Clusters of CDK2, CCND1, and CMYC genes involved in cancers: acute lymphocytic leukemia (ALL) as a modelq.
Acute Lymphoblastic Leukemia (ALL) is one of the most frequent types of cancer that afflicts children. It is characterized by accumulation of immature lymphocyte progenitor cells in the bone marrow. Although current long term survival rate in children is above 80%, this disease is not completely curable with the available treatment strategies (Crazzolara and Bendall 2009). A better understanding of the underlying mechanisms behind ALL requires information about the changes that occur during cell cycle and the genes that are involved in the process. Our earlier studies on leukemia in children determined the role of susceptibility biomarkers and risk factors (Reddy et al. 2006; Reddy and Jamil 2006; Jamil and Reddy 2007), further we also determined the SNP changes in drug metabolizing genes like GSTs and FLT3 which relate to drug-gene interactions (Reddy et al. 2006, Kumar et al. 2011), the signaling pathways and biomarkers of hematological malignancies were also determined (Mani et al. 2006, 2007). Cell division in organisms is regulated by a family of cyclin dependent kinases (CDKs), which consist of a subunit of CDK and an activating cyclin subunit. These CDK complexes phosphorylate several substrates such as the Retinoblastoma family of proteins, which are negative regulators of cell cycle. The inactivation of these CDKs is also part of the typical cell cycle process. The inhibitors of CDK such as p16Ink4a, p15Ink4b, p27Kip1, and p21Cip1 negatively regulate CDK activities (D'Andrilli et al. 2004). The cell cycle process is regulated by the tumor suppressor gene, p53. Several other genes and proteins are also involved in the normal cell cycle process. Several studies have been carried out to determine the changes in the cell cycle that lead to leukemogenesis. Homozygous inactivation of p16 INK4 gene has been reported in childhood ALL by several researchers (Okuda et al. 1995; Lemos et al. 2003). Aberrant p15 promoter methylation (Batova et al. 1997) and deletion of p15 (Okuda et al. 1995) have been reported in several cases of childhood ALL. A study based on a population of Chinese children has implicated polymorphism of cyclin D1 (CCND1) in relation to occurrence of ALL (Hou et al. 2005). Several studies have reported deletion of p27/Kip1 gene in childhood ALL (Markaki et al. 2006; Takeuchi et al. 2006). CDK2 catalytic activity was reported in a sample of childhood ALL samples using in vitro kinase assays (Schmitz et al. 2005). Studies on Notch-1 regulatory mechanisms have suggested that c-Myc deregulation may be part of the early events in T-cell leukemogenesis (Palomero et al. 2006; Weng et al. 2006). Overexpression of MDM2 has been reported in 15-25% of ALL patients at the time of diagnosis (Hendy et al. 2009). Tumor suppressor gene, Tp53, mutations have been reported in some children with ALL, though it is more frequently associated with relapse patients (Kawamura et al. 1995).
In the present study, sequences of selected genes involved in the cell cycle pathway were selected to infer phylogeny as well as to determine their homology across various species in the animal kingdom to better understand how these genes contribute to leukemogenesis. Although the same cell cycle genes exist in various organisms across the animal kingdom, but they function differently in different organisms, while in humans when these genes develop mutations leukemogenesis occurs. A study of this nature might help in better understanding leukemogenic pathway in humans.
Materials and Methods
(a) Search for cell cycle genes in ALL
Literature databases were queried to devise a list of genes which are involved in cell cycle and have been reported in association with ALL (Table 1). Further information about each of the genes in the list was obtained by querying GeneCards database version 3 (Safran et al. 2010) (www.genecards.org).
Table 1: Cell cycle genes associated with Acute Lymphoblastic Leukemia. S.No. Gene Name Function Reference 1 p53 regulates target genes Wojcik et al. that induce cell cycle 2005 arrest 2 p16 INK 4A Capable of inducing Lemos et al. (CDKN2A) cell cycle arrest in 2003 G1 and G2 phases. 3 p15 (CDKN2B) Encodes a protein that Iravani et al. functions as a cell 1997 growth regulator that controls cell cycle G1 progression 4 Cyclin D1 Essential for the Hou et al. 2005; (CCND1) control of the cell Aref et al. cycle at the G1/S 2006 (start) transition 5 c-MYB play a critical role Clappier et al. in regulating the 2007 G(1)/S cell cycle transition 6 CDK2 involved in the Schmitz et al. control of the cell 2005 cycle 7 CDKN 1B (p27, Important regulator of Markaki et al. Kip1) cell cycle 2006 progression 8 CDK6 Probably involved in Chilosi et al. the control of the 1998 cell cycle 9 CDKN 1A (p21, functions as a Roman-Gomez et Cip1) regulator of cell al. 2002 cycle progression at G1 10 CCND2 Essential for the Clappier et al. control of the cell 2006 cycle at the G1/S (start) transition 11 ABL1 Regulates cytoskeleton Chiaretti et al. remodeling during cell 2007 differentiation, cell division and cell adhesion. 12 CCND3 Essential for the Sicinska et al. control of the cell 2003 cycle at the G1/S (start) transition. 13 CDKN 1C (p57, Negative regulator of Gutierrez et al. Kip2) cell proliferation. 2005 May play a role in maintenance of the non-proliferative state throughout life 14 c-MYC plays a role in cell Weng et al. cycle progression, 2006 apoptosis and cellular transformation 15 Rb1 key regulator of entry Schmitz et al. into cell division 2005; Tsai et that acts as a tumor al. 1996 suppressor 16 MDM2 affects the cell Hendy et al. cycle, apoptosis, and 2009; Zhou et tumorigenesis through al. 2003 interactions with other proteins 17 ATM important cell cycle Gumy et al. checkpoint kinase 2003 S.No. GeneCards ID 1 GC17M007565 2 GC09M021957 3 GC09M021992 4 GC11P069455 5 GC06P135544 6 GC12P056360 7 GC12P012768 8 GC07M092234 9 GC06P036645 10 GC12P004382 11 GC09P133589 12 GC06M041949 13 GC11M002861 14 GC08P128748 15 GC13P048877 16 GC12P069201 17 GC11P108127
(b) DNA sequence data and sequence alignment
Three genes were selected for the study from the list of cell cycle genes. NCBI GenBank database (Benson et al. 2011) (at www.ncbi.nlm.nih.gov/) was queried to retrieve all available nucleotide sequences, across various species, of the mRNA transcript of the genes. These sequences were saved as fasta file and were used for further analysis. The sequences were first imported into the alignment explorer of MEGA version 4 software (Tamura et al. 2007). An initial multiple sequence alignment was carried out using the Clustal W (Thompson et al. 1994) algorithm. The aligned sequences were further manually edited and again aligned using Clustal W with default parameters for Gap Opening, Gap Extension Penalty and DNA weight matrix to obtain optimal global sequence alignment. This multiple sequence alignment file was then used to infer phylogeny.
(c) Phylogenetic tree construction
Phylogeny was reconstructed using MEGA version 4.0. The distance based Neighbour-Joining (Saitou and Nei 1987) method was chosen for phylogeny reconstruction of the sequences. Kimura 2-parameter (Kimura 1980) distance model, which assumes uniform rate of substitution among sites, was selected as the nucleotide substitution model. To further increase the reliability of the phylogenetic tree obtained, 1000 Bootstrap replications were performed.
(d) Functional divergence
Functional divergence is useful in identifying sites/residues that are subjected to functional constraints during evolution. In this study, functional divergence between the various species for each gene was calculated using Diverge 1.04 software (Gu and Velden 1999). Sequences of the corresponding proteins encoded by the genes were aligned using Clustal W in MEGA software using default parameters and this alignment was used as input for the software. Using this input, the software was used to build a Kimura 2 parameter tree to delineate clusters. These clusters were then used to estimate statistical parameters such as site specific profile, which is useful to predict the amino acid residues which are vital for functional divergence. Residues estimated to have a functional divergence value greater than 0.1 were highlighted in the sequence alignment.
(i) Phylogenetic analysis
From the genes listed in Table 1 we selected three genes CDK2 (606 bp), CCND1 (526 bp) and c-MYC (509 bp) genes and determined their phylogeny after multiple sequence alignment.
From Genbank database we obtained sequences of seventeen species, which were used in the construction of phylogenetic unrooted tree for CDK2 (Figure 1), which could be grouped in five clusters, one cluster with humans and other Mammals, an isolated cluster of Red Jungle Fowl, one cluster with different species of Fish, a cluster of Amphibians, a final cluster consisting of other organisms. Information about the gene was obtained from GeneCards database (GCid: GC12P056360).
Analyzing the phylogenetic tree constructed using sequences of cyclin D1 from thirteen species revealed four clusters-a cluster consisting of humans and few other Mammals, an isolated cluster of Red Jungle Fowl, a cluster with two species of Amphibians and a cluster of Fish (Figure 2). Information about the gene was accessed from GeneCards database by querying with GCid: GC11P069455.
Sequences from seventeen species were used to infer phylogeny resulting in five clusters, a cluster of ten Mammalian species, a single isolated cluster of Red Jungle Fowl, a single cluster of Amphibians, a cluster consisting of Fish and a cluster with a species of hemichordate and Atlantic salmon (Figure 3). Information about the gene was accessed from GeneCards database (GCid: GC08P128748).
(ii) Functional divergence
We used Diverge 1.04 to calculate the functional divergence of CDK2, CCND1 and c-MYC genes. In our analysis, CDK2 and CCND1 genes showed no significant functional divergence. This result could probably indicate that these two genes are highly conserved, especially in Mammalian species.For the functional divergence analysis, the c-MYC gene was designated into two clusters-the first cluster is composed of species other than Mammals and the second cluster contained all the Mammalian species. The coefficient of functional divergence between these two clusters was 0.41. We found 317 residues to have a posterior probability greater than 0.1.These residues showed a higher degree of variability in species belonging to cluster one than cluster two (Figure 4).
Loss of cell cycle regulation through changes in cell cycle gene in the bone marrow is a common cause for the progress of tumorigenesis process. ALL is a serious pediatric malignancy, exhibiting both normal and proliferative controls and blocking differentiation into functional cells. In ALL mostly cells reside in the G-1 phase, and only a few cells proceed to the next G0 phase. In normal cells during cell cycle progression early G1 cells respond to environmental stimuli inducing differentiation. However, in disease condition the cells do not respond or do not recognize the signals and no longer respond to differentiation process. It has been reported that cyclin dependent kinase CDK2 was active in ALL and contributed to the disease condition. The catalytic activity of CDK2 was reported to increase in childhood leukemia (Schmitz et al. 2005). Further it was suggested by these authors that CDK2 contributed to the functional inactivation of Retinoblastoma gene (Rb). In
Cyclin D1 is an important cell cycle regulatory protein, which is involved in the transition of cell cycle from G1 phase to S phase during the process of cell division. Change in cell cycle kinetics and acceleration of G1 phase, which might lead to abnormal cell proliferation, has been associated with overexpression of this protein (Pabalan et al. 2008). During early G1 phase, Cyclin D1 binds to and activates CDK4 and CDK6 kinases, which leads to phosphorylation of Retinoblastoma protein, thus contributing to its inactivation. Studies have reported overexpression of cyclin D1 in patients with ALL and have suggested that cyclin D1 may play a role in mobilization of blast cell from the Bone Marrow to lymph nodes (Aref et al. 2006). These reports indicate that CCND1 could serve as a prognostic marker in the detection of ALL and hence needs to be investigated in more detail to elicit information regarding its role in tumorigenesis. The c-Myc proto-oncogene encodes a transcription factor that is essential for cell growth and proliferation. It has also been reported in the control of DNA replication. It dimerizes with a protein called Max, to bind Enhancer Box sequences (E-boxes) and recruits view of the above findings it was important to determine the role of CDK2. histone acetyltransferases for regulation of gene expression. The c-Myc proto-oncogene is involved in transformation and cell proliferation partly through activation of cyclin D2 promoter and also induces programmed cell death which is mediated by nuclear respiratory factor 1 (NRF-1) and the Arf-p53 pathway (Luo et al.. 2005). In normal cells, c-MYC regulation is induced and regulated by mitogenic stimulation. In the absence of this induction, the cells revert back to the non-proliferative state. Studies suggest that in cancer cells, there is an absence of stringency in regulation attributed to mutations in the regulation of Myc genes and the persistent induction of Myc expression through oncogenic signals that lie upstream such as Wnt/[beta]-catenin, Notch or RTK/Ras pathways (Sodir and Evan 2009). Translocations t(8;14), t(8;22), and t(2;8) involving MYC deregulation have been reported in 2%-5% of childhood ALL along with reports of aberrant c-Myc stability in cell lines and bone marrow samples in pediatric patients. Studies have reported that MYC is a direct transcriptional target of oncogenic Notch1, which is common in T-ALL. These studies indicate the need to delve further into the exact correlation between c-MYC and leukemogenesis (Delgado and Leon 2010).
Phylogenetic studies play an essential role in understanding evolutionary history of genes and their impact on disease etiology. Several studies have calculated the functional divergence of genes based on phylogenetic reconstruction across various species and further implicate those sites which are subjected to functional constraints during evolution (Khan and Jamil 2008; Khan and Jamil 2010). Further, this information could be used to observe drug-gene interactions with the help of homology modeling and affinity modeling studies (Kotra et al. 2008). Our earlier studies on phylogeny of p53 and MDM2 revealed that these genes show a high degree of sequence similarity in Mammals, suggesting parallel carcinogenesis pathways involving these genes in the Mammalian species (Jayaraman et al. 2011).
Studies based on evidence from paleontology and genetics suggest that mechanisms of cancer are embedded deeply throughout evolution. Understanding the phylogenetic evolution of these genes could help in furthering our knowledge on the mechanisms involved in cancer (Davies and Lineweaver 2011).
In the present study, we applied bioinformatics approaches to mine databases to garner information regarding the CDK2, CCND1 and c-MYC cell cycle genes and their role in ALL. We inferred phylogeny of these genes across various species, for which sequence information is available in the databases. Analysis of the sequence alignments indicates that throughout the mammalian species, these genes are mostly similar/exhibit sequence homology and thus group under a single cluster. Though the avian species, the amphibians and the some species of fish tend to form three separate clusters due to the variation in their sequences, there appears to be a moderate degree of sequence similarity with those of mammalian species.
In our study of the phylogenetic analysis and tree constructed using sequences of these three genes, we observed that these gene sequences are more or less similar across these few taxa, this might indicate the presence of cancer like disease genes in the evolutionary history of these species.
In the future, when the sequence information for these genes across a wide range of taxa becomes available, a more intensive phylogenetic analysis would be possible which could help in delving further into the changes and the mechanisms of change through which these genes contribute to the evolution of leukemogenesis process and also assist in designing effective therapeutic measures.
Correlation between CDK2, CCND1, c-MYC CDK2, cyclin D1 and c-MYC genes are important components in the cell cycle pathway. Alterations in these genes have been reported in association with malignant transformations. Studies have reported that c-MYC gene might be involved stimulating the activity of cyclin E/CDK2 complex. The phosphorylation of MYC by CDK2 is helpful in suppression of senescence (Hydbring and Larsson 2010). c-MYC gene has also been reported to regulate the expression of cyclin D1 at an early stage of the cell cycle process. Cyclin D1-CDK2 complex might indirectly promote cell proliferation by sequestering p21 and p27 genes this complex has been detected previously in breast cancer cell lines and was reported to exhibit several features of transformation (Chytil et al. 2004). These studies indicated that the three genes functionally interact with each other and play a role in direct/indirect regulation of the other genes. It is essential to better understand the association between these genes because their interaction might be a significant aspect in the tumorigenesis process.
Conflict of Interests
Authors have no conflicting interests.
We are grateful to Jawaharlal Nehru Institute of Advanced Studies (JNIAS) for the facilities provided.
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A Jayaraman, K Jamil*
Centre for Biotechnology and Bioinformatics, School of Life Sciences, Jawaharlal Nehru Institute of Advanced Studies, 6th Floor, Budha Bhawan, Secunderabad, AP, India.
*Corresponding Author: firstname.lastname@example.org
Table 2: Sequence details of CDK2. S.No. Organism Common Name R Number (Nucleotide) Cluster 1 1 Homo sapiens Human X62071 2 Bostaurus Cattle BT020790 3 Cricetulusgriseus Chinese AJ223949 Hamster 4 Rattusnorvegicus Norway Rat NM_199501 5 Musmusculus House Mouse NM_183417 6 Ovisaries Sheep NM_001142509 7 Mesocricetusauratus Golden D17350 Hamster 8 Capra hircus Goat EF035041 Cluster 2 9 Gallus gallus Red Jungle NM_001199857 Fowl Cluster 3 10 Xenopuslaevis African NM_001090651 Clawed Frog 11 Xenopus (Silurana) Western NM_001008135 tropicalis Clawed Frog Cluster 4 12 Daniorerio Zebrafish NM_213406 13 Salmosalar Atlantic NM_001141734 Salmon Cluster 5 14 Sphaerechinusgranularis Purple Sea AJ224917 Urchin 15 Patiriapectinifera Starfish AB481376 16 Nasoniavitripennis Jewel Wasp NM_001161462 17 Paramecium tetraurelia Paramecium AF126147 S.No. Accession Number (Protein) 1 CAA43985 2 AAX08807 3 CAA11680 4 NP_955795 5 NP_904326 6 NP_001135981 7 BAA04165 8 ABK34941 9 NP_001186786 10 NP_001084120 11 NP_001008136 12 NP_998571 13 NP_001135206 14 CAA12223 15 BAH97197 16 NP_001154934 17 AAD34354 Table 3: Sequence details of CCND1. S.No. Organism Common Name Accession Number (Nucleotide) Cluster 1 1 Homo sapiens Human NM 053056 2 Musmusculus House Mouse S78355 3 Rattusnorvegicus Norway Rat X75207 4 Cricetulusgriseus Chinese Hamster EF524275 5 Pongoabelii Sumatran NM_001131301 Orangutan 6 Bostaurus Cattle BC112798 7 Rattusrattus Black Rat D14014 8 Canis lupus Dog NM_001005757 familiaris Cluster 2 9 Gallus gallus Red Jungle Fowl U40844 Cluster 3 10 Xenopuslaevis African Clawed X89475 Frog 11 Xenopus (Silurana) Western Clawed NM_001005452 tropicalis Frog Cluster 4 12 Daniorerio Zebrafish AF365874 13 Salmosalar Atlantic Salmon NM_001165391 S.No. Accession Number (Protein) 1 NP 444284 2 AAB34495 3 CAA53020 4 ABP73256 5 NP_001124773 6 AAI12799 7 BAA03115 8 NP_001005757 9 AAA83271 10 CAA61664 11 NP_001005452 12 AAM00355 13 NP_001158863 Table 4: Sequence details of cMYC. S.No. Organism Common Name Accession Number(Nucleotide) Cluster 1 1 Homo sapiens Human V00568 2 Canis lupus familiaris Dog X95367 3 Ovisaries Sheep Z68501 4 Musmusculus House Mouse NM_010849 5 Rattusnorvegicus Norway Rat NM_012603 6 Feliscatus Domestic Cat NM_001173446 7 Susscrofa Pig FJ882404 8 Macacamulatta Rhesus Monkey NM_001142873 9 Bostaurus Cattle NM_001046074 10 Pan troglodytes Chimpanzee NM_001142794 Cluster 2 11 Gallus gallus Red Jungle Fowl NM_001030952 Cluster 3 12 Xenopuslaevis African Clawed X14806 Frog Cluster 4 13 Takifugurubripes Tiger Puffer AB236413 14 Oncorhynchusmykiss Rainbow Trout AJ627208 15 Ictaluruspunctatus Channel Catfish AF283994 Cluster 5 16 Saccoglossuskowalevskii Acorn Worm NM_001164972 17 Salmosalar Atlantic Salmon NM_001173816 S.No. Accession Number (Protein) 1 CAA23831 2 CAA64654 3 CAA92814 4 NP_034979 5 NP_036735 6 NP_001166917 7 ACQ76904 8 NP_001136345 9 NP_001039539 10 NP_001136266 11 NP_001026123 12 CAA32911 13 BAE45315 14 CAF25507 15 AF283994 16 NP_001158444 17 NP_001167287
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|Date:||Jan 1, 2012|
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