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Background:
Communication

Low Blood-As Levels and Selected Genotypes Appears to Be Promising Biomarkers for Occurrence of Colorectal Cancer in Women

by
Piotr Baszuk
1,2,†,
Paulina Stadnik
1,†,
Wojciech Marciniak
1,2,
Róża Derkacz
1,2,
Anna Jakubowska
1,
Cezary Cybulski
1,2,
Tomasz Huzarski
1,2,3,
Jacek Gronwald
1,2,
Tadeusz Dębniak
1,
Katarzyna Białkowska
1,
Sandra Pietrzak
1,
Józef Kładny
4,
Rodney J. Scott
5,6,7,
Jan Lubiński
1,2,* and
Marcin R. Lener
1
1
International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University in Szczecin, ul. Unii Lubelskiej 1, 71-252 Szczecin, Poland
2
Read-Gene, Grzepnica, ul. Alabastrowa 8, 72-003 Grzepnica, Dobra (Szczecińska), Poland
3
Department of Clinical Genetics and Pathology, University of Zielona Góra, ul. Zyty 28, 65-046 Zielona Góra, Poland
4
Department of General Surgery and Surgical Oncology, First Clinical Hospital of Pomeranian Medical University in Szczecin, ul. Unii Lubelskiej 1, 71-252 Szczecin, Poland
5
Priority Research Centre for Cancer Research, Innovation and Translation, Hunter Medical Research Institute, New Lambton Heights, NSW 2308, Australia
6
School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia
7
Division of Molecular Medicine, Pathology North, John Hunter Hospital, New Lambton, NSW 2305, Australia
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Biomedicines 2021, 9(9), 1105; https://doi.org/10.3390/biomedicines9091105
Submission received: 31 July 2021 / Revised: 24 August 2021 / Accepted: 26 August 2021 / Published: 28 August 2021
(This article belongs to the Special Issue Role of Trace Elements in Chemoprevention and Cancer Therapy)
Review Reports Versions Notes

Abstract

:
In following study we examined whether blood arsenic (As) levels combined with specific polymorphisms in MT1B, GSTP1, ABCB1, NQO1, CRTC3, GPX1, SOD2, CAT, XRCC1, ERCC2 can be used as a marker for the detection of colorectal cancer (CRC) among Polish women. A retrospective case-control study of CRC included 83 CRC cases and 78 healthy controls. From each study participant pre-treatment peripheral blood was collected for As level measurement by inductively coupled–plasma mass spectrometry (ICP-MS). We estimated the odds ratio (OR) of the association between blood-As levels and CRC using multivariable unconditional logistic regression models. A low blood-As level (0.27–0.67 µg/L) was associated with an increased frequency of CRC (OR: 3.69; p = 0.005). This correlation was significantly greater when participants carried particular gene variants: CAT, rs1001179-nonCC (OR: 19.4; p = 0.001); ABCB1 rs2032582–CC (OR: 14.8; p = 0.024); GPX1 rs1050450-CC (OR: 11.6; p = 0.002) and CRTC3 rs12915189-nonGG (OR: 10.3; p = 0.003). Our study provides strong evidence that low blood-As levels are significantly associated with increased CRC occurrence and that particular gene variants significantly enhanced this correlation however, due to the novelty of these findings, we suggest further validation before a definitive statement that the combined effect of low blood-As levels with specific gene polymorphisms is a suitable CRC biomarker.

1. Introduction

There are 2 major methods to study association between biomarkers and cancer. The first one studies the risk of cancer development and is based on a prospective cohort when patients are initially unaffected. The other method, a case-control study explores cancer occurrence. Although the case-control study design has limitations as it does not exclude influence of tumour itself on biochemical parameters, this type of study is very useful to establish the most efficient criteria of cancer surveillance. Malignant tumours are the leading cause of death worldwide [1,2]. According to GLOBOCAN 2020 data, colorectal cancer (CRC) was the third most frequently diagnosed cancer and was classified as one of the most common types of cancers in both men and women [3]. It is believed that the interaction of various risk factors cause the accumulation of many genetic/epigenetic/metabolic changes within the cell has the greatest impact on cancer initiation and development [4,5,6,7,8,9]. It is known that low concentrations of some trace elements is beneficial for human health, however it has also been shown that genetic polymorphisms that alter the function or expression of important genes that play key roles in the metabolism of trace elements may contribute to the increased risk of cancer development [10,11]. Moreover, several trace elements are considered as chemical carcinogens that may contribute to the carcinogenic process [10,11]. The IARC report determined arsenic (As) and its compounds as one of the most carcinogenic trace elements that mankind is exposed to [10,12,13]. Although As is ubiquitous in the environment, and human exposure can occur from many natural and anthropogenic sources, diet is classified as one of the major source of As exposure [14]. Biomolecular mechanisms of As clearance are still poorly understood, however there are some theories that its biotransformation may exert carcinogenesis in both a genotoxic and non-genotoxic manner [15,16]. Recently we have been able to show that As is a major cancer risk factor for women in Poland–high levels of blood As (the highest quartile) is associated with more than 10-times higher risk of breast cancers as compared to quartile with the lowest As levels [17]. The above correlations have not been observed in our studies of men (data not shown). So far many retrospective revisions have indicated an association between the concentration of As in human samples and the occurrence of various cancer types [18,19,20,21,22,23,24,25,26], however none of these reports studied the relationship between As exposure and CRC occurrence. It is well established that increased risks of cancer are associated with polymorphisms of different genes. For the studies herein, we selected polymorphisms in genes reported to be directly involved in malignant transformation and/or xenobiotic metabolism and/or oxidative stress. As some studies have already explored the combined effects of metal levels with DNA variants of genes involved in carcinogenesis [27,28], we decided to explore whether functional polymorphisms in a panel of genes selected by us correlates with the frequency of CRC linked with blood-As levels in Polish women. Based on functional characteristics, high mutant-allele frequency (MAF > 25%) and potential relationship with cancer development and occurrence, 10 gene polymorphisms were studied. We selected the following genes: ATP Binding Cassette Subfamily B Member 1 (ABCB1) [29,30] and glutathione s-transferase P1 (GSTP1) [31] participating in elimination of some potentially toxic xenobiotics excision repair cross-complementing rodent repair deficiency group 2 (ERCC2) [32] and X-ray repair cross-complementing protein 1 (XRCC1) [33,34] that are involved in DNA repair, catalase (CAT), glutathione peroxidase-1 (GPX1), superoxide dismutase 2 (SOD2) [35] and NAD(P)H Quinone Dehydrogenase 1 (NQO1) [36] that are anti-oxidative stress enzymes, CREB Regulated Transcription Coactivator 3 (CRTC3) that plays a role in a regulation of CREB-dependent gene transcription in a phosphorylation-independent manner [37], metallothionein 1B (MT1B) which is involved in metal homeostasis and protection against heavy metal toxicity, DNA damage, and oxidative stress [38]. The aim of this study was to answer the following questions: Can blood-As levels be used as a biomarker for CRC occurrence in Polish women? Can specific gene polymorphisms be used as a biomarker for CRC occurrence in Polish women? Does the combined effect of blood-As levels and specific gene polymorphisms influence CRC frequency in Polish women?

2. Materials and Methods

2.1. Study Group

A population based retrospective case-control study of CRC was conducted on the cohort of 161 Polish women. The characteristics of cases and control participants are presented in Table 1. All study subjects provided written informed consent to participate in the study and were randomly included in the study between 2012 and 2017. For each cancer patient, one unaffected individual registered at the International Hereditary Cancer Centre, Pomeranian Medical University of Szczecin, was matched as a healthy control. Participants were matched for year of birth (±3 years), sex, smoking status (pack-years ±20%) and the total number of malignancies among first degree relatives. In all cases cancer was confirmed by histopathological examination. The study was conducted in accordance with the Helsinki Declaration and with the consent of the Ethics Committee of Pomeranian Medical University in Szczecin under the number KB-0012/73/10.

2.2. Measurement of Blood-As Level

10 mL of peripheral blood was collected into a vacutainer tube containing sodium ethylenediaminetetraacetic acid (EDTA) from all study participants and then stored at −80 °C until the day of analysis. Study subjects were fasting for at least six hours before sample collection. Blood samples were taken from patients’ pre-treatment at the time of diagnosis. Total arsenic concentration in their blood was measured by the inductively coupled plasma mass spectrometer method reported in our previous study [17].

2.3. Molecular Analysis

Ten selected variants in ten genes were genotyped: rs13181 in ERCC2, rs1799782 in XRCC1, rs7191779 in MT1B, rs1695 in GSTP1, rs2032582 in ABCB1, rs1800566 in NQO1, rs12915189 in CRTC3, rs1050450 in GPX1, rs4880 in SOD2, and rs1001179 in CAT. From each individual included in the study, a 10 mL peripheral blood sample was collected in a vacutainer tube containing 1 mL of 10% sodium EDTA. The genomic DNA was isolated using the detergent method [39]. SNP Analyses were performed using a pre-designed Genotyping Assay × 40 (Applied Biosystems, Waltham, Massachusetts, USA). Each reaction mixture consisted of 2.5 μL LightCycler 480 Probe Master Mix (Roche Diagnostics, Basel, Switzerland), the assay 0.125 μL (Genotyping Assay × 40 TaqMan) (Applied Biosystems, Waltham, Massachusetts, USA) and 1.375 μL deionized water (Roche Diagnostics, Basel, Switzerland). Samples were analyzed on 384-well plates. Each plate was included positive, negative and water-blind control. The genotyping data were collected and analyzed using the LightCycler 480 Instrument and the program of the LightCycler 480 Basic Software Version 1.5 (Roche Diagnostics, Basel, Switzerland).

2.4. Statistical Analysis

For the estimation of association of As levels or As level and genotype with female CRC occurrence, study participants were assigned to one of four categories (quartiles-Q) based on the As levels distribution among controls. The association of As level with CRC occurrence was estimated with odds ratio (OR) at 95% confidence intervals using multivariable unconditional logistic regression model. The fourth quarter was utilized as the reference category for the odds ratio calculation. All calculations were performed using: “R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria” (R version 4.0.4 (10 October 2020)).

3. Results

The lowest blood-As level (0.27–0.67 µg/L–Q1) was associated with a 3.69-fold (95% CI 1.50–9.50); p = 0.005) increase in the risk of CRC when compared to blood As levels of 4th quartile (1.47–7.11 µg/L) (Table 2). Apart from that, significant differences were observed in As levels between controls and Stage I-II patients (median 0.9 and 0.66 respectively)–p-value = 0.01.
By comparing quartiles, further examination of the candidate gene variants showed a significantly greater probability of CRC occurrence in women with the lowest (0.27–0.67 µg/L) blood-As levels carrying functional polymorphisms such as: CAT, rs1001179-nonCC (OR: 19.4 (95% CI 3.69–159.0); p = 0.001) (Table 3), ABCB1 rs2032582–CC (OR: 14.8 (95% CI 1.95–318); p = 0.024) (Table 4), GPX1 rs1050450-CC (OR: 11.6 (95% CI 2.74–60.9); p = 0.002) (Table 5), CRTC3 rs12915189-nonGG (OR: 10.3 (95% CI 2.42–52.8); p = 0.003) (Table 6). In the remaining 6 genes results were statistically non-significant or groups of cases/controls were very small.
None of the presented genotypes increased predisposition to CRC when blood-As level was not considered (Appendix A, Table A1, Table A2, Table A3 and Table A4).

4. Discussion

CRC is one of the major causes of morbidity and mortality in many well-developed countries and its occurrence is increasing in developing areas of the world.
This current retrospective report showed a novel finding that low blood-As levels are strongly associated with higher probability of CRC occurrence in women.
Since our published data achieved in our prospective cohort of women strongly suggested blood-As levels in women should be low, because it is correlated with an extremely low risk of all cancer development including CRC, we hypothesized that low blood-As levels in CRC patients (current retrospective study) may be due to significantly higher As metabolism occurring in cancerous cells during the growth of the CRC. Observed correlation may be also site-specific since in analogous studies performer in Our Centre, breast and lung cancer female patients did not show association between As level and tumour occurrence (data not shown). Mechanisms behind our observations need further investigations including somatic and genetic changes of various pathways involved in cancer development.
Recently, we recognized unexpectedly that one of mechanism of As induced carcinogenesis may be via estrogens. Experimental studies on animals have shown dependence of As effects on sex [40]. In prospective cohorts we also observed that As associated cancer risk was correlated with hormonal status: in women, higher blood As level was associated with higher cancer risk but in men, especially at age < 60 yrs, higher blood As level was associated with lower cancer risk (data not shown). In females, As may influence on development of cancers by disrupting the function of estrogen receptors and suppressing the signaling pathway of estrogen [41,42]. As is also a potential metallo-estrogen [43,44].
Surprisingly, to the best of our knowledge, there are no published retrospective case-control studies on the relationship between As levels in any biological sample and CRC occurrence.
It is well known that apart from many environmental factors, genetic predisposition plays a significant role in the CRC development and occurrence [45]. From the panel of selected genes in this study, we presented that gene variants such as: CAT, rs1001179-nonCC, ABCB1 rs2032582–CC, GPX1 rs1050450-CC, CRTC3 rs12915189-nonGG significantly enhanced already greater CRC occurrence among women with ≤0.67 µg/L blood-As concentration, although none of these genotypes presented a significant effect on CRC occurrence on their own when blood-As levels were not considered. It is in agreement with results of former studies presenting no impact of polymorphisms of ABCB1 rs2032582, GPX1 rs1050450, CAT rs1001179 on CRC occurrence among respectively Asian [29], Norwegian [46], Iranian [47] German [48] and US populations [49].
As far as we are aware, this is the first report exploring the impact of CRTC3 rs12915189 polymorphism on its own, but also in combination with blood-As levels on CRC occurrence. According to our findings, CRTC3 rs12915189-nonGG itself did not predispose to a higher frequency of CRC, however with blood-As levels below or equal to 0.67 µg/L it significantly increased the occurrence of CRC among women from Poland.
Based on our data and assumptions, we consider that to exclude the occurrence of CRC, a colonoscopy should be offered to women with a low blood-As level as a result of either an As-free diet or found in their initial regular blood tests and in association with gene variants described above.
We are convinced that after further validation (also on larger numbers of cases and controls) the combination effects of low blood-As levels with CAT rs1001179-nonCC, ABCB1 rs2032582–CC, GPX1 rs1050450-CC, CRTC3 rs12915189-nonGG maybe a suitable CRC biomarker in Polish women.

5. Conclusions

Low blood-As level (0.27–0.67 µg/L) significantly increases probability of the CRC occurrence in women.
CAT rs1001179-nonCC, ABCB1 rs2032582–CC, GPX1 rs1050450-CC, CRTC3 rs12915189-nonGG polymorphisms enhance the already existing, increased probability of female CRC occurrence associated with low blood-As levels (0.27–0.67 µg/L).

Author Contributions

Conceptualization, P.B., P.S. and J.L.; methodology, P.B., W.M. and J.L.; software, P.B.; validation, W.M.; formal analysis, P.B., M.R.L.; investigation, P.B., P.S., W.M., R.D., M.R.L., A.J., K.B. and J.K.; resources, M.R.L., A.J., C.C., T.H., J.G., T.D., J.K. and J.L.; data curation, P.B., P.S., W.M., R.D., K.B., S.P., J.L. and M.R.L.; writing—original draft preparation, P.B., P.S., R.J.S. and J.L.; writing—review and editing, R.J.S., J.L. and M.R.L.; visualization, P.B., P.S., S.P., R.J.S., M.R.L. and J.L.; supervision, J.L. and M.R.L.; project administration, A.J., J.K., M.R.L. and J.L.; funding acquisition, A.J. and J.L. All authors have read and agreed to the published version of the manuscript.

Funding

The study was funded by the National Centre for Research and Development Project: PBS3/B7/26/2015.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of Pomeranian Medical University in Szczecin (protocol code KB-0012/73/10.)

Informed Consent Statement

Written informed consent has been obtained from the patients to publish this paper.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

J.L. is the CEO of Read-Gene SA. These authors are part-time employees of Read-Gene SA: P.B., W.M., R.D., C.C., T.H., J.G. The other authors declare that they have no conflict of interest.

Appendix A

Table
Table A1. Numbers of CRC cases and healthy controls depending on CAT gene polymorphism only.
Table A1. Numbers of CRC cases and healthy controls depending on CAT gene polymorphism only.
CAT rs1001179
OverallCasesControls
CC97 (60%)48 (58%)49 (63%)
nonCC64 (40%)35 (42%)29 (37%)
CAT rs1001179-nonCC: OR: 1.23 (95% CI 0.65–2.33); p = 0.5.
Table
Table A2. Numbers of CRC cases and healthy controls depending on ABCB1 gene polymorphism only.
Table A2. Numbers of CRC cases and healthy controls depending on ABCB1 gene polymorphism only.
ABCB1 rs2032582
OverallCasesControls
CC61 (38%)29 (35%)32 (41%)
nonCC100 (62%)54 (65%)46 (59%)
ABCB1 rs2032582-nonCC: OR: 1.30 (95% CI 0.68–2.46); p = 0.4.
Table
Table A3. Numbers of CRC cases and healthy controls depending on GPX1 gene polymorphism only.
Table A3. Numbers of CRC cases and healthy controls depending on GPX1 gene polymorphism only.
GPX1 rs1050450
OverallCasesControls
CC68 (42%)35 (42%)33 (42%)
nonCC93 (58%)48 (58%)45 (58%)
GPX1 rs1050450-nonCC: OR: 1.01 (95% CI 0.54–1.88); p > 0.9.
Table
Table A4. Numbers of CRC cases and healthy controls depending on CRTC3 gene polymorphism only.
Table A4. Numbers of CRC cases and healthy controls depending on CRTC3 gene polymorphism only.
CRTC3 rs12915189
OverallCasesControls
CC90 (56%)47 (57%)43 (55%)
nonCC71 (44%)36 (43%)35 (45%)
CRTC3 rs12915189-nonGG: OR: 0.94 (95% CI 0.50–1.76); p = 0.8.

References

  1. Nagai, H.; Kim, Y.H. Cancer prevention from the perspective of global cancer burden patterns. J. Thorac. Dis. 2017, 9, 448–451. [Google Scholar] [CrossRef]
  2. Zawadzka, I.; Jeleń, A.; Pietrzak, J.; Żebrowska-Nawrocka, M.; Michalska, K.; Szmajda-Krygier, D.; Mirowski, M.; Łochowski, M.; Kozak, J.; Balcerczak, E. The impact of ABCB1 gene polymorphism and its expression on non-small-cell lung cancer development, progression and therapy-preliminary report. Sci. Rep. 2020, 10, 6188. [Google Scholar] [CrossRef] [Green Version]
  3. Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Andersson, T.M.-L.; Engholm, G.; Brink, A.-L.; Pukkala, E.; Stenbeck, M.; Tryggvadottir, L.; Weiderpass, E.; Storm, H. Tackling the tobacco epidemic in the Nordic countries and lower cancer incidence by 1/5 in a 30-year period-The effect of envisaged scenarios changing smoking prevalence. Eur. J. Cancer 2018, 103, 288–298. [Google Scholar] [CrossRef]
  5. Crowe, F.L.; Appleby, P.N.; Travis, R.C.; Key, T.J. Risk of hospitalization or death from ischemic heart disease among British vegetarians and nonvegetarians: Results from the EPIC-Oxford cohort study. Am. J. Clin. Nutr. 2013, 97, 597–603. [Google Scholar] [CrossRef] [Green Version]
  6. Huang, T.; Yang, B.; Zheng, J.; Li, G.; Wahlqvist, M.L.; Li, D. Cardiovascular disease mortality and cancer incidence in vegetarians: A meta-analysis and systematic review. Ann. Nutr. Metab. 2012, 60, 233–240. [Google Scholar] [CrossRef]
  7. Lewandowska, A.M.; Rudzki, M.; Rudzki, S.; Lewandowski, T.; Laskowska, B. Environmental risk factors for cancer—Review paper. Ann. Agric. Environ. Med. 2019, 26, 1–7. [Google Scholar] [CrossRef] [PubMed]
  8. Schulz, M.; Hoffmann, K.; Weikert, C.; Nöthlings, U.; Schulze, M.B.; Boeing, H. Identification of a dietary pattern characterized by high-fat food choices associated with increased risk of breast cancer: The European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Br. J. Nutr. 2008, 100, 942–946. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Weiderpass, E. Lifestyle and cancer risk. J. Prev. Med. Public Health 2010, 43, 459–471. [Google Scholar] [CrossRef] [PubMed]
  10. Mulware, S.J. Trace elements and carcinogenicity: A subject in review. 3 Biotech 2013, 3, 85–96. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  11. Nawi, A.M.; Chin, S.-F.; Azhar Shah, S.; Jamal, R. Tissue and Serum Trace Elements Concentration among Colorectal Patients: A Systematic Review of Case-Control Studies. Iran. J. Public Health 2019, 48, 632–643. [Google Scholar]
  12. Chung, J.-Y.; Yu, S.-D.; Hong, Y.-S. Environmental Source of Arsenic Exposure. J. Prev. Med. Public Health 2014, 47, 253–257. [Google Scholar] [CrossRef] [Green Version]
  13. IARC. Arsenic, Metals, Fibres, and Dusts; IARC: Lyon, France, 2012; ISBN 978-92-832-1320-8. [Google Scholar]
  14. Baker, B.A.; Cassano, V.A.; Murray, C.; Exposure, A.T.F. on A. Arsenic Exposure, Assessment, Toxicity, Diagnosis, and Management: Guidance for Occupational and Environmental Physicians. J. Occup. Environ. Med. 2018, 60, e634. [Google Scholar] [CrossRef] [PubMed]
  15. Im, J.; Chatterjee, N.; Choi, J. Genetic, epigenetic, and developmental toxicity of Chironomus riparius raised in metal-contaminated field sediments: A multi-generational study with arsenic as a second challenge. Sci. Total. Environ. 2019, 672, 789–797. [Google Scholar] [CrossRef] [PubMed]
  16. Sage, A.P.; Minatel, B.C.; Ng, K.W.; Stewart, G.L.; Dummer, T.J.B.; Lam, W.L.; Martinez, V.D. Oncogenomic disruptions in arsenic-induced carcinogenesis. Oncotarget 2017, 8, 25736–25755. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Marciniak, W.; Derkacz, R.; Muszyńska, M.; Baszuk, P.; Gronwald, J.; Huzarski, T.; Cybulski, C.; Jakubowska, A.; Falco, M.; Dębniak, T.; et al. Blood Arsenic Levels and the Risk of Familial Breast Cancer in Poland. Int. J. Cancer 2020, 146, 2721–2727. [Google Scholar] [CrossRef] [Green Version]
  18. Benderli Cihan, Y.; Sözen, S.; Oztürk Yıldırım, S. Trace elements and heavy metals in hair of stage III breast cancer patients. Biol. Trace Elem. Res. 2011, 144, 360–379. [Google Scholar] [CrossRef]
  19. Hsueh, Y.-M.; Su, C.-T.; Shiue, H.-S.; Chen, W.-J.; Pu, Y.-S.; Lin, Y.-C.; Tsai, C.-S.; Huang, C.-Y. Levels of plasma selenium and urinary total arsenic interact to affect the risk for prostate cancer. Food Chem. Toxicol. 2017, 107, 167–175. [Google Scholar] [CrossRef]
  20. Jablonska, E.; Socha, K.; Reszka, E.; Wieczorek, E.; Skokowski, J.; Kalinowski, L.; Fendler, W.; Seroczynska, B.; Wozniak, M.; Borawska, M.H.; et al. Cadmium, arsenic, selenium and iron- Implications for tumor progression in breast cancer. Environ. Toxicol. Pharmacol. 2017, 53, 151–157. [Google Scholar] [CrossRef]
  21. Kazi, T.G.; Wadhwa, S.K.; Afridi, H.I.; Talpur, F.N.; Tuzen, M.; Baig, J.A. Comparison of essential and toxic elements in esophagus, lung, mouth and urinary bladder male cancer patients with related to controls. Environ. Sci. Pollut. Res. Int. 2015, 22, 7705–7715. [Google Scholar] [CrossRef] [PubMed]
  22. Kim, T.-H.; Seo, J.-W.; Hong, Y.-S.; Song, K.-H. Case-control study of chronic low-level exposure of inorganic arsenic species and non-melanoma skin cancer. J. Dermatol. 2017, 44, 1374–1379. [Google Scholar] [CrossRef] [PubMed]
  23. Melak, D.; Ferreccio, C.; Kalman, D.; Parra, R.; Acevedo, J.; Pérez, L.; Cortés, S.; Smith, A.H.; Yuan, Y.; Liaw, J.; et al. Arsenic Methylation and Lung and Bladder Cancer in a Case-control Study in Northern Chile. Toxicol. Appl. Pharmacol. 2014, 274, 225–231. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Pineda-Belmontes, C.P.; Hernández-Ramírez, R.U.; Hernández-Alcaraz, C.; Cebrián, M.E.; López-Carrillo, L. Genetic polymorphisms of PPAR gamma, arsenic methylation capacity and breast cancer risk in Mexican women. Salud Publica Mex. 2016, 58, 220–227. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Ismail, P.; Yousif, A.; Harki, E. Alterations of Some Heavy Metals and Trace Elements Levels in Breast Cancer. Med. Chem. 2017, 7, 458–760. [Google Scholar] [CrossRef]
  26. Wadhwa, S.K.; Kazi, T.G.; Chandio, A.A.; Afridi, H.I.; Kolachi, N.F.; Khan, S.; Kandhro, G.A.; Nasreen, S.; Shah, A.Q.; Baig, J.A. Comparative study of liver cancer patients in arsenic exposed and non-exposed areas of Pakistan. Biol. Trace Elem. Res. 2011, 144, 86–96. [Google Scholar] [CrossRef]
  27. Safarzad, M.; Besharat, S.; Salimi, S.; Azarhoush, R.; Behnampour, N.; Joshaghani, H.R. Association between selenium, cadmium, and arsenic levels and genetic polymorphisms in DNA repair genes (XRCC5, XRCC6) in gastric cancerous and non-cancerous tissue. J. Trace Elem. Med. Biol. 2019, 55, 89–95. [Google Scholar] [CrossRef]
  28. Zhang, Q.; Jiang, C.; Li, H.; Zhang, C.; Wu, H.; Huang, F. Effect of the Interaction Between Cadmium Exposure and CLOCK Gene Polymorphisms on Thyroid Cancer: A Case-Control Study in China. Biol. Trace Elem. Res. 2020, 196, 86–95. [Google Scholar] [CrossRef]
  29. He, T.; Mo, A.; Zhang, K.; Liu, L. ABCB1/MDR1 gene polymorphism and colorectal cancer risk: A meta-analysis of case-control studies. Colorectal Dis. 2013, 15, 12–18. [Google Scholar] [CrossRef]
  30. Martinelli, M.; Scapoli, L.; Cura, F.; Rodia, M.T.; Ugolini, G.; Montroni, I.; Solmi, R. Colorectal cancer susceptibility: Apparent gender-related modulation by ABCB1 gene polymorphisms. J. BioMed. Sci. 2014, 21, 89. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Ritambhara, null; Tiwari, S.; Vijayaraghavalu, S.; Kumar, M. Genetic Polymorphisms of Xenobiotic Metabolizing Genes (GSTM1, GSTT1, GSTP1), Gene-Gene Interaction with Association to Lung Cancer Risk in North India; A Case Control Study. Asian Pac. J. Cancer Prev. 2019, 20, 2707–2714. [Google Scholar] [CrossRef]
  32. Rump, A.; Benet-Pages, A.; Schubert, S.; Kuhlmann, J.D.; Janavičius, R.; Macháčková, E.; Foretová, L.; Kleibl, Z.; Lhota, F.; Zemankova, P.; et al. Identification and Functional Testing of ERCC2 Mutations in a Multi-national Cohort of Patients with Familial Breast- and Ovarian Cancer. PLoS Genet. 2016, 12, e1006248. [Google Scholar] [CrossRef]
  33. Caldecott, K.W. XRCC1 protein; Form and function. DNA Repair (Amst.) 2019, 81, 102664. [Google Scholar] [CrossRef]
  34. Mok, M.C.Y.; Campalans, A.; Pillon, M.C.; Guarné, A.; Radicella, J.P.; Junop, M.S. Identification of an XRCC1 DNA binding activity essential for retention at sites of DNA damage. Sci. Rep. 2019, 9, 3095. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Ighodaro, O.M.; Akinloye, O.A. First line defence antioxidants-superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPX): Their fundamental role in the entire antioxidant defence grid. Alex. J. Med. 2018, 54, 287–293. [Google Scholar] [CrossRef] [Green Version]
  36. Ross, D.; Siegel, D. NQO1 in protection against oxidative stress. Curr. Opin. Toxicol. 2018, 7, 67–72. [Google Scholar] [CrossRef]
  37. Ozanne, J.; Prescott, A.R.; Clark, K. The clinically approved drugs dasatinib and bosutinib induce anti-inflammatory macrophages by inhibiting the salt-inducible kinases. BioChem. J. 2015, 465, 271–279. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Si, M.; Lang, J. The roles of metallothioneins in carcinogenesis. J. Hematol. Oncol. 2018, 11, 107. [Google Scholar] [CrossRef]
  39. Lahiri, D.K.; Schnabel, B. DNA Isolation by a Rapid Method from Human Blood Samples: Effects of MgCl2, EDTA, Storage Time, and Temperature on DNA Yield and Quality. BioChem. Genet. 1993, 31, 321–328. [Google Scholar] [CrossRef]
  40. Huang, M.C.; Douillet, C.; Su, M.; Zhou, K.; Wu, T.; Chen, W.; Galanko, J.A.; Drobná, Z.; Saunders, R.J.; Martin, E.; et al. Metabolomic profiles of arsenic (+3 oxidation state) methyltransferase knockout mice: Effect of sex and arsenic exposure. Arch. Toxicol. 2017, 91, 189–202. [Google Scholar] [CrossRef] [Green Version]
  41. Gamble, M.V.; Liu, X.; Slavkovich, V.; Pilsner, J.R.; Ilievski, V.; Factor-Litvak, P.; Levy, D.; Alam, S.; Islam, M.; Parvez, F.; et al. Folic acid supplementation lowers blood arsenic. Am. J. Clin. Nutr. 2007, 86, 1202–1209. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Chatterjee, A.; Chatterji, U. Arsenic abrogates the estrogen-signaling pathway in the sat uterus. Reprod. Biol. Endocrinol. 2010, 8, 80. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Aquino, N.B.; Sevigny, M.B.; Sabangan, J.; Louie, M.C. Role of cadmium and nickel in estrogen receptor signaling and breast cancer: Metalloestrogenes or not? J. Environ. Sci. Health C Environ. Carcinog. Ecotoxicol. Rev. 2012, 30, 189–224. [Google Scholar] [CrossRef] [Green Version]
  44. Ruiz-Ramos, R.; López-Carrillo, L.; Albores, A.; Hernández-Ramírez, R.U.; Cebrian, M.E. Sodium arsenite atlers cell cycle and MTHFR MT1/2, and c-Myc protein levels on MCF-7 cells. Toxicol. Appl. Pharmacol. 2009, 241, 269–274. [Google Scholar] [CrossRef] [PubMed]
  45. Marley, A.R.; Nan, H. Epidemiology of colorectal cancer. Int. J. Mol. Epidemiol. Genet. 2016, 7, 105–114. [Google Scholar] [PubMed]
  46. Hansen, R.; Saebø, M.; Skjelbred, C.F.; Nexø, B.A.; Hagen, P.C.; Bock, G.; Bowitz Lothe, I.M.; Johnson, E.; Aase, S.; Hansteen, I.L.; et al. GPX Pro198Leu and OGG1 Ser326Cys polymorphisms and risk of development of colorectal adenomas and colorectal cancer. Cancer Lett. 2005, 229, 85–91. [Google Scholar] [CrossRef] [Green Version]
  47. Jamhiri, I.; Saadat, I.; Omidvari, S. Genetic polymorphisms of superoxide dismutase-1A251G and catalase C-262T with the risk of colorectal cancer. Mol. Biol. Res. Commun. 2017, 6, 85–90. [Google Scholar]
  48. Funke, S.; Hoffmeister, M.; Brenner, H.; Chang-Claude, J. Effect modification by smoking on the association between genetic polymorphisms in oxidative stress genes and colorectal cancer risk. Cancer Epidemiol. Biomark. Prev. 2009, 18, 2336–2338. [Google Scholar] [CrossRef] [Green Version]
  49. Labadie, J.; Goodman, M.; Thyagarajan, B.; Gross, M.; Sun, Y.; Fedirko, V.; Bostick, R.M. Associations of oxidative balance-related exposures with incident, sporadic colorectal adenoma according to antioxidant enzyme genotypes. Ann. Epidemiol. 2013, 23, 223–226. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table
Table 1. Characteristics of female CRC cases and controls.
Table 1. Characteristics of female CRC cases and controls.
Total,
n = 161		ParticipantsAge (Mean/Range)Smoking StatusStage of CRC
YesNoIIIIIIIVUnknown
Cases8367.17 (35–90)236015322844
Controls7867.24 (36–88)2256-----
Table
Table 2. CRC occurrence risk associated with As level in blood in women.
Table 2. CRC occurrence risk associated with As level in blood in women.
As Blood Level (µg/L)Cases/Controls
Q1: 0.27–0.6740/20
Q2: 0.68–0.8811/19
Q3: 0.92–1.4421/19
Q4: 1.47–7.1111/20
Q1 vs. Q4 (reference), cases/controls: 40/20 vs. 11/20; OR: 3.69 (95% CI 1.50–9.50); p = 0.005.
Table
Table 3. Numbers of CRC cases and healthy controls depending on CAT gene polymorphism and blood-As concentration in women.
Table 3. Numbers of CRC cases and healthy controls depending on CAT gene polymorphism and blood-As concentration in women.
CAT rs1001179
As Blood Level (µg/L)nonCCCC
CasesControlsCasesControls
Q1: 0.27–0.6720 (57%)5 (17%)20 (42%)15 (31%)
Q2: 0.68–0.884 (11%)7 (24%)7 (15%)12 (24%)
Q3: 0.92–1.449 (26%)7 (24%)12 (25%)12 (24%)
Q4: 1.47–7.112 (5.7%)10 (34%)9 (19%)10 (20%)
CAT rs1001179-nonCC: Q1 vs. Q4 (reference), OR: 19.4 (95% CI 3.69–159); p = 0.001.
Table
Table 4. Numbers of CRC cases and healthy controls depending on ABCB1 gene polymorphism and blood-As concentration in women.
Table 4. Numbers of CRC cases and healthy controls depending on ABCB1 gene polymorphism and blood-As concentration in women.
ABCB1 rs2032582
As Blood Level (µg/L)CCnonCC
CasesControlsCasesControls
Q1: 0.27–0.6714 (48%)10 (31%)26 (48%)10 (22%)
Q2: 0.68–0.884 (14%)7 (22%)7 (13%)12 (26%)
Q3: 0.92–1.4410 (34%)7 (22%)11 (20%)12(26%)
Q4: 1.47–7.111 (3.4%)8 (25%)10 (19%)12(26%)
ABCB1 rs2032582-CC: Q1 vs. Q4 (reference), OR: 14.8 (95% CI 1.95–318); p = 0.024.
Table
Table 5. Numbers of CRC cases and healthy controls depending on GPX1 gene polymorphism and blood-As concentration in women.
Table 5. Numbers of CRC cases and healthy controls depending on GPX1 gene polymorphism and blood-As concentration in women.
GPX1 rs1050450
As Blood Level (µg/L)CCnonCC
CasesControlsCasesControls
Q1: 0.27–0.6718 (51%)4 (12%)22 (46%)16 (36%)
Q2: 0.68–0.885 (14%)8 (24%)6 (12%)11 (24%)
Q3: 0.92–1.446 (17%)8 (24%)15 (31%)11 (24%)
Q4: 1.47–7.116 (17%)13 (39%)5 (10%)7 (16%)
GPX1 rs1050450-CC: Q1 vs. Q4 (reference), OR: 11.6 (95% CI 2.74–60.9); p = 0.002.
Table
Table 6. Numbers of CRC cases and healthy controls depending on CRTC3 gene polymorphism and blood-As concentration in women.
Table 6. Numbers of CRC cases and healthy controls depending on CRTC3 gene polymorphism and blood-As concentration in women.
CRTC3 rs12915189
As Blood Level (µg/L)GGnonGG
CasesControlsCasesControls
Q1: 0.27–0.6719 (40%)15 (35%)21 (58%)5 (14%)
Q2: 0.68–0.887 (15%)7 (16%)4 (11%)12 (34%)
Q3: 0.92–1.4414 (30%)11 (26%)7 (19%)8 (23%)
Q4: 1.47–7.117 (15%)10 (23%)4 (11%)10(29%)
CRTC3 rs12915189-nonGG: Q1 vs. 4 (reference), OR: 10.3 (95% CI 2.42–52.8); p = 0.003.
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Baszuk, P.; Stadnik, P.; Marciniak, W.; Derkacz, R.; Jakubowska, A.; Cybulski, C.; Huzarski, T.; Gronwald, J.; Dębniak, T.; Białkowska, K.; et al. Low Blood-As Levels and Selected Genotypes Appears to Be Promising Biomarkers for Occurrence of Colorectal Cancer in Women. Biomedicines 2021, 9, 1105. https://doi.org/10.3390/biomedicines9091105

AMA Style

Baszuk P, Stadnik P, Marciniak W, Derkacz R, Jakubowska A, Cybulski C, Huzarski T, Gronwald J, Dębniak T, Białkowska K, et al. Low Blood-As Levels and Selected Genotypes Appears to Be Promising Biomarkers for Occurrence of Colorectal Cancer in Women. Biomedicines. 2021; 9(9):1105. https://doi.org/10.3390/biomedicines9091105

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Baszuk, Piotr, Paulina Stadnik, Wojciech Marciniak, Róża Derkacz, Anna Jakubowska, Cezary Cybulski, Tomasz Huzarski, Jacek Gronwald, Tadeusz Dębniak, Katarzyna Białkowska, and et al. 2021. "Low Blood-As Levels and Selected Genotypes Appears to Be Promising Biomarkers for Occurrence of Colorectal Cancer in Women" Biomedicines 9, no. 9: 1105. https://doi.org/10.3390/biomedicines9091105

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