- Open Access
Involvement of GTA protein NC2β in Neuroblastoma pathogenesis suggests that it physiologically participates in the regulation of cell proliferation
- Cinzia Di Pietro1,
- Marco Ragusa1,
- Davide Barbagallo1,
- Laura R Duro1,
- Maria R Guglielmino1,
- Alessandra Majorana1,
- Veronica Giunta1,
- Antonella Rapisarda1,
- Elisa Tricarichi1,
- Marco Miceli1,
- Rosario Angelica1,
- Agata Grillo2,
- Barbara Banelli3,
- Isabella Defferari4,
- Stefano Forte1,
- Alessandro Laganà1,
- Camillo Bosco1,
- Rosalba Giugno5,
- Alfredo Pulvirenti5,
- Alfredo Ferro1,
- Karl H Grzeschik6,
- Andrea Di Cataldo7,
- Gian P Tonini4,
- Massimo Romani3 and
- Michele Purrello1Email author
© Di Pietro et al; licensee BioMed Central Ltd. 2008
Received: 15 February 2008
Accepted: 06 June 2008
Published: 06 June 2008
The General Transcription Apparatus (GTA) comprises more than one hundred proteins, including RNA Polymerases, GTFs, TAFs, Mediator, and cofactors such as heterodimeric NC2. This complexity contrasts with the simple mechanical role that these proteins are believed to perform and suggests a still uncharacterized participation to important biological functions, such as the control of cell proliferation.
To verify our hypothesis, we analyzed the involvement in Neuroblastoma (NB) pathogenesis of GTA genes localized at 1p, one of NB critical regions: through RT-PCR of fifty eight NB biopsies, we demonstrated the statistically significant reduction of the mRNA for NC2β (localized at 1p22.1) in 74% of samples (p = 0.0039). Transcripts from TAF13 and TAF12 (mapping at 1p13.3 and 1p35.3, respectively) were also reduced, whereas we didn't detect any quantitative alteration of the mRNAs from GTF2B and NC2α (localized at 1p22-p21 and 11q13.3, respectively). We confirmed these data by comparing tumour and constitutional DNA: most NB samples with diminished levels of NC2β mRNA had also genomic deletions at the corresponding locus.
Our data show that NC2β is specifically involved in NB pathogenesis and may be considered a new NB biomarker: accordingly, we suggest that NC2β, and possibly other GTA members, are physiologically involved in the control of cell proliferation. Finally, our studies unearth complex selective mechanisms within NB cells.
Transcription initiation, the most important and regulated event along the pathway connecting genotype to phenotype, is governed by the General Transcription Apparatus (GTA): GTA proteins constitute the PreInitiation Complex (PIC) and guide its assembly [1–3]. Class II PIC, larger than 2 MDa, comprises more than fifty different polypeptides, including RNA polymerase II, GTFs, Mediator [4–6]. GTF2D consists of the TATA Box – Binding Protein (TBP) and TBP – Associated Factors (TAFs), a group of evolutionarily conserved proteins that participate in determining the state of chromatin, contribute to promoter recognition, serve as coactivators, and post-translationally modify other GTA proteins to facilitate PIC assembly and transcription initiation [1, 5]. Its DNA binding activity is regulated by positive and negative cofactors such as heterodimeric NC2 (also named Dr1/Drap 1), comprised of α- and β-type subunits [7, 8]. The molecular actions of GTA proteins were clarified through an extensive series of studies [1–3, 6, 9]. On the other hand, only scanty success was obtained in identifying their biological functions as well as in verifying their involvement in genetic pathology, including tumorigenesis [10, 11]. We examined the involvement of GTA proteins in the pathogenesis of Neuroblastoma (NB), exploiting our data and those from the literature on the genomics of GTA (see Additional file 1; reviewed in ref. ) to perform the positional and functional gene candidate approach. NB is a group of early childhood tumours with a complex molecular pathogenesis [13, 14]. It is generally believed that the abnormally proliferating cell in all types of NB is the neuroblast, a fleeting stem cell that transiently appears during the early stages of mammalian development . NB clinical phenotype is remarkably heterogeneous, ranging from spontaneous regression to restless progression [14, 16]. This variability is associated to a high genetic heterogeneity. The most important genomic alterations in NB are interstitial deletions at 1p, 11q, 17q, and MYCN amplification [14, 17]. NB molecular phenotype is characterized by the altered expression of a plethora of genes belonging to different Gene Ontology categories: all of them are potential NB biomarkers [14, 18]. Our analysis was initially focused on human chromosome 1 short arm, where one or more NB master genes are thought to reside [17, 19]. In this region, we had previously mapped the genes encoding TAF13, GTF2B, NC2β, TAF12 to 1p13.3, 1p21-p22, 1p22.1, 1p35.3, respectively [20–22].
NB patients were 30 males and 28 females. Tumour primary site was adrenal in 33 patients, abdominal nonadrenal in 18, thoracic in 5, cervical in 2. Tumours were classified according to the International Neuroblastoma Pathology Classification (INPC) . The final pathologic diagnosis fulfilled the International Criteria for Neuroblastoma Diagnosis . Patients were staged according to the International Neuroblastoma Staging System: 12 patients were at stage I, 8 at stage II, 6 at stage III, 23 at stage IV, and 9 at stage IVS. The clinical and molecular characteristics of the patients are reported (see Additional file 2).
Expression of TAF13, GTF2B, NC2α, TAF12, NC2β
Primers and RT-PCR conditions for expression analysis
NC2β fw: 5' CGATGATGATCTCACTATCC 3'
NC2β rev: 5' GTTGCTGTCTAGCTTTTGC 3'
50°C 30 min; (94°C 60 sec, 47°C 90 sec, 72°C 2 min) 25×; 72°C 10 min.
NC2α fw: 5' AGACGGACGAAGAGATTGG 3'
NC2α rev: 5' CATGTCGGGAACAGATGC 3'
50°C 30 min; (94°C 60 sec, 53°C 90 sec, 72°C 2 min) 27×; 72°C 10 min.
GTF2B fw: 5' AGAAGAGCCTGAAGGGAAGAGC 3'
GTF2B rev: 5' CAGCAACACCAGCAATATCTCC 3'
50°C 30 min; (94°C 60 sec, 50°C 90 sec, 72°C 2 min) 27×; 72°C 10 min.
TAF12 fw: 5' GAGCAGTTGGATGAAGATGTGG 3'
TAF12 rev: 5' TGAGATGGCAGGGAAAAGG 3'
50°C 30 min; (94°C 60 sec, 57°C 90 sec, 72°C 2 min) 26×; 72°C 10 min.
TAF13 fw: 5' GCAGATGAGGAAGAAGACC 3'
TAF13 rev: 5' TATCTTCAACTTGTACTCGACC 3'
50°C 30 min; (94°C 60 sec, 54°C 90 sec, 72°C 2 min) 27×; 72°C 10 min.
β actin fw: 5' GTGCCCATCTATGAGGGTTACG 3'
β actin rev: 5' TGATCCACATCTGCTGGAAGG 3'
50°C 30 min; (94°C 60 sec, 46°C 90 sec, 72°C 2 min) 25×; 72°C 10 min.
Genomics of TAF13, NC2β, TAF12 in NB samples
Microsatellite polymorphic markers used for GI analysis
92982656 – 92982869
5' AATGCCTGTCTTTATCCCTG 3'
5' AATGTAAGAGAAATGCCCCT 3'
196 – 212
95°C 10 min (95°C 30 sec, 52°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min
95036107 – 95036299
5' CTTTTGACTCACTGGAAGACAT 3'
5' CCCCACCGTATCTGGTAT 3'
185 – 205
95°C 10 min (95°C 30 sec, 55°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min
95718483 – 95718723
5' CAGCCCACAGAATAACACTG 3'
5' TTCATGCTATGATTTTCCGC 3'
202 – 254
95°C 10 min (95°C 30 sec, 54°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min
27999563 – 27999728
5' TTTAACCCTGGAAGGTTGAG 3'
5' ACAGGACAATGCTGTCAGTATG 3'
137 – 167
95°C 10 min (95°C 30 sec, 52°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min
30205319 – 30205625
5' AGCTGAGTCAGGGAAACCCATT 3'
5' TGTGCTCTTCAATGTGTTAGGGA 3'
307 – 340
95°C 10 min (95°C 30 sec, 56°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min
108849441 – 108849609
5' CACAGTTAAATTGCATTTCC 3'
5' GCTCACCATAAACAAGAGG 3'
161 – 173
95°C 10 min (95°C 30 sec, 50°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min
110103235 – 110103467
5' CCTACAACTCCATCCTGTCC 3'
5' GTCTTAAGTCGCTCTGCCTG 3'
215 – 225
95°C 10 min (95°C 30 sec, 56°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min
67069719 – 67069901
5' AGCTGGACTCTCACAGAATG 3'
183 – 207
95°C 10 min (95°C 30 sec, 60°C 30 sec, 72°C 30 sec) 30×; 72°C 10 min
67945684 – 67945935
5' CAGGCCCAGTCTCTTG 3'
5' CGTGTCCAGATGAAAGTG 3'
237 – 260
95°C 10 min (95°C 30 sec, 52°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min.
82130207 – 82130465
5' AGCTCTGTGACATTGGATAA 3'
5' CAGAACATAATAAGTGTGGCTA 3'
257 – 263
95°C 10 min (95°C 30 sec, 53°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min.
82540746 – 82540872
5' TGTTAGTTCCTGTTCTTGGTGA 3'
5' TTCCCTGGAAACAACCATAA 3'
155 – 163
95°C 10 min (95°C 30 sec, 58°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min
91331437 – 91331556
5' GGCCACATGGGAATTTTCT 3'
5' AGCAGTTCAAGGCCACAGT 3'
157 – 177
95°C 10 min (95°C 30 sec, 55°C 75 sec, 72°C 30 sec) 30×; 72°C 10 min
The location of CpG islands in the bone fide promoter regions of NC2β, TAF12 and TAF13 was determined with the CpGPLOT software , after masking the repeated sequences with Repeat Masker . The NB samples and cell lines analyzed are listed in Additional file 3. Quantitative methylation analysis was performed by pyrosequencing with a SPQ 96MA instrument (Biotage, Uppsala, Sweden) . Pyrosequencing is a sequencing by synthesis-analysis of short genomic sequences that is ideally suited for SNP analysis. In this respect, DNA methylation can be considered a special case of polymorphism revealed by the bisulfite chemical reaction that converts only the unmethylated Cs into Ts . 2 μl of bisulfite modified DNA were amplified with primers designed with the Assay Design Software for Pyrosequencing (Biotage, Uppsala, Sweden) to amplify target sequences independently of their methylation status. The amplified targets were then subjected to pyrosequencing analysis. Primers sequences were: NC2βF: gtttttgtgaaggaatggga; NC2βR: tcaaatttccccctccct (amplicon size: 153 bp, Ta 58°C); TAF12F: aagagtaagttgtagggtgtattt; TAF12R: acaaaaactaccccaataaaa (amplicon size: 214 bp, Ta 58°C); TAF13F: ggtttttttttttagagattgt; TAF13R: aaaatcttcttcctcatctactacca (amplicon size: 208 bp, Ta 58.5°C). Sequencing reactions were performed with the Pyro Gold reagent kit SPQ 96MA according to the manufacturer instructions (Biotage, Uppsala, Sweden).
We correlated our data by using an A-Priori data mining algorithm for tables with Unknown Values corresponding to missing data . Let T (A1, A2, ..., Ak) be a table with attributes (columns) A1, A2, ..., Ak. Each column Ai is a predicate (truth-value function) that assigns to every row r (experiment) one of the three values: True, False, Unknown. This means that Ai(r) = True/False/Unknown indicates that Ai holds/does not hold/is unknown in the experiment r. For example, rows may be NB samples and columns may be RT-PCR or GI data. In this case, Ai(r) = True (resp. False, resp. Unknown) may indicate that gene Ai is overexpressed (resp. is not overexpressed, resp. could not be unambiguously assigned a value) in sample r. Datamining searches for highly related facts that constitute a frequent itemset. Any datamining algorithm tries to construct the collection Lj of all frequent itemsets S of size j.
(frequent itemset). Given a positive threshold t, a frequent itemset S of size j includes j columns Ai1, Ai2, ..., Aij such that the ratio [Number of rows r in which (Ai1(r) AND*Ai2(r) AND* ... AND* Aij(r)) = True]/[Number of rows r in which (Ai1(r) AND* Ai2(r) AND* ... AND* Aij(r)) ≠ UNKNOWN] > t.
The commutative three-valued logical conjunction AND* is an extension of the classical logical conjunction by the following table rows:
A B A AND* B
True Unknown Unknown
False Unknown False
Unknown Unknown Unknown
The A-priori datamining algorithm exploits the monotonicity property: this in the classic two-valued logic (true/false) implies that subsets of frequent sets are themselves frequent. However, in the presence of Unknown Values this notion must be slightly modified in the following way.
(candidate set). A set S of j columns Ai1, Ai2, ..., Aij is candidate if
[Number of rows r in which (Ai1(r) AND* Ai2(r) AND* ... AND* Aij(r)) = True]/[Number of rows r in which there are NOT UNKNOWN values] >t.
Here is the pseudo-code for the A-priori data mining with unknown values
Let C1 be the set of candidate single columns.
Let L1 be the set of columns Ai in C1 which are also frequent.
For each j >1
Let Cj be the set of j columns Ai1, Ai2, ..., Aij, such that each subset of j-1 columns is in Cj-1.
Let Lj be the collection of sets in Cj that are frequent.
Since in practice very few rows have Unknown Values, the speed-up given by the above A-priori strategy is similar to that given by the classical two-valued logic A-priori datamining. To establish the statistical significance of our results, p-values were computed by using Efron multiple hypotheses testing .
Results and Discussion
Correlation between decrease of GTA genes mRNA and NB phenotype
NB patients with mRNA decrease
NB patients with normal mRNA levels
The data presented in this paper experimentally confirm our hypothesis that at least some GTA proteins may also be physiologically involved in the control of cell proliferation, at the same time underscoring the importance of natural selection within complex biopathological processes [22, 47]. They also suggest possible ways to exploit molecular omic profiling to determine biological functions and design rational anticancer therapies.
We thank Dr R Roeder (The Rockefeller University, New York, USA) for his interest in our studies along the years and the Reviewers for their careful analysis and suggestions. We also thank Drs A Battaglia, F Covato, M Santonocito, L Tomasello for collaborating to the experimental work, Mrs M Cocimano, Mr S Galatà, Mr L Messina, Mr F Mondio, Mr A Vasta for technical collaboration. This project was funded by Ministero dell'Università e della Ricerca Scientifica e Tecnologica (MUR) (MP), by Associazione Italiana per la Ricerca sul Cancro (AIRC) (MP and MR), and by Ministero della Salute (MR). Drs D Barbagallo, C Bosco, L Duro, MR Guglielmino, S Forte, A Laganà, A Majorana are PhD Students (Dottorato di Ricerca in Biologia, Genetica Umana, BioInformatica: Basi Molecolari e Cellulari del Fenotipo – Director: Prof M Purrello). Dr B Banelli is a fellow of the Fondazione Italiana per la Lotta al Neuroblastoma. We regret that due to space limitations we were unable to cite many papers, related to the subject of this work.
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