Greta Streleckienė

(1)

LITHUANIAN UNIVERSITY OF HEALTH SCIENCES MEDICAL ACADEMY

FACULTY OF MEDICINE LABORATORY MEDICAL BIOLOGY

SECOND CYCLE STUDIES

Greta Streleckienė

HSA-MIR-20B-5P, HSA-MIR-451A-5P AND HSA-MIR-1468-5P ROLE IN GASTRIC CANCER PATHOGENESIS

Master thesis

Supervisor PhD Jurgita Skiecevičienė

(2)

LIETUVOS SVEIKATOS MOKSLŲ UNIVERSITETAS MEDICINOS AKADEMIJA

MEDICINOS FAKULTETAS

LABORATORINĖS MEDICINOS BIOLOGIJA ANTROS PAKOPOS STUDIJOS

Greta Streleckienė

HSA-MIR-20B-5P, HSA-MIR-451A-5P IR HSA-MIR-1468-5P VAIDMUO SKRANDŽIO VĖŽIO PATOGENEZĖJE

Baigiamasis magistro darbas

Darbo vadovė Dr. Jurgita Skiecevičienė

(3)

3

SUMMARY

Author of Master thesis: Greta Streleckienė

Full title of Master thesis: Hsa-miR-20b-5p, hsa-miR-451a-5p and hsa-miR-1468-5p role in gastric cancer pathogenesis

Supervisor: PhD Jurgita Skiecevičienė

The aim of a study was to examine microRNAs (miR-20b-5p, miR-451a-5p and hsa-miR-1468-5p) function in gastric cancer pathogenesis by experimentally determining microRNA target-genes. Therefore, three study objectives were defined:

1. Determine expression level of hsa-miR-20b-5p, hsa-miR-451a-5p and hsa-miR-1468-5p in normal gastric tissue as a control and gastric cancer cell lines (AGS, MKN28).

2. Determine messenger RNA expression of target-genes in gastric cancer cell lines by experimentally inhibinting 20b-5p and increasing 451a-5p and hsa-miR-1468-5p level.

3. Determine protein expression of target-genes in gastric cancer cell lines by experimentally inhibinting hsa-miR-20b-5p and increasing hsa-miR-451a-5p and hsa-miR-1468-5p level.

The study object was gastric cancer associated miRNAs and their function in gastric cancer pathogenesis. For this purpose commercial gastric cancer cell lines (AGS, MKN28) were investigated.

Results showed that hsa-miR-451a-5p and hsa-miR-1468-5p were underexpressed in AGS and MKN28 cell lines. Moreover, both cell lines showed significant hsa-miR-20b-5p overexpression. Experimental analysis of qRT-PCR target-genes revealed that IRF, TXNIP, PTEN may be targets of hsa-miR-20b-5p, CAV1 – hsa-miR-451a-5p, and CITED2 – hsa-miR-1468-5p. Investigation of protein expression levels showed TXNIP protein level increase after hsa-miR-20b-5p inhibition and CAV1 protein decrease after hsa-miR-451a-5p overexpression.

In conclusion, it was determined that of 20b-5p, 451a-5p and hsa-miR-1468-5p expression differs between normal gastric tissue and commercial gastric cancer cell lines (AGS and MKN28). In addition, expression of hsa-miR-20b-5p, hsa-miR-451a-5p and hsa-miR-1468-5p predicted target-genes and proteins in cells transfected with miRNA inhibitors or mimics and negative control was determined. Hsa-miR-20b-5p inhibition had a significant impact and increased IRF1, TXNIP, PTEN mRNA and TXNIP protein levels. Hsa-miR-451a-5p overexpression had a significant impact and decreased CAV1 gene and CAV1 protein expression level. Hsa-miR-1468-5p

(6)

overexpression decreased CITED2 gene expression level only in MKN28 cell line, therefore further analysis with CITED2 were not performed.

Hsa-miR-20b-5p, hsa-miR-451a-5p and hsa-miR-1468 may play an important role in gastric cancer pathogenesis, for this reason additional investigation of gene-targets or physiological assays in cells (invasion and migration, apoptosis, proliferation and colony formation) would significantly improve understanding about function of these miRNAs in cancerogenesis.

(7)

SANTRAUKA

Magistro darbo autorius: Greta Streleckienė

Magistro darbo pavadinimas: Hsa-miR-20b-5p, hsa-miR-451a-5p ir hsa-miR-1468-5p vaidmuo skrandžio vėžio patogenezėje

Vadovė: Dr. Jurgita Skiecevičienė

Tyrimo darbo tikslas buvo ištirti mikro RNR (20b-5p, 451a-5p ir hsa-miR-1468-5p) funkciją skrandžio vėžio patogenezėje eksperimentiškai nustatant tiriamųjų mikro RNR genus taikinius. Šiam tikslui pasiekti buvo iškelti trys uždaviniai:

1. Nustatyti hsa-miR-20b-5p, hsa-miR-451a-5p ir hsa-miR-1468-5p raišką normaliame skrandžio audinyje ir komercinėse skrandžio vėžio ląstelių linijose (AGS ir MKN28). 2. Nustatyti mikro RNR genų taikinių informacinės RNR raišką vėžinėse skrandžio ląstelių

linijose eksperimentiškai blokuojant hsa-miR-20b-5p ir padidinant hsa-miR-451a-5p bei hsa-miR-1468-5p kiekį.

3. Nustatyti mikro RNR genų taikinių baltymų raišką vėžinėse skrandžio ląstelių linijose eksperimentiškai blokuojant 20b-5p ir padidinant 451a-5p bei hsa-miR-1468-5p kiekį.

Tyrimo objektas - su skrandžio vėžiu siejamos mikro RNR ir jų funkcija skrandžio vėžio patogenezėje. Komercinės skrandžio vėžio ląstelių linijos (AGS ir MKN28) buvo pasirinktos kaip sistema, tinkama tyrimo objektui studijuoti.

Tyrimo rezultatai parodė, kad hsa-miR-451a-5p ir hsa-miR-1468-5p raiška buvo statistiškai reikšmingai mažesnė komercinėse AGS ir MKN28 ląstelių linijose nei normaliame skrandžio audinyje, tuo tarpu hsa-miR-20b-5p raiška buvo reikšmingai didesnė palyginus normalų skrandžio audinį ir vėžines skrandžio ląstelių linijas. Atlikus kiekybinę tikro laiko polimerazės grandininės reakcijos (kTL-PGR) analizę, buvo nustaytyta kad IRF1, TXNIP, PTEN genai yra galimi hsa-miR-20b-5p taikiniai, CAV1 – hsa-miR-451a-5p taikinys, o CITED2 – hsa-miR-1468-5p genas taikinys. Tolimesnė baltymų raiškos analizė parodė TXNIP baltymo raiškos padidėjimą paveikus ląsteles hsa-miR-20b-5p inhibitoriumi ir CAV1 baltymo raiškos sumažėjimą paveikus ląsteles hsa-miR-451a-5p imitatoriumi.

Šis tyrimas parodė, kad hsa-miR-20b-5p, hsa-miR-451a-5p ir hsa-miR-1468-5p raiškos profilis statistiškai reikšmingai skiriasi tarp kontrolinio audinio ir vėžinių skrandžio ląstelių linijų (AGS ir MKN28). Taip pat buvo atlikta hsa-miR-20b-5p, hsa-miR-451a-5p ir hsa-miR-1468-5p genų taikinių eksperimentinė analizė, kurios metu nustatyta, kad hsa-miR-20b-5p slopinimas yra susijęs su

(8)

IRF, TXNIP ir PTEN genų raiškos ir TXNIP baltymo raiškos padidėjimu. Taip pat, hsa-miR-451a-5p imitavimas ląstelėje sumažino CAV1 geno ir CAV1 baltymo raišką. Hsa-miR-1468-5p imitavimas turėjo įtakos CITED2 geno raiškos sumažėjimui, tačiau tik vienoje MKN28 ląstelių linijoje, todėl šis genas toliau nebuvo tiriamas.

Hsa-miR-20b-5p, hsa-miR-451a-5p ir hsa-miR-1468-5p gali turėti svabų vaidmenį skrandžio vėžio patogenezėje, dėl šios priežasties tolimesnė papildomų genų taikinių analizė bei ląstelės fiziologinių pokyčių (migracijos ir invazijos, apoptozės, proliferacijos ir kolonijų formavimo) ištyrimas neabejotinai prisidėtų prie detalesnio tirtųjų mikro RNR funkcijos ištyrimo.

(9)

9

ABBREVIATIONS

3′ UTR - 3′ untranslated region

7-methyl-GDP - 7-methyl-guanosine diphosphate ADAR1/2 - Adenosine Deaminase, RNA Specific 1/2 AGO – Argonaute

AP - alkaline phosphatase

ATCC - American Type Culture Collection BCA - bicinchoninic acid

Bp – base pairs CAV1 - caveolin 1

cDNA - complementary deoxyribonucleic acid DCP2 - decapping protein 2

dCt – delta cycle threshold

eIF4F - eukaryotic initiation factor 4F FBS – fetal bovine serum

FC – fold change GC – gastric cancer

GTP - guanosine triphosphate GTP - guanosine-5'-triphosphate Hsa – lot. Homo sapiens

IFN – interferon

IRF1 - Interferon Regulatory Factor 1 KSRP - KH-type splicing regulatory protein LDS - lithium dodecyl sulfate

MEF2 - myocyte enhancer factor-2

miRISCs - miRNA-induced silencing complexes MiRNA – micro ribonucleic acid

miR-RISC - miRNA containing RNA-induced silencing complex mPC – mimic positive control

mRNA – messenger ribonucleic acid N – amount of cases

NC – negative control Nt – nucleotide

(10)

10 PABPC - poly(A)-binding protein complex

PBS - phosphate buffered saline

Pri-miRNA – primary miRNA transcript PVDF - polyvinylidene fluoride

qRT-PCR - quantitative real time polymerase chain reaction REST - RE1 Silencing Transcription Factor

RIPA – radio-immunoprecipitation assay RISC – RNA-induced silencing complex RNase III – ribonuclease III

R-SMAD - receptor-regulated SMAD protein RT – reverse transcription

RT-qPCR - real-time quantitate polymerase chain reaction

SD junction – region between the Single- and Double-stranded RNA SDS - sodium dodecyl sulphate

ssRNA - single-stranded RNA TRBP - TAR RNA binding protein tsmiRNA - tumor suppressor microRNA TXNIP - thioredoxin interacting protein VDUP-1 - vitamin D3 upregulated protein-1 WB – Western Blot

XPO5 - Exportin-5

(11)

11

1. INTRODUCTION

Gastric cancer is one of the most common malignancies in Lithuania and around the globe. It is also one of the leading causes of death, with rates of death being equivalent to rates from cardiovascular diseases. And one of the major issues in clinical settings is the lack of biomarkers for early diagnosis of gastric cancer. Considering bad survival and prognosis of patients, which depends on the stage of the tumor at the time of diagnosis, an early diagnosis would be associated with the wider treatment possibilities and better prognosis.

Despite the fact that the pathogenesis of gastric cancer development is multifactorial, recent studies showed big influence of genetics and epigenetics (1). Recently discovered microRNAs (miRNAs) are an evolutionarily conserved group of small noncoding RNAs that post-transcriptionally regulate gene expression and play important role in a variety of physiological and pathological processes, such as cell proliferation, apoptosis, differentiation, and signal transduction, cancer development, progression or response to therapy (2). MiRNAs gene expression profiles differ in different cancer types, therefore, it is considered as one of the possible cancer biomarkers or even as a potential candidate for molecular cancer therapy. Multiple reports now also suggest that miRNA expression signatures derived from tumor tissue could enable to make more accurate diagnosis and prognosis for patients with cancer. Scientific studies have identified dysregulated miRNA profiles in various cancers, however in order to understand functional relevance of miRNA dysregulation, studies analysing their target genes are of major importance. Biological function determination of tissue specific miRNAs and their target-genes could improve cancer diagnostic and even treatment possibilities.

The authors report no conflicts of interest in this work.

(12)

12

2. AIM AND OBJECTIVES OF THE THESIS

The aim of this study was to examine microRNAs (hsa-miR-20b-5p, hsa-miR-451a-5p and hsa-miR-1468-5p) function in gastric cancer pathogenesis by experimentally determining microRNA target-genes.

Study objectives:

1. Determine expression level of hsa-miR-20b-5p, hsa-miR-451a-5p and hsa-miR-1468-5p in normal gastric tissue as a control and gastric cancer cell lines (AGS, MKN28). 2. Determine messenger RNA expression of target-genes in gastric cancer cell lines by

experimentally inhibinting miR-20b-5p and increasing miR-451a-5p and hsa-miR-1468-5p level.

3. Determine protein expression of target-genes in gastric cancer cell lines by experimentally inhibinting miR-20b-5p and increasing miR-451a-5p and hsa-miR-1468-5p level.

(13)

13

3. LITERATURE REVIEW

Micro ribonucleic acid (miRNA) as regulatory genome element first was discussed in Lee R. C. research in 1993 (3). The study suggested that lin-4 transcript may represent a group of regulatory genes that encodes small antisense RNA products. Currently, more than 2 500 miRNAs are known to be encoded within genome of humans and are associated with important biological processes (miRBase version 21, February 2017) (4).

MiRNAs are 19 – 25 nucleotides (nt) in length and are conservative non-coding RNA sequences, which function as post-transcriptional gene expression regulators. Moreover, these molecules have an important role in all known biological processes (cell growth, proliferation and differentiation, metabolism and development) (5).

3.1 MiRNA biological impact

3.1.1 MiRNA biogenesis and maturation

MiRNAs are universal and can be translated from coding genes, intron regions as non-coding transcripts, and some from gene promoter regions as primary transcripts by the cellular machinery (6). MiRNAs first are transcribed by RNA polymerase II, yet other authors refer that some miRNAs can be transcribed by polymerase III (7). This primary transcript (pri-miRNA) is composed of 33 bp length hair pin stem, a terminal loop and a flanking single-stranded RNA (ssRNA) sequences. After transcription pri-miRNA is processed by RNase III Drosha and DGCR8 complex, which cleaves 11 bp of pri-miRNA away from hair pin stem at SD junction (region between the single- and double-stranded RNA) (8) (Figure 1A). Drosha digestion can occur at the same time as transcription or before splicing, this process results in an intermediary RNA molecule (pre-miRNA), which has about 22 bp in the stem and about 48 bp in the terminal loop (9) (Figure 1A).

After pre-miRNA is produced, Exportin-5 (XPO5) transports this molecule to the cytoplasm. XPO5 dependent transportation uses guanosine-5'-triphosphate (GTP) and also protects pre-miRNA against nuclear degradation (9). Dicer (another RNase III enzyme) digests the pre-miRNA in the cytoplasm of the cell into a 22 bp mature duplex miRNA, which is composed of two miRNAs (miRNA: miRNA* or miR-3p/miR-5p, referring to the direction of the functional miRNA), one (miRNA) is called the guide strand and other (miRNA*) - the passenger strand (Figure 1B). During this process, Dicer is associated with other proteins like TAR RNA binding protein (TRBP) and kinase R–activating protein (PACT) to increase its stability and processing activity (10,11). Dicer is an

(14)

14 essential protein of miRNA maturation and its down-regulation even decreases the mature miRNA levels. After miRNA duplex formation, the strand are unwounded and guide strand is incorporated in RNA-induced silencing complex (RISC), which is formed of Dicer, TRBP, PACT, Argonaute 2 (Ago2) and GW182 proteins (12) (Figure 1B). In mammals, selection of the guide strand is dictated by thermodynamic stability, the less stable strand at the 5′ end has a higher probability of being incorporated into the RISC, while the remaining strand (miRNA-passenger strand) is excluded and generally degraded.

3.1.2 Mechanisms of miRNA target silencing and degradation

Over the past several years, remarkable progress has been made in understanding the basis of miRNA target degradation. Animal miRNAs and Ago proteins are integrated by miRNA-containing RNA-induced silencing complexes (miR-RISCs). These complexes control post-transcriptional silencing of target messenger ribonucleic acids (mRNAs) which can be partially or fully complementary to miRNA. MRNA and miRNA complementary determines outcome of mRNA

Fig. 1. MiRNA biogenesis. A pri-miRNA processing at SD junction (processing center) (Jinju H, Yoontae L, Kyu-Hyeon Y et al.); B miRNA biogenesis, transportation and further processing

(Barca-Mayo O and Q. Richard L)

(15)

15 silencing. Perfectly complementary targets are cleaved by catalytically active Agos (5); whereas not perfectly complementary mRNA targets are the most common case and are not cleaved by Ago proteins (13). Ago proteins then incorporate additional proteins to mediate gene silencing. The binding site is recognized by base-pairing, which usually is located in 3′ untranslated region (3′ UTR) of mRNA. Although the 5′ end of the miRNA (seed site) has always been considered the most important for the binding to the mRNA, recently the target sites have been further divided into three main classes: the dominant seed site targets (5′ seed-only), the 5′ dominant canonical seed site targets (5′ dominant) and the 3′ complementary seed site targets (3′ canonical) (14).

Target genes silencing is implemented through a combination of translational repression, deadenylation, decapping and 5ʹ to 3ʹ mRNA degradation (Figure 2). First, mRNAs are deadenylated by cytoplasmic deadenylase complexes (PAN2-PAN3, CCR4-NOT). Deadenylation is a shortening of mRNA poly(A) tails (15). In eukaryotes, shortening of the 3′-poly(A) tail is the rate-limiting step in the degradation of most mRNAs (16). Second, deadenylated mRNAs are decapped. Decapping is hydrolysis of the 5′ cap structure on the mRNA. A major decapping enzyme in eukaryotes is decapping protein 2 (DCP2), which hydrolyses the cap structure, releasing 7-methyl-guanosine diphosphate (7-methyl-GDP) and a 5′ monophosphorylated mRNA. Finally, this 5′ monophosphorylated mRNA is a substrate for 5′ to 3′ exoribonuclease 1 (XRN1), which rapidly degrades decapped mRNA.

In addition, miRNAs can repress translation, but the precise molecular mechanism remains unknown. It is agreed that miRNAs repress translation initiation by blocking the eukaryotic initiation factor 4F (eIF4F) complex activity while this complex is essential for translation initiation (17) (Figure 2). Translational repression is observed at early time points after miRNA expression, but the effects are generally weak, and by the time full repression is established, mRNA deadenylation or full destabilization is the dominant effect of miRNA mediated silencing (18).

The mRNA decay pathway seems to be disrupted in oocytes, early embryos and neuronal cells. In these systems, miRNA targets stay in a deadenylated and translationally repressed form without undergoing further processes. As a result, silencing is potentially reversible in oocytes, early embryos and neurons, while repressed mRNAs could return to the active translational form after cytoplasmic polyadenylation (15).

Comprehensive analysis showed that miRNAs can bind to hundreds of different mRNAs. Dysregulation of miRNA expression is associated with various human diseases, including cancer. MiRNAs can act as tumor suppressor when underexpressed (tsmiRNA) or can promote tumor growth and progression of metastasis when overexpressed (oncomiRNA).

(16)

16

3.2 MiRNA deregulation in tumorigenesis

Deregulation of miRNA in human cancers is a result of abnormal miRNA biogenesis, genetic or epigenetic alterations, leading to the proto-oncogenic or tumor suppressive role of miRNA in tumorigenesis. Many human miRNA genes are located at fragile sites or in other genomic regions that are prone to mutation, deletion, amplification or translocation in cancer (2,19). In addition to this, a big variety of transcription factors (tumor suppressors or oncogenes) regulate miRNA transcription, such as well-known Myc and p53, also cell type–specific transcription factors: MEF2, PU.1 and REST. Furthermore, PDGF, TGF-b and BDNF factors can trigger pri-miRNA transcription (9). Epigenetic mechanisms are also important for miRNA transcriptional regulation. Different approaches have shown that DNA methylation and histone deacetylase inhibitors can modify the expression of several miRNAs (9). Potential post-transcriptional miRNA expression regulatory mechanisms are following: (i) miRNA hairpin base pairs editing carried out by the catalysing enzymes ADAR1 and ADAR2, in during this process, adenosine residues are replaced by inosine (A to I), and (ii) modifications in Drosha processing. Consequently, miRNA edition may influence the transition from pri-miRNA to pre-miRNA and it may also affect miRNA-target specificity by modifying the seed region. On the

Fig. 2. MiRNAs mediated gene silencing. AGO proteins interact with a GW182 protein, which in turn interacts with cytoplasmic poly(A)-binding protein (PABPC) and with the cytoplasmic deadenylase complexes PAN2–PAN3 and CCR4–NOT. Deadenylated mRNAs

are decapped and rapidly degraded by 5ʹ-to-3ʹ exoribonuclease 1 (XRN1; not shown) (Jonas S and Izaurralde E)

(17)

17 other hand, the important role of Drosha modification can be assigned to receptor-regulated SMAD proteins (R-SMADs) and the RNA-binding protein KH-type splicing regulatory protein (KSRP), which binds the terminal loop of pri-miRNAs to promote their processing by Drosha (20,21). The miRNA biogenesis pathway can also be affected by alterations in XPO5. Some tumors have mutations that generate pre-miRNA accumulation in the nucleus, reducing miRNA processing and reduced mature miRNA expression (9).

The first evidence of miRNA role in human cancerogenesis was suggested by Calin et al. in 2002 in chronic lymphocytic leukaemia (CLL) research. Group of scientists reported that tumor suppressor region at chromosome 13q14 is deleted in CLL and it contained two miRNA genes (MIR15A and MIR16-1) (22). Following these initial observations, the same group mapped all the known miRNA genes and found many of them to be located in chromosomal loci susceptible to deletions or amplifications, as was found in many different human tumors (23).

Abnormal miRNA expression patterns can be used in identifying the origin of tumors that are difficult to identify, for instance, when the tumor metastasize, suggesting that tumors preserve a unique miRNA expression profile. Rosenfeld et al. study in 2008 tried to classify 48 miRNAs from a 336 primary and metastatic tumor samples, and was able to use this classifier to accurately predict the tissue of origin in 86% of cases, including 77% of the metastatic tumors (24). Lawrie at al. showed that profile of circulating miRNAs in early neoplasia reflects the patterns which were determined in tumor tissues, implying possibility to use circulating miRNAs for early diagnosis (25).

Moreover, due to their small size miRNAs are more stable when compared to mRNAs, allowing expression profiling from frozen and paraffin-embedded tissues, blood (total blood, plasma or serum), circulating exosomes and different biologic fluids (urine, saliva and sputum) supporting their possible use as minimally invasive, easily detectible biomarkers (14).

3.3 Methods of miRNA targets identification

In order to reveal miRNA function, miRNA targets should be identified. If the target of miRNA is involved in some biological process or biological pathway it is reasonable to think that this miRNA is involved in particular biological process. There is a big variety of predictive and experimental methods of miRNA target identification.

To start with, in silico prediction programs are used to differentially weight various features of miRNA-mRNA target interaction to rank the predicted strength. Key points of this analysis are length and complementarity with the site of miRNA-target interaction (the seed site), other factors may be presence or absence of additional 3′ pairing, AU richness, site conservation and interaction site

(18)

18 location (26). Second, gene expression quantification after miRNA manipulation can be used. Expression levels of target mRNA, or target protein expression levels can be measured using real-time quantitate polymerase chain reaction (RT-qPCR), microarrays, RNA sequencing or global proteomic techniques. Target mRNA can be confirmed using Luciferase reporter assay. Similarly, ribosome profiling (27) or ribosome footprinting (28) can be used to measure the differential translation of genes after miRNA manipulation. In addition to this, AGO and miRNA immunoprecipitation approaches have been developed to capture and sequence miRNA-target complexes (27).

There are also several factors that make miRNA function analysis more complicated. One of these is accuracy of target prediction. Each miRNA has hundreds (or thousands) of potential targets, but the accurate identification of functionally relevant target genes remains challenging (29). Next, miRNAs act on their direct targets at both levels: transcript stability and translational suppression, but can also initiate indirect effects on gene expression through the downstream activities of miRNA-targeted transcription factors. There is a great possibility that most changes in mRNA level after miRNA manipulation may actually be due to altered transcription and not the direct effects of the miRNAs themselves (30). Moreover, the same miRNA can have different, or even opposite, functional outcomes in different contexts. For example, miR-182-5p is reported to behave as an oncogene in breast (31), ovarian (32) and bladder cancer (33), but as a tumor suppressor in lung cancer (34). These functional differences may occur due to diverse target genes expression between tissues. MiRNA function can also potentially be affected by number of targets and pseudogenes activity, long non-coding RNAs, circular RNAs and transcripts of protein-non-coding genes that have high miRNA-binding capacity (26).

3.4 Gastric cancer

3.4.1 Epidemiology and etiology

Gastric cancer (GC) is a multifactorial disease, resulting from a combination of environmental factors and genetic alterations. It is the fourth common cancer and the second leading cause of cancer worldwide (35). In principle, at the time of diagnosis one of two GC patients are already exposed to advanced disease stage and 5 year survival rate is lower than 30% (36). GC can be classified according to differentiation or to the histomorphological Lauren classification, which divides the tumors into intestinal and diffuse types (36). Adenocarcinoma is the most frequent histological form of this cancer type. Despite a decline in incidence and mortality in Lithuania (in period of 1985 – 2010 men’s

(19)

19 mortality rate decreased from 47.31 to 26.04 cases/ 100 000 people and women’s – from 21.37 to 9.27 cases/ 100 000 people) GC cases are diagnosed in late (III-IV) stage (37).

As shown in Figure 3 gastric cancer can be triggered by variety of conditions and etiological factors such as: age, gender - men have twice the risk, bacteria – H. pylori, race and ethnicity – GC is more common in Asia, Latin America, central and eastern Europe (Figure 4), diet with high salts, nitrates and pickled food intake, occupational exposure - certain dusts and fumes, smoking and alcohol, obesity, gastro-oesophageal reflux disease and inherited predisposition which accounts for

1-Fig. 3. Gastric cancer etiology (McLean MH and El-Omar EM)

Fig. 4. Estimated age-standardized rates of incident cases of gastric cancer (both sexes) (GLOBOCAN, 2012)

(20)

20 3% of cases. Another pathogen which can be associated with GC is the Epstein-Barr virus. This virus is found in the cancer cells, but not the normal epithelial cells, of 80% of gastric carcinomas. Its role in carcinogenesis, however, remains unclear (35). Alterations in cell proliferation apoptosis and tumor suppressor genes’ epigenetic modifications eventually lead to disrupted repairing mechanisms and inflammation-associated oncogenesis.

3.4.2 MiRNAs as biomarkers in gastric cancer

MiRNA signatures in GC tissues are determined by comparing miRNAs expression in tumorous tissue and miRNAs expression in non-tumorous tissue. In cancer, miRNAs can act as oncogenes or tumor suppressor genes (Figure 5). Both the overexpression of oncomiRNAs and the decreased expression of tsmiRNAs play important roles in GC, and many studies in the literature have identified a large number of upregulated and downregulated miRNAs and their potential targets.

Fig. 5. MicroRNAs as oncogenes or tumor suppressor genes (Iorio MV and Croce CM)

(21)

21 Systematic review completed in 2013, analysed eight different studies which were carried out in years 2008 – 2012 and identified five miRNAs that were most consistently upregulated (miR-21, miR-106a, miR-17, miR-18a and miR-20a) and one most consistently downregulated (miR-378) in GC. Those finding were also validated by qRT-PCR and correlation between miRNA expression and clinicopathological features was also obtained (38). Other systematic review carried out after one year by Shrestha S et al. confirmed that one of the constantly reported upregulated miRNAs are miR-21 (reported in ten studies). In addition to this, analysis of 14 miRNA expression profiling studies revealed upregulation of miR-25, miR-92 and miR-223, while miR-375, miR-148a and miR-30d were downregulated in GC tissues (39). Study of Yan W et al. summarized the most important miRNAs in different clinicopathological conditions. In tissue samples miR-181c, miR-196a and miR-21 were up-regulated and miR-193b, miR-217 and miR-34a were down-up-regulated in poorly differentiated GC groups consisting of patients with worse prognosis of survival. High expression of 130a and miR-25 was shown to stimulate the migration, invasion and proliferation of GC cells, on the other hand, miR-125, miR-520, miR-148a, miR-29c and miR-206 were down-regulated and were associated with different types of cells invasion (depth of invasion, organ or peritoneal invasion, etc.). Lymph node metastasis was strongly related with overexpression of miR-107, miR-181c, miR196a/b, miR-20b, miR-23a/b, miR-25 and miR-630, and reduced expression of miR-125, miR-153, miR-206, miR-22 and 520. In GC tissues, high expression of 107, 181c, 196a/b, 20b, miR-23a/b and miR-630 strongly correlated with advanced GC tumor stage (40). In addition to this, it is worth to mention that let-7a is one of the most important tsmiRNAs involved in gastric carcinogenesis. Yang et al. demonstrated that GC tumor and cell lines with lower expression of let-7a tended to have poor differentiation (41). Deregulated miRNAs and their targets in GC tumors are presented in Table 1.

Several studies indicated that the downregulation or upregulation of miRNAs plays important role in GC pathogenesis. It has been shown that miRNA expression profiles correlate with GC development, progression and response to therapy, suggesting their possible use as diagnostic, prognostic and predictive biomarkers. Moreover, miRNA-based anticancer therapies have recently been explored, either alone or in combination with current therapies (14).

miRNA Targets Clinicopathological features

OncomiRNAs

miR-17 UBE2C, FBXO31

Tumor size Tumor infiltration Clinical grade Table 1. Deregulated miRNA in gastric cancer

(22)

22 Prognosis

Tumor stage

miR-18a DICER1, Myc, HIF1A, ER-α

Lymph node metastasis Pathological grade

miR-19a MXD1, SOCS1, PTEN

Migration Invasion Metastasis Proliferation

Multidrug resistance

miR-20a EGR2, E2F1

Overall survival Relapse-free survival Self-renewal and

proliferation of GC stem cells Chemoresistance

miR-20b CDKN1A, MYLIP, ESR1, STAT3

Distance metastasis Tumor stage

Lymph node metastasis miR-21 PTEN, PDCD4, RECK, SERPINI1

Differentiation

Lymph node metastasis H. pylori infection Tumor stage Tumor size

miR-23a/b IL6R

Invasion

Lymph node metastasis Tumor size

miR-25 FBXW7, TOB1, RECK

Proliferation Invasion Migration Metastasis

Aggressive phenotype Poor long-term survival

miR-92 PARP2, CXCL9, SIX3, NRP2

Tumor growth Poor survival

miR-106a TIMP2, PTEN, FAS, RUNX3, P21

Invasion Differentiation Distant metastasis Lymph node metastasis Tumor stage

Tumor size

miR-107 FOXO1, DICER, CDK6, EGFR

Invasion Differentiation

Lymph node metastasis Tumor size Tumor stage Overall survival miR-130a RUNX3 Metastasis Invasion Proliferation

miR-181c NOTCH4, KRAS, BCLC

Invasion

Lymph node metastasis

miR-196a RDX

Differentiation Invasion

Lymph node metastasis Distant metastasis

(23)

23 miR-200b ZEB1, ZEB2, SUZ12, DNMT3A, DNMT3B,

SP1, WNT-1

Diffuse-type

Poor overall survival H. pylori infection Metastasis Tumor size

miR-223 EPB4IL, STMN, FBXW7, HMGA2

Poor metastasis-free survival Apoptosis

Proliferation Invasion

Poor clinical prognosis

miR-630 -

Invasion

Distant metastasis Tumor stage

Lymph node metastasis

TsmiRNAs

let-7a RAB40C, CDKN1, SPHK2, FN1

Differentiation

Lymph node metastasis Cell cycle arrest Growth suppression Overall survival Relapse-free survival

miR-22 SP1

Distant metastasis Lymph node metastasis Tumor stage

miR-29c TCEA3, PPP2R5E, HEBP2, MAFA

Invasion Tumor stage

miR-30d RUNX2, TP53, GNAI2 -

miR-34a BCL2

Differentiation Tumor recurrence Lymph node metastasis

miR-125 p53, MUC1, VDR, IL-6

Invasion

Lymph node metastasis Distant metastasis Tumor stage Tumor size

miR-148a ROCK1, MMP7, p27, DNMT1, SMAD4

Clinical stage

Lymph node metastasis Poor clinical outcome

Epithelial-mesenchymal transition

miR-153 -

Invasion

Lymph node metastasis Migration

miR-193b ARL8B, CACS3, PCDH17, CCR1

Differentiation Lauren type Tumor stage Invasion Metastasis miR-206 CCND2

Lymph node metastasis Hematogenous recurrence Tumor stage miR-217 - Distant metastasis Differentiation Invasion

(24)

24 Tumor size

miR-375 JAK2, HuD, N-Cadherin, CASP3

Cell proliferation Migration Invasion

miR-378 CDK6, VEGF, POLH, DFFA

Proliferation

miR-520 -

Invasion depth

Lymph node metastasis Tumor stage

3.5 MiR-20b-5p, miR-451a-5p, miR-1468-5p function

3.5.1 MiR-20b-5p

Human miR-20b (hsa-miR-20b) is a part of miR-17 precursor family. This family also includes miR-93 and miR-106a/b and is produced from several miRNA gene clusters, which apparently arose from a series of ancient evolutionary genetic duplication events, and also include members of the miR-19, and miR-25 families. Hsa-miR-20b is located in sex chromosome Xq26.2.

At the end of last decade two separate studies revealed association between hsa-miR-20b and GC (42,43). Later in year 2014 study by Espinosa-Parrilla at al. concluded that whole genetic variation of miR-106b family may have critical role in genetic susceptibility to GC (44). Study by Xue et al. suggested that hsa-miR-20b may serve as a potential molecular marker for GC prognosis (45). The most recent study by Danza et al. also reported aberrant expression of miR-20b association with chemotherapeutic response in GC HIF1A, MDR1 and HIPK2 genes modulation (46). It is worth to mention that the vast majority of miR-20b studies were carried out in non-European populations.

3.5.2 MiR-451a-5p

Hsa-miR-451a is located in 17q11.2. To this day only a few studies were performed to determine function of hsa-miR-451a-5p in GC. Study by Riquelme et al. suggested that miR-451a acts as potential tumor suppressor in primary GC as well as in GC-derived AGS cell line (47). However, the second study performed by Park et al. did not shown statistically significant differences for this miRNA using microarray technology (48).

(25)

25 3.5.3 MiR-1468-5p

Has-miR-1468 is located in sex chromosome Xq11.1.

There are no previous studies performed to associate hsa-miR-1468 expression level or genetic alterations and GC. GWAS study performed in year 2012 associated miR-1468 with lung cancer patient survival rates (49). Another study carried out by Lin et al. in year 2016 supported GWAS study findings and summarized that miR-1468 may help to predict the progression and prognosis of lung adenocarcinoma (50).

(26)

26

4. RESEARCH METHODOLOGY AND METHODS

This study is a part of national research program “Researcher teams” of Research Council of Lithuania financed project “MiR-20b, miR-451, miR-29c ir miR-125b vaidmuo skrandžio ir storosios žarnos vėžio patogenezėje” (MIP-007/2014).

First of all, two different commercial gastric cancer cell lines (AGS, MKN28) and normal gastric tissue as a control were analysed for expression of miR-20b-5p, miR-451a-5p and hsa-miR-1468-5p. Next, gastric cancer-associated putative target-genes of selected miRNAs were retrieved from databases according to their function in cancerogenesis (oncogenes or tumor suppressor genes). Three potential target genes were selected for hsa-miR-1468-5p, five - for hsa-miR-20b-5p, two - for hsa-miR-451a-5p (Table 2). Finally, experimental analysis of target genes using inhibitors or mimics of miRNAs in cell lines was performed. Changes of mRNA level target-genes were analysed using qRT-PCR and changes in protein level - Western Blot (WB) method.

MiRNA Sinthetical miRNA

function

Target-genes Target-genes

predicted function

hsa-miR-20b-5p Inhibitor EREG, FAT4, IRF1,

TXNIP, PTEN

Proto-oncogen

hsa-miR-451a-5p Mimic CAV1, ADAM28 Onco-suppressor

hsa-miR-1468-5p Mimic TNF, DNMT1, CITED2 Onco-suppressor

4.1 Study object

The study object was GC associated miRNAs and their function in GC pathogenesis. For this purpose commercial GC cell cultures (AGS, MKN28), which had different histopathological features, were investigated. AGS commercial cell line was derived from gastric adenocarcinoma tissue, while commercial MKN28 cell line was derived from gastric tubular adenocarcinoma metastatic site in liver.

(27)

27

4.2 Methods

4.2.1 Cell culture cultivation

The human gastric adenocarcinoma cell lines: AGS cell culture were purchased from the American Type Culture Collection (ATCC) and MKN28 cell line was kindly provided by Alexander Link (Department of Gastroenterology, Hepatology and Infectious Diseases, Otto von Guericke University, Germany). Cell cultures were cultivated according ATCC recommendations. The AGS cell line was grown in Ham's F-12K (Kaighn's) Medium (Gibco by Life Technologies, USA) and MKN28 was grown in RPMI 1640 medium (Gibco by Life Technologies, USA). The culture media was supplemented with 10% Fetal Bovine Serum (FBS) (Gibco by Life Technologies, USA) and 1% penicillin-streptomycin solution (5000 U/ml) (Gibco by Life Technologies, USA). The cells were cultured in humified incubator (Eppendorf New Brunswick, UK) containing 5% of CO2 at 37 °C.

Depending on the experiment cells were seeded into tissue-culture treated 24-well plates (Falcon by Thermo Fisher Scientific, USA) (40 000 cells/well) or 6-well plates (Falcon by Thermo Fisher Scientific, USA) (200 000 cells/well) and cultivated for 24 hours until transfection of cells.

4.2.2 Total RNA extraction for miRNAs genes expression analysis

Total RNA from normal gastric tissue and cell cultures (AGS and MKN28) was extracted using miRNeasy Micro Kit (Qiagen, Germany) following manufacturer’s recommendations. The miRNeasy Mini Kit combines phenol/guanidine based lysis of samples and silica membrane based purification of total RNA. First, cells or tissue samples are homogenized in QIAzol Lysis Reagent by vortexing or using MagNA Lyser Instrument (Roche, Switzerland). After addition of chloroform, the homogenate is separated into aqueous and organic phases by centrifugation. RNA partitions to the upper, aqueous phase. Ethanol is added to provide appropriate binding conditions for all RNA molecules sized from 18 nt and longer. The sample is then applied to the RNeasy Mini spin column, where the total RNA binds to the membrane. Finally total RNA is eluted in RNase-free water.

Total RNA concentration and quality was assessed by measuring absorbance at 260 nm wavelength, 260/280 nm wavelengths ratio and 260/230 nm wavelengths ratio using a NanoDrop 2000 spectrophotometer (Thermo Scientific, USA).

Aproximately 2-3 milion AGS and MKN28 cells were used for RNA extraction and RNA yeld was aproximately 20-40 ng.

(28)

28 4.2.3 MicroRNA Reverse Transcription using miRNA primers

MiRNA reverse transcription assay was performed by using The Applied Biosystems TaqMan MicroRNA Reverse Transcription Kit (Thermo Fisher Scientific, USA) in accordance with manufacturer’s recommendations. TaqMan Small RNA Assays are predesigned sets of primers and probes used to detect and quantify mature miRNAs. Three TaqMan Small RNA Assays were used: has-miR-16-5p (000391) as endogenous control, has-miR-20b-5p (001014), has-miR-451a-5p (001141) and has-miR-1468-5p (121107_mat).

RNA samples were diluted to 5 ng/µl concentrations and in total 12.5 ng total RNA were used per 20 µl reverse transcription (RT) reaction. RT reaction mixture contained 100mM dNTPs, MultiScribe Reverse Transcriptase (50 U/µL), 10× Reverse Transcription Buffer, RNase Inhibitor (20 U/µL) and nuclease-free water. Tubes containing sample, RT mixture and 5× Small RNA Assays were incubated on ice for 5 minutes and then loaded into the thermal cycler. Finally PCR reaction was performed.

4.2.4 Theoretical evaluation of potential miRNAs target-genes

MiRNAs target-genes were evaluated using RStudio Desktop v. 1.0.143 software and mathematical algorithms. First, DisGenet data base was used to determine GC associated genes. Second, DIANA-microT-CDS, ElMMo, MicroCosm, miRanda, miRDB, PicTar, PITA and TargetScan mathematical prediction tools were used for hsa-miR-20b-5p, hsa-miR-451a-5p, hsa-miR-1468-5p potential target-genes analysis. Next, depending on information in miRecords, miRTarBase and TarBase target-genes, which were already validated in other studies, were rejected. Finally, gene-targets were filtrated according their function in oncogenesis (oncosupressor or protooncogene) and literature analysis was performed.

4.2.5 Cells transfection

For expression analysis of miRNA target-genes using qRT-PCR, cells were seeded in 24-well, whereas for protein level expression analysis of miRNA gene targets using Western Blot cells – 6-well plates. For gene expression assays cell were seeded in triplicates for each experiment condition (transfection with negative control, positive controls or miRNAs of interest). After 24 hours (60-70 % confluence) cells were transfected with 20b-5p inhibitor, 451a-5p mimic, hsa-miR-1468-5p mimic (Ambion by Thermo Fisher Scientific, USA), miRNA Negative Control (mirVana miRNA Mimic, Negative Control #1; mirVana miRNA Inhibitor, Negative Control #1, Ambion by Life

(29)

29 Technologies, USA), mirVana miRNA Mimic, miR-1 Positive control (Ambion by Life Technologies, USA) and mirVana miRNA Inhibitor, let-7c Positive Control (Ambion by Life Technologies, USA). After 24 h, 48 h or 72 h post transfection cells were harvested and used in subsequent experiments. MiRNA and respective controls were transfected using Lipofectamine 3000 Reagent (Thermo Fisher Scientific, USA) in accordance with the manufacturer’s recommendations.

Transfection using Lipofectamine 3000 Reagent is based on lipid nanoparticle technology where cationic lipids facilitate miRNA delivery into cells. The basic structure of cationic lipids consists of a positively charged head group and one or two hydrocarbon chains. The charged head group governs the interaction between the lipid and the phosphate backbone of the nucleic acid. The positive surface charge of the liposomes mediates the interaction of the nucleic acid and the cell membrane, allowing for fusion of the liposome/nucleic acid transfection complex with the negatively charged cell membrane. The transfection complex is thought to enter the cell through endocytosis (Figure 6).

4.2.6 Total RNA extraction for expression analysis of miRNAs target-genes

Total RNA from transfected GC cell cultures was extracted using RNeasy Micro Kit (Qiagen, Germany) following manufacturer’s recommendations. First of all, samples (<5 mg tissue, or <5 × 105 cells) were lysed and then homogenized with guanidine-thiocyanate–containing lysis buffer. Ethanol was added to the sample to create conditions that promote selective binding of RNA to the RNeasy Mini Elute membrane. The sample was then applied to the spin column, RNA binds to the silica membrane. Traces of DNA were removed by on-column digestion of genomic DNA. DNase and any contaminants were washed away and total RNA was eluted in RNase-free water. RNA molecules longer than 200 nt were purified when using RNeasy Micro Kit.

(30)

30 Total RNA concentration and quality was assessed by measuring absorbance at 260 nm wavelength, 260/280 nm wavelengths ratio and 260/230 nm wavelengths ratio using a NanoDrop 2000 spectrophotometer.

For total RNA extraction with RNeasy Micro Kit cell were seeded in 24-well plates (40 000 cells/well), RNA yield was approximately 1.2 - 4.0 ng.

4.2.7 Reverse transcription using random primers

After total RNA extraction reverse transcription was performed using High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific, USA) for gene expression assays in accordance to manufacturer’s recommendations. Complementary DNA (cDNA) was synthesised using 1 µg total RNA per 20 µl reaction volume. Reaction mixture contains 10× RT Buffer, 25× dNTP Mix (100 mM), 10× RT Random Primers, MultiScribe Reverse Transcriptase, RNase Inhibitor and nuclease-free water. Tubes were briefly centrifuged and kept on ice until loading to the thermal cycler.

4.2.8 Quantitative real-time polymerase chain reaction

The expression level of hsa-miR-20b-5p, hsa-miR-451a-5p and hsa-miR-1468-5p was determined by using TaqMan miRNA assays (Ambion by Life Technologies, USA) with miRNA-specific primers and hsa-miR-16-5p was used as an endogenous control for data normalization. MiRNAs gene expression was evaluated in GC cell cultures AGS and MKN28 (n=7, each) and normal gastric tissue (n=11).

Expression of miRNAs target-genes in transfected GC cell lines was determined by using TaqMan Gene Expression Assays (Applied Biosystems, USA) which consist of a pair of unlabelled PCR primers and a TaqMan probe with an Applied Biosystems FAM or VIC dye label. ACTB was used as endogenous control for data normalization.

First, transfection procedure was optimized using mirVana miRNA Mimic, miR-1 Positive control, which targets TWF1 and mirVana miRNA Inhibitor, let-7c Positive Control, which targets HMGA2. Second, expression of miRNAs gene targets was evaluated in GC cell cultures (AGS, MKN28). Cells transfected with miRNA Negative Control (mirVana miRNA Mimic, Negative Control #1; mirVana miRNA Inhibitor, Negative Control #1) and hsa-miR-20b-5p inhibitor, hsa-miR-451a-5p mimic, hsa-miR-1468-5p mimic were compared.

QRT-PCR reaction mixture components (TaqMan Universal Master Mix II, no UNG 2×, TaqMan Gene Expression Assay 20×, nuclease-free water, cDNA) were pipetted into MicroAmp Optical 96-Well Reaction Plates (Applied Biosystems, USA). In total 50 ng of cDNA were used per 20

(31)

31 µl reaction. Two technical replicated were made for each gene assay, and reaction was performed on ABI 7500 Fast Real-Time PCR system (Applied Biosystems, USA). Relative fold mRNA levels were determined using the 2-ΔΔCt method, with ACTB as an internal control.

4.2.9 Protein extraction

Total protein from GC cell cultures was lysated in 1X radioimmunoprecipitation assay (RIPA) buffer (Abcam, UK) which contained protease and phosphatase inhibitor cocktail (Sigma Aldrich, USA). RIPA lysis buffer is commonly used for immunoprecipitation and general protein extraction from cells and tissues. It releases proteins from cells as well as disrupts most weak noncovalent protein-protein interactions (51).

First the culture medium was discarded and cells were washed twice with ice-cold phosphate buffered saline (PBS) (Gibco by Life Technologies, USA). Cells were then incubated for 15 min with RIPA lysis buffer. Lysates of cells were collected to microcentrifuge tubes and centrifuged. Lastly, supernatant containing proteins was carefully removed to a new tube.

Protein concentration was estimated using Pierce BCA Protein Assay Kit (Thermo Scientific, USA), which is based on colorimetric detection using the bicinchoninic acid (BCA). This method combines the reduction of Cu+2 to Cu+1 by protein in an alkaline medium with the highly sensitive and selective colorimetric detection of the cuprous cation (Cu+1) using a reagent containing bicinchoninic acid. This water-soluble complex exhibits a strong absorbance at 562 nm that is nearly linear with increasing protein concentrations.

Approximately 0.5 - 2 ng of total proteins was extracted for WB procedure.

4.2.10 Western Blot

Target-genes which were differentially expressed at mRNA level were further assessed at protein expression level. Cells transfected with negative control and miRNA modulators were compared.

WB uses specific antibodies to identify proteins of interest that have been separated based on size by gel electrophoresis. The immunoassay uses a membrane made of nitrocellulose or PVDF (polyvinylidene fluoride). The gel is placed next to the membrane and application of an electrical current induces the proteins to migrate from the gel to the membrane. The membrane can then be further processed with antibodies specific for the target of interest, and visualized using secondary antibodies and detection reagents. Proteins of interest and experimental conditions for WB are summarized in Table 3.

(32)

32

MicroRNA Protein Protein

size (kDa)

Antibody Antibody dilution/ concentration

Total protein concentration

miR-1* TWF1

(PTK9)

40 ab154725 (Abcam, UK) 1 : 1000 40 µg

hsa-let-7c** HMGA2 12 ab184616 (Abcam, UK) 1 :500 120 µg

hsa-miR-20b-5p IRF1 48 EPR18301 (Abcam, UK) 1 : 1000 50 µg

TXNIP (VDUP1)

50 40-4600 (Thermo Fisher

Scientific, USA)

7 µg/ml 150 µg

hsa-miR-451a-5p CAV1 17-20 EPR15554 (Abcam, UK) 1 : 500 350 µg

- GAPDH 36 AM4300 (Ambion by

Thermo Fisher Scientific, USA)

0.4 µg/ml -

Whole process consists of five major steps:

1. Sample preparation. Extracted protein sample was diluted, mixed with loading buffer (4X Bolt LDS Sample Buffer, Thermo Fisher Scientific, USA), which contains tracking dye and lithium dodecyl sulfate (LDS) necessary for protein structure reduction, and sample reducing agent (10× Bolt Sample Reducing Agent, Thermo Fisher Scientific, USA). Prepared samples were heated in 70°C for 10 min in order to denaturate higher order structures.

2. Gel electrophoresis. This step was performed using Mini Gel Tank (Thermo Fisher Scientific, USA) and Bolt 4-12% Bis-Tris Plus Mini Gels, 10-well (Novex by Thermo Fisher Scientific, USA). Samples and protein standards (SeeBlue Plus2 Pre-Stained Standard, Novex by Thermo Fisher Scientific, USA; MagicMark XP Western Protein Standard, Thermo Fisher Scientific, USA) were loaded into the wells. Proteins loaded on the gel have a negative charge and travel toward the positive electrode when current is applied. Mini Gel Tank was filled with 1× Bolt MES SDS Running Buffer (Thermo Fisher Scientific, USA) and 165 V voltage was applied for electrophoresis.

Table 3. Proteins and experimental conditions used in WB protein expression level analysis.

* mirVana miRNA Mimic Positive Control (know gene-target TWF1 (PTK9)) ** mirVana miRNA Inhibitor Positive Control (known gene-target HMGA2)

(33)

33 3. Blotting. Separated protein mixture was transferred to Invitrolon 0.2 or 0.45 µm PVDF membrane (Invitrolon by Thermo Fisher Scientific, USA) using Mini Gel Tank. Membrane was placed between the gel surface and the positive electrode in a sandwich, the transfer is done using an electric field (20 V voltage). Bolt Transfer Buffer (Thermo Fisher Scientific, USA) containing 10 or 20 % methanol and Bolt Antioxidant (Thermo Fisher Scientific, USA) was used to transfer proteins.

4. Washing, blocking antibody incubation. Blocking prevents antibodies from binding to a membrane non-specifically and membrane is washed to minimize background and remove unbound antibody. For those purposes WesternBreeze Blocker/Diluent (Part A and B) (Thermo Fisher Scientific, USA) and WesternBreeze Wash Solution (16X) (Thermo Fisher Scientific, USA) were used. The membranes were probed with primary antibodies (Table 2) overnight, followed by incubation with horseradish peroxidase-conjugated secondary antibodies (WesternBreeze Chemiluminescent Kit, anti-rabbit or anti-mouse, Thermo Fisher Scientific, USA).

5. Immunodetection. Western Breeze Chemiluminescent Kit (Thermo Fisher Scientific, USA) was used for protein detection. Proteins were detected using secondary antibodies labelled with horseradish peroxidase and chemiluminescence substrate alkaline phosphatase (AP). Reaction was visualised using ChemiDoc XRS+ System (Bio-Rad, USA).

After detection of protein of interest, membrane was striped (process when primary and secondary antibodies are removed) by using Restore Western Blot Stripping Buffer (Thermo Fisher Scientific, USA) and procedure was restarted from blocking for detection of other proteins. In this case anti-GAPDH primary antibody was used as endogenous control for data normalization and chemiluminescent immunodetection performed. The signal intensity of the protein bands was quantified by ImageLab Software (version 5.2.1) (Bio-Rad, USA). Normalized intensities were used for fold change (FC) calculations.

4.3 Statistical analysis

All statistical analyses were performed using GraphPad prism V5.0 (GraphPad Software, USA). Differences between groups were examined using the Mann Whitney U-test, and p<0.05 was considered statistically significant.

(34)

34

5. RESULTS

5.1 Evaluation of miRNAs expression level in GC cell lines

Expression level of hsa-miR-20b-5p, hsa-miR-451a-5p and hsa-miR-1468-5p was determined in GC cell cultures (AGS and MKN28) and normal gastric tissue as a control. Compared with control, the GC cell lines AGS and MKN28 showed downregulation of hsa-miR-1468-5p (p=0.0001 and p=0.003, respectively) and hsa-miR-451a-5p expression level (p=0.0002 and p=0.0002, respectively). Moreover compared with control, both cell lines showed significant upregulation of hsa-miR-20b-5p expression (p=0.008 and p=0.003, AGS and MKN28 respectively) (Figure 7).

Fig. 7. Hsa-miR-20b, hsa-miR-451 and hsa-miR-1468 genes’ expression analysis in AGS and MKN28 cell lines (normalized delta Ct (dCt) values are presented in logarithmic scale)

(35)

35

5.2 Experimental evaluation of miRNAs target-genes

5.2.1 Evaluation of target-genes of miRNA positive controls mRNA expression

MiRNA mimic and inhibitor positive controls were used to optimize transfection experiment: (i) functionally effective miRNA concentration, (ii) post-transfection incubation period and (iii) to control transfection efficiency between experiments. Consequently, miRNA mimic final concentration of 50 nM (for AGS and MKN28 cell cultures), miRNA inhibitor final concentration of 90 nM (AGS) and 150 nM (MKN28) were used for further experiments, and cells were cultivated 24 h and 48 h post-transfection.

After transfection of cells with mimic positive control (miR-1), TWF1 gene expression level on average decreased by: (i) 24 h post-transfection - 1.47 times in AGS (p=0.006) and 1.82 times in MKN28 (p=0.034), (ii) 48 h post-transfection gene expression decreased by 1.81 times in AGS (p=0.021) and 2.41 times in MKN28 cell line (p=0.0004) (Figure 8 and Figure 9).

After transfection of cells with inhibitor positive control (hsa-anti-let-7c), HMGA2 gene expression level on average increased by: (i) 24 h post-transfection - 6.27 times in AGS (p=0.0004) and 5.80 times in MKN28 (p=0.0004), (ii) 48 h post-transfection gene expression increased by 5.19 times in AGS (p=0.0004) and 4.46 times in MKN28 cell line (p=0.0004) (Figure 8 and Figure 9).

Fig. 8. Target-genes analysis after 24 and 48 hours in AGS cell line comparing cells treated with Negative Control and miRNA (normalized delta Ct (dCt) values are presented in logarithmic scale). Anti-has-let-7c target: HMGA2; miR-1: TWF1; miR-20b: IRF1, PTEN, TXNIP, EREG; miR-451a:

(36)

36 5.2.2 Evaluation of miRNAs potential target-genes mRNA expression

Expression of five hsa-miR-20b-5p target-genes (EREG, FAT4, IRF1, TXNIP, and PTEN) was analysed using ABI 7500 Fast RT-PCR system and 7500 Software v 2.0.6. EREG and FAT4 were rejected from further analysis, as expression level of these genes was undetermined in both GC cell lines (AGS and MKN28). Inhibition of hsa-miR-20b-5p expression significantly increased IRF1 gene expression level by 1.38 times in AGS (p=0.008) and 1.43 in MKN28 cell line (p=0.003) 24 h post-transfection; gene expression remained increased by 1.40 times only in AGS cell line (p=0.001) 48 h post-transfection. Target-gene PTEN expression level increased by 1.25 times in AGS cells (p=0.021) and 1.87 times in MKN28 cell line (p=0.005) 24 h post-transfection. 24 h post-transfection TXNIP gene expression on average increased by 1.65 times in AGS (p=0.046) and 1.70 times in MKN28 (p=0.0004), target-gene expression remained increased after 48h post-transfection by 1.63 and 1.80 times in both cell lines (p=0.006, p=0.001, AGS and MKN28, respectively) (Figure 8 and Figure 9).

Expression of two hsa-miR-451a-5p target-genes (CAV1 and ADAM28) was evaluated. ADAM28 was rejected from further analysis due to low gene expression in GC cell lines. Hsa-miR-451a-5p overexpression decreased CAV1 gene expression on average by 1.76 times only in AGS cell

Fig. 9. Target-genes analysis after 24 and 48 hours in MKN28 cell line comparing cells treated with Negative Control and miRNA (normalized delta Ct (dCt) values are presented in logarithmic scale). Anti-has-let-7c target: HMGA2; 1: TWF1; 20b: IRF1, PTEN, TXNIP, EREG;

(37)

37 line (p=0.008) after 24 h post-transfection, while after 48 h post-transfection gene expression remained decreased by 1.44 times in AGS (p=0.030) and 1.46 times in MKN28 cell culture (p=0.009) (Figure 8 and Figure 9)

Expression level of three hsa-miR-1468-5p target-genes (TNF, DNMT1, and CITED2) was determined. TNF was rejected from analysis due to low gene expression level in AGS and MKN28 cell cultures. After transfection of cells with hsa-miR-1468-5p mimic, DNMT1 increase in gene expression level was not consistent and din not reached statistical significance (p=0.052 and p=0.064 in AGS cell culture; p=0.134 and 0.250 in MKN28 cell culture; 24 and 48 hours respectively). CITED2 gene expression level decreased by 1.32 times only in MKN28 cell culture (p=0.021) when compared with cells transfected with negative mimic control (Figure 8 and Figure 9).

Every gene expression experiment was repeated 3 - 4 times and expression level of target-genes was evaluated 24 h and 48 h post-transfection. Protein expression analysis by WB was performed only for gene-targets corresponding to the following criteria: (i) expression level of target-gene’s statistically significantly (p>0.05) differs from cells transfected with inhibitor/mimic negative control and miRNA of interest, (ii) gene expression FC is more than 1.30 comparing cells transfected with inhibitor/mimic negative control and miRNA of interest, and (iii) expression difference of target-gene is consistent in both AGS and MKN28 cell lines. CAV1 (as a hsa-miR-451a-5p target), IRF1 and TXNIP (as hsa-miR-20b-5p targets) were used for further protein expression analysis.

5.2.3 Evaluation of miRNAs potential target-genes protein expression

For WB method optimization mimic and inhibitor positive controls were used, TWF1 (PTK9) and HMGA2 protein expression levels were analysed 48 h, 72 h, 96 h pot-transfection in both cell cultures (AGS and MKN28). Comparing cells transfected with miR-1 and mimic negative control, TWF1 protein expression decreased by 1.95, 2.63 and 2.38 times (48, 72 and 96 hours respectively) in

TWF1

(40 kDa)

GAPDH

(36 kDa)

Fig. 10. TWF1 protein expression in untransfected (UT), mimic positive control (mPC) and negative control (NC) transfected AGS cell line

(38)

38 AGS cell culture (Figure 10), while in MKN28 cell line TWF1 protein expression decreased by 1.94, 1.69 and 2.23 times (48, 72 and 96 hours respectively) (Figure 11). It was not possible to make HMGA2 protein analysis comparing cells transfected with hsa-let-7c inhibitor and inhibitor negative control. HMGA2 protein and antibody products were faint and the signals were weak.

After transfection of AGS and MKN28 cells with hsa-miR-20b-5p inhibitor, protein IRF1 expression did not differ when compared with cells transfected with inhibitor negative control. 48 h transfection FC in AGS and MKN28 cell lines was 1.17 and 1.26, respectively, 72 h post-transfection – 1.04 and 1.08, respectively (Figure 12).

TWF1

(40 kDa)

GAPDH

(36 kDa)

Fig. 11. TWF1 protein expression in untransfected (UT), mimic positive control (mPC) and negative control (NC) transfected MKN28

cell line (GAPDH protein expression was used for data normalization)

Fig. 12. IRF1 protein expression in hsa-miR-20b-5p and miRNA negative control (NC) transfected AGS and MKN28 cell cultures (GAPDH protein

expression was used for data normalization)

GAPDH

(36 kDa)

IRF1

(39)

39 After transfection of AGS and MKN28 cells with hsa-miR-20b-5p inhibitor, protein TXNIP expression was very low and inconsistent when compared with cells transfected with inhibitor negative control. 48 h post-transfection FC in AGS and MKN28 cell lines was 1.04 and 1.54, respectively, 72 h post-transfection – 0.80 and 0.79, respectively (Figure 13). Moreover, TXNIP protein expression was higher in MKN28 cell culture then in AGS cells. RKO cells’ lysate was used as a positive control.

After transfection of AGS and MKN28 cells with hsa-miR-451a-5p mimic, protein CAV1 expression was very low and complicated to analyse, however compared cells transfected with mimic negative control and hsa-miR-451a-5p, 48 h post-transfection FC in AGS and MKN28 cell lines was 1.56 and 1.19, respectively, 72 h post-transfection – 1.62 and 1.12, respectively (Figure 14).

GAPDH

(36 kDa)

TXNIP

(50 kDa)

Fig. 13. TXNIP protein expression in hsa-miR-20b-5p and miRNA negative control (NC) transfected AGS and MKN28 cell cultures (GAPDH protein

expression was used for data normalization, RKO cell lysate – as positive control)

GAPDH

(36 kDa)

CAV1

(20 kDa)

Fig. 14. CAV1 protein expression in hsa-miR-451a-5p and miRNA negative control (NC) transfected AGS and MKN28 cell cultures (GAPDH protein

(40)

40

6. DISCUSSION

GC is one of the most common cancers worldwide. Despite the significant progress in treatment of this type of malignancy, the prognosis for GC patients in advanced stages remains poor. Therefore, knowledge about genetic and epigenetic alterations underlying GC development and progression is still needed. Scientific studies analyzing miRNAs in GC pathogenesis could yield new insights into the biological behaviour of this disease. For manipulation of oncogenic miRNAs antagomirs are used. MiRNAs antagomirs is a type of antisense oligonucleotides that inhibit miRNA function in vivo effectively and can have an antitumor effect. Therefore, identification of cancer-specific miRNAs and their targets is not only critical for understanding their roles in tumorigenesis, and may be important for finding out novel therapeutic targets. In this study, experimental analysis of new target-genes of hsa-miR20b-5p, hsa-miR-451a-5p and hsa-miR-1468 was performed.

Firstly, the expression levels of three human miRNAs (hsa-miR-20b-5p, hsa-miR-451a-5p and hsa-miR-1468-5p) were assessed in control gastric tissue (n=11) and GC-derived cell lines (AGS and MKN28, n=7 each). It was found that the level of hsa-miR-451a-5p and hsa-miR-1468-5p were lower in GC cell lines compared to control, whereas hsa-miR-20b-5p levels in GC cell cultures were upregulated comparing to control. Results of hsa-miR-451a-5p expression level in AGS cell line are consistent with Riquelme et al. study (47), whereas the expression of this miRNA in MKN28 cell line was different. However, Riquelme et al. reported different control used in analysis (non-biological calibrator consisting of a pool of total RNAs from 10 non-tumor gastric tissues). Previous studies have also reported downregulation of hsa-miR-451a-5p in tumor tissues compared to adjacent non-tumor tissues in oesophageal carcinoma, lung adenocarcinoma, papillary thyroid carcinoma, colorectal cancer and hypopharyngeal squamous cell carcinoma (52-57). To our knowledge this is the first study reporting hsa-miR-1468-5p association with GC. Until now this miRNA was associated only with lung cancer (49,50). The expression data of hsa-miR-20b-5p in GC cell lines corresponds to the results reported in several previous GC studies (43,45). Moreover, hsa-miR-20b-5p is reported to be upregulated in brain metastases from primary breast cancers and periampullary adenocarcinoma (58,59).

Secondly, we examined the effect of miRNAs under-study for expression of potentially new targets. MiRNAs target-genes were evaluated using mathematical algorithms, databases and prediction tools. Three potential target genes were selected for hsa-miR-1468-5p (CITED2, DNMT1, TNF), five - for hsa-miR-20b-5p (EREG, FAT4, IRF1, TXNIP, PTEN), two - for hsa-miR-451a-5p (CAV1, ADAM28). However, experimental analysis showed that manipulation of miRNA expression level significantly affected mRNA expression level of IRF1, TXNIP and CAV1. Therefore, these gene were chosen for further analysis. IRF1 gene expression showed possible dependence on hsa-miR-20b-5p

Greta Streleckienė

TABLE OF CONTENTS

SUMMARY

SANTRAUKA

ABBREVIATIONS

1. INTRODUCTION

2. AIM AND OBJECTIVES OF THE THESIS

3. LITERATURE REVIEW

3.1 MiRNA biological impact

3.2 MiRNA deregulation in tumorigenesis

3.3 Methods of miRNA targets identification

3.4 Gastric cancer

3.5 MiR-20b-5p, miR-451a-5p, miR-1468-5p function

4. RESEARCH METHODOLOGY AND METHODS

4.1 Study object

4.2 Methods

4.3 Statistical analysis

5. RESULTS

5.1 Evaluation of miRNAs expression level in GC cell lines

5.2 Experimental evaluation of miRNAs target-genes

6. DISCUSSION