Universidade de Aveiro Ano 2012
Departamento de Biologia
Rui Augusto
Martins Cordeiro
Caraterização, in vitro, de um novo gene associado a
cancro.
Universidade de Aveiro Ano 2012
Departamento de Biologia
Rui Augusto Martins
Cordeiro
Caraterização, in vitro, de um novo gene associado a
cancro.
In vitro
characterization of a new cancer-related gene.
Dissertação apresentada à Universidade de Aveiro para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Biologia Aplicada, realizada sob a orientação científica da Professora Doutora Etelvina Figueira do Departamento de Biologia da Universidade de Aveiro, e do Professor Doutor João Pedro de Magalhães, do Institute of Integrative Biology da Universidade de Liverpool.
o júri
presidente Professora Doutora Maria Adelaide de Pinho Almeida
Professor Auxiliar do Departamento de Biologia da Universidade de Aveiro
orientadores Professora Doutora Etelvina Maria Paula Figueira
Professora Auxiliar do Departamento de Biologia da Universidade de Aveiro
Professor Doutor João Pedro de Magalhães
Professor Auxiliar do Institute of Integrative Biology da Universidade de Liverpool
arguente principal Doutora Isabel Alexandra Marcos Miranda
Investigadora Auxiliar do Laboratório de Microbiologia da Faculdade de Medicina da Universidade do Porto
Agradecimentos
Em primeiro lugar gostaria de agradecer ao Professor Doutor João Pedro Magalhães não só por ter proporcionado a possibilidade e o privilégio de desenvolver esta tese no Institute of Integrative Genomics of Ageing, mas também por toda a paciência e sabedoria transmitida ao longo destes anos. Sem a sua ajuda e toda a confiança depositada em mim, esta tese não seria possivel.
À Professora Doutora Etelvina agradeço a prontidão com que aceitou orientar-me e não só me ter ensinado muito do que hoje sei mas também pela amizade e disponibildade demonstrada.
To all my English speaking friends: Andrew, Thomas, Robi, Michael and Simon; for all the help and good times at the lab, and especially to Dr. Shona Wood, for all her attention to detail and her invaluable advice.
To my good friends (and favorite gingers) Ian and Sarah, thank you for listening and for caring. You are the best and it would not be the same without you. To Jen, Jo, Louise, Corrado, Chris, Nick, Jane and Julie, thanks for brightening up lunch time with all the irrelevant topics that made me laugh.
Last but definitively not least: Sipko. I can’t thank you enough for all the friendship, all the help and patience. I am especially grateful for that which many times saved me from starving, our weekly “dirty burger” with the rest of the “internationals”.
Aos meus amigos portugueses, Rute, André e Ricardo, transientes habitantes de Liverpool, obrigado pelas gargalhadas e companheirismo. Os raros momentos em que podiamos retornar à língua mãe eram sempre os meus predilectos.
Agradecimentos
Aos amigos em Portugal, demais para serem enumerados mas sem os quais as minhas noites (principalmente as primeiras) teriam sido muito mais cinzentas, um grande obrigado. Não posso porém de deixar de referir a yin para o meu yang – Filipa Domingues – que não só sempre foi uma grande companheira como uma ajuda na elaboração desta tese. É importante ainda destacar os meus usuais companheiros de Skype: Maria, Filipe, Inês, Cátia e Vanessa
Por último mas não menos importante à minha familia. Sem eles também não seria possível. Aos meus tios e tias, sempre preocupados e sempre interessados, em particular à minha tia Filomena, que é talvez a razão pela qual me quis dedicar à biologia. Agradeço ainda aos dois opostos cronológicos: a minha avó Bela porque tudo o que há de importante e que não se aprende na escola foste tu que me ensinaste, e não só estás estás no meu coração como és todo o meu coração; e ao meu pequeno afilhado Martim, cujo sorriso, sem ele saber, é um raio de alegria nos dias mais sombrios.
Finalmente aos meus pais por todos os sacrificios e pela clarividência que tiveram na minha educação que tornou uma estadia no estrangeiro muito mais fácil. Em especial à minha mãe pela paciência e compreensão, às minhas irmãs por nunca estarem mais longe que uma chamada Skype e serem sempre o meu lado mais positivo, e ao meu pai não só pelo entusiasmo com o meu trabalho mas principalmente por ser o meu herói e o meu exemplo.
Abbreviations
AURKA Aurora kinase A
AURKB Aurora kinase B
AURKC Aurora kinase C
bp Base pairs
βME β-Mercaptoethanol
BRCA1 breast cancer susceptibility gene 1
BRCA2 breast cancer susceptibility gene 2
cDNA complementary DNA
DEPC Diethylpyrocarbonate (treated water)
dNTPs Deoxyribonucleotide triphospates
DMEM Dulbeco’s Modified Eagle Medium
DMSO Dimethyl Sulfoxide
DNA deoxyribonucleic acid
DSBs Double-strand breaks
dsRNA double stranded RNA
DTT Dithiothreitol
EDTA Ethylenediaminetetraaceit acid
FBS Fetal Bovine Serum
HRR Homologous recombinational DNA repair
MgCl2 Magnesium Chloride
mRNA messenger RNA
min. minutes
Oligo dT deoxy-Thymine nuleotides
PCR Polymerase chain reaction
PBS Phosphate buffered saline
Pen Penicillin
RNA Ribonucleic acid
RNAi RNA interference
RT Reverse transcriptase
siRNA small interfering RNA
shRNA small hairpin RNA
Strep Streptomycin
Palavras chave
Resumo
Gene, Genética, Expressão Genética, Co-expressação, Cancro, siRNA, células HeLa, RNA interferencia, Ciclo Celular, Divisão Celular, Replicação do DNA, reparação do DNA
Ánalises de co-expressão, usando um método de “culpado por associação”, de um grupo de genes relacionados com cancro, revelou que o gene Bc055324 (um gene de ratinho não anotado e sem funções conhecidas) é fortemente co-expresso com muitos outros genes associados a patologias cancerígenas, como por exemplo os conhecidos Brca1 e Brac2 no cancro da mama. Bc055324 está também não só associado a genes cancerígenos como a genes relacionados com o ciclo celular, replicação e reparação do DNA. Isto sugere que o seu homólogo humano (também não estudado) – C1ORF112 – tem um papel no desenvolvimento de cancro e, de fato este gene é altamente expresso em vários cancros. Neste trabalho é mostrado que a proliferação celular é significativamente diminuída aquando do silenciamento do gene C1ORF112 em células cancerígenas HeLa.
Como C1ORF112 é sobrexpresso em várias cancros, particularmente em cancro da mama, é possivel que tenha um papel no desenvolvimento de cancro e, por isso, o objectivo deste trabalho era avaliar o papel do gene C1ORF112 na proliferação de células cancerígenas, bem como elucidar preliminarmente as suas funções de forma a contribuir para futuros estudos que poderão indicar este gene como um potencial alvo para novos
Keywords
Abstract
Gene, Genetics, Gene Expression, Co-expression, Cancer, siRNA, HeLa cells, RNA interference, Cell Cycle, Cell Division, DNA replication, DNA repair
Co-expression analysis of a set of causative cancer genes using a "guilt-by-association" method revealed Bc055324 (an un-annotated mouse gene, strongly co-expressed with many cancer-related genes and in particular with genes associated with cell cycle, DNA replication and repair. Its unstudied human homolog - C1ORF112 – is highly expressed in several cancers, suggesting it plays a role in cancer. The aim of this project is to assess the role of C1ORF112 in the proliferation of cancer cells as well as begin to elucidate its functions. To this end, a knockdown C1ORF112 was produced in HeLa cells, which showed cell growth is significantly decreased indicating this gene is required for cancer cell growth.
Overall, further studies of this novel cancer-associated gene may provide new insights into cancer development and may well reveal new target for cancer diagnostics and/or therapies.
i
I
NDEX
Index of Figures ... v
Index of Tables ... vii
1. GENERAL INTRODUCTION ... 1
1.1. INTRODUCTION ... 3
1.2. Co-expression map ... 4
1.3. Bc055324 ... 5
1.4. C1ORF112 ... 6
1.5. Genes most strongly co-expressed with C1ORF112 ... 6
1 . 5 . 1 . BRCA1 and B R C A 2 ... 6 1 . 5 . 2 . R A D 5 1 ... 9 1 . 5 . 3 . A U R K B ... 10 1 . 6 . H e l a c e l l s ... 12 1 . 7 . R N A i n t e r f e r e n c e ( R N A i ) ... 14 1.7.1.1. The mechanism ... 15 1.7.1.2. Applications ... 16 1.8. Objectives ... 16
2. Materials and Methods ... 19
2.1. Starting Cell Culture from frozen Cells: ... 21
2.2. Maintenance of HeLa cells ... 21
2.2.1. Sub-cultivating ... 21
2.2.2. Changing medium ... 22
2.3. Reverse Transfection of HeLa cells (6-well plates): ... 22
2.4. RNA Extraction ... 23
2.5. Quantifying RNA ... 24
2.6. cDNA transformation ... 24
iii
2.7.1. Diluting primers ... 26
3. Results and Discussion ... 29
3.1. In silico ... 31 3.1.1. Bc055324 ... 31 3.1.2. C1ORF112 ... 35 3.2. In vitro ... 38 4. Conclusion ... 42 5. Bibliography ... 46
v
Index of Figures
Figure 1 - BRCA1’S 3D protein configuration ... 7
Figure 2 - BRCA2’s 3D protein configuration ... 8
Figure 3 - RAD51’s 3D protein configuration ... 10
Figure 4 - AURKB’s 3D protein configuration ... 11
Figure 5 - HeLa cells in culture ... 13
Figure 6 - RNAi theory model ... 15
Figure 7 - Number of articles showing were Bc055324 was found to be over/under-expressed in mouse tissues ... 31
Figure 8 - Bc055324’s gene tree showing a high degree of conservation amongst the various species ... 34
Figure 9 – Number of articles showing were C1ORF112 was found to be over/Under-expressed in human tissues ... 35
Figure 10 - C1ORF112’s expression in both normal and cancerous tissues . ... 38
Figure 11 – Cell counts following the exposures to the siRNAs ... 39
Figure 12 –Real-time PCR results showing a 60% decrease in C1ORF112’s expression after siRNA silencing. ... 40
vii
Index of Tables
Table 1 - Top 10 most co-expressed genes with Bc055324 ... 31
Table 2 - Functional enrichment among genes co-expressed with Bc055324 ... 32
Table 3 –Pairwise alignment scores between Bc055324’s protein and DNA sequences
and its homologs’ sequences. ... 33
Table 4 – Top 10 most co-expressed genes with C1ORF112 ... 36
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3
1.1.
INTRODUCTION
More and more researchers attribute cancer to genetic factors, based on aberrant changes in either sequence or expression [1]. The universe of genetic and epigenetic abnormalities that characterize cancer cells presents, in its vastness, new and more specific targets for cancer treatment and prevention. Over the last decade, the mapping of the human genome, along with improved understanding of signal transduction and tumor survival pathways, have been improving therapeutic oncology from a more ubiquitous targeting chemotherapy towards a more selective approach. So much so that antibody-based Herceptin became the first breast cancer targeted therapy and in 2001 the small molecule “Gleevec” became the first approved kinase inhibitor for cancer targeting in chronic myeloid leukemia (and since then has been approved for other tumors) [2].
Proteomic, genetic and pharmacogenomic tools are a long desired concept of personalized cancer therapy. Genetic abnormalities of each patient’s tumor can be analyzed a variety of ways, to determine gene or protein over/under expression, making possible to target key molecular relays for highly selective therapies. This has to be preceded by the use of the nowadays-available tools of candidate gene prioritization, such as in this case, a co-expression map.
Such tools allow the identification of the most promising candidates among a large group of candidates, allowing maximization of yield and relevance of experimental validation and functional studies. In the past few years, gene prioritization methods have thrived since users can freely access them [3].
The “recent” discovery of RNAi, presents an invaluable tool for cancer research (and personalized therapy). This natural process, through which gene expression of the target gene can be silenced, has the potential to selectively knockdown key molecular abnormalities in patients’ tumors. In a less therapeutic view, and more to the point of this thesis, RNAi allows the identification relevant bio molecular functions of a targeted gene by silencing it which then allows, through any phenotypical alterations, to ascertain the gene’s function [2].
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1.2.
Co-expression map
With the emergence of technologies such as that of the microarrays, the ability to measure expression levels across large numbers of genes became easier. The identification of genes’ biological processes is now possible even when expression is low.
As microarrays provide genome-wide expression data, the changes in gene expression can be examined to understand factors involved in disease processes. Biomarkers and genes [4–7] involved in diseases, such as cancer, have been successfully identified using microarrays [8]. In fact, both Aid-Pavlidis et al. and Stuart
et al. have demonstrated that meta-analyses can be successfully used to identify
biological functions and relationships between genes and even to identify new candidate disease genes [9, 10].
A co-expression analysis is a type of meta-analysis in which genes’ relationships are established through their “behavior” towards each other. This enables the discoveries of groups that are functional and/or genetically related [11]. The main concept behind a expression analysis is that genes are more likely to be co-expressed with other functionally related genes [12–14]. This “guilt by association” approach has already been used to associate hundreds of unidentified genes to inflammation, steroid-synthesis, insulin-synthesis, neurotransmitter processing, matrix remodeling, and others [10, 15]. Predicted results have been successfully verified through experimental validation, demonstrating the significance of this approach [10]. Target genes for diseases like cancer, Parkinson’s and Schizophrenia have already been identified using this approach [15, 16].
In order to create a co-expression map, over 1,000 mouse microarray datasets were used, comprising over 20,000 individual microarrays from previously published experiments. As mouse experiments are in general better controlled than the human counterpart and there is less variation caused by genotypic and environmental factors in the mouse, Mus musculus data was chosen over Homo sapiens to reduce noise. Using mouse data also allows more datasets to be used [17], and potentially allows for
5
investigation of target genes in the different mouse models of aging, including progeroid mice.
This genome wide co-expression map – GeneFriends [18] – designed by Sipko van Dam is validated by showing that functionally related genes are more likely to be co-expressed. Multiple candidate genes associated with cancer and mitochondrial diseases, including un-annotated and poorly studied genes, were identified. Two novel candidates, of unknown function, that were co-expressed with cancer-associated genes were selected for experimental validation in HeLa cells. Of these two genes, Bc055324 had the strongest association with the initial cancer seed list as wel as being co-expressed with a much larger number of cancer genes that was not present in this specific seed list. This not only validates that the Bc055324 gene is strongly associated with many cancer genes, but also shows that this approach is capable of identifying other cancer genes that were not present in the initial seed list. For this reason – Bc055324 and its human homolog C1ORF112 – were selected as the target of this thesis.
1.3.
Bc055324
Genes involved in common biological processes and diseases are often co-expressed. Therefore, analyses of genes co-expressed with known disease-associated genes may help identify and prioritize new candidates for further studies. Co-expression analysis of a set of causative cancer genes in a "guilt-by-association" method revealed several potential novel candidates suitable for experimental and/or clinical follow-up. Amongst the strongest co-expressed with disease related genes, Bc055324 (an un-annotated gene) was on the top of the list, being strongly co-expressed with many cancer genes.
Very little is known about this gene beyond the tissues where it was found to be expressed. There are no functions, processes or known cellular locations associated with it; Bc055324’ DNA and protein sequences are particularly conserved within
6
mammalians, e.g. Homo sapiens with whom it shares 76.8% homology with its protein and 81.4% with its DNA sequence.
1.4.
C1ORF112
If little is known about Bc055324 the same is true for its human homolog – C1ORF112 – with whom it shares 81.4% homology. C1ORF112 is evolutionarily conserved and, like its mouse homologue is strongly co-expressed with many genes that are active in cell cycle and with cancer-related genes
1.5.
Genes most strongly co-expressed with
C1ORF112
Since both C1ORF112 and Bc055324 are un-annotated genes it is through their known closest “friends” (i.e. GeneFriends) that we can derive C1ORF112’s role in the pathofisiology. Through the descriptions below a pattern can be established, linking C1ORF112 to its putative functions.
1 . 5 . 1 .
BRCA1 and
B R C A 2
BRCA1 and BRCA2 are putative tumor suppressors in the regions were BRCA1 and BRCA2 are located with a role in genomic stability , identified in the early 90s as the genetic elements underlying breast and ovarian cancer, followed by a rapid implementation of clinical testing for mutations in these genes [19].
In 1990, through linkage analysis, King et al. [20] associated BRCA1 (Figure 1) with inherited early-onset breast cancer. Shortly after Narod’s Group demonstrated that BRCA1 is also responsible for inherited susceptibility to ovarian cancer[21]. Later, a second gene was identified – BRCA2 – by genetic linkage analysis [22]. Since then BRCA1 and BRCA2 have been isolated and, as a result, direct screening for mutations has replaced indirect methods for identifying women at risk [23]. Following their identification BRCA1 and BRCA2 have been extensively studied, furthering the knowledge of the genetic basis of these cancers. However many questions remain
7
unanswered, concerning the molecular mechanisms of how BRCA1 and BRCA2 function as tumor suppressors.
FIGUR E 1-BRCA1’S3D PR OTEIN CONF IGURAT ION
BRCA1 is located in the long arm of chromosome 17, spans 100kb of genomic DNA, and encodes a protein of 1863 amino acids. Near the NH2-terminus there is sequence with remarkable similarity to zinc finger domains. This sequence resembles, in many ways, a zinc finger motif (RING finger) [23], that is characteristic of several viral proteins, proto-oncoproteins and regulatory an transcription factors [24]. However a function has not been identified for this motif, it appears to interact with DNA, either directly binding or indirectly mediating protein/protein interactions [25]. Has so, this might suggest that BRCA1 is a transcription factor, which is supported by other studies [22, 26].
BRCA1 and 2 are evolutionarily conserved, especially in mammals and are expressed in numerous tissues, besides breast and ovary. Mutations of BRCA1 have been identified in 63 distinct germline mutations in more than 100 patients with breast and/or ovarian cancer [27]. Mutations in this gene are responsible for 45% of registered breast/ovarian cancer patients [22], whose carriers have a substantial lifetime risk of breast/ovarian cancer [19], and are distributed across the entire coding region of the genes. No somatic mutations have been identified in breast cancers though five mutations have been found in ovarian tumors, suggesting that this gene
8
plays an important role in the tumorigenesis of hereditary breast cancer (but not sporadic breast cancer [27].
Despite not being investigated as extensively as BRCA1, the second breast cancer susceptibility gene, BRCA2 (Figure 2), is thought to be a nuclear protein [28] and accounts for roughly the same proportion of breast cancers as BRCA1. Concentration analysis of Brca2’s mRNA in mouse tissue (95% homology with humans) revealed a very similar pattern to that
of Brca1 [29].
FIGUR E 2 - BRCA2’S 3D PROT EIN CONF IGURAT ION
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BRCA2 mutation carriers appear to confer a high risk of early-onset breast cancer (63% at age 70 and 87% at age 80). In contrast to BRCA1, BRCA2 families only have a moderate increase incidence of ovarian cancer, also, male carriers have a 6% lifetime risk of developing breast cancer – a dramatic 100-200 –fold increased risk as compared to the general population [32]. Recently a study attributed 14% of male breast cancers to BRCA2 mutations with almost all of the patients having in their family history, male or female, breast cancers [30]. Within the 3rd exon of BRCA2 lies a region with some similarity to c-jun [31] – a transcription factor. Therefore, it is possible that BRCA2 is responsible for regulating transcription. Another area was shown to be able to bind to RAD51, implicating that this gene might intervene in the DNA repair process [32].
In spite of the poor prognostic indicators, mutation carriers tend to, overall, have better survival rates than patients with sporadic breast cancers.[33].
1 . 5 . 2 .
R A D 5 1
RAD51 (Figure 3) is an eukaryotically conserved gene (from yeast to humans) and the protein it encodes is a member of the RAD51 protein family, which assist in the repair of DNA double-strand breaks (DSBs) [34] and is a key protein for homologous recombinational DNA repair (HRR) [35]. It interacts with proteins such as BRCA2 and RAD52 (also responsible for DSBs repair and homologous recombination) which suggests an important role in cellular response to DNA damage[34].
10
FIGUR E 3-RAD51’S 3D PROT EIN CONF IGURAT ION
Overexpression of RAD51 in different organisms has various consequences, from increased homologous recombination and increased DNA damage resistance, to the disruption of the cell cycle and apoptosis. RAD51 has its expression increased in p53-negative cells and since p53 is often mutated in tumor cells RAD51 tends to be overexpressed as well, leading to increased DNA damage resistance and chemotherapy drugs[36]. Although RAD51 is overexpressed in many tumors [37] and increasingly related with p53 function [36], no mutations in the RAD51’s open reading frame have been detected in cancers. RAD51’s increased expression comes from its increased transcription (rather than amplification) and possibly post-translational modifications. RAD51’s expression is cell cycle-regulated, as so, it is lowest in non-growing cells and highest in S/G2 [36].
In spite of its DNA damage repair functions it is also related to increased genomic instability and may, therefore, contribute to carcinogenesis. Therefore a careful and balanced between RAD51 and other repair factors must be maintained in order to avoid deleterious consequences on the cell cycle and cell survival [36].
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Aurora kinases are highly conserved cell division regulators. There are 3 Aurora kinase isoforms: A, B and C; the first 2 have been thoroughly studied and were found to be expressed ubiquitously in mammals, while the third – AURKC - is largely restricted to germ cells [38]. All three Isoforms seem to be overexpressed in many human cancers and their over-expression has been correlated with chromosomal instability and clinically aggressive disease [39].
The Aurora B kinase is a protein (Figure 4) responsible for the attachment of the mitotic spindle to the centromere. The Aurora family of Kinases associates with microtubules during chromosomal segregation and movement. In cancerous cells, its over-expression causes the unequal distribution of genetic information, creating aneuploidy cells - a hallmark of cancer[40]. Substrates identified for the Aurora-A and Aurora-B kinases include p53.
FIGUR E 4-AURKB’S 3D PR OT EIN CONF IGURAT ION
The over-expression of Aurora Kinases in human cancer could indicate that they are involved in errors relating to centrosome duplication, chromosome segregation and
12
cytokinesis [41]. Identifying these mechanisms underlying the development of malignant cells offers the possibility of designing novel therapies[39].
1 . 6 .
H
E L A C E L L SAs the oldest and most widely distributed permanent human cell line, the HeLa cell line is a common inhabitant of laboratories around the world. Ever since their isolation from a young African-American woman’s (Henrietta Lacks although the cells were, for many years, known as Helen Lane or Helen Larson in order to preserve Lacks anonymity) aggressive cervical cancer, more than 50 years ago, it has been used to study almost every process that occurs in human cells [42].
The history of the HeLa cell line is somewhat controversial; they were propagated by George Otto Gey, shortly before Lacks died in 1951. This first human cell line to be cultivated in vitro proved to be invaluable to science. Both the cells and the tools used in the cultivation process were donated by Otto Gey to any scientist who requested them simply for the benefit of science while neither Lacks or her family gave their permission to harvest the cells (although back then there was no requirement to inform a patient about such matters) [43]. The cells were later commercialized although they were never patented in their original form.
Deemed “immortal”, HeLa cells can divide an unlimited number of times, as long as cell survival conditions are met. There are many strains of HeLas as the cells continued to evolve in cultures in labs throughout the world. It is estimated that the total number of HeLa cells that in existence in cell culture far exceeds the total number of cells that were in Herietta Lacks’s body[44].
The first great breakthrough these cells enabled was done by Jonas Salk, to test the first polio vaccine in the 1950’s. Since then, HeLas have been used for research in cancer, AIDS, gene mapping, radiation and toxic substance effects evaluations, and a variety of scientific pursuits [45] and, according to Rebecca Skloot by 2009 “more than
13
60,000 scientific articles had been published about research done on HeLa” and that number is increasing steadily at a rate of more than 300 papers each month [46].
FIGUR E 5-HELA CELL S IN CULTUR E (100X M AGNIF IC ATION)
Due to their unusual proliferation rate even when compared to other cancer cells, these cells are especially used for cancer research [20]. Like many other cancer cells, HeLa cells have an active version of telomerase during cell division [21]. This enzyme prevents the successive shortening of the telomeric region that is implicated in aging and eventual cell death, circumventing the Hayflick limit.
HeLa cells are even more important today than they were 50 years ago. These cell lines are, and will continue to be, the model system for cancer used by most cancer researchers, in spite of their contestable past.
14
1 . 7 .
R N A
I N T E R F E R E N C E( R N A
I)
Establishing a reliable method of knocking-out genes at the RNA level has been the goal of many molecular biologists for the past 15 years
.
Efforts to generate loss-of function in cells or organism using various approaches including anti-sense sequences, ribozymes and oligonucleotides have been tested but the design of such molecules was largely based on trial and error as it depended on the properties of the target gene. Furthermore, the effects were difficult to predict and often only weak suppression of the gene’s expression was achieved.In 1990, two teams of botanists reported the co-suppression of an over-expressed
Chalcone synthase (CHS) in plants. When attempting to create more purple petunias,
they sometimes achieved the opposite result. The mechanism of this phenomenon remained a mystery but soon it was proposed that the products of degradation of the double-stranded RNA region in the CHS gene might be related to this post-transcriptional gene silencing [47]
A study in the fungi Neurospora crassa revealed that an overexpressed transgene can also induce gene silencing at the post-transcriptional level – quelling [Romano and Maciano 1992].
Building on these previous studies, in 1998, Andy Fire of the Carnegie Institute and Craig Mello of the University of Massachusetts demonstrated for the first time that double-strand RNA (dsRNA) may specifically and selectively inhibit gene expression. In their experiment, the sequence of the first strand coincides with the sequence of the target messenger RNA, the second strand (antisense) is complementary to this mRNA. The resulting dsRNA turned out to be far more efficient than the corresponding single stranded molecules (several orders of magnitude). Fire
et al named this phenomenon RNAi. This powerful gene silencing mechanism has been
15
1.7.1.1.
The mechanism
The RNAi mechanism begins when an enzyme (DICER) encounters dsRNA and cuts it into smaller pieces – siRNAs. A complex of proteins rounds up these RNA remains and uses their code as a guide to seek and destroy any RNAs in the cell with a matching sequence such as the target mRNA [48].
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1.7.1.2.
Applications
Since RNAi is very active in several invertebrate species, adapting this technology to mammals would prove invaluable. However, mammalian cells have several protections against viral infections that could hinder the use of RNAi. In 2000, a first attempt was made with dsRNA in mouse embryos. The dsRNA was designed to specifically inhibit 3 genes in the mouse oocyte and hinder the development of the early embryo. Translational arrest was not observed as the embryos continued to develop. However, a year later, the decisive step would be developed by Ribopharma
AG (Germany). It was the first time that RNAi worked within mammalian cells and the
Ribopharma’s Researchers theorized that smaller dsRNA – similar to those produced
by DICER – should not trigger cell death. This proved to be correct. Using short dsRNAs (20/24 bp) they silenced genes even in human cells. Thus RNAi became suitable for gene target validation and therapeutic applications in many species, including humans. From then on siRNAs became the preferred RNAi effector in many laboratories.
RNAi is broadly applicable for gene silencing as demonstrated by its ability to suppress protein biosynthesis in many different mammalian cell lines. Based on this, RNAi has rapidly become a recognized tool for validating (identifying and assigning) gene functions.
1.8.
Objectives
As the initial experimental validation of the co-expression map was promising, namely the few selected cancer related genes that that slowed down the proliferation of HeLa cells, the project for this thesis emerged. The project aimed at further establishing the role of C1ORF112 in the proliferation of cancer cells. Since it could reveal a new target for cancer therapies and/or diagnosis, its main aim was to ascertain if this gene is a good candidate for further experimental and clinical trials. To that end several experiments were designed and conducted to further prove that the
17
significant difference in cell number counts between normal growing HeLa cells and ones that had the gene silenced was directly attributed to C1ORF112’s cellular role.
19
21
2.1.
Starting Cell Culture from frozen Cells
:
Cells were a kind gift from Dr. Roger Barraglough.
Frozen cryovials were placed in a water bath at 37ºC, for 1-2minutes, until defrosted. Slowly, drop by drop, cells were diluted in pre-warmed DMEM in a 15 mL tube and then centrifuged for 5-10 minutes.
The supernatant was removed (as much as possible), making sure the pellet was not touched so as to remain intact. The pellet was then ressuspended in DMEM (10% FBS + 1% Antibiotics) and the entire tube’s content transferred to a 25 cm2 Flask (T25). The flask was then incubate at 37ºC with 5% CO2 for 24 hours, upon which all the
medium was removed and replaced with new medium to ensure no DMSO remained.
2.2.
Maintenance of HeLa cells
A schedule of cell maintenance, feeding and passaging, should be developed to maintain appropriate cell density, nutrient concentration and pH levels in cultures. Cells are best passaged when they are growing logarithmically, at 70 to 80 % confluency. As an example of the schedule used for routine maintenance, every 2 days medium is changed if the confluency is below 40/50% and every day until a 70/80% confluency upon which they are passaged.
2.2.1.
Sub-cultivating
DMEM (complemented with+10% FBS + 1% Pen/Strep) was pre-warmed to 37ºC. The culture was inspected for contamination. If no contamination was present and the cells were at 70-80% confluence the medium was aspirated with a sterile Pasteur pipette and the cells were washed with 5 mL of PBS to remove any residual medium (~15 seconds). After the PBS was aspirated with a sterile Pasteur pipette, 1 mL of 0.05% trypsin-EDTA (TE) was added, evenly dispersed over the surface by gently rocking the flask (after thawing TE was stored at 4ºC for up to 2 weeks so as not to freeze-thaw). The flask was then placed in the incubator with the cap screwed tightly.
22
After 2 minutes the flask was taken to the microscope to check the progress of the detachment.
When the cells were detached, 5 mL of new media was added, rinsing the surface of the flask. To dissociate cell clumps a few “up-and-downs” were performed using a pipette, taking care to minimize foaming, and again the microscope was used to check that cells were dispersed in a single cell suspension and that any clumps would not have more than 5 or 6 cells.
The volume of cell suspension for the desired seeding density was calculated depending on the number of nights before the next passage and the appropriate volume was then added to a new flask with enough media to make 5 mL total. The cells were first mixed with the medium, using a pipette with the flask upright and then, with the cap tightly screwed and the flask laid down, gently swirling to make sure the cells were evenly distributed. The flask was then returned to the incubator.
2.2.2.
Changing medium
Cells were fed with DMEM (10%FBS and 1%Pen/Strep)
The culture was inspected under the microscope to ensure no contamination was present and cells look "normal". The old medium was aspirated from the flask with a sterile Pasteur pipette and 5 mL of new medium was added.
2.3.
Reverse Transfection of HeLa cells (6-well
plates):
Six 1.5 mL Eppendorf tubes (Epp. Tubes) were prepared so as to add to each: 250µL of DMEM (without antibiotics or FBS), 10µL of 20µM siRNA and 5µL of HiPerfect Transfection Reagent. The tubes were then mixed by vortexing and then incubated for 20-45 minutes, at room temperature to allow formation of the transfection complexes. Meanwhile the cells were prepared for reverse transfection. The T25 flasks were washed with 5 mL of PBS and, after aspirating the same PBS the cells were trypsinised (±500µL of trypsin). The cells were then observed under the microscope to make sure
23
all the cells were detached. DMEM (without antibiotics or FBS) was then added to inhibit trypsin reaction (±500µL or in a 1:1 ratio of trypsin:DMEM). The cells were then taken to the Cell Coulter Counter and the appropriate volume to pipette, to obtain 2.5.5x108 cells per well/Eppendorf Tube, was calculated.
After the incubation step, the volume of cell suspension was then added into the Epp. Tubes containing the siRNAs (now called the Transfection Complexes tubes).
6-well plates with 2 mL of DMEM (with 1% FBS and antibiotics) per well, were the prepared and stored in the incubator to be taken out just prior to the rest of the experiment. The contents of each of the Transfection Complexes tubes were then transferred into each of the wells of the 6-well plates, gently swirling the plates to ensure uniform distribution of cells and transfection complexes.
The cells were then incubated under their normal growth conditions and, 24 hours later, inspected under the microscope to see if any phenotype could be distinguished. The media was then changed to DMEM with 10% FBS + 1% antibiotics. Measurements were then taken the following days as appropriate (using the cell Coulter Counter).
2.4.
RNA Extraction
The cells were pelleted in a 15 mL tube. 350 µL of buffer RLT was added (see Qiagen RNeasy handbook page 29 table 6, for volumes of RLT per cell number) and 10 µL of 14.3M βME per 1 mL of RLT, just before the RNA extraction. The mixture was vortexed for 10s and the lysate was passed 5-10 times through an 18-20 gauge needle fitted to an RNase-free syringe. 1 volume of 70% ethanol was added to the lysate. The mix was then shaken vigorously and the sample (including any precipitate) was transferred to an RNeasy micro column.
The tube was then closed and placed on a centrifuge and ran at 3000-5000g for 5 minutes. The flow-through was discarded and 350 µL of Buffer Rw1 was added; another centrifugation followed (15seconds at 8000g) and the flow-through was discarded. 10 µL of DNase was added to 70 µL of Buffer RDD (Incubation Mix). The 80 µL of the Incubation
24 Mix was then added directly to the spin column’s membrane. An incubation of 15 minutes at room temperature then followed.
After the incubation time another 350 µL of Buffer RW1 was added and the spin column was centrifuged at 8000g for 15 seconds. The tube was then discarded and the Mini-elute spin column was put in a new 2 mL collection tube. 500 µL of Buffer RPE (ethanol added according to label) was then added and the sample was centrifuge again for 2 min at 8000g. The flow-through was discarded
500 µL of 80% ethanol was added to the spin column and centrifuged for 2 min at 8000g. After the centrifugation the collection tube was discarded and the spin-column was put on a new 2 mL collection tube. With the lid open, the column was again centrifuged at full speed to dry the membrane. The collection tube was again discarded.
The spin column was placed in new 1.5mL collection tube and 14 mL of RNase free water was added directly to the center of the spin column’s membrane. With the lid closed, a 1 minute centrifugation, at full speed, followed to elute RNA.
2.5.
Quantifying RNA
Nanodrop software was blanked with RNAse free water when requested (1 µL). The water was pipetted into the small dot on the Nanodrop platform. The arm was then lowered and blank button was clicked alongside with the assay selection – RNA40. The concentration (ng/µl) was then recorded, the 260/280 (absorption) ratio and the 230/260 ratio (ratios need to be around 2, otherwise there might have been contamination).
2.6.
cDNA transformation
The components were briefly centrifuged before starting. The following components were mixed in a 0.2mL tube for each RNA-to-cDNA reaction:
• 8 µL of RNA
• 1 µL of Oligo dT [50uM] • 1 µL of dNTPs
25 • 2 µL of DEPC-treated water
(to make a total volume of 10µL)
The mix was then incubated for 5 min at 65ºC in the PCR block. Immediately after the samples were placed on ice for at least 1 minute (possible stopping point). The cDNA synthesis mix was prepared adding, in order:
• 2 µL of 10x RT buffer • 4 µL of [25mM] MgCl2
• 2 µL of [0.1M] DTT; • 1 µL of RNase out; • 1 µL of SuperScript III RT;
• 10 µL of cDNA synth. Mix to each RNA tube
The tube was then gently mixed by flicking and then all the volume collected by briefly centrifugation (20 seconds). Using the PCR block the samples were incubated for 50 minutes at 50ºC and then 5 minutes at 85ºC, after which the samples were put immediately on ice and then centrifuged for 20 seconds. After the spin-down, 1 µL of RNase H was added to each tube and incubated for 20min at 37º (PCR block). The cDNA is now ready for immediate use for downstream experiments or to be stored at -20ºC.
2.7.
qPCR procedures
Serial dilutions were done to test primers and to choose the best concentration of cDNA through a standard curve (qPCR efficiency))
20 µL of cDNA was added to 180 µL of distilled water (dH2O) - dilution 1 (dil.1). A
series of 10 fold dilutions were then done as follows: • 20 µL of (1) into 180 µL of dH2O=(dil.2)
• 20 µL of (2) into 180 µL of dH2O=(dil.3)
• 20 µL of (3) into 180 µL of dH2O=(dil.4)
26
2.7.1.
Diluting primers
Using the provided information (Sigma-Aldrich) the primers were rehydrated (usually to get 100 µM). The working concentration for the primers was found to be 20 µM, therefore they should be mixed as follows (Primer Master Mix):
• 10µL of forward primer (100µM) • 10µL of reverse primer (100µM) • 80µL of dH2O 1 2 3 4 5 6 7 8 9 10 11 12 A (1) BC (1) BC (1) BC (2) BC (2) BC (2) BC (3) BC (3) BC (3) BC (4) BC (4) BC (4) BC B (5) BC (5) BC (5) BC NTC BC NTC BC NTC BC C D (1) R (1) R (1) R (2) R (2) R (2) R (3) R (3) R (3) R (4) R (4) R (4) R E (5) R (5) R (5) R NTC R NTC R NTC R F G H
DIAGR AM 1- REACT ION PL AT E SET U P
In the above diagram, numbers represent the dilution, BC - the gene of interest (although the experiments were aimed at the human homolog of BC055324 – C1ORF112 – it is referred as BC for simplification purposes only), R - the reference gene (in this experiment GADPH), NTC – Non Template Control (dH2O instead of cDNA)
10.5 µL of cDNA was added to each well, as listed on the diagram, pipetted carefully and into the bottom of the plate. Working quickly and on ice (SYBR is light reactive) 12.5 µL SYBR Green was added to 2 µL of Primer Master Mix for each sample summing up to a total of 25 µL of reaction volume. The plate was then tapped to get the qPCR mix to go to the bottom of the plate. A normal plate film was used to cover
27
the reaction plate while briefly vortexing the plate and spinning down in the centrifuge. The film was then changed to optical, taking care not to make the film dirty and then wrapping it in tin foil so as to take it to the real time qPCR machine.
29
31
3.1. In silico
3.1.1.
Bc055324
To this day, very little is known about this gene beyond the tissues were it was found to be expressed (Figure 7[49]).
FIGUR E 7 - NUMB ER OF ARTICL ES SH OWING WERE BC055324 W AS F OUND T O BE OVER(R ED)/U NDER(BLUE)-EXPR ESSED IN MOU SE TISSUES
Through bioinformatic analyses, Bc055324 was found to be co-expressed with many cancer related genes such as Rad51, Ccd6, Ccnb1, Kif20a, Uhrf1 and Aurkb (Table 1 [18]); even the well-known Brca1 and Brca2 are among the 50 strongest co- expressed genes with Bc055324.
TABLE 1-TOP 10 M OST CO-EXPRESSED GENES WITH BC055324
Official Symbol Molecular and biological functions
Ncapg DNA binding, nucleotide and nucleic acid metabolism.
Rad51 ATP binding, DNA binding, protein binding, DNA repair, meiosis, meiotic recombination, response to DNA damage.
Fignl1 ATP binding, hydrolase activity, nucleotide binding.
Cdc6 ATP binding, chromatin binding, nucleotide binding, DNA replication, Cell cycle, cell division, mitosis, signal transduction.
Ccnb1 Cell cycle, cell division, mitosis, regulation of cell cycle, signal transduction.
32 Kif20a ATP binding, microtubule motor activity, nucleotide binding, protein
transport, cell growth and/or maintenance.
Uhrf1 DNA binding, ligase activity, protein binding, DNA repair, cell cycle, cell proliferation, protein modification process, regulation of transcription, response to DNA damage, ubiquitin.
Aurkb ATP binding, kinases activity, nucleotide binding, transferase activity, Cell cycle, cell division, mitosis, signal transduction.
Ercc6l ATP binding, DNA binding, helicase activity, hydrolase activity, nucleotide binding, Cell cycle, cell division, mitosis.
Pole DNA binding, metal ion binding, nucleic acid binding, nucleotide binding, transferase activity, DNA repair, DNA replication, response to DNA damage.
Although there are no functions, processes or known cellular locations associated with Bc055324, functional enrichment analysis revealed that genes co-expressed with Bc055324 are associated with cell cycle, chromosome, DNA replication, nucleus and DNA repair (Table 2 [50]). These results associate Bc055324 with cancer-related pathways and suggest that Bc055324 may play a role in cancer.
TABLE 2-FU NCT IONAL ENR ICHMENT AM ONG GENES C O-EXPR ESSED W ITH BC055324
Enrichment Score per Annotation Cluster GO Function P-value Annotation Cluster 1 Enrichment Score: 60.786
GO:0043232 intracellular non-membrane-bounded organelle GO:0005694 chromosome 1.14E-61 3.35E-61 Annotation Cluster 2 Enrichment Score: 51.759
GO:0022402 cell cycle process
GO:0000279 M phase
GO:0051301 cell division
GO:0007067 mitosis
GO:0000280 nuclear division
GO:0048285 organelle fission
4.41E-68 8.11E-62 6.31E-50 2.32E-44 4.32E-44 2.13E-43
33
Bc055324 is evolutionarily well-conserved; DNA and protein sequences are particularly conserved within mammalians, e.g. Homo sapiens with whom it shares 76.8% homology with its protein and 81.4% with its DNA sequence (Table 3 [51]). The gene tree for Bc055324 shows a high degree of conservation between species with very few exceptions (Figure 8 [49]and Table 2 [50]).
TABLE 3 –PAIRW ISE AL IGNM ENT SCOR ES BETW EEN BC055324’S PROTEIN AND DNA SEQU ENCES AND ITS HOMOL OGS’ SEQ UENCES.
M. musculus –
Bc055324
Identity
Species Gene Symbol Protein DNA
R. norvegicus Loc498265 84.6% 89.8% M. mulatta Loc71646 73.5% 80.8% H. sapiens C1ORF112 73% 81.4% P. troglodytes Loc457501 73% 81.4% B. Taurus C16h1orf112 72.6% 79.2% C. lupus C7h1orf112 70.6% 79.6% G. gallus C8h1orf112 52.6% 61.3%
34
35
3.1.2.
C1ORF112
Like its mouse homolog Bc055324, C1ORF112 is largely unknown. C1ORF112 is evolutionarily conserved in chimpanzee (99.3% identity), dog (87.6%), mouse (81.4%), rat (81.7%), chicken (65.9%), and zebrafish (54.3%). The human tissues that express it are nearly the same that express it in mouse (Figure 9 [49]) and, like its mouse homologue, C1ORF112 is strongly co-expressed with cancer-related genes (such as RAD51, KIF20A, AURKB and CDC6) and also with ATP and DNA binding genes and genes involved in DNA repair, the cell cycle and its regulation. According to the IntoGen database (http://www.intogen.org/), gain in copy number in C1orf112 have been observed in some types of cancer and most significantly in breast cancer (p = 2.98E-6).
FIGUR E 9–NUMBER OF ART ICL ES SHOW ING WER E C1ORF112 W AS FOUND T O BE OVER (R ED)/UND ER-EXPR ESSED (BLUE) IN HUM AN TISSU ES
36
TABLE 4–TOP 10 M OST C O-EXPR ESSED GENES WITH C1ORF112
Using the C1ORF112 as a seed list for the disease geneset analyses (in the GeneFriends [18] co-expression map), about 50% of the cancer genes co-expressed with the mice are also co-expressed in human. The majority of the co-expressed genes are related to cell cycle (Table 4) and signaling functions. Some like CDC25C and E2F1 have been found to be overexpressed in several cancers (Breast, cervical, liver, lung, pancreatic, prostate, skin, stomach, testis, thyroid, etc…[52, 53]) much like C1ORF112 (Table 5)
Interestingly C1ORF112 is highly expressed in embryonic stem cells and fibroblasts, probably due to its relation with cell cycle. More importantly C1ORF112
Official Symbol
RefSeq Status Functions
CKAP2 Validated Cell Growth and/or maintenance CENPJ Reviewed Cell Communication;
Signal Transduction CDC25C Reviewed Cell Communication;
Signal Transduction BUB1 Reviewed Cell Communication;
Signal Transduction
GINS4 Validated Unknown
E2F1 Reviewed Transcription Factor
GTSE1 Reviewed Unknown
PSMC3IP Reviewed DNA Binding
MPHOSPH9 Validated Cell Communication; Signal Transduction;
Unknown RBL1 Reviewed Cell Cycle Regulation
37
itself was found to be overexpressed in many types of cancer, whether from data gather from public gene expression repositories, that analyzed different types of tumors extracted from cancer patients (Table 5 [54]) or from data compiled from more than 20.000 microarray samples of different tissues (Figure 10 [55]).
TABLE 5–NON-EXHAU ST IVE LIST OF CANC ER S OVER EXPR ESSING C1ORF112.
Anatomical Part/Type of Cancer
Tumor details Expression Level (signal value)
Mammary gland Primary Extremely-High (22452)
Dedifferentiated liposarcoma Primary Extremely-High (19661)
Ductal carcinomas Non-smoker, primary, stage 2 grade 3
Very-high (12905)
Activated B-cell like lymphoma Primary, stage II Very-High (12607)
Blastic NK-cell lymphoma primary High (8020)
Hepatocellular carcinoma Primary High (7225)
38
FIGUR E 10-C1ORF112’S EXPRES SION I N B OTH NORMAL (GR EEN) AND CANCER OUS TISSUES (RED).
3.2.
In vitro
Based on all this data and to further validate the connection between C1ORF112 and the cell cycle and possibly even cancer proliferation, C1ORF112 was knocked down in the widely used HeLa cancer cell line using previously validated siRNAs (from Qiagen). The results obtained show that silencing C1ORF112 affects growth of cancer cells (Figure 10).
39
FIGUR E 11–CELL COUNT S FOLLOWING THE EXPOSUR ES T O THE SIRNAS (Positive control= apoptotic mix of siRNAs (in blue); Negative Control=Chlorophyll related siRNAs (in red))
As shown in Figure 11 [55], cells exposed to the RNA’s that silenced C1ORF112’s expression have decreased cell count numbers when compared to the Negative Control (according to the information divulged by Qiagen, these are siRNA’s that should only interfere with chlorophyll related genes). The cells exposed to the C1ORF112 silencing RNA maintain their quantity between the Positive Control (apoptotic mix of siRNA’s) and the Negative Control throughout the entire experiment, proving that silencing C1ORF112 affects growth in cancer cells. This could ultimately mean that this gene has importance in the cell cycle, although it is not clear at which stage.
Real-time PCR was employed to further prove that siRNAs had indeed silenced C1ORF112’s expression (Figure 12) and that the phenotypical changes observed were, therefore, a direct response to the silencing.
40 These experiments serve therefore as further support to the initial predictions of the Co-expression map “GeneFriends”, that this gene plays an important role in cancer development.
FIGUR E 12 –REAL-TIME PCR R ESULTS SH OWING A 60% D ECREASE IN C1ORF112’S EXPR ESSION AF TER SIRNA SIL ENCING.
42
44 The work presented in this thesis represents the first step towards understanding the role of C1ORF112, specifically within the cell cycle.
The bioinformatics analysis points to both Bc055324 and its human counterpart C1ORF112 having a role in cancer development. This is highlighted by BC055324’s dehydrogenase activity, which implies it is involved in metabolic pathways whose disruption may result or help cancer development.
The limited data available on both genes makes it difficult to quantify its role in cancer proliferation, however given the genes that are co-expressed with C1ORF112 the hypothesis behind this thesis was that C1ORF112 is important in cell cycle progression and that, in this context, it might be crucial for cancer cells’ proliferation.
C1ORF112 is expressed in both normal tissue and cancer tissue but it is overexpressed in cancerous tissue, particularly in breast, colon and testicular cancer (Figure 10). Although it is shown that C1ORF112 is important for cell growth in cancer lines, it is still unknown whether C1ORF112 may be specifically necessary for the proliferation of cancer cells versus. normal cells. Even though it is likely that these siRNA’s are having an impact on cell cycle progression, it cannot be ruled out these siRNA’s are having some apoptotic effects as well.
However, several other experiments should provide further insights into C1ORF112’s cellular role. For starters assaying the cell cycle through FACs could show whether or not the gene is having an effect in the cell cycle and where its being affected, laying to rest (or not) the idea that it might actually cause cells to enter apoptosis (which could also be verified through apoptotic assays).
The next step could include similar experiments in non-cancerous cells to evaluate the effects of silencing this gene in normal human cell lines, as well as, other cancer cell lines.
45
Still in vitro more stable/permanent silencing could be obtained by using shRNAs, that would no doubt confirm the results obtained with siRNA, but also allow to do several cell cycle assays using DNA damaging agents to ascertain how the silenced cells react by comparison with non-silenced cells (again both in cancerous cell lines and non-cancerous). Since recently Sigma-Aldrich has developed an antibody for C1ORF112 (which would still be validated), a western blot could be used to confirm the results obtained through qPCR, as well as, immunohistochemical assays in cells, tissues and, more importantly, in clinical samples, to further understand C1ORF112’s part in cancer molecular pathways.
In vivo, mouse knockouts should also provide interesting insights into C1ORF112’s
function.
Notwithstanding, the results obtained show that C1ORF112 is functional and has a role in the growth of cancer cells. In this context, unraveling C1ORF112’s function might prove it a worthy candidate for clinical trials and an attractive target for future cancer diagnosis and or therapies.
46
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