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Regulation of HMGA2 and KRAS genes in epithelial ovarian cancer by miRNA hsa-let-7d-3p

1 Department of Molecular Biology and Genetics, Faculty of Science, Istanbul University, Istanbul, Turkey
2 Department of Obstetrics and Gynecology, Istanbul University, Istanbul Medical Faculty, Istanbul, Turkey
3 Medicus Health Center, Istanbul, Turkey

Correspondence Address:
Tuba Gunel,
Department of Molecular Biology and Genetics, Faculty of Science, Istanbul University, Istanbul 34134
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcrt.JCRT_866_18

 > Abstract 

Aim of the Study: The purpose of this study was to identify specific circulating microRNAs (miRNAs) and investigate expression level of their target genes for evaluation of pathogenesis of epithelial ovarian cancer (EOC).
Materials and Methods: In this study, we have studied on EOC patients' serum and whole blood, healthy control (HC) serum, and whole blood samples. Sixteen serum samples were collected to compare miRNA expression analysis through microarray. According to microarray results, one of the dysregulated miRNA in serum, hsa-let-7d-3p, was validated by RT-qPCR for discriminate two groups. The hsa-let-7d-3p is one of the tumor suppressive let-7d family members. Let-7d is downregulated in numerous types of cancer, including ovarian cancer and directly targets various oncogenes. We analyzed the let-7d targets, which are High Mobility Group A2 (HMGA2) and (Kirsten Rat Sarcoma Viral Oncogene Homolog), as the oncogenes that are associated with EOC. The relation between target genes of hsa-let-7d-3p and EOC has been examined by Pathway Studio. Twenty serum and whole blood samples collected to analyze expression level of target genes were analyzed by real-time PCR.
Results: 31 significantly dysregulated miRNAs were identified by microarray in serum. Hsa-let-7d-3p has been selected for the validation, according to P-value and dysregulated level. RT-qPCR results showed that hsa-let-7d-3p could discriminate EOC patients from HC (P = 0.0484, AUC = 0.7). Furthermore, we identified hsa-let-7d-3p's target genes (HMGA2,KRAS) by bioinformatic analysis. The expression level of genes could discriminate patients with EOC from HC, with a power area under the ROC curves (AUC) of 62 and 64.2, respectively.
Conclusion: HMGA2 and KRAS could be translationally downregulated by the hsa-let-7d-3p, and the loss of hsa-let-7d-3p expression led to the progression of EOC related to the tumorigenesis, invasion, and metastasis.

Keywords: Epithelial ovarian cancer, High Mobility Group A2, hsa-let-7d-3p, KRAS, microarray, microRNA

How to cite this URL:
Gunel T, Dogan B, Gumusoglu E, Hosseini MK, Topuz S, Aydinli K. Regulation of HMGA2 and KRAS genes in epithelial ovarian cancer by miRNA hsa-let-7d-3p. J Can Res Ther [Epub ahead of print] [cited 2019 Nov 21]. Available from: http://www.cancerjournal.net/preprintarticle.asp?id=269914

 > Introduction Top

Epithelial ovarian cancer (EOC) is the most lethal ovarian cancer as lack of screening tests and usually asymptomatic.[1] The diagnosis of EOC and imaging methods such as transvaginal ultrasonography, magnetic resonance imaging, and positron emission tomography are used with the serum protein biomarker CA-125 “Cancer Antigen 125” test. However, the sensitivity and specificity of these methods used for diagnosis are low. Therefore, it is necessary to identify and understand the progression and pathogenesis of EOC.[2]

MicroRNAs (miRNAs) are highly conserved RNA molecules with about 22 nucleotides that play a role in cell proliferation, differentiation, and cell cycle regulation.[3] There are two types of miRNAs with two different functions that play an important role in cancer development: tumor suppressor miRNAs “tumor suppressor miRs” and oncogenic miRNAs “oncomiRs.”[4] The defect in the regulation of both types of miRNAs influences the proliferation, invasion, epithelial-mesenchymal transition (EMT), and metastasis of tumor cells.[5] The let-7 family was first discovered in the Caenorhabditis elegans and presents the largest known family with conserved roles in several diseases.[6] In tumorigenesis, the let-7 family is considered to act in a tumor-suppressive manner since it interferes with the expression of various oncogenes or oncogenic factors, respectively.[5] Let-7 family targeted oncogenes which are c-Myc, KRAS (Kras Kirsten Rat Sarcoma Viral Oncogene), High Mobility Group A2 (HMGA2), Janus Protein Tyrosine Kinase, Signal Transducer, and Activator of Transcription 3.[7] Let-7 acts as a tumor suppressor by negatively regulating the expression of KRAS and HMGA2.[8] The loss of let-7 expression led to the progression of some human cancers through inability to suppress oncogenes.

HMGA2 is the nonhistone protein that binds to small A-T'-rich regions in the DNA strand which is including in HMGA protein family.[9] It acts locally and temporally in the mechanism of chromatin modification by the histones.[10] The HMGA2 oncogene is also expressed in ovarian cancer;[11] it is an important regulator for cell growth, cell differentiation, apoptosis, EMT, and metastasis, and this overexpression is partially related to the TP53 mutation.[12]

KRAS has been implicated in the development of human malignancies and involved in the mitogen-activated protein (MAP)-kinase signal transduction pathway, modulating cellular differentiation and proliferation. Mutations of the KRAS result in constitutive activation of this signal transduction pathway and consequently unregulated proliferation and impaired differentiation.[13] The downstream proteins of Ras signaling pathways downregulated when let-7 is overexpressed in cancer cells, resulting in changes in cell function.[7]

Hence, in this study, we evaluated mRNA levels of HMGA2 and KRAS genes expression which are targeted by hsa-let-7d-3p in EOC patients' serum and whole blood. Our analyses showed that circulating cell-free HMGA2 and KRAS mRNA were significantly elevated in the whole blood of EOC patients. High levels of HMGA2 and KRAS were associated with cancer progression. In conclusion, our data indicate the significance of HMGA2 and KRAS genes regulated by hsa-let-7d-3p for considering pathology and early diagnosis of EOC.

 > Material and Methods Top

Sample collection

In this study, sixteen serum samples were collected to compare miRNA expression levels by microarray. After microarray step, twenty serum and whole blood samples were collected by Department of Obstetrics and Gynecology, Istanbul Medical Faculty in Istanbul University and Medicus Health Centre, Istanbul (recruitment between February 2018 and April 2018). This study was approved by the Istanbul University Faculty of Medicine Clinical Researches Ethics Committee (Permission No: 2016/1427) on December 9, 2016. All experiments were performed in accordance with the approved guidelines and regulations.

The median age of HC and EOC is 44 and 47, respectively. The mean of the CA-125 level of EOC is 1520.2 U/ml. Alcohol and smoke profiles of all samples are negative. Histological type of EOC patients is high-grade serous. The control groups are HC for serum and whole blood.

Peripheral blood was collected into ethylenediaminetetraacetic acid tubes (5 ml) and immediately centrifuged at 3500 ×g for 15 min at 4°C. The supernatant fluid, which is called serum, was transferred to the cryo tubes after centrifugation process. Sample serum fractions were collected and stored at −80°C until laboratory workup. For whole blood samples' collection, about 3–4 ml of blood samples were taken in sterile clot activator tubes and stored at −80°C until workup.

Total RNA nextraction

Total RNA was extracted from whole blood and serum using “mirVana™ PARIS™ RNA and Native Protein Purification Kit” (Ambion, Life Technology, USA) according to the manufacturer's instructions. To test purification quality and to normalize variation, synthetic Caenorhabditis elegans miRNA (cel-miR-39/working solution 1.6x10-8 copies/ml), were spiked to each serum sample before the extraction protocol started. Synthetic cel-miR-39 (QIAGEN, Germany) has been chosen as spike-in due to the absence of homologous sequences in Homo sapiens. Total RNA was eluted with 35 μl mirVana elution solution. The concentration of RNA was determined using Qubit 1.0 Fluorometer with “Qubit RNA High Sensitivity Assay Kit” (Thermo Fisher Scientific, Waltham, MA, USA) and stored at −80°C.

Serum microRNAs' microarray analysis

The total RNA extracted from all serum samples have been used for microarray. MiRNA expression analysis has been done by Agilent miRNA microarray chips (Agilent Sure Print G3 Human miRNA r21 8 × 60K) using the miRNA Labeling and Hybridization Kit (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer's instructions. Total RNAs have been labeled by cyanine 3-cytidine bisphosphate (pCp-Cy3). The labeled miRNAs have been hybridized for 24 h on “Human miRNA Microarray Version 16” (Agilent Technologies, Santa Clara, CA, USA) slides which include 1368 miRNAs encoded by genes located across all chromosomes. The hybridized slides have been scanned by an Agilent Sure Scan Microarray Scanner (Model G2600D), and the images provided after scanning have been analyzed by “Agilent Feature Extraction (v. 12.0)” software (Agilent Technologies, Santa Clara, CA, USA).

Reverse transcription

The hsa-let-7d-3p (P< 0.05 and fold change (FC) > 2) obtained from microarray bioinformatics analysis was validated by stem-loop RT-qPCR. miRNAs were quantified using TaqMan MicroRNA Assays (Thermo Fisher Scientific, Waltham, MA, USA). Total RNA samples were reverse transcribed into cDNA using “TaqMan MicroRNA Reverse Transcription Kit” (AB, Applied Biosystem™, Lithuania) for miRNA analysis. For HMGA2 and KRAS genes expression analysis, total RNA samples were reverse transcribed into cDNA using the “High Capacity cDNA Reverse Transcription Kit” (Thermo Fisher, Shanghai, China) according to instructions provided by the manufacturer. All the reverse transcription reaction was performed with the Sure Cycler 8800 Thermal Cycler (Agilent Technologies Santa Clara, CA, USA).


RT-qPCR was performed using the Stratagene Mx3005P RT-qPCR system (Agilent Technologies, Santa Clara, CA, USA). For TaqMan RT-qPCR, each 20 μL PCR reaction, 10 μL TaqMan miRNA RT-qPCR Assay (AB applied biosystem, Universal PCR Master Mix, USA) and 20×TaqMan MicroRNA Assays containing PCR primers and probes (5'-FAM and 3'-TAMRA), 2.5 μL of cDNA for serum, and 6.5 μL of Invitrogen™ UltraPure™ DNase/RNase-Free Distilled Water were mixed together. Every batch of amplifications included two water blanks and primers as no template negative controls for each of the cDNA products and RT-qPCR steps. The reaction was first incubated at 50°C for 2 min and 95°C for 10 min, followed by 40 cycles of 95°C for 15 s and 60°C for 1 min. Data were normalized to cel-miR-39 for serum samples and GAPDHGlyceraldehyde-3-phosphate” housekeeping gene for whole blood samples. Data were analyzed with Stratagene Mx3005P RT-qPCR system (Agilent Technologies, Santa Clara, CA, USA) with the automatic Ct setting for adapting baselines and thresholds for Ct determination. The 2ΔΔCt method calculates relative FCs using Ct values. For SYBR Green RT-qPCR, each 20 μL PCR reaction, 12.5 μL FastStart Universal SYBR Green Master– Rox (Sigma-Aldrich, St. Louis, Missouri, ABD), 0.25 μL Quantiscript® Reverse Transcriptase (QIAGEN, Germany), 1.5 μL forward and 1.5 μL reverse primers, 2.5 μL template, and 6.75 μL Invitrogen™ UltraPure™ DNase/RNase-Free Distilled Water were mixed together. The primers used in this study were as follows: HMGA2 forward 5'-ACTTCAGCCCAGGGACAAC-3', HMGA2 reverse 5'-GCTGCTTTAGAGGGACTCTTGTT-3', KRAS forward 5'-AAGGCCTGCTGAAAATGACTG-3', KRAS reverse 5'-GGTCCTGCACCAGTAATATGCA-3', GAPDH forward 5'-CCCTTCATT GACCTCAACTACATG-3', and GAPDH reverse 5'-TGGGATTTCCATTGATGACAAG C-3'.

Statistical analysis

Statistical analysis of raw microarray data extracted from “Agilent Feature Extraction (v. 12.0)” software has been done using “GeneSpring v. 12.6” software (Agilent Technologies, Santa Clara, CA, USA). Raw data are normalized by quantile normalization, and probes <50% coefficient of variation have been filtered. Differentially expressed miRNAs were determined with a Student's t-test with Bonferroni FWER correction and the following fold change and P-value threshold of FC > 2 and P< 0.05. Samples with high variation and low-quality level were eliminated in the quality control step. GeneSpring software has given the list of the dysregulated miRNAs.

GraphPad Prism (v.7.04) (GraphPad Software, Inc., San Diego, CA) was used to perform statistical analysis for validation of data. The P value is an important parameter for the level of significance, and the confidence intervals (CIs) help to determine the CI for the ΔCt and ΔΔCt estimation. For analysis, statistical significance was characterized by P < 0.05. In this study, the Mann–Whitney U test was used to analyze the difference in serum miRNAs and targeted genes expression between EOC and HC. Standard deviation, CI, and P value were calculated using Ct values obtained from RT-qPCR results. Receiver operating characteristic (ROC) curves were generated, and area under the ROC curves (AUC) was calculated to obtain sensitivity and specificity. The best threshold or “cut-off” value for the distinction between control and patient outcomes was set at 0.5.

Pathway analysis

The pathway analysis for target genes of hsa-let-7d-3p and ovarian cancer were examined using computation bioinformatics program, which is Pathway Studio® (v., Elsevier B.V).

 > Results Top

Microarray results

Eight EOC serum samples and eight HC serum samples were compared for miRNA expression levels by microarray. The expression of serum miRNAs was found to be significantly downregulated by t-test Bonferroni FWER-corrected P < 0.05 and FC >2, in EOC serum samples. Microarray analysis has shown that 31 significantly dysregulated miRNAs were identified in serum [Table 1].
Table 1: Differentially expressed signature microRNAs in epithelial ovarian cancer compared to healthy control serum samples by microarray results and also miRBase accession number, P value and regulation

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The hierarchical clustering of dysregulated miRNAs which clarified that the subgroups were welldifferentiated from the unified set of differentially expressed miRNAs has been provided by miRNA microarray [Figure 1]. The expression level of hsa-let-7d-3p in serum has been presented as box whisker plot [Figure 2].
Figure 1: Eight epithelial ovarian cancer serum samples and eight HC serum samples compared with P < 0.05 determined by microarray analysis. Red indicates downregulation and green indicates upregulation. Each column represents a single microarray analysis

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Figure 2: Box whisker plot of serum microRNAs hsa-let-7d-3p in both epithelial ovarian cancer and HC by microarray analysis

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RT-qPCR results

Serum miRNA hsa-let-7d-3p has been selected for validation according to their P values (P< 0.05) and study frequency on EOC. To confirm miRNA microarray results, same samples were analyzed of miRNAs expression by TaqMan RT-qPCR. According to RT-qPCR results of EOC and HC serum samples, different expression of hsa-let-7d-3p was statistically significant (P< 0.05). Hsa-let-7d-3p was found to be down-regulated (log FC= -2.35) in EOC patients when compared with HC with a marginally significant P-value (P=0.0488). Hsa-let-7d-3p was significantly downregulated and validated in EOC (95% CI 0.4595–0.9405, standard error 0.1227). ROC curve analysis was performed to determine the discriminability of miRNA used in the medical decision-making of the process for hsa-let-7d-3p [Figure 3]a. Because of the AUC ≥0.50, hsa-let-7d-3p seems to be successful in distinguishing EOC patients from HC in serum. In addition, relative expression of hsa-let-7d-3p has shown [Figure 3]b in two groups.
Figure 3: (a) Receiver operating characteristic parameter for hsa-let-7d-3p (b) Relative expression of the hsa-let-7d-3p level was significantly lower in EOC patients than HC

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Pathway Analysis of hsa-let-7d-3p

Target genes of hsa-let-7d-3p were examined by Pathway Studio program. Two of the target genes (KRAS and HMGA2) involves in ovarian cancer pathogenesis [Figure 4]. Expression levels of two target genes (HMGA2 and KRAS) examined both serum samples and whole blood samples.
Figure 4: It is shown that the genes, regulated by hsa-let-7d-3p, are involved in the ovarian cancer machinery. Arrows indicate the effect of microRNAs; if plus sign is present, it demonstrates a stimulation of target genes or processes

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Target genes analysis of hsa-let-7d-3p

We further investigated HMGA2 gene expression in the same serum samples by TaqMan real-time PCR. We did not determine the expression level of the HMGA2 gene in serum samples; hence, we examined whole blood samples of ovarian cancer patients. In addition, we analyzed the expression level of another target gene, i.e., KRAS, expression via SYBR Green PCR. [Figure 5] shows these two genes' expression levels.
Figure 5: Comparison of expression level of target genes of hsa-let-7d-3p between epithelial ovarian cancer and HC in whole blood by SYBR Green qPCR platform

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According to RT-qPCR results of EOC and HC whole blood samples, different expression of KRAS and HMGA2 was statistically not significant (P > 0.05). Because of the AUC ≥0.50, KRAS and HMGA2 expression level seem to be successful in distinguishing EOC patients from HC in whole blood [Figure 6].
Figure 6: Results of receiver operating characteristic parameter for HMGA2 and KRAS for EOC patients were shown in (a and b), respectively. The area under the ROC curve (AUC) for HMGA2 is 62 and KRAS is 64.2. Relative expression of target genes was significantly higher in EOC patients. (c) Relative expression levels of HMGA2 and KRAS. Y-axis indicates the relative expression level

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 > Discussion Top

Despite the numerous research and clinical studies, ovarian cancer still has a very low survival rate among gynaecological malignancies since lack of effective biomarkers for early detection and prognosis. The liquid biopsy is a noninvasive perspective that has the potential of providing information on prognosis, response to therapeutic agents, and early diagnosis. The main liquid biopsy approaches: detection and molecular characterization of circulating tumor cells, circulating tumor DNA, circulating cell-free miRNAs, and exosomes.[14]

Numerous circulating miRNAs have been shown to be involved in epithelial ovarian carcinogenesis. Tumor suppressive let-7 family, one of these circulating miRNAs, targets various oncogene-encoding mRNAs.[9] Let-7 family is a tumor suppressor miRNAs family and most of the member down-regulated in cancers and directly targeting a great number of oncogenes including RAS, HMGA2, and MYC which are crucially involved in cell differentiation and proliferation during development.[15]

HMGA2, an oncofetal protein, participates in ovarian carcinogenesis.[16] However, there have been few studies focusing on the detection of circulating HMGA2 mRNA in the blood.[17] Galdiero et al. detected for the first time the expression of HMGA2 in the plasma of patients with EOC, but not in the plasma of healthy donors.[18] Silencing of HMGA2 expression in ovarian cancer cells has been found to have a therapeutic effect on ovarian cancer.[19] In this study, we found higher levels of HMGA2 in whole blood of EOC patients. All these results indicated that circulating HMGA2 mRNA could serve as a potential biomarker for cancer diagnosis.

KRAS is one of the most frequently mutated oncogenes and contributes to the MAP kinase pathway, which controls cell differentiation and growth.[20] Clinically, approximately 30% of low-grade serous ovarian cancers have KRAS mutations and approximately 11% of high-grade serous ovarian cancers have KRAS amplifications.[21] In EOCs, the incidence of KRAS point mutations is between 15% and 39%.[22]KRAS mutations were correlated with the histological type of tumor but not with other clinicopathological parameters such as grade, stage, or patients' age.[13] These results suggest that KRAS genomic status may serve as a potential biomarker in EOC and highly related to tumor histology.

HMGA2 and KRAS have a long 3'UTR and are targeted by the let-7 in mammalian cells.[23]HMGA2 and KRAS commonly had let-7 family complementary sites in their 3'UTR and showed seven and eight let-7 target sites, respectively.[24] First, we found that the expression level of hsa-let-7d-3p lower in EOC patients than HC, thus hsa-let-7d-3p a potential biomarker for early diagnosis of EOC. Second, we detected target genes of hsa-let-7d-3p via bioinformatic analysis. After that, we examined the level of target genes (HMGA2 and KRAS), which are oncogenes and knowing related to EOC, in serum and whole blood samples. Although we tried several times, we did not detect HMGA2 mRNA in serum. Finally, we analyzed these two oncogenes in EOC and HC of whole blood; consequently, we found increased level of these genes in EOC via reduction of expression hsa-let-7d-3p. Further studies are required to examine other target genes of hsa-let-7d-3p.

 > Conclusion Top

To the best of our knowledge, this is the first study focusing on the detection of cell-free HMGA2 and KRAS mRNAs in the whole blood of EOC patients, simultaneously. The level of circulating HMGA2 and KRAS were found to be higher in EOC than in HC. Our data suggest that the effect of let-7 may be distinct in EOC and that the inhibitory effect of let-7 on HMGA2 and KRAS may be effective for prognosis of EOC. In summary, our study indicated that HMGA2 and KRAS were translationally downregulated by the hsa-let-7d-3p, and the loss of hsa-let-7d-3p expression led to the progression of EOC related to the tumorigenesis, invasion, and metastasis.

Financial support and sponsorship

The present study was supported by Istanbul University Scientific Research Projects Department (Grant No: 26721).

Conflicts of interest

There are no conflicts of interest.

 > References Top

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