Next Article in Journal
New Understandings from the Biophysical Study of the Structure, Dynamics, and Function of Nucleic Acids 2.0
Next Article in Special Issue
Traffic-Related Air Pollution and Ground-Level Ozone Associated Global DNA Hypomethylation and Bulky DNA Adduct Formation
Previous Article in Journal
Immunopathological Inflammation in the Evolution of Mucositis and Peri-Implantitis
Previous Article in Special Issue
Cysteine Regulates Oxidative Stress and Glutathione-Related Antioxidative Capacity before and after Colorectal Tumor Resection
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 23
Issue 24
10.3390/ijms232415817
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

miRNAs Participate in the Regulation of Oxidative Stress-Related Gene Expression in Endometrioid Endometrial Cancer

by
Paweł Mieszczański
1,*,
Szmon Januszyk
2,
Nikola Zmarzły
3,
Piotr Ossowski
4,
Konrad Dziobek
3,5,
Dorota Sagan
6,
Dariusz Boroń
3,5,7,8,
Marcin Opławski
7,8 and
Beniamin Oskar Grabarek
3,5,7,9,10
1
Hospital of Ministry of Interior and Administration, 40-052 Katowice, Poland
2
ICZ Healthcare Hospital in Zywiec, 34-300 Zywiec, Poland
3
Department of Histology, Cytophysiology and Embryology, Faculty of Medicine, Academy of Silesia, 41-800 Zabrze, Poland
4
Woman and Child Medical Center in Cracow, 30-002 Cracow, Poland
5
Department of Gynaecology and Obstetrics Faculty of Medicine, Academy of Silesia, 41-800 Zabrze, Poland
6
Medical Center Dormed Medical SPA, 28-105 Busko-Zdroj, Poland
7
Department of Gynecology and Obstetrics with Gynecologic Oncology, Ludwik Rydygier Memorial Specialized Hospital, 31-826 Cracow, Poland
8
Department of Gynecology and Obstetrics, Faculty of Medicine and Health Sciences, Andrzej Frycz Modrzewski University in Cracow, 30-705 Cracow, Poland
9
Department of Gynecology and Obstetrics, TOMMED Specjalisci od Zdrowia, 40-662 Katowice, Poland
10
Gyncentrum, Laboratory of Molecular Biology and Virology, 40-851 Katowice, Poland
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2022, 23(24), 15817; https://doi.org/10.3390/ijms232415817
Submission received: 21 November 2022 / Revised: 8 December 2022 / Accepted: 12 December 2022 / Published: 13 December 2022
(This article belongs to the Special Issue DNA Damage, Oxidative Stress and Related Metabolic By-Products in Cancer and Environmental Studies 2.0)
Versions Notes

Abstract

:
Reactive oxygen species are formed as by-products of normal cell metabolism. They are needed to maintain cell homeostasis and signaling, which is possible due to defense systems. Disruption of this balance leads to oxidative stress that can induce cancer. Redox regulation by miRNAs may be a potential therapeutic target. The aim of the study was to assess the activity of genes associated with oxidative stress in endometrial cancer and to determine their relationship with miRNAs. The study included 45 patients with endometrioid endometrial cancer and 45 without neoplastic changes. The expression profile of genes associated with oxidative stress was determined with mRNA microarrays, RT-qPCR and ELISA. The miRNA prediction was performed based on the miRNA microarray experiment and the mirDB tool. PRDX2 and AQP1 showed overexpression that was probably not related to miRNA activity. A high level of PKD2 may be the result of a decrease in the activity of miR-195-3p, miR-20a, miR-134. A SOD3 level reduction can be caused by miR-328, miR-363. In addition, miR-363 can also regulate KLF2 expression. In the course of endometrial cancer, the phenomenon of oxidative stress is observed, the regulation of which may be influenced by miRNAs.

1. Introduction

Reactive oxygen species (ROS) are mainly produced by the mitochondria under both physiological and pathological conditions. Their production is based on both enzymatic and non-enzymatic reactions [1,2]. Endogenous production may be associated with inflammation, infection, activation of immune cells, aging, and even cancer. Exogenous production of free radicals may, in turn, be a by-product resulting from exposure to heavy metals, drugs, alcohol or radiation [3,4]. Depending on the level, free radicals can have a beneficial effect on the body. They are involved in cell signaling [5] as well as in the elimination of intracellular pathogens and cancer cells [6]. Interestingly, phagocytes synthesize and store free radicals to destroy invading pathogenic microbes [7]. The proper course of apoptosis, differentiation, activation of transcription factors or protein phosphorylation depends on the low level of ROS in cells [8]. The increase in their production negatively affects proteins, lipids and nucleic acids [9].
Oxidative stress is therefore caused by an imbalance between the production and accumulation ROS in cells and the ability of the biological system to detoxify them. If left unchecked, it can accelerate aging and induce neurodegenerative and cardiovascular diseases, and even cancer [10]. Oxidation of DNA results in the formation of hydrolyzed DNA bases, which impairs cell growth by altering the gene expression profile and promoting the occurrence of gene mutations. In addition, damage to the DNA structure may occur, which promotes the formation of cancer [11,12]. It is important that antioxidant systems, such as molecules that scavenge ROS, heme and iron-dependent proteins or drug-metabolizing enzymes, function properly [13], as it enables cells to efficiently adapt to oxidative stress [14].
ROS may therefore contribute to tumor induction and survival, as well as to treatment resistance [15], but their consistently high levels have a cytotoxic effect, which may be helpful in anticancer therapy [16]. The potential relationship of ROS with microRNAs (miRNAs) is also interesting. These non-coding RNA molecules post-transcriptionally modulate gene expression and can act as oncogenes or tumor suppressors, affecting cancer development, metastasis or survival [17]. The possibility of redox regulation by miRNAs may be a potential therapeutic target in breast cancer [18], hepatocellular carcinoma [19], lung cancer [20], renal cell carcinoma [21], prostate cancer [22].
Endometrial cancer (EC) is one of the most frequently diagnosed gynecological malignancies in the world. It occurs mainly in postmenopausal women, although the number of younger women affected increases every year [23]. Almost half of EC cases are related to obesity. Lifestyle changes, including exercise and a healthy diet, are therefore recommended to lower the risk of this cancer [24]. The diagnosis of endometrial cancer is based on classification systems that take into account both genetic and histological features [25]. However, the complexity of carcinogenesis requires further research to improve the current diagnosis of endometrial cancer and find new therapeutic targets.
The aim of the study was to assess the activity of genes associated with oxidative stress in endometrial cancer and to determine their relationship with miRNAs.

2. Results

2.1. Oxidative Stress-Related Gene Expression Profile Determined by mRNA Microarrays

A one-way ANOVA with the following Tukey’s post hoc test revealed that out of 600 mRNAs representing oxidative stress-related genes, the number of mRNAs differentiating each cancer grade from the control was as follows: G1 vs. C, 56 mRNAs; G2 vs. C, 112 mRNAs; G3 vs. C, 118 mRNA (p < 0.05; FC > 2 or FC < −2). Further analysis indicated that 17 mRNAs were characteristic of G1 cancer, 48 mRNAs for G2 cancer and 56 mRNAs for G3 cancer. In addition, the expression of 25 mRNAs significantly changed regardless of endometrial cancer grade.
The next step involved the overrepresentation test for these 25 common mRNAs representing 18 genes and the selection of the “cellular response to reactive oxygen species” biological process and its subprocesses (Table 1).
A total of 4 out of 18 genes were not classified as related to oxidative stress. On the other hand, PRDX2, PKD2, AQP1, SOD3, KLF2 participate in all subprocesses related to the response to oxidative stress. Detailed results of the microarray experiment for 14 genes associated with oxidative stress are presented in Table 2.
The experiment showed that AQP1, CYBA, MELK, PKD2, PRDX2 were significantly overexpressed in endometrial cancer, while ATP2B4, FOXO1, KCNMA1, KLF2, PRNP, SNCA, SOD3, THBS1, and TXNIP were downregulated.

2.2. PRDX2, PKD2, AQP1, SOD3, KLF2 Expression Profile Determined by RT-qPCR and ELISA

The results of the microarray experiment were first verified by RT-qPCR. The Shapiro–Wilk test confirmed the lack of normal distribution of the data. The Kruskal–Wallis and Dunn’s tests were performed. Table 3 shows the results of the statistical analysis together with the median, first (Q1) and third (Q3) quartiles.
The results showed the overexpression of PRDX2, PKD2, and AQP1 with reduced levels of SOD3 and KLF2, which is consistent with the microarray experiment.
Then, the expression of PRDX2, PKD2, AQP1, SOD3, and KLF2 was also determined at the protein level (Table 4).
The obtained results indicate the overexpression of PRDX2 and PKD2 in endometrial cancer, regardless of its grade, which is consistent with the analysis at the mRNA level. Similar results were found for KLF2, whose expression was downregulated. In the case of SOD3 and AQP1, their expression was significantly altered in G2 and G3 cancer.

2.3. miRNA Target Prediction

Of the 1105 miRNAs found on the microarray, the number of miRNAs differentiating each cancer grade from the control was as follows: G1 vs. C, 131 miRNAs; G2 vs. C, 58 miRNAs; G3 vs. C, 84 miRNAs (p < 0.05; FC > 2 or FC < −2). The next step was to assess which of the differentiating miRNAs could participate in the regulation of the activity of PRDX2, PKD2, AQP1, SOD3, and KLF2 (Table 5).
The obtained results indicate that overexpression of PKD2 may be related to significantly reduced activity of miR-195-3p, miR-20a and increased the levels of miR-106a, miR-328 in the early stages of endometrial cancer. At a later stage, the involvement of miR-134 is also possible. Interestingly, miR-183 initially shows a decrease in activity, which changes dramatically in G3 cancer. The reduced expression of SOD3 may be due to the increased activity of miR-328 in G1 cancer and miR-363 in G3 cancer. In the case of KLF2, miR-195-3p level was reduced while miR-363 was overexpressed. PRDX2 and AQP1 expression is most likely not regulated by miRNAs selected in microarray analysis with our criteria.

3. Discussion

ROS are formed as by-products of normal cell metabolism. They are needed to maintain cell homeostasis and signaling, which is possible due to defense systems that keep ROS at a low level by converting free radicals into stable, less harmful molecules. Disruption of this balance leads to a phenomenon called oxidative stress [26].
In our study, we analyzed the expression profile of genes related to oxidative stress in endometrial cancer at both mRNA and protein levels. The use of the GeneCards database and the following Overrepresentation test using the Protein Analysis Through Evolutionary Relationship (PANTHER) tool allowed the selection of five genes that were present in all subprocesses related to the cellular response to ROS. An important step was also the identification of miRNAs significantly differentiating endometrial cancer from the control and further prediction of which of them may regulate their expression of peroxiredoxin 2 (PRDX2), polycystin 2 (PKD2), aquaporin 1 (AQP1), superoxide dismutase 3 (SOD3), and Krueppel-like factor 2 (KLF2).
The generation of ROS in cancer cells has been associated with the promotion of proliferation through increased activity of PI3K/Akt signaling as a result of PTEN inactivation [27]. The Akt pathway also promotes cell survival by inactivating the pro-apoptotic transcription factors Bad, Bax, Bim and Foxo [28]. Interestingly, elevated intracellular Ca2+ is also associated with the activation of pro-survival pathways [29]. Oxidative stress responses therefore require an influx of Ca2+ from both extracellular and intracellular environments as the initial step in combating cellular damage [30]. PKD1 is a large transmembrane sensor protein that interacts with PKD2, a Ca2+ permeable cation channel [31].
In our work, PKD2 was significantly overexpressed regardless of cancer grade, which could be due to the miRNA activity. In the early stages of the disease, miR-106a, miR-195-3p and miR-20a appear to be important. Lu et al. observed that miR-106a promotes prostate cancer proliferation through PTEN [32]. Similar conclusions were reached by Xie et al. in the non-small cell lung cancer (NSCLC) study [33]. In turn, Li et al. indicated the promotion of pancreatic cancer metastasis by targeting TIMP-2 [34]. Interestingly, miR-106a acts as a tumor suppressor in renal target carcinoma [35] and colorectal cancer [36]. For endometrial cancer, Tang et al. observed elevated miR-106a level in cell lines (HEC-1-A, HEC-1B, RL95-2, AN3CA, Ishikawa, and JEC), which promotes tumor growth by targeting BCL2L11 [37]. Similar conclusions were drawn by Li et al. in a study on the EC cell line (RL95-2), where overexpression of this miRNA promoted proliferation and inhibited apoptosis [38]. For endometrial cancer tissue samples, studies to date have also shown overexpression of miR-106a [39,40,41], which is consistent with our observations. High levels of miR-106a in G1 endometrial cancer and overexpression of PKD2 may indicate that the potential regulation of expression does not occur directly, and perhaps the activity of elements modulating the normal level of PKD2 is suppressed. It is also possible that there is a loss of the regulatory effects of miR-195-3p and miR-20a, which are silenced in the early stages of the disease. For both miRNAs, our results are consistent with previous studies in endometrial cancer [42,43,44]. High levels of PKD2 in endometrial cancer may also be associated with a significant decrease in miR-134 activity in G2 and G3 cancer. This is not consistent with the study by Hiroki et al. However, it should be noted that our study material was endometrioid EC and not serous EC [42]. MiR-134 is considered a tumor suppressor in gastric cancer [45], esophageal squamous cell carcinoma [46] as well as colorectal cancer [47]. An interesting case is miR-183, whose activity is initially reduced and then dramatically increases in G3 cancer. Furthermore, studies by other researchers indicate that in endometrial cancer, it may be an oncogene as well as a tumor suppressor [48].
In our study, we also noted a reduced expression of SOD3, which may be a consequence of the increased activity of miR-328 and miR-363. SOD3 regulates tissue redox balance and plays a protective role by preventing oxidative damage to proteins and lipids. Low levels of SOD3 are associated with a higher incidence of cancer and poor prognosis [49]. Wang and Xia showed that restoring miR-328 expression in cervical cancer has therapeutic potential [50]. Similarly, in non-small cell lung cancer, the upregulation of this miRNA sensitizes cancer cells to radiotherapy [51]. On the other hand, Wang et al. observed that miR-328 targets PTEN, which confers resistance to cisplatin in NSCLC cells [52]. In addition, targeting LOXL4 promotes growth, survival and migration of this tumor [53]. In the case of miR-363, Lu et al. noted its overexpression in endometrial cancer, which is consistent with our results [54]. In turn, miR-363 also acts as a tumor suppressor in colorectal cancer [55] and gastric cancer [56].
KLF2 regulates the expression of many antithrombotic, antioxidant and anti-inflammatory genes in endothelial cells [57]. Its reduced expression has been reported in colorectal cancer [58], non-small cell lung cancer [59] and prostate cancer [60]. Predictive analysis in our study showed that reduced KLF2 expression could potentially be associated with low miR-195-3p activity and high miR-363 levels, which were described previously.
As part of our research, we also determined the expression profile of PRDX2 and AQP1 at the mRNA and protein levels. Peroxiredoxins are peroxidases that affect differentiation, proliferation and apoptosis [61]. Interestingly, their low levels can sensitize cells to apoptosis and chemotherapy, while their excess promotes resistance to radiation and chemotherapeutic agents [62]. Feng et al. observed that overexpression of PRDX2 inhibited the migration of colorectal cancer cells, which is the result of blocking the epithelial-mesenchymal transition (EMT) [63]. On the other hand, Zheng et al. showed that PRDX2 promotes the progression of this tumor by activating the p38 MAPK pathway [64]. In turn, Chen et al. reported that a high level of PRDX2 promotes a poor prognosis in patients with lung cancer [65]. Aquaporin 1 is a small hydrophobic transmembrane protein that plays a dominant role in transcellular water transport. It is also believed to have a significant role in the migration and invasion of cancer cells [66]. Ji et al. demonstrated that the knockdown of AQP1 inhibited growth, migration and invasion of triple-negative breast cancer [67]. Yamazato et al. showed that AQP1 affects death receptor signaling, resulting in the inhibition of apoptosis and poor prognosis [68]. In turn, Huo et al. observed that hypoxia upregulates AQP1 expression, which contributes to the change of the tumor phenotype to migratory [69].
In the case of PRDX2 and AQP1, further analysis failed to identify miRNAs potentially interacting with these genes. It is possible that they did not meet our criteria or they were not included in our version of the microarrays. It would be promising to expand the list of analyzed miRNAs, as well as to experimentally verify the found interactions. Nevertheless, as part of this work, genes associated with oxidative stress were selected for which a comprehensive analysis was performed, and potential targets for further research were outlined.

4. Materials and Methods

The following study was approved by the Bioethical Committee operating at the Regional Medical Chamber in Krakow, no. 185/KBL/OIL/2020 and 186/KBL/OIL/2020, 20 September 2020. All procedures involving human participants were performed in accordance with the guidelines of the 2013 Declaration of Helsinki. Informed consent was obtained from every patient.
All patients enrolled in the study were qualified for hysterectomy. The control group consisted of 45 patients without cancer who underwent surgery for uterine prolapse. A total of 45 patients diagnosed with endometrioid endometrial cancer (EEC) constituted the study group. The collected cancer tissue samples were divided into three subgroups (grades) based on histopathological evaluation: G1, 15 samples; G2, 15 samples; G3, 15 samples. The exclusion criteria included the diagnosis of cancer different than EEC, the coexistence of another cancer, endometriosis, the use of hormone therapy 24 months prior to surgery.
The obtained samples were stored in tubes with Allprotect Tissue Reagent (Qiagen GmbH, Hilden, Germany). TRIzol reagent (Invitrogen Life Technologies, Carlsbad, CA, USA) was used to extract total RNA.
The expression profile of genes involved in oxidative stress was assessed using HG-U133A 2_0 oligonucleotide microarrays (Affymetrix, Santa Clara, CA, USA) and the GeneChip™ HT 3′IVT PLUS kit (Thermo Fisher Scientific, Inc., Waltham, MA, USA) according to the manufacturer’s instruction. The list of genes was prepared based on data from the GeneCards database (https://www.genecards.org/), using the keywords: oxidative AND stress, accessed on 25 August 2022 [70,71]. Then, for genes differentiating endometrial cancer from control, regardless of its grade, the Binomial Overrepresentation test with Bonferroni correction was performed using the Protein Analysis Through Evolutionary Relationship (PANTHER) tool. From GO Biological Process, “cellular response to reactive oxygen species” was selected [72].
RT-qPCR was then performed to validate the results. The SensiFast SYBR No-ROX One-Step Kit (Bioline, London, UK) and β-actin (ACTB), an endogenous control, were used to evaluate the expression profile of PRDX2, PKD2, AQP1, SOD3, KLF2 using a DNA Engine Opticon detector system (MJ Research Inc., Watertown, MA, USA). The thermal profile included reverse transcription (45 °C, 10 min), polymerase activation (95 °C, 2 min) and 40 cycles of denaturation (95 °C, 5 s), hybridization (60 °C, 10 s), and elongation (72 °C, 5 s). Primer sequences are listed in Table 6.
The expression profile of PRDX2, PKD2, AQP1, SOD3, and KLF2 proteins was assessed by ELISA according to the manufacturer’s instructions (Abbexa, Cambridge, UK) using the following kits: Human Peroxiredoxin 2 (PRDX2) ELISA Kit, Human Polycystin-2 (PKD2) ELISA Kit, Human Aquaporin 1 (AQP1) ELISA Kit, Human Superoxide Dismutase 3, Extracellular (SOD3) ELISA Kit, Human Krueppel-like factor 2 (KLF2) ELISA Kit. An Infinite M200 PRO microplate reader (Tecan, Männedorf, Switzerland) was used to evaluate absorbance at 540 nm.
The next step was to determine miRNAs significantly changing expression in endometrial cancer. For this purpose, miRNA 2.0 microarrays (Affymetrix, Santa Clara, CA, USA), FlashTag Biotin HSR RNA Labeling Kit (Affymetrix, Santa Clara, CA, USA) and Hybridization Wash and Stain Kit (Affymetrix, Santa Clara, CA, USA) were used in accordance with the manufacturer’s instructions. The mirDB tool (http://mirdb.org; accessed on 16 October 2022) was then used to predict miRNA targets among the studied genes (target score ≥ 75) [73].
Transcriptome Analysis Console software (Thermo Fisher Scientific, Waltham, MA, USA) was used to analyze the results of the microarray experiments. One-way ANOVA and Tukey’s post hoc test were performed (p < 0.05; FC > 2 or FC < −2). Analysis of RT-qPCR and ELISA results was conducted on R using RStudio (version 116 4.2.0, RStudio, Inc., Boston, MA, USA). Data distribution was examined with the Shapiro-Wilk test. The lack of distribution normality allowed the Kruskal–Wallis and Dunn’s post-hoc tests to be performed. A P-value adjustment for multiple testing was carried out with the Benjamini–Hochberg false discovery rate correction.

Author Contributions

Conceptualization, P.M. and S.J.; methodology, P.M., S.J. and B.O.G.; software, N.Z.; validation, N.Z. and K.D.; investigation, P.M., S.J. and N.Z.; resources, D.S. and P.O.; data curation, N.Z.; writing—original draft preparation, N.Z., P.M. and S.J.; writing—review and editing, B.O.G., D.B. and M.O.; supervision, B.O.G., D.B. and M.O.; project administration, B.O.G., D.B. and M.O. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The following study was approved by the Bioethical Committee operating at the Regional Medical 64 Chamber in Krakow, no. 185/KBL/OIL/2020 and 186/KBL/OIL/2020, 20 September 2020.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper.

Data Availability Statement

The data used to support the findings of this study is included in the article. The data will not be shared due to third-party rights and commercial confidentiality.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Valko, M.; Leibfritz, D.; Moncol, J.; Cronin, M.T.D.; Mazur, M.; Telser, J. Free Radicals and Antioxidants in Normal Physiological Functions and Human Disease. Int. J. Biochem. Cell Biol. 2007, 39, 44–84. [Google Scholar] [CrossRef] [PubMed]
  2. Genestra, M. Oxyl Radicals, Redox-Sensitive Signalling Cascades and Antioxidants. Cell. Signal. 2007, 19, 1807–1819. [Google Scholar] [CrossRef] [PubMed]
  3. Valko, M.; Morris, H.; Cronin, M.T.D. Metals, Toxicity and Oxidative Stress. Curr. Med. Chem. 2005, 12, 1161–1208. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Sharifi-Rad, M.; Anil Kumar, N.V.; Zucca, P.; Varoni, E.M.; Dini, L.; Panzarini, E.; Rajkovic, J.; Tsouh Fokou, P.V.; Azzini, E.; Peluso, I.; et al. Lifestyle, Oxidative Stress, and Antioxidants: Back and Forth in the Pathophysiology of Chronic Diseases. Front. Physiol. 2020, 11, 694. [Google Scholar] [CrossRef] [PubMed]
  5. Krylatov, A.V.; Maslov, L.N.; Voronkov, N.S.; Boshchenko, A.A.; Popov, S.V.; Gomez, L.; Wang, H.; Jaggi, A.S.; Downey, J.M. Reactive Oxygen Species as Intracellular Signaling Molecules in the Cardiovascular System. Curr. Cardiol. Rev. 2018, 14, 290–300. [Google Scholar] [CrossRef] [PubMed]
  6. Villalpando-Rodriguez, G.E.; Gibson, S.B. Reactive Oxygen Species (ROS) Regulates Different Types of Cell Death by Acting as a Rheostat. Oxid. Med. Cell. Longev. 2021, 2021, 9912436. [Google Scholar] [CrossRef] [PubMed]
  7. Canton, M.; Sánchez-Rodríguez, R.; Spera, I.; Venegas, F.C.; Favia, M.; Viola, A.; Castegna, A. Reactive Oxygen Species in Macrophages: Sources and Targets. Front. Immunol. 2021, 12, 734229. [Google Scholar] [CrossRef]
  8. Zhang, J.; Wang, X.; Vikash, V.; Ye, Q.; Wu, D.; Liu, Y.; Dong, W. ROS and ROS-Mediated Cellular Signaling. Oxid. Med. Cell. Longev. 2016, 2016, 4350965. [Google Scholar] [CrossRef] [Green Version]
  9. Juan, C.A.; Pérez de la Lastra, J.M.; Plou, F.J.; Pérez-Lebeña, E. The Chemistry of Reactive Oxygen Species (ROS) Revisited: Outlining Their Role in Biological Macromolecules (DNA, Lipids and Proteins) and Induced Pathologies. Int. J. Mol. Sci. 2021, 22, 4642. [Google Scholar] [CrossRef]
  10. Sies, H. Oxidative Stress: A Concept in Redox Biology and Medicine. Redox Biol. 2015, 4, 180–183. [Google Scholar] [CrossRef]
  11. Valko, M.; Izakovic, M.; Mazur, M.; Rhodes, C.J.; Telser, J. Role of Oxygen Radicals in DNA Damage and Cancer Incidence. Mol. Cell. Biochem. 2004, 266, 37–56. [Google Scholar] [CrossRef] [PubMed]
  12. Valko, M.; Rhodes, C.J.; Moncol, J.; Izakovic, M.; Mazur, M. Free Radicals, Metals and Antioxidants in Oxidative Stress-Induced Cancer. Chem. Biol. Interact. 2006, 160, 1–40. [Google Scholar] [CrossRef] [PubMed]
  13. Hayes, J.D.; Dinkova-Kostova, A.T.; Tew, K.D. Oxidative Stress in Cancer. Cancer Cell 2020, 38, 167–197. [Google Scholar] [CrossRef]
  14. Kuehne, A.; Emmert, H.; Soehle, J.; Winnefeld, M.; Fischer, F.; Wenck, H.; Gallinat, S.; Terstegen, L.; Lucius, R.; Hildebrand, J.; et al. Acute Activation of Oxidative Pentose Phosphate Pathway as First-Line Response to Oxidative Stress in Human Skin Cells. Mol. Cell 2015, 59, 359–371. [Google Scholar] [CrossRef] [Green Version]
  15. Kumari, S.; Badana, A.K.; Malla, R. Reactive Oxygen Species: A Key Constituent in Cancer Survival. Biomark. Insights 2018, 13, 1177271918755391. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Galadari, S.; Rahman, A.; Pallichankandy, S.; Thayyullathil, F. Reactive Oxygen Species and Cancer Paradox: To Promote or to Suppress? Free Radic. Biol. Med. 2017, 104, 144–164. [Google Scholar] [CrossRef] [PubMed]
  17. O’Brien, J.; Hayder, H.; Zayed, Y.; Peng, C. Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation. Front. Endocrinol. 2018, 9, 402. [Google Scholar] [CrossRef] [Green Version]
  18. Cosentino, G.; Plantamura, I.; Cataldo, A.; Iorio, M.V. MicroRNA and Oxidative Stress Interplay in the Context of Breast Cancer Pathogenesis. Int. J. Mol. Sci. 2019, 20, 5143. [Google Scholar] [CrossRef] [Green Version]
  19. Xu, Y.; He, X.; Deng, J.; Xiong, L.; Chen, B.; Chen, J.; Zhang, X.; Chen, W.; Liu, X.; Hu, X.; et al. ROS-Related MiRNAs Regulate Immune Response and Chemoradiotherapy Sensitivity in Hepatocellular Carcinoma by Comprehensive Analysis and Experiment. Oxid. Med. Cell. Longev. 2022, 2022, 4713518. [Google Scholar] [CrossRef]
  20. Yin, M.; Ren, X.; Zhang, X.; Luo, Y.; Wang, G.; Huang, K.; Feng, S.; Bao, X.; Huang, K.; He, X.; et al. Selective Killing of Lung Cancer Cells by MiRNA-506 Molecule through Inhibiting NF-ΚB P65 to Evoke Reactive Oxygen Species Generation and P53 Activation. Oncogene 2015, 34, 691–703. [Google Scholar] [CrossRef]
  21. Li, X.; Xin, S.; He, Z.; Che, X.; Wang, J.; Xiao, X.; Chen, J.; Song, X. MicroRNA-21 (MiR-21) Post-Transcriptionally Downregulates Tumor Suppressor PDCD4 and Promotes Cell Transformation, Proliferation, and Metastasis in Renal Cell Carcinoma. Cell. Physiol. Biochem. Int. J. Exp. Cell. Physiol. Biochem. Pharmacol. 2014, 33, 1631–1642. [Google Scholar] [CrossRef] [PubMed]
  22. Jajoo, S.; Mukherjea, D.; Kaur, T.; Sheehan, K.E.; Sheth, S.; Borse, V.; Rybak, L.P.; Ramkumar, V. Essential Role of NADPH Oxidase-Dependent Reactive Oxygen Species Generation in Regulating MicroRNA-21 Expression and Function in Prostate Cancer. Antioxid. Redox Signal. 2013, 19, 1863–1876. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Rizzo, S.; Femia, M.; Buscarino, V.; Franchi, D.; Garbi, A.; Zanagnolo, V.; Del Grande, M.; Manganaro, L.; Alessi, S.; Giannitto, C.; et al. Endometrial Cancer: An Overview of Novelties in Treatment and Related Imaging Keypoints for Local Staging. Cancer Imaging Off. Publ. Int. Cancer Imaging Soc. 2018, 18, 45. [Google Scholar] [CrossRef] [PubMed]
  24. Moore, K.; Brewer, M.A. Endometrial Cancer: Is This a New Disease? Am. Soc. Clin. Oncol. Educ. Book Am. Soc. Clin. Oncol. Annu. Meet. 2017, 37, 435–442. [Google Scholar] [CrossRef] [PubMed]
  25. Raffone, A.; Travaglino, A.; Raimondo, D.; Neola, D.; Renzulli, F.; Santoro, A.; Insabato, L.; Casadio, P.; Zannoni, G.F.; Zullo, F.; et al. Prognostic Value of Myometrial Invasion and TCGA Groups of Endometrial Carcinoma. Gynecol. Oncol. 2021, 162, 401–406. [Google Scholar] [CrossRef] [PubMed]
  26. Arfin, S.; Jha, N.K.; Jha, S.K.; Kesari, K.K.; Ruokolainen, J.; Roychoudhury, S.; Rathi, B.; Kumar, D. Oxidative Stress in Cancer Cell Metabolism. Antioxidants 2021, 10, 642. [Google Scholar] [CrossRef]
  27. Nogueira, V.; Patra, K.C.; Hay, N. Selective Eradication of Cancer Displaying Hyperactive Akt by Exploiting the Metabolic Consequences of Akt Activation. eLife 2018, 7, e32213. [Google Scholar] [CrossRef]
  28. Yue, D.; Sun, X. Idelalisib Promotes Bim-Dependent Apoptosis through AKT/FoxO3a in Hepatocellular Carcinoma. Cell Death Dis. 2018, 9, 935. [Google Scholar] [CrossRef] [Green Version]
  29. Ermak, G.; Davies, K.J.A. Calcium and Oxidative Stress: From Cell Signaling to Cell Death. Mol. Immunol. 2002, 38, 713–721. [Google Scholar] [CrossRef]
  30. Brill, A.L.; Fischer, T.T.; Walters, J.M.; Marlier, A.; Sewanan, L.R.; Wilson, P.C.; Johnson, E.K.; Moeckel, G.; Cantley, L.G.; Campbell, S.G.; et al. Polycystin 2 Is Increased in Disease to Protect against Stress-Induced Cell Death. Sci. Rep. 2020, 10, 386. [Google Scholar] [CrossRef]
  31. Lemos, F.O.; Ehrlich, B.E. Polycystin and Calcium Signaling in Cell Death and Survival. Cell Calcium 2018, 69, 37–45. [Google Scholar] [CrossRef] [PubMed]
  32. Lu, J.; Mu, X.; Yin, Q.; Hu, K. MiR-106a Contributes to Prostate Carcinoma Progression through PTEN. Oncol. Lett. 2019, 17, 1327–1332. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Xie, X.; Liu, H.-T.; Mei, J.; Ding, F.-B.; Xiao, H.-B.; Hu, F.-Q.; Hu, R.; Wang, M.-S. MiR-106a Promotes Growth and Metastasis of Non-Small Cell Lung Cancer by Targeting PTEN. Int. J. Clin. Exp. Pathol. 2015, 8, 3827–3834. [Google Scholar] [PubMed]
  34. Li, P.; Xu, Q.; Zhang, D.; Li, X.; Han, L.; Lei, J.; Duan, W.; Ma, Q.; Wu, Z.; Wang, Z. Upregulated MiR-106a Plays an Oncogenic Role in Pancreatic Cancer. FEBS Lett. 2014, 588, 705–712. [Google Scholar] [CrossRef] [Green Version]
  35. Ma, J.; Wang, W.; Azhati, B.; Wang, Y.; Tusong, H. MiR-106a-5p Functions as a Tumor Suppressor by Targeting VEGFA in Renal Cell Carcinoma. Dis. Markers 2020, 2020, 8837941. [Google Scholar] [CrossRef]
  36. Huang, Q.; Ma, Q. MicroRNA-106a Inhibits Cell Proliferation and Induces Apoptosis in Colorectal Cancer Cells. Oncol. Lett. 2018, 15, 8941–8944. [Google Scholar] [CrossRef] [Green Version]
  37. Tang, W.; Li, J.; Liu, H.; Zhou, F.; Liu, M. MiR-106a Promotes Tumor Growth, Migration, and Invasion by Targeting BCL2L11 in Human Endometrial Adenocarcinoma. Am. J. Transl. Res. 2017, 9, 4984–4993. [Google Scholar]
  38. Li, X.; Yi, X.; Bie, C.; Wang, Z. Expression of MiR-106 in Endometrial Carcinoma RL95-2 Cells and Effect on Proliferation and Invasion of Cancer Cells. Oncol. Lett. 2018, 16, 2251–2254. [Google Scholar] [CrossRef] [Green Version]
  39. Boren, T.; Xiong, Y.; Hakam, A.; Wenham, R.; Apte, S.; Wei, Z.; Kamath, S.; Chen, D.-T.; Dressman, H.; Lancaster, J.M. MicroRNAs and Their Target Messenger RNAs Associated with Endometrial Carcinogenesis. Gynecol. Oncol. 2008, 110, 206–215. [Google Scholar] [CrossRef]
  40. Chung, T.K.H.; Cheung, T.-H.; Huen, N.-Y.; Wong, K.W.Y.; Lo, K.W.K.; Yim, S.-F.; Siu, N.S.S.; Wong, Y.-M.; Tsang, P.-T.; Pang, M.-W.; et al. Dysregulated MicroRNAs and Their Predicted Targets Associated with Endometrioid Endometrial Adenocarcinoma in Hong Kong Women. Int. J. Cancer 2009, 124, 1358–1365. [Google Scholar] [CrossRef]
  41. Donkers, H.; Bekkers, R.; Galaal, K. Diagnostic Value of MicroRNA Panel in Endometrial Cancer: A Systematic Review. Oncotarget 2020, 11, 2010–2023. [Google Scholar] [CrossRef] [PubMed]
  42. Hiroki, E.; Akahira, J.-I.; Suzuki, F.; Nagase, S.; Ito, K.; Suzuki, T.; Sasano, H.; Yaegashi, N. Changes in MicroRNA Expression Levels Correlate with Clinicopathological Features and Prognoses in Endometrial Serous Adenocarcinomas. Cancer Sci. 2010, 101, 241–249. [Google Scholar] [CrossRef] [PubMed]
  43. Tsukamoto, O.; Miura, K.; Mishima, H.; Abe, S.; Kaneuchi, M.; Higashijima, A.; Miura, S.; Kinoshita, A.; Yoshiura, K.; Masuzaki, H. Identification of Endometrioid Endometrial Carcinoma-Associated MicroRNAs in Tissue and Plasma. Gynecol. Oncol. 2014, 132, 715–721. [Google Scholar] [CrossRef] [PubMed]
  44. Huang, Y.; Yang, N. MicroRNA-20a-5p Inhibits Epithelial to Mesenchymal Transition and Invasion of Endometrial Cancer Cells by Targeting STAT3. Int. J. Clin. Exp. Pathol. 2018, 11, 5715–5724. [Google Scholar] [PubMed]
  45. Qiu, Z.-A.; He, G.-P. MicroRNA-134 Functions as a Tumor Suppressor Gene in Gastric Cancer. Am. J. Transl. Res. 2016, 8, 4320–4328. [Google Scholar]
  46. Yuan, Y.; Wang, Q.; Cao, F.; Han, B.; Xu, L. MiRNA-134 Suppresses Esophageal Squamous Cell Carcinoma Progression by Targeting FOXM1. Int. J. Clin. Exp. Pathol. 2019, 12, 2130–2138. [Google Scholar]
  47. Xie, Y.; Song, J.; Zong, Q.; Wang, A.; Yang, Y.; Liu, F.; Meng, X. Decreased Expression of MIR-134 and Its Clinical Significance in Human Colorectal Cancer. Hepatogastroenterology 2015, 62, 615–619. [Google Scholar]
  48. Cao, D.; Di, M.; Liang, J.; Shi, S.; Tan, Q.; Wang, Z. MicroRNA-183 in Cancer Progression. J. Cancer 2020, 11, 1315–1324. [Google Scholar] [CrossRef] [Green Version]
  49. Mira, E.; Carmona-Rodríguez, L.; Pérez-Villamil, B.; Casas, J.; Fernández-Aceñero, M.J.; Martínez-Rey, D.; Martín-González, P.; Heras-Murillo, I.; Paz-Cabezas, M.; Tardáguila, M.; et al. SOD3 Improves the Tumor Response to Chemotherapy by Stabilizing Endothelial HIF-2α. Nat. Commun. 2018, 9, 575. [Google Scholar] [CrossRef] [Green Version]
  50. Wang, X.; Xia, Y. MicroRNA-328 Inhibits Cervical Cancer Cell Proliferation and Tumorigenesis by Targeting TCF7L2. Biochem. Biophys. Res. Commun. 2016, 475, 169–175. [Google Scholar] [CrossRef]
  51. Ma, W.; Ma, C.-N.; Zhou, N.-N.; Li, X.-D.; Zhang, Y.-J. Up- Regulation of MiR-328-3p Sensitizes Non-Small Cell Lung Cancer to Radiotherapy. Sci. Rep. 2016, 6, 31651. [Google Scholar] [CrossRef] [Green Version]
  52. Wang, C.; Wang, S.; Ma, F.; Zhang, W. MiRNA-328 Overexpression Confers Cisplatin Resistance in Non-small Cell Lung Cancer via Targeting of PTEN. Mol. Med. Rep. 2018, 18, 4563–4570. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Ji, Y.; You, Y.; Wu, Y.; Wang, M.; He, Q.; Zhou, X.; Chen, L.; Sun, X.; Liu, Y.; Fu, X.; et al. Overexpression of MiR-328-5p Influences Cell Growth and Migration to Promote NSCLC Progression by Targeting LOXL4. Ann. Transl. Med. 2022, 10, 301. [Google Scholar] [CrossRef] [PubMed]
  54. Lu, J.; Liang, J.; Xu, M.; Wu, Z.; Cheng, W.; Wu, J. Identification of an Eleven-MiRNA Signature to Predict the Prognosis of Endometrial Cancer. Bioengineered 2021, 12, 4201–4216. [Google Scholar] [CrossRef] [PubMed]
  55. Dong, J.; Geng, J.; Tan, W. MiR-363-3p Suppresses Tumor Growth and Metastasis of Colorectal Cancer via Targeting SphK2. Biomed. Pharmacother. Biomedecine Pharmacother. 2018, 105, 922–931. [Google Scholar] [CrossRef]
  56. Song, B.; Yan, J.; Liu, C.; Zhou, H.; Zheng, Y. Tumor Suppressor Role of MiR-363-3p in Gastric Cancer. Med. Sci. Monit. Int. Med. J. Exp. Clin. Res. 2015, 21, 4074–4080. [Google Scholar] [CrossRef] [Green Version]
  57. Dabravolski, S.A.; Sukhorukov, V.N.; Kalmykov, V.A.; Grechko, A.V.; Shakhpazyan, N.K.; Orekhov, A.N. The Role of KLF2 in the Regulation of Atherosclerosis Development and Potential Use of KLF2-Targeted Therapy. Biomedicines 2022, 10, 254. [Google Scholar] [CrossRef]
  58. Wang, H.-G.; Cao, B.; Zhang, L.-X.; Song, N.; Li, H.; Zhao, W.-Z.; Li, Y.-S.; Ma, S.-M.; Yin, D.-J. KLF2 Inhibits Cell Growth via Regulating HIF-1α/Notch-1 Signal Pathway in Human Colorectal Cancer HCT116 Cells. Oncol. Rep. 2017, 38, 584–590. [Google Scholar] [CrossRef] [Green Version]
  59. Li, W.; Sun, M.; Zang, C.; Ma, P.; He, J.; Zhang, M.; Huang, Z.; Ding, Y.; Shu, Y. Upregulated Long Non-Coding RNA AGAP2-AS1 Represses LATS2 and KLF2 Expression through Interacting with EZH2 and LSD1 in Non-Small-Cell Lung Cancer Cells. Cell Death Dis. 2016, 7, e2225. [Google Scholar] [CrossRef]
  60. Wang, B.; Liu, M.; Song, Y.; Li, C.; Zhang, S.; Ma, L. KLF2 Inhibits the Migration and Invasion of Prostate Cancer Cells by Downregulating MMP2. Am. J. Mens Health 2019, 13, 1557988318816907. [Google Scholar] [CrossRef] [Green Version]
  61. Mu, Z.M.; Yin, X.Y.; Prochownik, E.V. Pag, a Putative Tumor Suppressor, Interacts with the Myc Box II Domain of c-Myc and Selectively Alters Its Biological Function and Target Gene Expression. J. Biol. Chem. 2002, 277, 43175–43184. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Yo, Y.D.; Chung, Y.M.; Park, J.K.; Ahn, C.M.; Kim, S.K.; Kim, H.J. Synergistic Effect of Peroxiredoxin II Antisense on Cisplatin-Induced Cell Death. Exp. Mol. Med. 2002, 34, 273–277. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Feng, J.; Fu, Z.; Guo, J.; Lu, W.; Wen, K.; Chen, W.; Wang, H.; Wei, J.; Zhang, S. Overexpression of Peroxiredoxin 2 Inhibits TGF-Β1-Induced Epithelial-Mesenchymal Transition and Cell Migration in Colorectal Cancer. Mol. Med. Rep. 2014, 10, 867–873. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Zheng, X.; Wei, J.; Li, W.; Li, X.; Wang, W.; Guo, J.; Fu, Z. PRDX2 Removal Inhibits the Cell Cycle and Autophagy in Colorectal Cancer Cells. Aging 2020, 12, 16390–16409. [Google Scholar] [CrossRef]
  65. Chen, Y.; Yang, S.; Zhou, H.; Su, D. PRDX2 Promotes the Proliferation and Metastasis of Non-Small Cell Lung Cancer In Vitro and In Vivo. BioMed Res. Int. 2020, 2020, 8359860. [Google Scholar] [CrossRef]
  66. Tomita, Y.; Dorward, H.; Yool, A.J.; Smith, E.; Townsend, A.R.; Price, T.J.; Hardingham, J.E. Role of Aquaporin 1 Signalling in Cancer Development and Progression. Int. J. Mol. Sci. 2017, 18, 299. [Google Scholar] [CrossRef] [Green Version]
  67. Ji, Y.; Liao, X.; Jiang, Y.; Wei, W.; Yang, H. Aquaporin 1 Knockdown Inhibits Triple-Negative Breast Cancer Cell Proliferation and Invasion In Vitro and In Vivo. Oncol. Lett. 2021, 21, 437. [Google Scholar] [CrossRef]
  68. Yamazato, Y.; Shiozaki, A.; Ichikawa, D.; Kosuga, T.; Shoda, K.; Arita, T.; Konishi, H.; Komatsu, S.; Kubota, T.; Fujiwara, H.; et al. Aquaporin 1 Suppresses Apoptosis and Affects Prognosis in Esophageal Squamous Cell Carcinoma. Oncotarget 2018, 9, 29957–29974. [Google Scholar] [CrossRef] [Green Version]
  69. Huo, Z.; Lomora, M.; Kym, U.; Palivan, C.; Holland-Cunz, S.G.; Gros, S.J. AQP1 Is Up-Regulated by Hypoxia and Leads to Increased Cell Water Permeability, Motility, and Migration in Neuroblastoma. Front. Cell Dev. Biol. 2021, 9, 605272. [Google Scholar] [CrossRef]
  70. Stelzer, G.; Rosen, N.; Plaschkes, I.; Zimmerman, S.; Twik, M.; Fishilevich, S.; Stein, T.I.; Nudel, R.; Lieder, I.; Mazor, Y.; et al. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses. Curr. Protoc. Bioinform. 2016, 54, 1.30.1–1.30.33. [Google Scholar] [CrossRef]
  71. Safran, M.; Rosen, N.; Twik, M.; BarShir, R.; Stein, T.I.; Dahary, D.; Fishilevich, S.; Lancet, D. The GeneCards Suite. In Practical Guide to Life Science Databases; Abugessaisa, I., Kasukawa, T., Eds.; Springer Nature: Singapore, 2021; pp. 27–56. ISBN 9789811658129. [Google Scholar]
  72. Mi, H.; Thomas, P. PANTHER Pathway: An Ontology-Based Pathway Database Coupled with Data Analysis Tools. Methods Mol. Biol. Clifton NJ 2009, 563, 123–140. [Google Scholar] [CrossRef]
  73. Chen, Y.; Wang, X. MiRDB: An Online Database for Prediction of Functional MicroRNA Targets. Nucleic Acids Res. 2020, 48, D127–D131. [Google Scholar] [CrossRef] [PubMed]
Table
Table 1. List of genes involved in response to oxidative stress.
Table 1. List of genes involved in response to oxidative stress.
Biological ProcessNumber of GenesFold ChangeGene Symbolp-Value
cellular response to reactive oxygen species558.66PRDX2, PKD2, AQP1, SOD3, KLF20.0002
response to reactive oxygen species649.31PRDX2, PKD2, AQP1, SOD3, KLF2, TXNIP<0.0001
response to oxygen-containing compound1311.50PRDX2, PKD2, AQP1, SOD3, KLF2, TXNIP, KCNMA1, ATP2B4, CYBA, SNCA, THBS1, FOXO1, PRNP<0.0001
response to oxidative stress1037.40PRDX2, PKD2, AQP1, SOD3, KLF2, TXNIP, SNCA, FOXO1, PRNP, MELK<0.0001
cellular response to oxidative stress849.46PRDX2, PKD2, AQP1, SOD3, KLF2, SNCA, FOXO1, MELK<0.0001
cellular response to chemical stress840.22PRDX2, PKD2, AQP1, SOD3, KLF2, SNCA, FOXO1, MELK<0.0001
cellular response to oxygen-containing compound1012.96PRDX2, PKD2, AQP1, SOD3, KLF2, ATP2B4, CYBA, SNCA, FOXO1, PRNP<0.0001
Table
Table 2. List of mRNAs representing genes significantly differentiating endometrial cancer from control regardless of its grade, involved in response to oxidative stress (p < 0.05).
Table 2. List of mRNAs representing genes significantly differentiating endometrial cancer from control regardless of its grade, involved in response to oxidative stress (p < 0.05).
IDmRNAFold Change
G1 vs. CG2 vs. CG3 vs. C
207542_s_atAQP13.775.053.54
209047_atAQP12.94.392.01
212135_s_atATP2B4−2.77−3.55−4.59
212136_atATP2B4−3.43−3.66−3.48
203028_s_atCYBA2.233.262.98
202723_s_atFOXO1−5.1−8.03−7.99
202724_s_atFOXO1−3.27−5.4−3.89
221583_s_atKCNMA1−6.41−6.43−5.65
221584_s_atKCNMA1−17.35−18.23−11.35
219371_s_atKLF2−2.66−5.13−3.25
204825_atMELK3.173.843.07
203688_atPKD22.263.613.75
39729_atPRDX22.613.182.45
201300_s_atPRNP−2.89−8.14−4.09
215707_s_atPRNP−2.2−3.75−4.25
204466_s_atSNCA−2.42−4.62−4.29
205236_x_atSOD3−2.47−2.15−2.49
201108_s_atTHBS1−2.4−3.57−5.01
201009_s_atTXNIP−2.16−3.58−4.27
ID—number of the probe; C—control; G—grade of endometrial cancer.
Table
Table 3. Values of descriptive statistics, Kruskal–Wallis and Dunn’s tests in endometrial cancer and control (p < 0.05).
Table 3. Values of descriptive statistics, Kruskal–Wallis and Dunn’s tests in endometrial cancer and control (p < 0.05).
GeneGroupmRNA Copies/μg Total RNAKruskal–Wallis TestDunn’s Test
MeQ1Q3
PRDX2C22,98020,34325,632<0.001G1 vs. C, p < 0.001
G2 vs. C, p < 0.001
G3 vs. C, p < 0.001
G2 vs. G1, p = 0.014
G141,32139,46944,499
G251,32649,25056,410
G346,45239,82048,895
PKD2C19,34015,37522,048<0.001G1 vs. C, p = 0.001
G2 vs. C, p < 0.001
G3 vs. C, p < 0.001
G3 vs. G1, p = 0.003
G132,50129,79338,531
G243,03338,63748,262
G349,90646,57958,913
AQP1C7804505010,637<0.001G1 vs. C, p = 0.001
G2 vs. C, p < 0.001
G3 vs. C, p < 0.001
G112,230927816,038
G214,68310,71317,373
G315,92310,93818,431
SOD3C48,16241,26851,671<0.001G2 vs. C, p < 0.001
G3 vs. C, p < 0.001
G2 vs. C, p < 0.001
G115,36812,21517,756
G211,203982514,341
G311,823828418,383
KLF2C82,25777,98187,367<0.001G1 vs. C, p = 0.001
G2 vs. C, p < 0.001
G3 vs. C, p < 0.001
G3 vs. G1, p = 0.005
G119,67118,16323,383
G213,900928517,330
G38900390810,063
Me—median; Q1—lower quartile; Q3—upper quartile; C—control; G—grade of endometrial cancer.
Table
Table 4. Concentration of PRDX2, PKD2, AQP1, SOD3, and KLF2 in the study and control groups (p < 0.05).
Table 4. Concentration of PRDX2, PKD2, AQP1, SOD3, and KLF2 in the study and control groups (p < 0.05).
Concentration of Protein [ng/mL]CG1G2G3
PRDX20.45 ± 0.270.92 ± 0.12 *1.01 ± 0.08 *0.97 ± 0.08 *
PKD26.63 ± 19.06 ± 1.32 *10.7 ± 1.32 *11.1 ± 1.44 *,#
AQP15.23 ± 0.736.90 ± 1.428.21 ± 0.90 *8.20 ± 1.03 *
SOD3138.85 ± 14.869.2 ± 9.6645.1 ± 6.19 *32.0 ± 9.46 *,#
KLF25.79 ± 0.682.83 ± 0.36 *2.52 ± 0.50 *2.16 ± 0.64 *
C—control; G—grade of endometrial cancer. * p < 0.05 vs. C group; # p < 0.05 vs. G1 group.
Table
Table 5. List of selected genes associated with oxidative stress whose activity may be regulated by miRNAs in endometrial cancer.
Table 5. List of selected genes associated with oxidative stress whose activity may be regulated by miRNAs in endometrial cancer.
mRNAExpressionmiRNAFold Change
G1 vs. CG2 vs. CG3 vs. C
PKD2upregulatedmiR-106a9.33 *1.11.91
miR-195-3p−2.1 *−1.52−1.67
miR-20a−25.77 *−1.011.06
miR-134−3.15−6.02 *−16.07 *
miR-183−1.49−6.02 *79.9 *
SOD3downregulatedmiR-3287.74 *1.871.24
miR-363−1.212.1434.47 *
KLF2downregulatedmiR-195-3p−2.1 *−1.52−1.67
miR-363−1.212.1434.47 *
C—control; G—grade of endometrial cancer. * p < 0.05 vs. C group.
Table
Table 6. RT-qPCR primers.
Table 6. RT-qPCR primers.
mRNART-qPCR Amplification Primers (5′-3′)
PRDX2Forward: CCTTCCAGTACACAGACGAGCA
Reverse: CTCACTATCCGTTAGCCAGCCT
PKD2Forward: AAATGTCTGGCTGGACCGAGGA
Reverse: GGAATCACACCACCTGTTGCTG
AQP1Forward: TATGCGTGCTGGCTACTACCGA
Reverse: GGTTAATCCCACAGCCAGTGTAG
SOD3Forward: ACGCTGGCGAGGACGACCTG
Reverse: GCTTCTTGCGCTCTGAGTGCTC
ACTBForward: TCACCCACACTGTGCCCATCTACGA
Reverse: CAGCGGAACCGCTCATTGCCAATGG
PRDX2—peroxiredoxin 2; PKD2—polycystin-2; AQP1—aquaporin 1; SOD3—superoxide dismutase 3; KLF2—Krueppel-like factor 2; ACTB—β-actine.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Mieszczański, P.; Januszyk, S.; Zmarzły, N.; Ossowski, P.; Dziobek, K.; Sagan, D.; Boroń, D.; Opławski, M.; Grabarek, B.O. miRNAs Participate in the Regulation of Oxidative Stress-Related Gene Expression in Endometrioid Endometrial Cancer. Int. J. Mol. Sci. 2022, 23, 15817. https://doi.org/10.3390/ijms232415817

AMA Style

Mieszczański P, Januszyk S, Zmarzły N, Ossowski P, Dziobek K, Sagan D, Boroń D, Opławski M, Grabarek BO. miRNAs Participate in the Regulation of Oxidative Stress-Related Gene Expression in Endometrioid Endometrial Cancer. International Journal of Molecular Sciences. 2022; 23(24):15817. https://doi.org/10.3390/ijms232415817

Chicago/Turabian Style

Mieszczański, Paweł, Szmon Januszyk, Nikola Zmarzły, Piotr Ossowski, Konrad Dziobek, Dorota Sagan, Dariusz Boroń, Marcin Opławski, and Beniamin Oskar Grabarek. 2022. "miRNAs Participate in the Regulation of Oxidative Stress-Related Gene Expression in Endometrioid Endometrial Cancer" International Journal of Molecular Sciences 23, no. 24: 15817. https://doi.org/10.3390/ijms232415817

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop