Patent Application: US-8382406-A

Abstract:
method and device for the in vitro analysis of mrna of genes involved in hematological neoplasias . the device , composed of probes which specifically hybridize with genes involved in hematological neoplasias , designed so that its behaviour in the hybridization is similar , permits the evaluation of the mrna level in biological samples taken from subjects suspected to be suffering from hematological neoplasia and facilitating the comparison between the different samples and their grouping by similarity in the gene expression patterns , especially when the probes are disposed in the form of microarray . the application of the method of the invention to obtain and process data of gene expression differences from the device of the invention permits the identification of genes significant for distinguishing samples associated to hematological neoplasias , facilitates the diagnosis of neoplasias as cll and permits making a prognosis of the evolution thereof .

Description:
a revision was performed of the scientific literature and genes were selected due to their special involvement in the biology of blood cells or in the pathology of the different neoplasias the genes selected can be included within these 4 large groups : a ) with an important role in the biology of the hematopoietic cells : genes whose protein is expressed or repressed in the different steps through which these cells pass in their differentiation to mature forms . genes whose protein is specifically expressed in accordance with the line whereto the cell belongs . genes whose expression ( a level of mrna or protein ) is altered in different types of neoplasias , or associated to resistance to chemotherapy genes which code proteins associated with proliferation , metastasis or genes whose expression is increased in a large number of tumours . genes which , without having a special ratio with hematological neoplasias or blood cell biology , have appeared in the scientific literature as statistically associated to a type of neoplasia the characteristics of the genes can be consulted , for example , in : www . ncbi . nlm . nih . qov / genbank , selecting the “ gene ” option in the drop - down menu which appears and entering the corresponding identification number ( genid ) in the genbank . the genes whose expression can be analysed with the microarray , their corresponding identification number in the genbank , as well as the oligonucleotides present in the microarray to be used as probes to analyse the expression of said genes appear below in table 1 . for each one of the 534 genes related to hematological neoplasias , as well as for the genes corresponding to β - actin , glyceraldehyde - 3 - phosphate dehydrogenase , 18s rrna and 28s rrna , the mrrna sequence is sought in genbank ( www . ncbi . hlm . nih . gov / genbank /). an oligonucleotide is designed ( probe ) from the genbank sequence , specific for each one of the genes selected . in some genes several oligonucleotides were designed situated in zones 5 ′ and 3 ′ of the gene , in order to analyse the integrity of the mrna . to ensure specificity in the design of the probes , the following criteria were taken into consideration : length of the probe to guarantee that all the probes are going to have a similar behaviour , gc content of the probe between 40 and 60 %. this characteristic is also taken into consideration to ensure that all the probes are going to have a similar behaviour . localization in the gene . probes localized at least 3000 nucleotides from 3 ′ ( poly ( a )) of the selected mrna sequence were localized . sense of the probe . a strand was chosen with “ sense ”, i . e . the sequences of the oligonucleotides coincide with sequences of fragments of the corresponding mrna , instead of being sequences complementary to said fragments . this decision involves that the labelled genetic material has to be antisense ( complementary to sense ). specificity of the probe . to avoid non - specific hybridization , probes were selected which have a percentage of homology , calculated by the blast tool ( available on the website http :// www . ncbi . nlm . nih . gov /), less than 70 %. the data on the oligonucleotides used as probes , the identification number of its corresponding sequence in the attached list , as well as data ( identification number in genbank , usual abbreviation and name ) of the genes for the detection of whose expression said oligonucleotides have been designed , are shown below in the table 1 . from among these genes , four of them ( actb , gapd , 18s rrna and 28s rrna ), do not have a special relation with neoplasias and were initially included in the microarray because , for a long time , it was believed that their expression remained constant and they were used when normalizing the microarray data : they are the type of genes alluded to when we speak of “ constitutive ” genes at other points in the specification . at present , it is not thought that there is a gene whose expression remains constant in any circumstance , for which reason , in the present study , the genes actb , gapd , 18s rrna and 28s rrna have received the same treatment as the other genes of the microarray , except for the fact that the first two of them have been used as integrity controls , as described further on . in table 1 it can be observed that there are genes which are represented by more than one oligonucleotide . this is the case because the existence of two or more probes per gene can be used to measure the integrity of the synthesized crna . the genes for which more than one oligonucleotide have been designed to act as probe , each one of which hybridizes with a different sequence , are indicated below in table 2 . to decrease the variability , a large number of controls were included in each microarray . these controls suppose an objective measurement on the process quality , and therefore , of the quality of the data obtained . they are of several types and origins : these probes were 2 pairs of oligonucleotides complementary to ends 5 ′ and 3 ′ of the β - actin genes ( probes code sg463 and sg464 ) and glyceraldehyde - 3 - phosphate dehydrogenase ( probes code sg466 and sg467 ). the ratio between the intensities of the probe located at end 3 ′ and 5 ′ makes it possible to check the quality of the starting rna and the functioning of the labelling reaction . the details on these oligonucleotides appear in table 3 . these probes are largely formed by a group of oligonucleotides of 50 nucleotides ( 50 - mer ) which are not complementary to any known human sequence . for them , the blast tool was applied to these probes and it was observed that they did not hybridize with any human sequence . they are identified with codes sc1 ( seq id no : 564 ), sc2 ( seq id no : 565 ), sc3 ( seq id no : 566 ), sc4 ( seq id no : 567 ), sc5 ( seq id no : 568 ), sc6 ( seq id no : 569 ) and sc7 ( seq id no : 570 ) and oligonucleotides scn1 ( seq id no : 571 ), scn5 ( seq id no : 575 ), scn7 ( seq id no : 577 ) and scn10 ( seq id no : 580 ) are also used as negative controls . they are used to determine the optimum conditions of hybridization , washing and developing of the chips or microarrays . the appearance of a signal associated to them indicates the existence of non - specific hybridization . “ spiked controls ” are synthetic oligonucleotides whose sequence coincides with a fragment of a transcript of a non - human gene or of any other sequence of nucleotides of low homology with transcripts of human genes which is polyadenylated at 3 ′, which is used as positive control , in the determination of the process quality , in the normalization of data and for the establishment of the linear range of the process ( benes v et al ., 2003 ). to do this , the transcripts or corresponding polyadenylated sequences are added to the total starting rna before starting the labelling process , and therefore , they suffer the same reactions ( labelling , hybridization and developing ) as the total 7 “ spiked controls ” are used . to ensure low homology with human genes 5 transcripts of bacillus subtilis genes ( dap , thr , trp , phe and lys ) and 2 transcripts of genes of the sharkav virus are used , frequently referred to as “ plum poxvirus ” ( sppv ), which is a plant virus . the details on these oligonucleotides are shown below in table 4 . the atcc ( american type culture collection ) numbers which appear after the name of the source genes refer to the identification number in the atcc of e . coli strains containing recombinant plasmids which contain the sequence of the genes from which the transcripts added to the rna are obtained and which were also used for the design of the sequences of the corresponding oligonucleotides bound to the microarray . the e . coli bacteria with the recombinant plasmids were acquired from atcc ( rockville , md . usa ) the plasmids ( pbluescript ii - ks ) contained the cloned cdna of a bacillus subtilis gene , with cut - off sites for the noti enzymes at end 5 ′ and bamhi at end 3 ′ and a poly extension ( da ) prior to the cut - off site for bamhi . after reconstituting and allowing the cells to grow during the night at 37 ° c . in lb + ampicillin medium , the plasmid was obtained with the midipreps kit ( jetstar ) following the manufacturer &# 39 ; s recommendations . 10 μg of each one of the plasmids was linearized by digestion with 30 u of noti restriction enzyme , in the presence of 1xne3 and 1xbsa buffer during 3 hours at 37 ° c . the linearized plasmids were subjected to extraction with phenol : chloroform : isoamilic alcohol ( ambion ), precipitation with 0 . 1 vol of 3m sodium acetate ( sigma ) and 2 . 5 vol of 100 % ethanol and elimination of salts with 80 % ethanol , following the aforementioned protocol . the dna obtained was resuspended in 10 μl of rnase - free water . next , the transcripts with sense were synthesized with an in vitro transcription reaction ( i . v . t ) from 1 μg of plasmid linearized using the megascript t3 kit ( ambion ) and following the manufacturer &# 39 ; s recommendations . the plasmids obtained were purified with the rneasy total rna isolation kit ( qiagen ), following the manufacturer &# 39 ; s recommendations . the quantification , determination of the purity , quality and size of the transcripts obtained were performed following the same methods which are described below for the total rna . c . 2 . preparation of the 2 “ spiked controls ” which represent sppv genes cdna of the two sppvl and sspv2 genes inserted between two pvuii and psti restriction sites . end 3 ′ of each insert contains a polyadenylation extension . jm109 cells were transformed with the plasmids which contained the transcripts . the cells were left to grow in plates with lb + ampicillin medium at 37 ° c ., the colonies with the transferred cells were selected and they were grown in lb + amp liquid medium . the recovery of the plasmids was performed with the midipreps plasmid purification kit ( qiagen ), following the manufacturer &# 39 ; s recommendations . 10 μg of each plasmid was linearized with 30 u of the pvuii restriction enzyme . the insert was extracted with phenol : chloroform : isoamilic alcohol ( ambion ), precipitation with 0 . 1 volumes of 7 . 5 m sodium acetate and 2 . 5 volumes of 100 % ethanol . the salts were eliminated by two washings with 80 % ethanol . the dna obtained was resuspended in 10 μl of rnase - free water . next , the transcripts with sense were synthesized with 1 μg of plasmid linearized using the t7 megascript kit ( ambion ) and following the manufacturer &# 39 ; s recommendations . the product of the reaction was cleaned with the rneasy total rna isolation kit ( qiagen ). the quantification , measuring of the purity of the transcripts obtained and verification of their size were then performed a solution of “ spiked controls ” was prepared from the transcripts obtained with different concentrations of each one of those “ spiked ” ( see table 3 ), so that they covered the whole range of intensities of the “ scanner ” reader system ( values of intensity which go from 0 to 65 , 535 in arbitrary units ). this solution was added in the same quantity to 5 □ μg of total starting rna from each sample before starting the process . so that the behaviour of the probes was as similar as possible to the probes designed for the genes to be studied , with the oligo 6 . 0 programme ( m . b . i ), those sequences were selected for each “ spiked control ” which complied with the same requirements established for the probes of the genes represented ( length , gc content , “ sense ” strand and distance to end 3 ′) and which did not form stable loops ( energy less than − 7 kcal / mol ). the blast tool was applied to the sequences which complied with those requirements and that with less homology with human sequences was chosen . after depositing and immobilizing the probes corresponding to the “ spiked controls ” on the glass , it was verified : a ) that the probes did not hybridrize in non - specific manner with the samples to analyse , b ) that all the probes had similar hybridization characteristics , and c ) that the signal of intensity obtained from each one of them can be related to the quantity of transcript added to the rna . snthetic oligonucleotides of dna with 70 nucleotides ( 70 - mer ) were used as hybridization controls , modified at one end with a biotin molecule . these molecules are added in the same quantity to the sample just before hybridization , so that their value only depends on the processes of hybridization , developing and capture of images of the microarray . for each one of these 70 - mer oligonucleotides , on the microarray there are several copies of an oligonucleotide with 50 nucleotides in length ( 50 - mer ), complementary to the corresponding 70 - mer oligonucleotide with which it must hybridize . the 50 - mer oligonucleotides which form part of the microarray and which are complementary to 70 - mer oligonucleotides which are added to the crna before hybridizing are of codes scn2 , scn3 , scn6 , scn8 , scn11 , scn12 and scn13 . to ensure low homology with human sequences , the sequences of these oligonucleotides were obtained from sequences of arabidopsis thaliana and tripanosoma brucei . their characteristics appear in table 5 for the design of the 50 - mer oligonucleotides it was verified , in a manner similar to that previously described for the “ spiked controls ”, that the oligonucleotides to be used did not hybridize in non - specific form with the samples to be analysed , that all the probes had similar hybridization characteristics and that the signal of intensity obtained from each one of them could be related to the quantity of the corresponding 70 - mer oligonucleotide added to the crna . this made it possible to take as valid the oligonucleotides indicated in table 5 . the scn4 ( seq id no : 574 ) and scn9 ( seq id no : 579 ) oligonucleotides , designed in principle to act as hybridization controls , were seen to produce specific hybridization when human crna hybridized , for which reason they also appear in the microarray , as if they were probes which represent a human gene , but they are not taken into account as positive hybridization controls . for their part , oligonucleotides scn1 ( seq id no : 571 ), scn5 ( seq id no : 575 ), scn7 ( seq id no : 577 ) and scn10 ( seq id no : 580 ), which did not hybridize either in non - specific form with the samples , are also present in the microarray as negative hybridization controls , as no oligonucleotide complementary thereto were added to the crna . for its part , the hybridization controls solution , which contained the 70 - mer oligonucleotides complementary to the 50 - mer oligonucleotides present in the microarray as positive hybridization controls , was prepared from the corresponding biotinylated 70 - mer sequences using a different concentration for each one of them , as shown in table 6 : dimethyl sulfoxide ( dmso ) without any probe was used , as this is the solvent wherein the oligonucleotides are found at the time of being deposited on the surface of the microarray . twelve replicas of each probe were deposited in different localizations on the surface of a solid support ( glass in similar form to a microscope slide ) using microgrid ii spoter ( biorobotics ). the 12 replicas of each probe were distributed on the support at random : 6 in the upper area and 6 in the lower area . aminosylanized glass ( corning ) was used as solid support . the moisture and the temperature were controlled throughout the printing process . the covalent binding of the probes to the solid supports was carried out by cross - linking by ultraviolet radiation using the “ stratalinker ” apparatus ( stratagene ). the quality control of the production process of the microarrays was the following : a ) in each production run a microarray was stained with ethydium bromide which made it possible to analyze the size and form of the points printed . b ) another array of each run was hybridized with an already hybridized crna , analysing the hybridization signal , the background noise and the reproducibility of the replicas . the characteristics of the array are shown below in table 7 : cultures of jurkat cells ( cell line from leukemia t ) and u937 ( cell line from promonocytic leukemia ) were centrifuged for 10 minutes at 1200 rpm and , after decanting the supernatant , the precipitate was resuspended in rnalater ( ambion inc ) and it was stored at − 80 ° c . at the time of extraction of the rna . the rna was extracted with trizol ( gibco - brl carlbad , calif ., usa ) following the manufacturer &# 39 ; s recommendations . the blood samples were directly collected in paxgene blood rna tubes - preanalytix ( qiagen ) tubes . 2 . 5 ml of blood were extracted in each tube and two tubes per individual . the tubes were inverted several times to allow the blood to mix with the stabilizing liquid which the tube contains , and they were stored at − 20 ° c . until the night before rna extraction . the tubes with the sample were incubated at ambient temperature during the night previous to the rna extraction . the paxgene blood rna kit ( qiagen ) was used for the extraction following the manufacturer &# 39 ; s recommendations , including the intermediate step of treatment with dnase ( rnase - free dnase set , quiagen ) in column . the rna of each extraction tube was eluted in 80 μl of br5 buffer . the rna of the two tubes which correspond to each patient was gathered in a single tube . to ensure that the rna obtained is free from free from contaminants that can interfere in later labelling reactions , it was purified in the following way : 16 μl ( 0 . 1 vol ) of 7 . 5 m sodium acetate ( sigma ) and 400 μl ( 2 . 5 vol ) of 100 % ethanol were added to 160 μl of total rna solution . the solution was mixed in a “ vortex ” stirrer and it was incubated for 1 hour at − 20 ° c . after 20 minutes of centrifugation at 12 , 000 × g at 4 ° c ., the precipitate was washed twice with 500 μl of 80 % ethanol and it was resuspended in 35 μl of rnase - free water . the rnas obtained were stored at − 80 ° c . until their later use . the quantification of the total rna was carried out by the measurement of the absorbance at 260 nm in a spectrophotometer ( du 65 , beckman coulter ). 2 μl of the total rna solution were diluted in 98 μl of 1 mm tris - hcl ph 7 . 5 and the concentration was estimated ( μg / ml ) taking into account that 1 unit of optical density at 260 nm corresponds to a rna concentration of 44 μg / ml . the degree of purity was established from the absorbance ratio a260 / a280 ( nucleic acid / proteins ), considering that the rna is suitable , of “ good quality ”, when the a260 / a280 ratio is between 1 . 9 and 2 . 1 . the quality of the total rna was determined by viewing the rna after electrophoresis . 500 ng of total rna were subjected to electrophoresis in 1 % agarose gel ( fmc ) in tae 1 × buffer with bret ( 0 . 5 mg / ml ), under a potential differenceof 100v for 25 minutes in ac electrophoresis cuvettes ( biorad ). as marker of molecular weights , phage φ29 digested with the bamh i restriction enzyme was used . the gels were viewed in a gel doc ( biorad ) ultraviolet light transiluminator . the choice of the strand with sense as probe limited the labelling strategy at those approximations which yield an antisense labelled product ( complementary to the probe immobilized on the solid support ). this type of labelling was performed during the course of an amplification process which consists of the use for the synthesis of single - strand cdna , of an oligo ( dt ) primer which contains a promoter for the polymerase rna enzyme of the t7 phage , an enzyme which will be used in the sample amplifications step . a .— cdna synthesis : step wherein dna ( cdna ) complementary to the starting mrna was synthesized . 5 μg of total rna was incubated with 2 μl of the “ spiked controls ” solution and 100 pmol of t7 -( dt ) 24 ( genset corp ) primer in final volume of 12 μl during 10 minutes at 70 ° c . in a thermoblock , the mixture was cooled on ice and 4 μl of 5 × first strand buffer ( gibco brl life technologies ), 0 . 1m 2 μl dtt ( gibco brl life technologies ), 1 μl dntp mix 10 mm ( gibco brl life technologies ) and 1 μl of superscript ii rnase h rt ( 200 or / μl ) ( gibco brl life technologies ) were added . after 1 hour of incubation in a bath equipped with a thermostat ( selecta ) at 42 ° c ., the reaction was cooled on ice . b .— double chain dna synthesis ( dsdna ): a double chain of dna was synthesized from the cdna synthesized in the previous step . to 20 μl of previous reaction were added 91 μl of rnase - free water , 30 μl of “ second strand reaction buffer ” ( gibco brl life technologies ), 3 μl 10 mm dntps ( gibco brl life technologies ), 10 u e . coli dna ligase ( gibco brl life technologies ), 40 o e . coli dna polymerase i ( gibco brl life technologies ), 2 u e . coli rnase h ( gibco brl life technologies ) in a final volume of 150 μl . the reaction was incubated in a thermoblock at 16 ° c . for 2 hours . next , 10 u of t4 dna polymerase ( gibco brl life technologies ) were added and the mixture was incubated at 16 ° c . for 5 minutes . to stop the reaction , 10 μl of 0 . 5 m edta were added . c .— purification of the dsdna : to eliminate possible remains of reaction products which may interfere in later labelling reactions , the dna obtained through phenol / chloroform extraction and later precipitation was purified . to 162 μl of previous reaction 162 μl of phenol : chloroform : isoamilic alcohol solution ( 25 : 24 : 1 ) ( ambion ) were added . it was centrifuged for 2 min at 12 , 000 × g in a centrifuge at ambient temperature , the upper aqueous phase was collected . to this upper phase 0 . 5 volumes of 7 . 5m ammonium acetate ( sigma chemical ) and 2 . 5 volumes of 100 % ethanol cooled to − 20 ° c .) were added . after stirring with “ vortex ” to mix well the components and centrifugation for 20 minutes at 12000 × g at ambient temperature , the supernatant was eliminated and the precipitate was washed twice with 80 % ethanol . the dna obtained was resuspended in 10 μl of rnase - free water and it was concentrated in a “ speed - vac ” concentrator to a volume of 2 μl . this dnase was stored at − 20 ° c . until its later use . d .— synthesis and labelling of the crna : this reaction was carried out in a volume of 20 μl and using the t7 megascript kit ( ambion ), following the manufacturer &# 39 ; s instructions and incorporating nucleotides modified with biotin , bio - 11 - ctp and bio - 11 utp ( perkin elmer ) in non - modified nucleotide / modified nucleotide ratio of 1 : 3 . the reaction was incubated during 5 h and 15 minutes in a bath with thermostat ( selecta ) at 37 ° c ., stirring the reaction every 45 minutes . after this incubation , 1 μl of dnase was added and it was incubated for 30 min at 37 ° c . e .— purification of the biotinylated crna : the biotinylated crna was purified with the rneasy total rna isolation kit ( qiagen ) following the manufacturer &# 39 ; s instructions . the biotinylated crnas obtained were eluted in a volume of 80 μl and they were stored at − 80 ° c . until its later use . the quantity , purity and quality of the crna obtained were determined following the same methods described for the total rna . the crna was stored at − 80 ° c . until its later use . 10 μg of biotinylated crna were fragmented in the presence of 5 × ( 200 mm tris - acetate , ph 8 . 1 , 500 mm hoac , 150 mm mgoac ) fragmentation buffer during 35 minutes at 94 ° c . in a thermoblock . it was verified that the fragmentation reaction had been carried out by viewing 1 μl of fragmentation solution in electrophoresis on 1 % agarose gel . in this step the labelled genetic material were placed in contact with the probes immobilized on the solid support . 10 μl of the hybridization control solution were added to the biotinylated and fragmented crna solution and the mixture was incubated for 3 min at 95 ° c . to denature the possible secondary structures . after incubation , the mixture was immediately taken to ice to prevent the possible renaturing of the sample . the hybridization was carried out for 6 hours at 42 ° c . in the ventana discovery automatic hybridization station ( ventana medical systems ). the hybridization and washing buffers were supplied by ventana medical system . the microarrays were automatically stained in the hybridization station with streptavidin conjugated with cy3 ( amersham biosciences ) using the manufacturer &# 39 ; s recommendations . after the hybridization and developing , the images of the microarrays were identified and analysed by the scanarray 4000 confocal fluorescent scanner ( perkin elmer ) equipped with a laser for the green ( 543 nm to excite the fluorophore cy3 ). the “ software ” used was scanarray 3 . 1 . the use of the computer programme quantarray 3 . 0 ( perkin elmer ) provided the absolute values of the intensity of hybridization and background noise in accordance with the light emitted by the cy3 in each probe in an excel format . in first place , the value of the background noise were subtracted from the values of absolute intensity of all the oligonucleotides . to do this , the values of absolute intensity and the values of background noise , which the programme used to convert the signals of the fluorophore returns , automatically , were used for each one of the microarray points : the corresponding in tensity value is obtained from the zone which has been defined as point and the value of the background noise is obtained from the zone situated around the point . next , the average level of hybridization intensity of each one of the oligonucleotides of the microarray was calculated from the trimmed mean of the intensities of the 12 replicas of each one of the oligonucleotides . to do this , before calculating the average , the upper and lower values of the distribution points of hybridization signals obtained with each one of the replicas of the same oligonucleotide have to be eliminated . the calculation was performed using the excel programme from microsoft and , specifically , the trimmean function thereof , wherein the “ percentage ” parameter was set at 0 . 2 , which supposes fixing the percentage of values eliminated in 20 % of the upper values and 20 % of the lower values ; the function rounds up the number of data points excluded to the closest multiple of 2 . in last place , and to be able to determined the validity of the hybridization , it is necessary that a series of established criteria are met : 1 ) the ratio between the average intensity and the aver age background of all the oligonucleotides of the chip is greater than 10 ; 2 ) the value of the average coefficient of variation ( standard deviation of the replicas compared with the average of the replicas ) of all the replicas of oligonucleotides of the chip should be less than 0 . 3 ; 3 ) the average value of the negative control should be less than 2 . 5 times the value of the dmso medium ; 4 ) a signal should be obtained both in the hybridization controls and in the exogenous internal positive controls ( spiked controls ). the data analysis was performed in r , version 1 . 9 . 1 . r is a programming language wherein both classical and modern statistical techniques can be applied ( r developmental core team , 2004 ; http :// www . r - project . org ), which has a series of functions stored in packages for the handling , calculation and graphic representation of data ( venables et al ., 2004 ). there are hundreds of packages written by different authors for r , with special statistical functions or which permit the access and handling of data and are available for downloading from the websites of cran ( http :// cran . r - project . org /) or bioconductor ( http :// www . bioconductor . org ). in some specific cases , the spss commercial statistical analysis software was used ( chicago , usa ). results obtained on using the microarray device with samples of u937 vs jurkat cells in order to know if the device permits differentiating two cells lines hybridized in 10 microchips : 5 samples of biotinylated crnas synthesized following the optimized working protocol , obtained from rna of u937 cells ( cell line from promonocytic leukemia ) and 5 samples of biotinylated crnas obtained from rna of jurkat cells ( cell line from t leukemia ). the initial steps of preliminary processing of the data and validation of the hybridization mentioned previously in the “ data analysis : preliminary processing ” section were carried out and then the data was normalized and filtered : data normalization . the “ variance stabilization normalization ” method was used , available in the “ vsn ” package in r . there are different packages available on the internet for r , with special statistical functions or which permit the access and processing of data and are available for downloading from cran ( http :// cran . r - project . orq /) or bioconductor ( http :// www . bioconductor . orq ) ata filtering . two filtering operations have been carried out with the “ filterfun ” function of the of the “ genefilter ” filter in r . the genes which did not pass any of the two filters were not used in the data analysis . the filters carried out were : filtering to exclude genes with an intensity value close to the dmso . this filter made it possible to work with genes with an intensity value minus average background noise greater than 550 arbitrary units ( approximately 2 times the value of the dmso ). filtering to exclude genes with minimum intensity variation throughout the samples . genes were worked with an interquartile range of normalized intensity throughout samples greater than 0 . 3 . the data filtering left 83 probes which constituted the working list . with them a grouping was made of the non - supervised samples , which are those groupings wherein the structure of the data is not previously known , the system learning how the data are distributed among classes based on a distance function . a tree or hierarchical group was obtained with the grouping , wherein the samples are grouped in accordance with their similarity in the expression of certain genes , those corresponding to the oligonucleotides of the working list , so that the closest samples are those which have a similar expression profile . the grouping was performed with the hclust function of the stats package in r . the non - supervised analysis of the 10 samples produced their separation in two groups or main branches in accordance with the cell type whereto the samples belong : a group contains the 5 hybridizations carried out from u937 cells and the other group contains the 5 hybridizations carried out from jurkat cells . the resulting tree of this non - supervised grouping is shown in part a of fig1 . next , to find out if there were statistically significant differences between the two groups of samples , the “ step - down maxt multiple testing methods ” method ( maxt ) was used , which is an application of the mt . maxt function of the multtest package of the software in r from bioconductor , which applies a statistical test and carries out a strong control over the rate of false positives . to this function , the following should be provided : a ) values on which one wants to apply the statistical tests , in this case , on the normalized values of the 83 oligonucleotides which passed the filters b ) groups of which one wants to seek differences , in this case the 5 samples of jurkat cells against the 5 samples of cells u937 c ) number of permutations one wants to perform . in this case , 100 , 000 permutations are carried out . d ) by default , welch &# 39 ; s test was chosen to specify the statistical tool to be used to test the hypothesis of non - association between the variables and the class labels . the application of this analysis with a value of p & lt ; 0 . 001 provided a list of 69 statistically significant probes between the two groups , which are the following : sg12 , sg20 , sg23 , sg24 , sg38 , sg39 , sg45 , sg49 , sg53 , sg59 , sg60 , sg62 , sg76 , sg78 , sg89 , sg92 , sg94 , sg102 , sg474 , sg478 , sg487 , sg114 , sg120 , sg140 , sg142 , sg145 , sg150 , sg154 , sg158 , sg174 , sg175 , sg194 , sg195 , sg211 , sg230 , sg231 , sg235 , sg260 , sg264 , sg266 , sg268 , sg270 , sg272 , sg282 , sg294 , sg308 , sg311 , sg330 , sg332 , sg333 , sg339 , sg344 , sg364 , sg403 , sg423 , sg434 , sg456 , sg506 , sg513 , sg514 , sg515 , sg524 , sg533 , sg538 , sg541 , sg559 once the statistically significant genes to distinguish between the two groups of samples are known ( which would be the genes corresponding to the probes identified as statistically significant ) the supervised grouping was carried out of the samples in accordance with the intensity of the signal of the 69 statistically significant probes obtained . the term “ supervised ”, applied to a grouping , makes reference to the fact that the data structure is previously known , which makes it possible to use the prior information ; with this , after a training process which allows the system to learn to distinguish between classes , it is possible to use the network to assign new members to the predefined classes . in this case , the supervised grouping of the samples in accordance with the intensity of the signal obtained with the 69 statistically significant probes obtained , is again a tree which is divided in two main branches in accordance with the cell type to which the samples belong . the tree obtained with the supervised grouping is shown in part b of fig1 . results obtained on using the “ array ” device with samples from healthy subjects vs u937 and jurkat cells the expression of 5 samples of u937 cells and 5 samples of jurkat cells was compared with the expression of 10 samples from total blood from healthy subjects . in a manner similar to that carried out in example 1 , the initial data processing steps , validation of the hybridizations , normalization and filtering were carried out . a total of 180 genes passed the filtering processes . the non - supervised grouping of the samples ( carried out with the hclust function of the stats package of r applying pearson &# 39 ; s correlation ) in accordance with the expression of the 180 genes , provided a tree with two main branches : one branch contains all the samples from cell cultures and the other branch contains all the samples from total blood from healthy subjects , which demonstrates that the tool is capable of finding expression differences . the tree obtained after making this non - supervised grouping is shown in part a of fig2 . the maxt test ( p & lt ; 0 . 001 ) to find genes with statistically significant differences between the samples from u937 and jurkart cell cultures and the 10 samples from total blood of healthy subjects was performed . the statistical analysis provided a list of 131 probes with statistically significant differences between both groups of samples . they are the following : sg1 , sg4 , sg7 , sg8 , sg10 , sg13 , sg15 , sg16 , sg17 , sg18 , sg19 , sg20 , sg26 , sg29 , sg30 , sg34 , sg36 , sg39 , sg42 , sg44 , sg49 , sg51 , sg52 , sg58 , sg64 , sg65 , sg67 , sg76 , sg77 , sg80 , sg84 , sg86 , sg89 , sg92 , sg93 , sg94 , sg98 , sg99 , sg101 , sg102 , sg107 , sg463 , sg464 , sg474 , sg475 , sg485 , sg487 , sg466 , sg467 , sg471 , sg472 , sg473 , sg120 , sg129 , sg138 , sg141 , sg144 , sg145 , sg147 , sg158 , sg163 , sg164 , sg176 , sg185 , sg186 , sg197 , sg207 , sg208 , sg217 , sg227 , sg231 , sg265 , sg266 , sg277 , sg278 , sg283 , sg285 , sg299 , sg307 , sg308 , sg311 , sg313 , sg318 , sg319 , sg328 , sg333 , sg336 , sg342 , sg344 , sg357 , sg361 , sg376 , sg384 , sg389 , sg395 , sg398 , sg403 , sg404 , sg407 , sg416 , sg420 , sg423 , sg430 , sg436 , sg446 , sg455 , sg461 , sg489 , sg491 , sg492 , sg493 , sg498 , sg500 , sg504 , sg505 , sg506 , sg514 , sg516 , sg517 , sg520 , sg526 , sg530 , sg533 , sg538 , sg545 , sg547 , sg554 , sg555 , sg558 . the grouping of the 20 samples , in accordance with the expression of the statistically significant probes found , gave rise again to a tree with two main branches , one corresponding to the samples from cell cultures and another corresponding to the samples from healthy individuals . said grouping appears in part b of fig2 . results obtained with samples from patients with chronic lymphatic leukemia ( cll ) vs u937 and jurkat cells the expression profiles were compared of samples from u937 and jurkats cell cultures with 26 samples from total blood of subjects with cll . the samples underwent preliminary processing of the data , they were normalized and filtered in a manner analogous to those used in examples 1 and 2 and a total of 236 probes passed through the filters . the non - supervised grouping of the samples in accordance with the expression of the probes which passed through the filters showed a tree with two main branches : one which contained the samples of cell cultures and the other the cll samples . said tree is shown in part a of fig3 . the maxt test ( p & lt ; 0 . 001 ) to find genes with statistically significant differences between the two groups of samples was carried out . this analysis provided a list of 120 probes . they are the following : sg2 , sg4 , sg8 , sg10 , sg13 , sg15 , sg16 , sg19 , sg20 , sg23 , sg26 , sg28 , sg31 , sg34 , sg36 , sg39 , sg48 , sg58 , sg60 , sg65 , sg76 , sg77 , sg84 , sg89 , sg94 , sg9 , sg97 , sg99 , sg102 , sg106 , sg107 , sg463 , sg464 , sg474 , sg475 , sg481 , sg465 , sg485 , sg487 , sg466 , sg467 , sg471 , sg473 , sg115 , sg116 , sg117 , sg120 , sg129 , sg134 , sg135 , sg138 , sg139 , sg141 , sg145 , sg158 , sg161 , sg163 , sg176 , sg178 , sg185 , sg207 , sg208 , sg210 , sg217 , sg227 , sg231 , sg237 , sg264 , sg272 , sg277 , sg281 , sg283 , sg286 , sg294 , sg298 , sg299 , sg307 , sg308 , sg319 , sg328 , sg330 , sg333 , sg336 , sg342 , sg344 , sg345 , sg347 , sg361 , sg384 , sg389 , sg395 , sg404 , sg407 , sg416 , sg423 , sg428 , sg430 , sg432 , sg434 , sg444 , sg446 , sg453 , sg458 , sg459 , sg491 , sg498 , sg507 , sg508 , sg511 , sg517 , sg518 , sg522 , sg526 , sg530 , sg533 , sg538 , sg541 , sg554 , sg558 , sg561 . the grouping of the 30 samples in accordance with the expression of the 120 statistically significant probes found again gave rise to a tree with two main branches , one corresponding to the samples from cell cultures and another corresponding to the samples from healthy individuals . said grouping appears in part b of fig3 . results obtained with samples from healthy subjects vs patients with chronic lymphatic leukemia ( cll ) 68 hybridizations which met the quality criteria from 68 samples of different healthy subjects and with clinical diagnosis of cll were divided in 2 groups : training group used to obtain the functions of the classifier and test group , used to test the classifier obtained . the training group was composed of 30 samples ( 10 from healthy subjects and 20 from cll subjects ) and the test group was composed of 38 samples ( 5 samples from healthy subjects and 33 samples from subjects with cll ). to obtain the classification function , the results obtained from the hybridizations of the training group were worked with . the steps carried out to obtain the classification function were : data normalization . the “ variance stabilization normalization ” method , available in the “ vsn ” package in r , was used . data filtering . two filtering operations have been carried out with the “ filterfun ” function of thee “ genefilter ” package in r . the genes which did not pass any of the two filters were not used in the data analysis . from the 588 oligonucleotides of the chip , 224 passed through the 2 filters and constituted the working list . 2 . filtering to exclude genes with an intensity value close to the dmso . this filter made it possible to work with genes with an intensity value minus average background noise greater than 550 arbitrary units ( approximately 2 times the value of the dmso ) in more than 25 % of the samples ( 7 samples ) which compose the training group . 3 . filtering to exclude genes with minimum intensity variation throughout the samples . genes were worked with which had an interquartile range of normalized intensity throughout samples greater than 0 . 3 . to identify groups of genes which best characterize each type of sample and verify the classification rate of these groups of genes prediction analysis for microarrays ( pam ) was used , available as “ pamr a ” package in r . it is a statistical technique which identifies a group of genes which best characterizes a predefined class and uses this group of genes to predict the class whereto new samples belong . pam uses a modified version of the “ nearest centroids ” classification method ( tibshirani et al ., 2002 ) called “ nearest shrunken centroids ”. a validation called “ 10 fold cross validation ” was performed , which consists of constructing the model with 90 % of the samples and an attempt is made to predict the class of 10 % of the samples which have not intervened in the construction of the model . this method is repeated 10 times and the classification error of 10 % of the samples is added to calculate the overall error . this error reflects the number of badly classified samples ( bullinger et al ., 2005 ). 4 . 1 . 1 . construction of the model . from the filtered and normalized data of the 30 samples which compose the training group , attributing in an arbitrary form the healthy group to group 0 and the cll group to group 1 , performing the 10 cross - validations and with a threshold value of delta 3 . 1 . the model obtained was formed by the following oligonucleotides : sg459 , sg428 , sg507 , sg508 , sg117 , sg237 . the coefficients of the classifier corresponding to each one of these oligonucleotides are shown below in table 8 : from the filtered and normalized data of the 38 samples which compose the test group , probability values p were obtained belonging to group 0 ( healthy group ) or group 1 ( cll group ). the greater the value of p , the greater the probability of belonging to that group . it has been considered that the values greater than 0 . 5 indicate belonging to that group . the values of p obtained for each sample are indicated in table 9 . with this model 37 of the 38 samples of the test group are correctly classified : all the samples corresponding to healthy individuals ( those whose name is headed by the letter “ s ”) have a probability greater than 0 . 5 of belonging to group 0 , whilst all the samples corresponding to individuals suffering from cll ( which are the samples whose name starts with letters “ cll ”) minus one have a probability greater than 0 . 5 of belonging to group 1 . 4 . 2 . 1 .— selection of genes with statistically significant differences among healthy and cll ( training group ). from the filtered and normalized data as has been previously described , the “ step - down maxt multiple testing methods ” method ( maxt ) was used for the selection of genes with significant differences , which is an application of the mt . maxt function of the multtest package of the software in r from bioconductor , which applies a statistical test and carries out a strong control over the rate of false positives . the application of this statistical test , with a value of p & lt ; 0 . 001 , to the 224 oligonucleotides which passed through the filters , produced a list of 7 oligonucleotides : sg117 , sg428 , sg459 , sg461 , sg493 , sg507 , sg508 . the steps used to obtain the list of 7 significant genes among healthy and cll were : method which makes permutations and adjusts the values of p rest & lt ;- mt . maxt ( exprs ( 224 oligonucleotides which have passed through the filters and normalized of the training group , types of samples in the training group , test =“ t ”, b = 100000 ): mt . maxt function which through permutations adjusts the probability values ( signification ) which entails a strong control of the rate of false positives . 1 . values on which one wants to apply the statistical tests , in this case , on the normalized values of the 83 oligonucleotides which passed through the filters 2 . groups of which one wants to seek differences , in this case the 5 samples of jurkat cells against the 5 samples of cells u937 3 . number of permutations one wants to perform . in this case , 100 , 000 permutations are carried out . the statistically significant genes at a level of p & lt ; 0 . 001 were selected by this test and a number of 7 was obtained . 4 . 2 . 2 .— obtainment of the classification function with spss . by logistical regression from the normalized values of the 7 statistically significant oligonucleotides obtained from the 30 samples which compose the training group and assigning in arbitrary manner group 0 to the healthy samples and group 1 to the cll samples , the values of the classification function were obtained . the coefficients corresponding to each oligonucleotide were those which are shown below in table 10 : from the value x i a value of probability ( p i ) is calculated . the closer the value of p is to 0 , the greater the probability of belonging to the group of healthy subjects ( assigned as group 0 ) and the closer the value of p is to 1 , the greater the probability there is of the sample belonging to the group of cll subjects ( assigned as group 1 ). the formula used to determine the value of p is : as is shown in table 11 , the function obtained correctly classified the 30 samples belonging to the training group . the closer to 0 , the greater the probability that it is healthy and the closer to 1 the greater probability of cll . 4 . 2 . 3 . validation of the system classifier .— from the filtered and normalized filters as detailed above , the imn i values were obtained of the 7 oligonucleotides which compose the classifier of each one of the 38 samples which compose the test group . results of the validation of the system classifier . below , tables are shown wherein the imn i value is obtained of each one of the 7 oligonucleotides included in the classifier and the values of x i and p i calculated according to the formulas previously described , obtained for each one of the 38 samples of the test group . the samples which begin with s correspond to healthy subjects and the samples which start with cll are from cll subjects . 37 out of 38 samples are correctly classified . only sample cll175 , for which a value of pi = 0 is obtained is incorrectly classified . a third group of 40 samples was formed . to do this , replicas of hybridization or of labelling were used ( the samples whose name begins with s and strans are samples from people considered healthy and those which start with cll are samples from patients with chronic lymphatic leukemia ). this group of samples was used to validate the classification system . the data were normalized as has been previously described . the results of the classification are shown in the table 13 . 40 out of the 40 samples are correctly classified . “ cll - stable type ” ( s ) samples are considered those of patients who have had stable cll for over 5 years and “ cll - progressive type ” ( p ) samples are considered the samples of patients classified as stable at the time of diagnosis and whose disease has progressed in less than one year . in total 6 s samples and 6 p samples were analysed . the 12 samples were collected at the time of diagnosis , without clinical differences between them , but after one year , 6 of those patients had progressed . the 12 hybridizations have passed the aforementioned quality criteria . data normalization . in this case , and to avoid the significant genes obtained are due to a real difference between samples and not to the effect of normalization , the data were normalized in two different forms (“ variance stabilization normalization ” ( vsn ) and by robust quantiles ) and the same statistical analysis was performed with each one of the normalizations . statistical analysis with normalized data by “ variance stabilization normalization ”. the list of statistically significant genes was obtained from a welch &# 39 ; s test with the mt . maxt function of the multtest package in r , with a value of p & lt ; 0 . 05 without adjusting , i . e . without performing any control on the false positives and produced a list of 29 genes with stat istically significant differences between the cll - stable type and cll - progressive type groups . sg26 , sg31 , sg70 , sg98 , sg177 , sg194 , sg195 , sg208 , sg213 , sg216 , sg272 , sg293 , sg301 , sg309 , sg321 , sg333 , sg343 , sg352 , sg357 , sg366 , sg368 , sg405 , sg426 , sg439 , sg447 , sg452 , sg521 , sg555 , sg556 . the samples were grouped , which was performed with the hclust function of the stats package in r applying pearson correlations . the tree obtained is shown in part a of fig4 . the hierarchical grouping of the 12 samples in accordance with the expression of the 29 statistically significant genes obtained grouped the samples correctly : the tree contains two large branches , of which the right branch contains the 6 stable samples and the left branch contains the 6 progressive samples . statistical analysis with normalized data by robust quantiles the list of statistically significant genes was obtained from a welch &# 39 ; s test with the mt . maxt function of the multtest package in r with the values of p without adjusting i . e . without exerting any control over the rate of false positives , with a value of p & lt ; 0 . 05 , and produced a list of 19 genes with statistically significant differences between the cll - stable type and cll - progressive type groups : sg26 , sg31 , sg177 , sg194 , sg195 , sg197 , sg213 , sg216 , sg293 , sg301 , sg309 , sg333 , sg343 , sg357 , sg366 , sg439 , sg452 , sg555 , sg556 . the supervised grouping of the 12 samples in accordance with the expression of the 19 statistically significant genes obtained gave rise to the tree which appears in part b of fig4 , wherein the samples also appear correctly grouped . 18 oligonucleotides common to both lists of statistically significant genes were selected and the average intensity of each one of them in the group of stable samples and in the group of progressive samples was calculated , as well as the variation in average intensity between the stable and progressive groups . to validate the results obtained with the microarray , 5 of the common statistically significant probes were selected obtained on comparing expression data from stable cll subjects compared to progressive cll subjects and the expression was studied with rt - pcr of the genes represented by those probes . the criteria used to select the 5 probes were : hybridization intensity , change of intensity between groups of stable and progressive and value of statistical significance . in this way , 5 probes were selected which represent genes psmb4 , cd23a , lcp1 , abcc5 and pou2f2 . the expression of these 5 genes was determined in 11 of the 12 cll type samples , as there was no total rna of sample 105 . with the expression value of the genes in each sample , the rate of change was determined between the group of stable and progressive and the value of significance of that variation and it was compared with the results obtained with the microarrays . the technique used for the validation was rt - pcr or pcr in real time using a lightcycler . this technique is the technique of choice to validate data chips and as with the microarrays , measures mrna level . primers were designed for each one of the 5 genes whose representative oligonucleotide was selected . the details thereof are shown below in table 15 . fig5 shows the distribution of the expression data obtained by rt - 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168 . westbrook c a . the molecular basis of neoplasia . in hoffman r hematology basic principles and practice . 4 ed . churchill livingstone new york 2005 ; 941 - 945 zhan f , hardin j , kordsmeier b , et al : global gene expression profiling of multiple myeloma , monoclonal gammopathy of undetermined significance , and normal bone marrow plasma cells . blood 99 : 1745 , 2002 fig1 shows the grouping of samples of cells u937 compared with jurkat cells in accordance with differences in the gene expression between the samples . part a corresponds to the non - supervised grouping ; part b corresponds to the supervised grouping . fig2 shows the grouping of samples of healthy subjects compared with u937 and jurkat cells in accordance with differences in the gene expression between the samples . part a corresponds to the non - supervised grouping ; part b corresponds to the supervised grouping . fig3 shows the grouping of samples of patients with chronic lymphatic leukemia compared with u937 and jurkat cells in accordance with differences in the gene expression between the samples . part a corresponds to the non - supervised grouping ; part b corresponds to the supervised grouping . fig4 shows the grouping of samples of patients with “ stable ” chronic lymphatic leukemia compared with samples of patients with “ progressive ” chronic lymphatic leukemia in accordance with differences in gene expression . part a corresponds to the grouping in accordance with the genes identified as significant after normalization with “ vsn ” and use of the mt . maxt function in r ; part b corresponds to the grouping in accordance with the genes identified as significant after normalization by robust quartiles and use of the mt . maxt function in r . fig5 shows the distribution of the expression data obtained by rt - pcr ( left - hand graphic ) and from the intensity values obtained from the microarray ( right - hand graphic ) for the psmb4 genes ( part a : upper graphic ), cd23a ( part b : intermediate graphic ) and pou2f2 ( part c : lower graphics ) in samples of patients with “ stable ” chronic lymphatic leukemia ( bars marked with “ e ”) and in samples of patients with “ progressive ” chronic lymphatic leukemia ( bars marked with “ p ”).