SULT1A1 gene deletion in BRCA2-associated male breast cancer: a link between genes and environmental exposures?

The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases

The recent advances in gene chip technology have led to the identification of multiple metabolism-related genes that are closely associated with colorectal cancer (CRC). Nevertheless, none of these genes could accurately diagnose or predict CRC. The prognosis of CRC has been made by previous prognostic models constructed by using multiple genes, however, the predictive function of multi-gene prognostic models using metabolic genes for the CRC prognosis remains unexplored. In this study, we used the TCGA-CRC cohort as the test dataset and the GSE39582 cohort as the experimental dataset. Firstly, we constructed a prognostic model using metabolic genes from the TCGA-CRC cohort, which were also associated with CRC prognosis. We analyzed the advantages of the prognostic model in the prognosis of CRC and its regulatory mechanism of the genes associated with the model. Secondly, the outcome of the TCGA-CRC cohort analysis was validated using the GSE39582 cohort. We found that the prognostic model can be employed as an independent prognostic risk factor for estimating the CRC survival rate. Besides, compared with traditional clinical pathology, it can precisely predict CRC prognosis as well. The high-risk group of the prognostic model showed a substantially lower survival rate as compared to the low-risk group. In addition, gene enrichment analysis of metabolic genes showed that genes in the prognostic model are enriched in metabolism and cancer-related pathways, which may explain its underlying mechanism. Our study identified a novel metabolic profile containing 11 genes for prognostic prediction of CRC. The prognostic model may unravel the imbalanced metabolic microenvironment, and it might promote the development of biomarkers for predicting treatment response and streamlining metabolic therapy in CRC.

Relationship of SULT1A1 copy number variation with estrogen metabolism and human health

Human cytosolic sulfotransferase 1A1 (SULT1A1) is considered to be one of the most important SULT isoforms for metabolism, detoxification, and carcinogenesis. This theory is driven by observations that SULT1A1 is widely expressed in multiple tissues and acts on a wide range of phenolic substrates. SULT1A1 is subject to functional common copy number variation (CNV) including deletions or duplications. However, it is less clear how SULT1A1 CNV impacts health and disease. To better understand the biological role of SULT1A1 in human health, we genotyped CNV in 14,275 Marshfield Clinic patients linked to an extensive electronic health record. Since SULT1A1 is linked to steroid metabolism, select serum steroid hormones were measured in 100 individuals with a wide spectrum of SULT1A1 CNV genotypes. Furthermore, comprehensive phenome-wide association studies (PheWAS) were conducted using diagnostic codes and clinical text data. For the first time, individuals homozygous null for SULT1A1 were identified in a human population. Thirty-six percent of the population carried >2 copies of SULT1A1 whereas 4% had ≤1 copy. Results indicate SULT1A1 CNV was negatively correlated with estrone-sulfate to estrone ratio predominantly in males (E1S/E1; p=0.03, r=-0.21) and may be associated with increased risk for common allergies. The effect of SULT1A1 CNV on circulating estrogen metabolites was opposite to the predicted CNV-metabolite trend based on enzymatic function. This finding, and the potential association with common allergies reported herein, warrants future studies.

Expression analysis of E-cad and vascular endothelial growth factor in triple-negative breast cancer patients of different ethnic groups in western China

The aim of this article is to investigate the expression of E-cadherin (E-cad) and vascular endothelial growth factor (VEGF) in triple-negative breast cancer (TNBC) of Han and Uygur women patients in western China, and their relationship with clinical features of TNBC.Totally, 172 cases of Han TNBC patients and 79 cases of Uighur TNBC patients were enrolled. The expressions of E-cad and VEGF were detected with immunohistochemistry. The correlation of E-cad and VEGF expression with lymph node metastasis, TNM stage, and histological grade were analyzed. The 5-year disease-free survival rate of the 2 groups was also evaluated.There was no significant difference in the 5-year disease-free survival rate (P > .05) and the expression of E-cad between the 2 groups. The positive rate of VEGF in Han was significantly lower than that in Uygur (P < .05). The expression of E-cad was negatively correlated with lymph node metastasis, TNM stage, and histological grade (-1≤r < 1, P < .05). However, the expression of VEGF was positively correlated with lymph node metastasis and TNM staging (0 < r < 1, P < 0.05), but not with histological grading.The expression of E-cad and VEGF and their relationship with clinical features of TNBC suggest that Uygur TNBC patients might have different prognostic factors as compared with Han patients.

Association of SULT1A1 Arg²¹³His polymorphism with male breast cancer risk: results from a multicenter study in Italy

Male breast cancer (MBC) is rare and poorly understood. Like female breast cancer (FBC), MBCs are highly sensitive to hormonal changes, and hyperestrogenism, specifically, represents a major risk factor for MBC. MBC is considered similar to late-onset, post-menopausal estrogen/progesteron receptors positive FBC (ER+/PR+). Sulfotransferase 1A1 (SULT1A1) is an enzyme involved in the metabolism of estrogens. Recently, SULT1A1 common functional polymorphism Arg(213)His (638G>A) variant has been found to be associated with increased breast cancer (BC) risk, particularly in post-menopausal women. For this reason, we decided to explore whether SULT1A1 Arg(213)His could exert an effect on MBC development. The primary aim of this study was to evaluate the influence of the SULT1A1 Arg(213)His polymorphism on MBC risk. The secondary aim was to investigate possible associations with relevant clinical-pathologic features of MBC. A total of 394 MBC cases and 786 healthy male controls were genotyped for SULT1A1 Arg(213)His polymorphism by PCR-RFLP and high-resolution melting analysis. All MBC cases were characterized for relevant clinical-pathologic features. A significant difference in the distribution of SULT1A1 Arg(213)His genotypes was found between MBC cases and controls (P < 0.0001). The analysis of genotype-specific risk showed a significant increased MBC risk in individuals with G/A (OR 1.97, 95% CI 1.50-2.59; P < 0.0001) and A/A (OR 3.09, 95% CI 1.83-5.23; P < 0.0001) genotypes in comparison to wild-type genotype, under co-dominant model. A significant association between SULT1A1 risk genotypes and HER2 status emerged. Results indicate that SULT1A1 Arg(213)His may act as a low-penetrance risk allele for developing MBC and could be associated with a specific tumor subtype associated with HER2 overexpression.

Pharmacogenetics of SULT1A1

Cytosolic SULT1A1 participates in the bioconversion of a plethora of endogenous and xenobiotic substances. Genetic variation in this important enzyme such as SNPs can vary by ethnicity and have functional consequences on its activity. Most SULT1A1 genetic variability studies have been centered on the SULT1A1*1/2 SNP. Highlighted here are not only this SNP, but other genetic variants associated with SULT1A1 that could modify drug efficacy and xenobiotic metabolism. Some studies have investigated how differential metabolism of xenobiotic substances influences susceptibility to or protection from cancer in multiple sites. This review will focus primarily on the impact of SULT1A1 genetic variation on the response to anticancer therapeutic agents and subsequently how it relates to environmental and dietary exposure to both cancer-causing and cancer-preventative compounds.

Application of Machine Learning to Development of Copy Number Variation-based Prediction of Cancer Risk

In the present study, recurrent copy number variations (CNVs) from non-tumor blood cell DNAs of Caucasian non-cancer subjects and glioma, myeloma, and colorectal cancer-patients, and Korean non-cancer subjects and hepatocellular carcinoma, gastric cancer, and colorectal cancer patients, were found to reveal for each of the two ethnic cohorts highly significant differences between cancer patients and controls with respect to the number of CN-losses and size-distribution of CN-gains, suggesting the existence of recurrent constitutional CNV-features useful for prediction of predisposition to cancer. Upon identification by machine learning, such CNV-features could extensively discriminate between cancer-patient and control DNAs. When the CNV-features selected from a learning-group of Caucasian or Korean mixed DNAs consisting of both cancer-patient and control DNAs were employed to make predictions on the cancer predisposition of an unseen test group of mixed DNAs, the average prediction accuracy was 93.6% for the Caucasian cohort and 86.5% for the Korean cohort.