Correlations between 13 Trace Elements and Circulating Tumor Cells in Patients with Colorectal Cancer in Guangzhou, China

Research on the Effect and Mechanism of Selenium on Colorectal Cancer Through TRIM32

The intake of selenium (Se) in the human body is negatively correlated with the risk of colorectal cancer (CRC), but its mechanism in the occurrence and development of CRC is not clear. This study aimed to evaluate the therapeutic effect of Se on CRC, and explore the anti-tumor effect of Se supplementation on CRC and its molecular mechanism. In this study, we utilized colony formation assay, cell scratch test, Transwell migration, and flow cytometry to assess cell proliferation, migration, and apoptosis. Our findings demonstrate that Se effectively suppresses the growth and proliferation of CRC cell lines HCT116 and SW480 and promoting cellular apoptosis. In vivo experiments demonstrated a significant inhibitory effect of Se on tumor growth. CRC-related datasets were extracted from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases for differential expression analysis of TRIM32 and survival analysis. We found that TRIM32 was highly expressed in tumor tissues of CRC patients and correlated with a poor prognosis. Furthermore, through RNA sequencing analysis, we identified TRIM32 as a gene that was significantly decreased after Se treatment in HCT116 cells. This finding was subsequently validated by Western blot results. Moreover, TRIM32 knockdown combined with Se treatment significantly inhibited cell growth proliferation and migration and further induced apoptosis of colorectal cancer cells. In conclusion, our findings provided evidence that Se inhibited the growth of colorectal cancer cells by down-regulating TRIM32.

The role of heavy metals in the development of colorectal cancer

OBJECTIVE

To investigate the relationship among 18 heavy metals, microsatellite instability (MSI) status, ERCC1, XRCC1 (rs25487), BRAF V600E and 5 tumor markers and their role in the development of colorectal cancer (CRC).

METHODS

A total of 101 CRC patients and 60 healthy controls were recruited in the present study. The levels of 18 heavy metals were measured by ICP-MS. MSI status and the genetic polymorphism were determined by PCR (FP205-02, Tiangen Biochemical Technology Co., Ltd., Beijing, China) and Sanger sequencing. Spearman's rank correlation was used to analyze the relationship among various factors.

RESULTS

The level of selenium (Se) was lower in the CRC group compared with the control group (p < 0.01), while vanadium (V), arsenic (As), tin (Sn), barium (Ba) and lead (Pb) were higher (p < 0.05), chromium (Cr) and copper (Cu) were significantly higher (p < 0.0001) in the CRC group than those in the control group. Multivariate logistic regression analysis indicated that Cr, Cu, As and Ba were the risk factors for CRC. In addition, CRC was positively correlated with V, Cr, Cu, As, Sn, Ba and Pb, but negatively correlated with Se. MSI was positively correlated with BRAF V600E, but negatively correlated with ERCC1. BRAF V600E was positively correlated with antimony (Sb), thallium (Tl), CA19-9, NSE, AFP and CK19. XRCC1 (rs25487) was found to be positively correlated with Se but negatively correlated with Co. The levels of Sb and Tl were significantly higher in the BRAF V600E positive group compared to the negative group. The mRNA expression level of ERCC1 was significantly higher (P = 0.035) in MSS compared to MSI. And there was a significant correlation between XRCC1 (rs25487) polymorphism and MSI status (P<0.05).

CONCLUSION

The results showed that low level of Se and high levels of V, As, Sn, Ba, Pb, Cr, and Cu increased the risk of CRC. Sb and Tl may cause BRAF V600E mutations, leading to MSI. XRCC1 (rs25487) was positively correlated with Se but negatively correlated with Co. The expression of ERCC1 may be related to MSS, while the XRCC1 (rs25487) polymorphism is related to MSI.

Recent advances in the application of metallomics in diagnosis and prognosis of human cancer

Metals play a critical role in human health and diseases. In recent years, metallomics has been introduced and extensively applied to investigate the distribution, regulation, function, and crosstalk of metal(loid) ions in various physiological and pathological processes. Based on high-throughput multielemental analytical techniques and bioinformatics methods, it is possible to elucidate the correlation between the metabolism and homeostasis of diverse metals and complex diseases, in particular for cancer. This review aims to provide an overview of recent progress made in the application of metallomics in cancer research. We mainly focuses on the studies about metallomic profiling of different human biological samples for several major types of cancer, which reveal distinct and dynamic patterns of metal ion contents and the potential benefits of using such information in the detection and prognosis of these malignancies. Elevated levels of copper appear to be a significant risk factor for various cancers, and each type of cancer has a unique distribution of metals in biofluids, hair/nails, and tumor-affected tissues. Furthermore, associations between genetic variations in representative metalloprotein genes and cancer susceptibility have also been demonstrated. Overall, metallomics not only offers a better understanding of the relationship between metal dyshomeostasis and the development of cancer but also facilitates the discovery of new diagnostic and prognostic markers for cancer translational medicine.

Serum Copper and Zinc Levels and Colorectal Cancer in Adults: Findings from the National Health and Nutrition Examination 2011-2016

Several studies have indicated an association between serum copper and zinc levels and colorectal cancer, but results were controversial. This study assessed the association of serum copper, zinc, and copper/zinc ratio with colorectal cancer in US adults aged 20 years and older through the use of National Health and Nutrition Examination Survey (NHANES) 2011-2016 data. Serum concentrations of copper and zinc were measured using inductively coupled plasma dynamic reaction cell mass spectrometry (ICP-DRC-MS). Odds ratios with 95% confidence intervals (ORs with CIs) were calculated for serum copper, zinc, and copper/zinc ratio by multivariate logistic regression. A total of 4663 participants (2320 males and 2343 females) with 24 colorectal cancer patients were included in the analyses. We did not observe a statistically significant association between serum copper level and colorectal cancer (top vs bottom quartile multivariate OR 1.71; 95% CI, 0.37-7.88; P for trend = 0.429). In addition, serum zinc level was also not significantly associated with colorectal cancer (top vs bottom quartile multivariate OR 0.72; 95% CI, 0.12-4.27; P for trend = 0.346). While in the age- and gender-adjusted model, there seemed to be a trend that participants with higher copper/zinc ratio level had higher odds of colorectal cancer than participants with lower copper/zinc ratio level; no statistically significant association was observed in multivariate-adjusted models. Our findings did not support a significant association between serum copper and zinc level and colorectal cancer risk in the general US population. Furthermore, large longitudinal studies should be needed to confirm these findings.

Investigation of the relationship between GSTM1 gene variations and serum trace elements, plasma malondialdehyde levels in patients with colorectal cancer

BACKGROUND

The aim of this study is to investigate of the relationship between GSTM1 gene variations and serum trace elements, plasma malondialdehyde levels in patient with colorectal cancer. Mateials and Methods. Genotype distributions of GSTM1 gene variations were determined using real-time polymerase chain reaction method. Serum trace element levels were determined using atomic absorption spectrophotometer method and plasma MDA levels were measurement by spectrophotometric method.

RESULTS

Serum Cu levels, plasma MDA levels and Cu/Zn ratio were determined significantly higher in the group of CRC patient carrying the GA heterozygous genotype of the GSTM1 (rs 112,778,559) gene variation compared to healthy controls (p < 0.05). Serum Cu, Zn levels, plasma MDA levels and Cu/Zn ratio were determined significantly higher in patients carrying GG homozygous genotype of the GSTM1 (rs 112778559) gene variation compared to healthy controls carrying same genotype (p < 0.05). Serum Cu, Zn levels, plasma MDA levels and Cu/Zn ratio were determined significantly higher in the group of CRC patient carrying the GG homozygous genotype of the GSTM1 (rs 12068997) gene variation compared to healthy controls (p < 0.05). On the other hand, serum Se levels were detected significantly lower in CRC patients carrying GA heterozygous and GG homozygous genotypes for GSTM1 (rs 112,778,559) and (rs 12,068,997) gene variations compared to healthy controls (p < 0.05).

CONCLUSION

In our study, the evaluation of serum Cu, Zn and Se trace element levels and plasma MDA levels according to GSTM1 gene variations genotype distributions were enabled to obtain important biomarkers in terms of CRC development and progression.

An integrated mass spectrometry imaging and digital pathology workflow for objective detection of colorectal tumours by unique atomic signatures

Tumours are abnormal growths of cells that reproduce by redirecting essential nutrients and resources from surrounding tissue. Changes to cell metabolism that trigger the growth of tumours are reflected in subtle differences between the chemical composition of healthy and malignant cells. We used LA-ICP-MS imaging to investigate whether these chemical differences can be used to spatially identify tumours and support detection of primary colorectal tumours in anatomical pathology. First, we generated quantitative LA-ICP-MS images of three colorectal surgical resections with case-matched normal intestinal wall tissue and used this data in a Monte Carlo optimisation experiment to develop an algorithm that can classify pixels as tumour positive or negative. Blinded testing and interrogation of LA-ICP-MS images with micrographs of haematoxylin and eosin stained and Ki67 immunolabelled sections revealed Monte Carlo optimisation accurately identified primary tumour cells, as well as returning false positive pixels in areas of high cell proliferation. We analysed an additional 11 surgical resections of primary colorectal tumours and re-developed our image processing method to include a random forest regression machine learning model to correctly identify heterogenous tumours and exclude false positive pixels in images of non-malignant tissue. Our final model used over 1.6 billion calculations to correctly discern healthy cells from various types and stages of invasive colorectal tumours. The imaging mass spectrometry and data analysis methods described, developed in partnership with clinical cancer researchers, have the potential to further support cancer detection as part of a comprehensive digital pathology approach to cancer care through validation of a new chemical biomarker of tumour cells.