Masarykova univerzita přírodovědecká fakulta diplomová práce brno 2017 Veronika Krmeská masarykova univerzita

MASARYKOVA UNIVERZITA
Přírodovědecká fakulta

DIPLOMOVÁ PRÁCE

Brno 2017 Veronika Krmeská

MASARYKOVA UNIVERZITA

Přírodovědecká fakulta

Ústav experimentální biologie

Oddělení genetiky a molekulární biologie
Úloha dlouhých nekódujících RNA

v biologii chronické lymfocytární leukémie

Diplomová práce

Veronika Krmeská


Vedoucí práce: doc. MUDr. Mgr. Marek Mráz, Ph.D. Brno 2017

Bibliografický záznam

Autor: Bc. Veronika Krmeská

Přírodovědecká fakulta, Masarykova univerzita

Ústav experimentální biologie
Název práce: Úloha dlouhých nekódujících RNA v biologii chronické lymfocytární leukémie
Studijní program: Experimentální biologie
Studijní obor: Molekulární biologie a genetika
Vedoucí práce: doc. MUDr. Mgr. Marek Mráz, Ph.D.
Akademický rok: 2016/2017
Počet stran: 75
Klíčová slova: CLL; lncRNA; XIST; H19; GAS5; TUG1; MALAT1; LincRNA-p21; INXS

Bibliographic Entry

Author: Bc. Veronika Krmeská

Faculty of Science, Masaryk University

Department of Experimental Biology
Title of Thesis: The role of long-noncoding RNAs in the biology of chronic lymphocytic leukemia
Degree Programme: Experimetal Biology
Field of Study: Molecular Biology and Genetics
Supervisor: doc. MUDr. Mgr. Marek Mráz, Ph.D.
Academic Year: 2016/2017
Number of Pages: 75
Keywords: CLL; lncRNA; XIST; H19; GAS5; TUG1; MALAT1; LincRNA-p21; INXS

Abstrakt

Pouze 2 % lidského genomu jsou přepisována a přeložena do proteinů. V současnosti je stále více pozornosti věnováno transkribované DNA, která se dále do proteinu nepřekládá. Do této nekódující části patří microRNA (miRNA), které jsou již dobře popsány v souvislosti s mnoha chorobami, ale také dlouhé nekódující RNA (lncRNA). LncRNA jsou definovány jako RNA delší než 200 nukleotidů (nt), které postrádají jakýkoliv otevřený čtecí rámec. V této práci bylo vybráno a zkoumáno několik lncRNA (XIST, H19, GAS5, TUG1, MALAT1, LincRNA-p21, INXS) ve vztahu k nejčastějšímu typu leukémie dospělého věku, chronické lymfocytární leukémii (CLL). Výběr lncRNA byl založen na vztahu mezi lncRNA a signalizačními dráhami, které jsou u CLL deregulované nejčastěji. Exprese lncRNA byla dále porovnána mezi jednotlivými subtypy CLL s cílem odhalit jejich možnou roli ve klinické a biologické variabilitě tohoto onemocnění.

Abstract

Only 2% of human genome is transcribed and translated into proteins. Nowadays, more and more attention is paid to DNA, which is trascribed but does not encode any protein. This noncoding part contains not just short noncoding RNAs such as microRNAs (miRNAs) which are already well described in relation to many diseases, but also long noncoding RNAs (lncRNAs). LncRNAs are defined as RNAs longer than 200 nucleotides (nt) without any open reading frame. In this thesis, several lncRNAs were selected (XIST, H19, GAS5, TUG1, MALAT1, LincRNA-p21, INXS) and examined in relation to the most common type of adult leukemia, chronic lymphocytic leukemia (CLL). Selection of lncRNAs was based on relationship between these and pathways frequently deregulated in CLL. The expression of lncRNAs was measured and compared between the CLL subtypes to reveal their hypothetical roles in the clinical and biological heterogeneity of CLL.

Poděkování

Na tomto místě bych ráda poděkovala svému školiteli doc. MUDr. Mgr. Marku Mrázovi, Ph.D. za odborné vedení a trpělivost při vypracovávání této práce. Také bych ráda poděkovala Mgr. Kateřině Černé za pomoc a čas, který mi věnovala při psaní práce. Díky patří také Mgr. Kateřině Musilové, Mgr. Gabriele Pavlasové, Mgr. Václavu Šedovi a Bc. Evě Vojáčkové za vytvoření příjemného pracovního prostředí.

Prohlášení

Prohlašuji, že jsem svoji diplomovou práci vypracoval/a samostatně s využitím informačních zdrojů, které jsou v práci citovány.

Brno, 4.1.2017 ……………………….

Veronika Krmeská


Content

1. INTRODUCTION ......................................................................................................... 12

1.1. Chronic lymphocytic leukemia............................................................................. 12

1.1.1. Pathogenesis.............................................................................................. 12

1.1.2. Genomic aberrations................................................................................. 14

1.1.3. Microenvironment..................................................................................... 16

1.2. LncRNAs............... ............................................................................................... 16

1.2.1. Function.................................................................................................... 17

1.2.2. Selection of profiled lncRNAs.................................................................. 19

1.2.2.1. XIST.................................................................................. 20

1.2.2.2. GAS5................................................................................. 20

1.2.2.3. TUG1................................................................................. 21

1.2.2.4. H19.................................................................................... 21

1.2.2.5. MALAT1........................................................................... 22

1.2.2.6. LincRNA-p21.................................................................... 25

1.2.2.7. INXS.................................................................................. 25

2. AIMS....................... ........................................................................................................ 27

3. MATERIALS AND METHODS.................................................................................... 28

3.1. Materials................................................................................................................ 28

3.2. Equipment............................................................................................................. 28

3.2.1. Instruments ............................................................................................... 28

3.2.2. Software.................................................................................................... 29

3.2.3. Reagents.................................................................................................... 29

3.3. Isolation of lymphocytes from peripheral blood................................................... 30

3.4. RNA/protein lysate prepearation........................................................................... 31

3.5. RNA isolation........................................................................................................ 32

3.5.1. RNA concentration................................................................................... 32

3.5.2. RNA quality.............................................................................................. 32

3.6. Reverse transcription............................................................................................. 33

3.7. qRT-PCR............................................................................................................... 34

3.7.1. qRT-PCR optimization............................................................................. 34

3.7.1.1. LincRNA-p21 optimization............................................... 34

3.7.1.2. INXS optimization............................................................ 36

3.7.2. qRT-PCR using TaqMan probes............................................................... 37

3.7.3. Normalization of relative expression........................................................ 39

3.8. Protein analysis..................................................................................................... 39

3.8.1. Protein concentration................................................................................ 39

3.8.2. Western blot.............................................................................................. 39

4. RESULTS.. ..................................................................................................................... 42

4.1. Optimization of qRT-PCR..................................................................................... 42

4.1.1. LincRNA-p21 optimization...................................................................... 42

4.1.2. INXS optimization.................................................................................... 44

4.2. Expression of selected lncRNAs in the CLL cohort............................................. 44

4.3. Expression of lncRNAs after DNA-damage response in vitro.............................. 49

4.4. Validation cohort ................................................................................................... 51

4.4.1. MALAT1.................................................................................................. 51

4.4.2. INXS ........................................................................................................ 54

4.5. LncRNAs in different cellular processes.............................................................. 55

4.5.1. STAT3 activity and fibronectin................................................................ 56

4.5.1.1. MALAT1........................................................................... 56

4.5.1.2. INXS.................................................................................. 56

4.5.2. DNA-damage response............................................................................. 57

4.5.2.1. MALAT1........................................................................... 57

4.5.2.2. INXS.................................................................................. 58

4.5.3. Microenvironment..................................................................................... 58

4.5.3.1. MALAT1........................................................................... 59

4.5.3.2. INXS.................................................................................. 59

4.6. LncRNAs and a regulation of the Bcl-2 protein family........................................ 59

4.6.1. MALAT1.................................................................................................. 60

4.6.2. INXS ........................................................................................................ 61

5. DISCUSSION................................................................................................................. 63

6. SOUHRN......................... ............................................................................................... 67

7. SUMMARY.................................................................................................................... 68

8. LITERATURE................. ............................................................................................... 69

Abbreviations

ABALON apoptotic BCL2L1-antisense long non-coding RNA (INXS)

ATM ataxia telengiectasia mutated

BCP 1-bromo-3-chloropropane

BCR B-cell receptor

BIRC3 baculoviral IAP repeat-containing protein 3

bp base pairs

BSA bovine serum albumin

CCT4 chaperonin-containing tailless complex polypetide, subunit 4

cDNA complementary DNA

ceRNA competing endogenous RNA

CLL chronic lymphocytic leukemia

Cohort 60 cohort used for first profiling of lncRNAs (n=60)

Cohort 92 validation cohort (n=92)

Ct cycle threshold

CTCF CCCTC-binding factor

CTHRC1 collagen triple helix repeat containing 1

DBD DNA-binding domain

DDR DNA-damage response

del11q deletion 11q

del13q14 deletion 13q14

del17p deletion 17p

DOX doxorubicin

FISH fluorescent in situ hybridization

FLU fludarabine

FN fibronectin

GAS5 growth-arrest-specific 5

GR glucocorticoid receptor

GRE glucocorticoid response elements

hnRNP-K heterogeneous nuclear ribonucleoprotein K

HS5 bone marrow stromal cell line

ICR imprinting control regions

Igf2 insulin-like growth factor 2

IgVH heavy-chain immunoglobulin variable region

IL-6 interleukin-6

LincRNA-p21 large intergenic ncRNA, locus near gene P21 locus

lncRNA long non-coding RNA

MALAT1 metastasis associated in lung adenocarcinoma transcript 1

mascRNA MALAT1-associated small cytoplasmic RNA

M-CLL/M-IgVH mutated IgVH

MEC-1 B-CLL cell line

miRNA microRNA

MM multiple myeloma

mRNA messenger RNA

ncRNA non-coding RNA

NEAT2 nuclear-enriched abundant transcript 2 (MALAT1)

nt nucleotides

PRC2 polycomb repressive complex 2

qRT-PCR quantitative real-time polymerase chain reaction

RAMOS Burkitt lymphoma derived cell line

RIN RNA integrity number

SR serine/arginine splicing factors

STAT3 signal transducer and activator of transcription

STAT3i STAT3 inhibitor

TBE buffer Tris/Borate/EDTA buffer

TF transcription factor

TNF tumor necrosis factor

tRNA transfer RNA

TUG1 taurine upregulated gene 1

U-CLL/U-IgVH unmutated IgVH

WSU-NHL B-cell lymphoma cell line

wt wild type

Xi inactive chromosome X

XIC X-inactivating centre

XIST X-inactive specific transcript

ZAP-70 T-cell-specific protein tyrosine kinase zeta-associated protein of 70

1. INTRODUCTION
1.1. Chronic lymphocytic leukemia

The chronic lymphocytic leukemia is the most frequent type of leukemia in the Western world and it affects especially elderly people (median 65 years).

CLL is extremely heterogenous disease with overall survival varying from months to decades. There are two clinical staging systems used for prognosis estimation - Rai and Binet (Rai et al., 1975; Binet et al., 1981). Both systems define early, intermediate and advanced stages with similar survival rates (table 1) and are based on sites of disease manifestation and presence of anemia and/or trombocytopenia, although there is heterogeneity within the same stage group too.

	Rai	Binet	survival (years)
early	0 - blood, bone marrow	A - less then 3 lymphoid sites involved	˃10
intermediate	I - enlarged lymph nodes	B - 3 or more lymphoid sites involved	5 - 7
	II - spleen. liver
advanced	III - bone marrow failure + anemia	C - presence of anemia and/or trombocytopenia	1 - 3
	IV - bone marrow failure + anemia + trombocytopenia

Table 1. Rai and Binet staging systems.
1.1.1. Pathogenesis

CLL is a result of accumulation of functionally incompetent B-cells in the blood, secondary lymphoid tissues and bone marrow that fail to undergo apoptosis. These B-CLL cells are mature CD5+/CD19+/CD23+ B lymphocytes with low levels of surface immunoglobulins (IgM or IgD) and arrested in the G₀ or early G₁ phase of cell cycle (Matutes et al., 2000).

Apoptosis is triggered in cell via extrinsic or intrinsic pathway. Extrinsic pathway is regulated by receptors and ligands of TNF (tumor necrosis factor) family and intrinsic pathway by Bcl-2 family proteins through intrinsic apoptotic pathway. This proteins are classified according to their Bcl-2 homology domains BH1-4 and function:

1. 
   Anti-apoptotic (BH1-BH4): Bcl-2, Bcl-XL, Bcl-W, Mcl-1, Bfl-1, Bcl-b
   
2. 
   Pro-apoptotic (BH1-BH3): Bax, Bak, Bok
   
3. 
   Anti-apoptotic (BH3 only): Bim, Puma, Noxa
   

In CLL there is a shift in expression of Bcl-2 family members towards survival, higher expression of Bcl-2, Mcl-1 and Bcl-XL was observed (Gottardi et al., 1996).

The B-cell receptor (BCR) signaling is also associated with resistance to apoptosis, which plays critical role not just in CLL but also in other B-cell malignancies. BCR is the antigen-specific surface membrane immunoglobulin paired with signal transduction heterodimers CD79A and CD79B (figure 1). When antigen binds to the BCR, cytoplasmic tails of CD79A and B are phosphorylated which later leads to the activation of downstream pathways including MAP kinase, RAS, ERK, Akt and NF-κB, but also results in intracellular calcium influx and hence activation of anti-apoptotic Bcl-2 family members such as Mcl-1 (Petlickovski et al., 2005). This in general leads to survival and proliferation of B-cells.

Figure 1. B-cell receptor signaling pathway (Choi et al., 2012).

BCR and its stimulation of pro-survival factors is higly associated with well-known prognostic factors of CLL - status of IgVH (heavy-chain immunoglobulin variable region) and expression of the ZAP-70 (T-cell-specific protein tyrosine kinase zeta-associated protein of 70kD).

Patients with better prognosis usually express mutated IgVH (M-CLL) and less ZAP-70 protein. ZAP-70 was originally identified in T-cells, shortly after that in activated normal B cells. It enhances the BCR signalling capacity leading to more agressive disease (Chen et al., 2008), it is also used as a marker of unmutated-IgVH CLL (U-CLL).

Patient is considered to have U-CLL if B-cells share 98% or more sequence homology with the germline sequence. M-CLL B-cells carry then less 98% homology. Unmutated IgVH means higher risk for patient because BCR is polyreactive and responds more to the enviromental or auto-antigens.

1.1.2. Genomic aberrations

Besides the IgVH status and ZAP-70 expression, another factors can provide prognostic information, such as age, gender, lymphocyte count and multiple genomic aberrations which were frequently observed in CLL patients as a secondary manifestation of the disease.

Genomic aberrations are identified by fluorescent in situ hybridization (FISH) and most frequent abnormalities involve deletion 17p (del17p), deletion 11q (del11q), trisomy 12 and deletion 13q14 (del13q14).

At the short arm of chromosome 17 is localized well known tumor suppressor gene TP53. Function of TP53 gene can be disrupted not only by del17p but also by other mutations (Gaidano et al., 1991).

The majority of del11q involve ATM gene (ataxia telengiectasia mutated) which also leads to dysfunction of p53. Del11q is associated with lyphadenopathy and together with del17p and unmutated IgVH represent high-risk markers in CLL (Dohner et al., 1999).

Trisomy 12 is associated with overexpression of few cell cycle control genes such as p27, CDK4, BAX and E2F1 (Nourse et al., 1994).

Deletion 13q14 (del13q14) as a sole abnormality is associated with better prognosis (Dohner et al.,2000). It is also the most frequent abnormality in CLL. It was shown that this reagion contains two microRNAs, namely, miR-15a and miR-161-1. This discovery was the very first link between miRNAs and cancer (Calin et al., 2002). MicroRNAs are small noncoding RNAs with transcript length of about 19-25 nt. Nowadays they are well known post-transcriptional regulators of messenger RNAs (mRNAs). Subsequently, a deregulation of more miRNAs in CLL (such as miR-29, miR-155, and miR-150) was discovered (Fulci et al., 2007). This deregulation contributes to higher expression of anti-apoptotic genes such as Bcl-2 or Mcl-1 (Musilová and Mráz, 2015).

These aberrations were examined by Dohner et al. (2000) in association with survival (figure 2). In this study was created hierarchical model with five categories and different prognosis. Patients are divided into categories according to their highest risk cytogenetic aberration.

Categories in Dohner hierarchy:

1. del17p or other mutation including gene TP53 (the worst prognosis, the shortest overall survival)