanism by which FCGBP participates in the immune tolerance of glioma, and implied the potential of FCGBP as a therapeutic target or predictive marker for patients.

CK1BP Reduces α-Synuclein Oligomerization and Aggregation Independent of Serine 129 Phosphorylation

The pathological accumulation of α-Synuclein (α-Syn) is the hallmark of neurodegenerative α-synucleinopathies, including Parkinsons's disease (PD). In contrast to the mostly non-phosphorylated soluble α-Syn, aggregated α-Syn is usually phosphorylated at serine 129 (S129). Therefore, S129-phosphorylation is suspected to interfere with α-Syn aggregation. Among other kinases, protein kinase CK1 (CK1) is known to phosphorylate α-Syn at S129. We overexpressed CK1 binding protein (CK1BP) to inhibit CK1 kinase activity. Using Bimolecular Fluorescence Complementation (BiFC) in combination with biochemical methods, we monitored the S129 phosphorylation and oligomerization of α-Syn in HEK293T cells. We found that CK1BP reduced the overall protein levels of α-Syn. Moreover, CK1BP concomitantly reduced S129 phosphorylation, oligomerization and the amount of insoluble α-Syn. Analyzing different α-Syn variants including S129 mutations, we show that the effects of CK1BP on α-Syn accumulation were independent of S129 phosphorylation. Further analysis of an aggregating polyglutamine (polyQ) protein confirmed a phosphorylation-independent decrease in aggregation. Our results imply that the inhibition of CK1 activity by CK1BP might exert beneficial effects on NDDs in general. Accordingly, CK1BP represents a promising target for the rational design of therapeutic approaches to cease or at least delay the progression of α-synucleinopathies.

Prognostic and immunological roles of Fc fragment of IgG binding protein in colorectal cancer

Valuable diagnostic and prognostic biomarkers are urgently needed for colorectal cancer (CRC), which is one of the leading causes of mortality worldwide. Previous studies have reported altered expression of a mucin-like protein Fc fragment of IgG binding protein (FCGBP) in various types of cancer, but its potential diagnostic, prognostic and immunological roles in CRC remain to be determined. Therefore, the aim of current study was to investigate the potential roles of FCGBP in CRC. The present study investigated FCGBP mutations and changes in its expression levels using a combination of microarray and public dataset analyses, as well as immunohistochemistry. The results demonstrated a 10.5% mutation frequency in the FCGBP coding sequence in CRC tissues, and identified decreased FCGBP mRNA or protein expression levels in colorectal adenoma and CRC (compared with those in normal colorectal tissues from healthy control subjects), including pathologically advanced CRC (stage III+IV vs. I+II). Survival analysis using the GEPIA and Kaplan-Meier Plotter databases revealed that low FCGBP expression levels were associated with short overall, disease-free, relapse-free and event-free survival times in patients with CRC. Notably, analysis using the online Tumor IMmune Estimation Resource database revealed a positive correlation between FCGBP expression levels and the extent of infiltrating immune cells, such as B cells and dendritic cells. Consistently, the expression levels of most markers (51/57) for various types of immune cells were significantly correlated with FCGBP expression levels in CRC tissues. These findings suggested that FCGBP may serve as a diagnostic and prognostic biomarker, and that FCGBP may be associated with immune infiltration in CRC.

Discovering the molecular differences between right- and left-sided colon cancer using machine learning methods

Background

In recent years, the differences between left-sided colon cancer (LCC) and right-sided colon cancer (RCC) have received increasing attention due to the clinicopathological variation between them. However, some of these differences have remained unclear and conflicting results have been reported.

Methods

From The Cancer Genome Atlas (TCGA), we obtained RNA sequencing data and gene mutation data on 323 and 283 colon cancer patients, respectively. Differential analysis was firstly done on gene expression data and mutation data between LCC and RCC, separately. Machine learning (ML) methods were then used to select key genes or mutations as features to construct models to classify LCC and RCC patients. Finally, we conducted correlation analysis to identify the correlations between differentially expressed genes (DEGs) and mutations using logistic regression (LR) models.

Results

We found distinct gene mutation and expression patterns between LCC and RCC patients and further selected the 30 most important mutations and 17 most important gene expression features using ML methods. The classification models created using these features classified LCC and RCC patients with high accuracy (areas under the curve (AUC) of 0.8 and 0.96 for mutation and gene expression data, respectively). The expression of PRAC1 and BRAF V600E mutation (rs113488022) were the most important feature for each model. Correlations of mutations and gene expression data were also identified using LR models. Among them, rs113488022 was found to have significance relevance to the expression of four genes, and thus should be focused on in further study.

Conclusions

On the basis of ML methods, we found some key molecular differences between LCC and RCC, which could differentiate these two groups of patients with high accuracy. These differences might be key factors behind the variation in clinical features between LCC and RCC and thus help to improve treatment, such as determining the appropriate therapy for patients.

MicroRNAs Associated With Colon Cancer: New Potential Prognostic Markers and Targets for Therapy

MicroRNAs (miRNAs) are a kind of non-coding RNA (ncRNA) that regulate the expression of target genes and play a role in the occurrence and development of cancers. Colon cancer (COAD) is the second most common cause of cancer-related mortality. However, the prognostic value of miRNAs in COAD is still confusing. In this study, we obtain miRNAs and messenger RNAs (mRNAs) expression profiles of COAD from the Cancer Genome Atlas (TCGA) database. After preliminary data screening and preprocessing, we acquire the expression data of 894 miRNAs and 17,019 mRNAs. Then, compared with the normal samples, 39 upregulated miRNAs and 54 downregulated miRNAs are identified by differential expression analysis. Furthermore, we obtain 1,487 upregulated mRNAs and 2,847 downregulated mRNAs. We confirm nine key miRNAs related to the survival rate of COAD patients. Moreover, by using bioinformatics methods, we get 461 common genes from both the target genes of these nine key miRNAs and differentially expressed mRNAs. Through analyzing the protein-protein interaction (PPI) network of these 461 common genes and survival analysis, we confirm five hub genes as promising biomarkers for COAD prognosis. It is worth mentioning that no previous reports have found that PGR and KCNB1 are related to COAD. We expect these key miRNAs and hub genes will provide a new way for the study of COAD.

Silencing of synaptotagmin 13 inhibits tumor growth through suppressing proliferation and promoting apoptosis of colorectal cancer cells

The treatment of colorectal cancer is currently hampered by the lack of early detection technology. The identification of molecular biomarkers for colorectal cancer is crucial for improving prognosis. Synaptotagmin (SYT) 13 has been reported to be associated with several human tumors, but its role in colorectal cancer remains elusive. In the present study, immunohistochemistry was utilized to detect the expression of SYT13 in colorectal cancer tissues and cells. MTT, colony formation, wound healing and Transwell assays were conducted to evaluate the effect of SYT13 knockdown on the biological behavior of RKO and HCT116 cells. Cell apoptosis and cell cycle profiles were detected by FACS. A mouse xenograft model was constructed to investigate the effect of SYT13 on colorectal cancer in vivo. The results indicated that SYT13 was upregulated in colorectal tumor tissues compared with paracancerous tissues. Silencing of SYT13 inhibited the proliferation, colony formation, migration and invasion ability of RKO and HCT116 cells. Moreover, SYT13 knockdown arrested the cell cycle in the G2 phase, thus inducing cell apoptosis. The in vivo experiments also demonstrated the inhibitory effect of SYT13 on tumor growth. In conclusion, the present study demonstrated that SYT13 may act as a promoter in the development and progression of colorectal cancer and, therefore, may be of value as a target for the development of novel treatment strategies.

miRNA-34a suppresses colon carcinoma proliferation and induces cell apoptosis by targeting SYT1

BACKGROUND

MicroRNAs are emerging as the important regulators in cancer-related processes. This research were performed to find the function and mechanism of miR-34a effect on colon cancer.

METHODS

In this study, we examined the expression of miR-34a in colon cancer tissues and cell lines by qRT-PCR. In vitro cell functional assays studies were built to define miR-34a and SYT1 function involved in cell growth, migration, and invasion and apoptosis. EGFP reporter assay was used to determine the relationship of SYT1 and miR-181a. To confirmed the relationship between SYT1 and miR-34a, the SYT1 restoration rescued miR-34a mediated growth and inhibited cell apoptosis were detect.

RESULT

Our studies show that microRNA-34a (miR-34a) is downregulated in human colon cancer relative to normal colon mucosal epithelial cells, and downexpression of miR-34a promotes cell proliferation, migration, and invasion, nevertheless overexpression of miR-34 facilitates cell apoptosis in vitro. Furthermore, SYT1 3'-UTR is found to be down-regulated directly by miR-34a, demonstrating that SYT1 is a important target of miR-34a in colon cancer. The knockdown of SYT1 markedly inhibits colon cancer cell proliferation, migration, and invasion, and induces cell apoptosis, indicating that SYT1 may function as an oncogene in colon cancer. The restoration of SYT1 expression can counteract the effect of miR-34a on cell proliferation, and induces cell apoptosis, of colon cancer cells.

CONCLUSION

Together, these results indicate that miR-34a is a new regulator of SYT1, and both miR-34a and SYT1 play the important roles in the pathogenesis of colon cancer.

Chromogranin-A Expression as a Novel Biomarker for Early Diagnosis of Colon Cancer Patients

Colon cancer is one of the major causes of cancer death worldwide. The five-year survival rate for the early-stage patients is more than 90%, and only around 10% for the later stages. Moreover, half of the colon cancer patients have been clinically diagnosed at the later stages. It is; therefore, of importance to enhance the ability for the early diagnosis of colon cancer. Taking advantages from our previous studies, there are several potential biomarkers which have been associated with the early diagnosis of the colon cancer. In order to investigate these early diagnostic biomarkers for colon cancer, human chromogranin-A (CHGA) was further analyzed among the most powerful diagnostic biomarkers. In this study, we used a logistic regression-based meta-analysis to clarify associations of CHGA expression with colon cancer diagnosis. Both healthy populations and the normal mucosa from the colon cancer patients were selected as the double normal controls. The results showed decreased expression of CHGA in the early stages of colon cancer as compared to the normal controls. The decline of CHGA expression in the early stages of colon cancer is probably a new diagnostic biomarker for colon cancer diagnosis with high predicting possibility and verification performance. We have also compared the diagnostic powers of CHGA expression with the typical oncogene KRAS, classic tumor suppressor TP53, and well-known cellular proliferation index MKI67, and the CHGA showed stronger ability to predict early diagnosis for colon cancer than these other cancer biomarkers. In the protein-protein interaction (PPI) network, CHGA was revealed to share some common pathways with KRAS and TP53. CHGA might be considered as a novel, promising, and powerful biomarker for early diagnosis of colon cancer.

The impact of resection margin on overall survival for patients with colon cancer liver metastasis varied according to the primary cancer location

INTRODUCTION

Investigation into right and left-sided primary colon liver metastasis (CLM) has revealed differences in the tumor biology and prognosis. This indicates that preoperative and operative factors may affect outcomes of right-sided primary CLM differently than left. This retrospective analysis investigated the effects of resection margin stratified by left and right-sided primary CLM on overall survival (OS) for patients undergoing hepatectomy.

METHODS

A total of 732 patients undergoing hepatic resection for CLM at the Cleveland Clinic and Johns Hopkins were identified between 2002 and 2016. Clinically significant variables were analyzed using Cox proportional hazard regression. The cohort was then divided into patients with right and left-sided CLM and analyzed separately using Kaplan Meier analysis and Cox proportional hazard regression.

RESULTS

Cox proportional hazard regression showed that left-sided CLM with an R0 margin was a statistically significant predictor of OS even after controlling for other important factors (HR = 0.629, P = 0.024) but right-sided CLM with R0 margin was not (HR = 0.788, P = 0.245). Kaplan-Meier analysis demonstrated that patients with a left-sided CLM and R0 margin had the best prognosis (P = 0.037).

CONCLUSION

Surgical margin is an important prognostic factor for left-sided primary CLM but tumor biology may override surgical technique for right-sided CLM.

Association of specific gene mutations derived from machine learning with survival in lung adenocarcinoma

Lung cancer is the second most common cancer in the United States and the leading cause of mortality in cancer patients. Biomarkers predicting survival of patients with lung cancer have a profound effect on patient prognosis and treatment. However, predictive biomarkers for survival and their relevance for lung cancer are not been well known yet. The objective of this study was to perform machine learning with data from The Cancer Genome Atlas of patients with lung adenocarcinoma (LUAD) to find survival-specific gene mutations that could be used as survival-predicting biomarkers. To identify survival-specific mutations according to various clinical factors, four feature selection methods (information gain, chi-squared test, minimum redundancy maximum relevance, and correlation) were used. Extracted survival-specific mutations of LUAD were applied individually or as a group for Kaplan-Meier survival analysis. Mutations in MMRN2 and GMPPA were significantly associated with patient mortality while those in ZNF560 and SETX were associated with patient survival. Mutations in DNAJC2 and MMRN2 showed significant negative association with overall survival while mutations in ZNF560 showed significant positive association with overall survival. Mutations in MMRN2 showed significant negative association with disease-free survival while mutations in DRD3 and ZNF560 showed positive associated with disease-free survival. Mutations in DRD3, SETX, and ZNF560 showed significant positive association with survival in patients with LUAD while the opposite was true for mutations in DNAJC2, GMPPA, and MMRN2. These gene mutations were also found in other cohorts of LUAD, lung squamous cell carcinoma, and small cell lung cancer. In LUAD of Pan-Lung Cancer cohort, mutations in GMPPA, DNAJC2, and MMRN2 showed significant negative associations with survival of patients while mutations in DRD3 and SETX showed significant positive association with survival. In this study, machine learning was conducted to obtain information necessary to discover specific gene mutations associated with the survival of patients with LUAD. Mutations in the above six genes could predict survival rate and disease-free survival rate in patients with LUAD. Thus, they are important biomarker candidates for prognosis.

Differential expression of DUSP2 in left- and right-sided colon cancer is associated with poor prognosis in colorectal cancer

Dual-specificity phosphatase-2 (DUSP2), a negative regulator of extracellular-regulated kinase activity, has been identified as an important kinase with emerging roles in cancer. However, the clinical significance of DUSP2 in colorectal cancer (CRC) remains to be fully elucidated. In the present study, the expression of DUSP2 was investigated using immunohistochemistry in 96 patients with CRC. Cell viability was estimated using a cell counting kit-8 assay, and cell apoptosis by flow cytometry. The relationship between DUSP2 expression and patient characteristics, including overall survival, were studied retrospectively in these patients. It was found that DUSP2 was differentially expressed between left-sided colon carcinoma (LSCC) and right-sided colon carcinoma (RSCC). It was also found that decreased expression of DUSP2 was correlated with significantly shorter overall survival (P=0.001) and short distant-metastasis-free survival (P=0.002). In univariate comparisons, the decreased expression of DUSP2 was found to be an independent risk factor for poor survival rate (HR 3.55, CI 1.092-9.896; P=0.002). It was also found that the enforced overexpression of DUSP2 sensitized CRC cells to cetuximab. In conclusion, the findings demonstrated that DUSP2 was differentially expressed between RSCC and LSCC, and that the overexpression of DUSP2 increased the inhibitory effect of cetuximab in CRC, suggesting that DUSP2 may be a novel biomarker and therapeutic target in CRC therapy.

Exome sequencing of synchronously resected primary colorectal tumours and colorectal liver metastases to inform oncosurgical management

BACKGROUND

Next generation sequencing technology has facilitated mapping of the colorectal cancer genotype and furthered our understanding of metastogenesis. The aim of this study was to investigate for conserved and different mutations in the exomes of synchronously resected primary colorectal tumour and liver metastases. This information could potentially be utilised to guide the treatment of advanced disease with the help of biological information from the primary tumour.

METHODS

We performed exome sequencing of synchronously resected primary colorectal cancer and colorectal liver metastases as well as normal colonic mucosa and liver parenchyma, from four patients who had received neo-adjuvant chemotherapy, at a depth of 50X using the Ion Proton platform. Raw data was mapped to the reference genome prior to variant calling, annotation and downstream analysis.

RESULTS

Exome sequencing identified 585 non-synonymous missense single nucleotide variants (SNVs), of which 215 (36.8%) were unique to the primary tumour, 226 (38.6%) unique to the metastasis and 81 (13.8%) present in patient matched pairs. SNVs identified in the ErbB pathway appear to be concordant between primary and metastatic tumours.

CONCLUSION

Only 13.8% of the metastatic exome can be predicted by the genotype of the primary tumour. We have demonstrated concordance of a number of SNVs in the ErbB pathway, which may inform selection of therapeutic agents in advanced colorectal cancer.

Synaptotagmin-7 is overexpressed in hepatocellular carcinoma and regulates hepatocellular carcinoma cell proliferation via Chk1-p53 signaling

Background

Synaptotagmin-7 (Syt-7) is a member of the synaptotagmin (Syt) family, which plays an important role in many physiological and pathological processes. However, to the best of our knowledge, there is no study describing its function in tumors, particularly in hepatocellular carcinoma (HCC). Therefore, in this study, we examined the role of Syt-7 in HCC and attempted to elucidate its underlying mechanism.

Materials and methods

We examined the expression levels of Syt-7 in HCC cell lines and normal hepatocytes by real-time quantitative polymerase chain reaction analysis. The effects of Syt-7 knockdown on in vitro cell growth were assessed by Celigo image cytometry, MTT assay, colony formation assay, and cell cycle analysis. In vivo tumorigenesis was evaluated using a nude mouse model. The underlying molecular mechanism was evaluated using a PathScan Stress Signaling Antibody Array.

Results

Syt-7 mRNA levels were highly expressed in Huh-7 and Hep3B cells; moderately expressed in SMMC-7721, HepG2, and BEL-7402 cells; and lowly expressed in normal hepatocytes L-O2. Functional experiments demonstrated that Syt-7 knockdown significantly suppressed cell proliferation and induced cell cycle arrest by increasing phosphorylation of Chk1 and p53. Furthermore, Syt-7 knockdown remarkably reduced the growth of xenograft tumors in mice.

Conclusion

The results of this study suggest that Syt-7 plays a vital role in tumorigenesis and in the development of HCC. Syt-7 can be used as a new diagnostic and therapeutic target in HCC.

Differences of protein expression profiles, KRAS and BRAF mutation, and prognosis in right-sided colon, left-sided colon and rectal cancer

To compare protein expression levels, gene mutation and survival among Right-Sided Colon Cancer (RSCC), Left-Sided Colon Cancer (LSCC) and rectal cancer patients, 57 cases of RSCC, 87 LSCC and 145 rectal cancer patients were included retrospectively. Our results demonstrated significant differences existed among RSCC, LSCC and rectal cancer regarding tumor diameter, differentiation, invasion depth and TNM stage. No significant difference was identified in expression levels of MLH1, MSH2, MSH6, PMS2, β-Tubulin III, P53, Ki67 and TOPIIα, and gene mutation of KRAS and BRAF among three groups. Progression Free Survival (PFS) of RSCC was significantly lower than that of LRCC and rectal cancer. In univariate analyses, RSCC, preoperative chemoradiotherapy, poor differentiation, advanced TNM stage, elevated serum CEA and CA19-9 level, tumor deposit, perineural and vascular invasion were found to be predictive factors of shorter PFS. In multivariate analyses, only differentiation and TNM stages were found to be independent predictors of PFS. In conclusion, compared with LSCC and rectal cancer, RSCC has larger tumor size, poor differentiation, advanced TNM stage and shorter survival. The shorter survival in RSCC might be attributed to the advanced tumor stage caused by its inherent position feature of proximal colon rather than genetic difference.

Copy number variation analysis reveals additional variants contributing to endometriosis development

PURPOSE

Endometriosis is a gynecological disease influenced by multiple genetic and environmental factors. The aim of the current study was to use SNP-array technology to identify genomic aberrations that may possibly contribute to the development of endometriosis.

METHODS

We performed an SNP-array genotyping of pooled DNA samples from both patients (n = 100) and controls (n = 50). Copy number variation (CNV) calling and association analyses were performed using PennCNV software. MLPA and TaqMan Copy-Number assays were used for validation of CNVs discovered.

RESULTS

We detected 49 CNV loci that were present in patients with endometriosis and absent in the control group. After validation procedures, we confirmed six CNV loci in the subtelomeric regions, including 1p36.33, 16p13.3, 19p13.3, and 20p13, representing gains, while 17q25.3 and 20q13.33 showed losses. Among the intrachromosomal regions, our results revealed duplication at 19q13.1 within the FCGBP gene (p = 0.007).

CONCLUSIONS

We identified CNVs previously associated with endometriosis, together with six suggestive novel loci possibly involved in this disease. The intergenic locus on chromosome 19q13.1 shows strong association with endometriosis and is under further functional investigation.

Genetic variants within obesity-related genes are associated with tumor recurrence in patients with stages II/III colon cancer

OBJECTIVE

Obesity is an established risk factor for colorectal cancer (CRC) incidence and it is also linked to CRC recurrence and survival. Polymorphisms located in obesity-related genes are associated with an increased risk of developing several cancer types including CRC. We evaluated whether single-nucleotide polymorphisms in obesity-related genes may predict tumor recurrence in colon cancer patients.

MATERIALS AND METHODS

Genotypes were obtained from germline DNA from 207 patients with stage II or III colon cancer at the Norris Comprehensive Cancer Center. Nine polymorphisms in eight obesity-related genes (PPAR, LEP, NFKB, CD36, DRG1, NGAL, REGIA, and DSCR1) were evaluated. The primary endpoint of the study was the 3-year recurrence rate. Positive associations were also tested in an independent Japanese cohort of 350 stage III CRC patients.

RESULTS

In univariate analysis, for PPARrs1801282, patients with a CC genotype had significantly lower recurrence probability (29 ± 4% SE) compared with patients with a CG genotype (48 ± 8% SE) [hazard ratio (HR): 1.77; 95% confidence interval (CI), 1.01-3.10; P = 0.040]. For DSCR1rs6517239, patients with an AA genotype had higher recurrence probability than patients carrying at least one allele G (37 ± 4% SE vs. 15 ± 6% SE) (HR: 0.51; 95% CI, 0.27-0.94; P = 0.027). This association was stronger in the patients bearing a left-sided tumor (HR: 0.34; 95% CI, 0.13-0.88; P = 0.018). In the Japanese cohort, no associations were found.

CONCLUSION

This hypothesis-generating study suggests a potential influence of polymorphisms within obesity-related genes in the recurrence probability of colon cancer. These interesting results should be evaluated further.