Patent Application: US-81057608-A

Abstract:
the present invention relates to a method for analyzing cancer . e . g ., breast cancer including detection of differential expression of at least one of the 16 genes encoding serine / threonine kinases listed in table 1 , or of the 16 genes , and to a polynucleotide library including at least one the 16 genes . this finds use in the development of novel applications , in particular in the development of prognosis or diagnostic of breast cancer or for monitoring the treatment of a patient with a breast cancer .

Description:
breast cancer ( bc ) is a heterogeneous disease made of various molecular subtypes with different prognosis . however , evolution remains difficult to predict within some subtypes such as luminal a , and treatment is not as adapted as it should be . refinement of prognostic classification and identification of new therapeutical targets are needed . using oligonucleotide microarrays , we profiled 227 bcs . we focused our analysis on two major bc subtypes with opposite prognosis , luminal a ( n = 80 ) and basal ( n = 58 ), and on genes encoding protein kinases . whole - kinome expression separated luminal a and basal tumors . the expression ( measured by a kinase score ks ) of 16 genes encoding serine / threonine kinases involved in mitosis distinguished two subgroups of luminal a tumors : aa , of good prognosis , and ab , of poor prognosis . this classification and its prognostic impact were validated in 276 luminal a cases from three independent series profiled across different microarray platforms . the classification outperformed the current prognostic factors in univariate and multivariate analyses in both training and validation sets . the luminal ab subgroup , characterized by high mitotic activity as compared to luminal aa tumors , displayed clinical characteristics and a ks intermediate between the luminal aa subgroup and the luminal b subtype , suggesting a continuum in luminal tumors . some of the mitotic kinases of the signature represent therapeutical targets under investigation . the identification of luminal a cases of poor prognosis should help select appropriate treatment , while the identification of a relevant kinase set provides potential targets . our study focused on the kinome of luminal a and bc cancers , whose relevance to cancer biology and therapeutics is well established ( manning g , whyte d b , martinez r , hunter t , sudarsanam s . the protein kinase complement of the human genome . science 2002 ; 298 : 1912 - 34 [ 8 ]). to our knowledge , this is the first study of profiling and exclusive and comprehensive analysis of kinase genes in bc . the breast cancer kinome differs between luminal a and basal subtypes as an exploratory step , we applied hierarchical clustering to 435 kinase genes . we found that luminal a and basal tumors had different global kinome expression patterns , with some degree of transcriptional heterogeneity within luminal a tumors . this observation suggests differential expression of many kinases , and consequently different phosphorylation programs between the two subtypes . global clustering revealed broad coherent kinase clusters corresponding to cell processes ( proliferation , differentiation ) or to cell type ( immune response ), with overxepression of the proliferation cluster in basal samples and of the differentiation cluster in luminal a samples . interestingly , a kinase score ( ks ) based on their expression distinguished two subgroups of luminal a tumors ( aa and ab ) with different survival . identified in our tumor series , this classification and its prognostic impact were validated in 276 luminal a cases from three independent series profiled across different microarray platforms . importantly , the ks outperformed the current prognostic factors in uni - and multivariate analyses in both training and validation sets . analysis of molecular function and biological processes revealed that the prognostic value of this kinase signature is mainly related to proliferation . indeed , the 16 genes encode kinases involved in g2 and m phases of the cell cycle . aurora - a and - b are two major kinases regulating mitosis and cytokinesis , respectively . bub1 ( budding inhibited by benzimidazole ), bub1b , chek1 ( checkpoint kinase 1 ), plk1 ( polo - like kinase 1 ), nek2 ( never in mitosis kinase 2 ) and ttk / mps1 play key roles in the various cell division checkpoints . plk4 ( polo - like kinase 4 ) is involved in centriole duplication . cdc2 / cdk1 is a major component of the cell cycle machinery in association with mitotic cyclins . cdc7 , melk ( maternal embryonic leucine zipper kinase ) and vrk1 ( vaccinia - related kinase 1 ) are regulators of the s / g2 and g2 / m transitions . srpk1 regulates splicing . not much is known about mastl and pbk kinases . prognostic gene expression signatures related to grade ( sotiriou c , wirapati p , loi s , et al . gene expression profiling in breast cancer : understanding the molecular basis of histologic grade to improve prognosis . j natl cancer inst 2006 ; 98 : 262 - 72 ; ivshina a v , george j , senko o , et al . genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer . cancer res 2006 ; 66 : 10292 - 301 [ 18 , 19 ]) or proliferation ( dai h , van &# 39 ; t veer l , lamb j , et al . a cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients . cancer res 2005 ; 65 : 4059 - 66 [ 20 ]) have been reported . we found respectively 8 and 10 of our 16 kinase genes in the lists of genes differentially expressed in grade i vs grade iii bcs reported by sotiriou et al ( 97 genes ) and ivshina et al ( 264 genes ). three kinase genes , aurka , aurkb , and bub1 , are included in a prognostic set of 50 cell cycle - related genes [ 20 ], and aurkb is one of the 5 proliferation genes included in the recurrence score defined by paik et al ( paik s , shak s , tang g , et al . a multigene assay to predict recurrence of tamoxifen - treated , node - negative breast cancer . n engl j med 2004 ; 351 : 2817 - 26 [ 21 ]). furthermore , proliferation appears to be the most prominent predictor of outcome in many other published prognostic gene expression signatures ( desmedt c , sotiriou c . proliferation : the most prominent predictor of clinical outcome in breast cancer . cell cycle 2006 ; 5 : 2198 - 202 [ 22 ]). this link of our signature with proliferation also explains the correlation of our luminal a subgrouping with histological grade , which is in part based on a mitotic index . but interestingly , comparison with ki67 and grade showed that our mitotic kinase signature performed better in identifying these tumors and predicting the survival of patients . targeting cell proliferation is a main objective of anticancer therapeutic strategies . kinases have proven to be successful targets for therapies . mitotic kinases have stimulated intense work focused on identifying novel antimitotic drugs . some of them included in our signature represent targets under investigation ( miglarese m r , carlson r o . development of new cancer therapeutic agents targeting mitosis . expert opin investig drugs 2006 ; 15 : 1411 - 25 [ 23 ]). for example , targeting of aurora kinases is a promising way of treating tumors ( carvajal r d , tse a , schwartz g k . aurora kinases : new targets for cancer therapy . clin cancer res 2006 ; 12 : 6869 - 75 [ 24 ]). clinical trials of four aurora kinase inhibitors are ongoing in the united states and europe : mk0457 and pha - 739358 inhibit aurora - a and aurora - b , mln8054 selectively inhibits aurora - a , and azd1152 selectively inhibits aurora - b . similarly , small - molecule inhibitors of plk1 such as on01910 and bi2536 are being tested ( strebhardt k , ullrich a . targeting polo - like kinase 1 for cancer therapy . nat rev cancer 2006 ; 6 : 321 - 30 [ 25 ]), as well as flavopiridol ( inhibitor of the cyclin - dependant kinase cdc2 ), and ucn - 01 ( inhibitor of chek1 ). other less studied but potential therapeutic targets include ttk , bub and nek proteins ( de carcer g , de castro i p , malumbres m . targeting cell cycle kinases for cancer therapy . curr med chem 2007 ; 14 : 969 - 85 [ 26 ]). despite their relatively good prognosis as compared to luminal b tumors , luminal a tumors display a heterogeneous clinical outcome after treatment , which generally includes hormone therapy . it is important to define the cases that may evolve unfavorably , all the more so that different types of hormone therapy , chemotherapy , and targeted molecular therapy are available . our poor prognosis subgroup of luminal a tumors ( ab cases ) is characterized by high mitotic activity as compared to other luminal a tumors ( aa cases ). any error in the key steps in division regulated by these kinases — centrosome duplication , spindle checkpoint , microtubule - kinetochore attachment , chromosome condensation and segregation , cytokinesis — may lead to aneuploïdy and progressive chromosomal instability . this may in part explain the high grade and poor prognosis of these tumors . in fact , the luminal ab subgroup displayed clinical characteristics and a ks intermediate between the luminal aa subgroup and the luminal b subtype . these subgroups were not previously recognized by the sorlie &# 39 ; s intrinsic gene set . we interpret this finding as follows . the use of intrinsic set distinguishes a large proportion of luminal b cancers but is unable to pick all proliferative cases . a small proportion of cases is left to cluster with the luminal a cases , and are therefore labeled luminal a . an explanation for the poor efficacy of sorlie &# 39 ; s set to define all proliferative luminal cases may be the low number of genes involved in proliferation , including a very low number of kinases . our mitotic kinase signature makes possible to identify all proliferative luminal cases , and reveals a continuum of luminal cases from the more proliferative ( luminal b ) to the less proliferative ( luminal aa ). reciprocally , there may be a gradient of luminal differentiation giving a continuum of luminal bcs , including , from poorly - differentiated to highly - differentiated , luminal b , ab and aa ( fig3 b ). optimal response to hormone therapy would be obtained with luminal aa bcs , whereas luminal b and ab would benefit from chemotherapy and / or new drugs targeting the cell cycle and various kinases as discussed above . a total of 227 pre - treatment early breast cancer samples were available for rna profiling on affymetrix microarrays . they were collected from 226 patients with invasive adenocarcinoma who underwent initial surgery at the institut paoli - calmettes and hôpital nord ( marseille ) between 1992 and 2004 . samples were macrodissected by pathologists , and frozen within 30 min of removal in liquid nitrogen . all profiled specimens contained more than 60 % of tumor cells . characteristics of samples and treatment are listed in supplementary table 1 . in addition , we profiled rna extracted from 8 cell lines that provided models for cell types encountered in mammary tissues : 3 luminal epithelial cell lines ( hcc1500 , mda - mb - 134 , zr - 75 - 30 ), 3 basal epithelial cell lines ( hme - 1 , hmec - derived 184b5 , mda - mb - 231 ), and 2 lymphocytic b and t cell lines ( daudi and jurkatt , respectively ). all cell lines were obtained from atcc ( rockville , md .— http :// www . atcc . org /) and were grown as recommended gene expression analyses were done with affymetrix u133 plus 2 . 0 human oligonucleotide microarrays containing over 47 , 000 transcripts and variants , including 38 , 500 well - characterized human genes . preparation of crna from 3 μg total rna , hybridizations , washes and detection were done as recommended by the supplier ( affymetrix ). scanning was done with affymetrix genearray scanner and quantification with affymetrix gcos software . hybridization images were inspected for artifacts . expression data were analyzed by the rma ( robust multichip average ) method in r software ( brian d . ripley . the r project in statistical computing . msor connections . the newsletter of the ltsn maths , stats & amp ; or network ., 1 ( 1 ): 23 - 25 , february 2001 [ 28 ] and http :// www . r - project . org / doc / bib / r - other_bib . html # r : ripley : 2001 using bioconductor and associated packages ( irizarry r a , hobbs b , collin f , et al . exploration , normalization , and summaries of high density oligonucleotide array probe level data . biostatistics 2003 ; 4 : 249 - 64 [ 12 ]). before analysis , a filtering process removed from the dataset the genes with low and poorly measured expression as defined by expression value inferior to 100 units in all 227 breast cancer tissue samples , retaining 31189 genes / ests . before unsupervised hierarchical clustering , a second filter excluded genes showing low expression variation across the 227 samples , as defined by standard deviation ( sd ) inferior to 0 . 5 log 2 units ( only for calculation of sd , values were floored to 100 since discrimination of expression variation in this low range can not be done with confidence ), retaining 14486 genes / ests . data was then log 2 - transformed and submitted to the cluster program ( eisen m b , spellman p t , brown p o , botstein d . cluster analysis and display of genome - wide expression patterns . proc natl acad sci usa 1998 ; 95 : 14863 - 8 [ 13 ]) using data median - centered on genes , pearson correlation as similarity metric and centroid linkage clustering . results were displayed using treeview program [ 13 ]. quality threshold ( qt ) clustering identifies sets of genes with highly correlated expression patterns among the hierarchical clustering . it was applied to the kinase probe sets and basal and luminal a tumors using treeview program [ 13 ]. the cut - offs for minimal cluster size and minimal correlation were 15 and 0 . 7 , respectively . the gene clusters were interrogated using ingenuity software ( redwood city , calif ., usa ) to assess significant representation of biological pathways and functions . the kinome database established by manning et al [ 8 ] was used as reference to extract the kinase - encoding genes from the affymetrix genechip u133 plus 2 . 0 . first , because annotation of the hugo ( human genome organisation ) symbols did not correspond necessarily between the genes represented on the affymetrix chip and the kinome , we used the mrna accession number as cross - reference . cdna sequences of the kinome were compared with the representative mrna sequences of the unigene database using blastn , and alignements between these sequences were obtained . all mrnas with exact match were retained , and their accession number compared with those of the 31 , 189 selected probe sets given by affymetrix . second , some kinase genes were represented by several probe sets on the affymetyrix chip . this may introduce bias in the weight of the groups of genes for analysis by qt - clustering . in these cases , probe sets with an extension & lt ;& lt ; _at & gt ;& gt ;, next & lt ;& lt ; s_at & gt ;& gt ; and followed by all other extensions were preferentially kept . when several probe sets with the best extension were available , the one with the highest median value was retained . from the initial list of 518 kinases , we finally retained 435 probe sets representing 435 kinase genes . to test the performance of our multigene signature in other bc samples , we analyzed three major publicly available data sets : van de vijver et al ( van de vijver m j , he y d , van &# 39 ; t veer u , et al . a gene - expression signature as a predictor of survival in breast cancer . n engl j med 2002 ; 347 : 1999 - 2009 [ 14 ]), wang et al wang y , klijn j g , zhang y , et al . gene - expression profiles to predict distant metastasis of lymph - node - negative primary breast cancer . lancet 2005 ; 365 : 671 - 9 ( wang y , klijn j g , zhang y , et al . gene - expression profiles to predict distant metastasis of lymph - node - negative primary breast cancer . lancet 2005 ; 365 : 671 - 9 [ 15 ]) collected from ncbi / genbank geo database ( series entry gse2034 ), and loi et al ( loi s , haibe - kains b , desmedt c , et al . definition of clinically distinct molecular subtypes in estrogen receptor - positive breast carcinomas through genomic grade . j clin oncol 2007 ; 25 : 1239 - 46 [ 16 ]) collected from ncbi / genbank geo database ( series entry gse6532 ). analysis of each data set was done in several successive steps : identification of molecular subtypes based on the common intrinsic gene set , identification of the kinase gene set common with ours , followed by computing of the kinase score ( see below ) for the luminal a samples . clinical data of luminal a samples from our series and public series used for analyses are detailed in supplementary table 3 . in supplementary table 3 , loi et al . refers to loi s , haibe - kains b , desmedt c , et al . definition of clinically distinct molecular subtypes in estrogen receptor - positive breast carcinomas through genomic grade . j clin oncol 2007 ; 25 : 1239 - 46 [ 16 ], vdv et al . refers to van de vijver mj , he yd , van &# 39 ; t veer lj , et al . a gene - expression signature as a predictor of survival in breast cancer . n engl j med 2002 ; 347 : 1999 - 2009 [ 14 ], and wand et al . refers to wang y , klijn jg , zhang y , et al . gene - expression profiles to predict distant metastasis of lymph - node - negative primary breast cancer . lancet 2005 ; 365 : 671 - 9 [ 15 ]. we defined a score , called the kinase score ( ks ), which was based on the expression level of 16 kinase genes . it was defined as : where a and b represent normalization parameters , which make the ks comparable across the different datasets , n the number of available kinase genes ( 7 to 16 ), and xi the logarithmic gene expression level in tumor i . using a cut - off value of 0 , each tumor was assigned a low score ( ks & lt ; 0 , i . e . with overall low expression of 16 kinase genes ) or a high score ( ks & gt ; 0 , i . e . with overall strong expression of 16 kinase genes ). in the present invention , the number of available kinase genes , i . e . n , is from 1 to 16 . the samples included in the statistical analysis ( luminal a subtype ) were er and / or pr - positive as defined using immunohistochemistry ( ihc ). we introduced two qualitative variables based on the mrna expression level of er and pr ( esr1 estrogen receptor 1 probe set 205225_at and pgr progesterone receptor probe set 208305_at ): the cut - off for defining esr1 or pgr - rich or - poor was the median expression level of the corresponding probe set . the two probe sets were chosen by using the same above - cited criteria . correlations between sample groups and histoclinical factors were calculated with the fisher &# 39 ; s exact test for qualitative variables with discrete categories , and the wilcoxon test for continuous variables . follow - up was measured from the date of diagnosis to the date of last news for patients without relapse . relapse - free survival ( rfs ) was calculated from the date of diagnosis until date of first relapse whatever its location ( local , regional or distant ) using the kaplan - meier method and compared between groups with the log - rank test . the univariate and multivariate analyses were done using cox regression analysis . the p - values were based on log - rank test , and patients with one or more missing data were excluded . all statistical tests were two - sided at the 5 % level of significance . statistical analysis was done using the survival package ( version 2 . 30 ), in the r software ( version 2 . 4 . 1 — www . cran . r - project . org ). a total of 227 samples were profiled using whole - genome dna microarrays . hierarchical clustering was applied to the 14 , 486 genes / ests with significant variation in expression level across all samples ( supplementary fig1 ). clusters of samples and clusters of genes were identified , and represented previously recognized groups ( bertucci f , finetti p , cervera n , et al . gene expression profiling shows medullary breast cancer is a subgroup of basal breast cancers . cancer res 2006 ; 66 : 4636 - 44 [ 17 ]). we looked whether the five molecular subtypes reported by others [ 2 - 4 ] were also present in our series of samples by using the 476 genes common to the intrinsic 500 - gene set . we had previously shown that clustering of the available rna expression data for these 476 genes in the 122 samples from sorlie et al discriminated the same five molecular subtypes [ 17 ], allowing the definition of typical expression profile of each subtype for our gene set ( thereafter designated centroid ) with 96 % of concordance with those defined on the whole intrinsic gene set . we measured the pearson correlation of each of our 227 tissue samples with each centroid . the highest coefficient defined the subtype , with a minimum threshold of 0 . 15 . subtypes are color - coded in supplementary fig1 : they included 91 luminal a samples , and 67 basal samples , as well as other subtypes . whole kinome expression profiling separates basal and luminal a breast cancers we wanted to identify kinase genes whose differential expression is associated with clinical outcome . we focused our analysis on two major subtypes of bc with opposite prognosis , the basal and the luminal a subtypes . from our subtyping , we selected a series of 138 bc samples with available full histoclinical annotations , including 80 luminal a and 58 basal bcs . we identified a total of 435 unique affymetrix probe sets for 435 kinases as satisfying simultaneously presence , quality and reliability ( supplementary table 4 ). a hierarchical clustering analysis was applied to these probe sets and 138 bcs and 8 cell lines ( fig1 a ). the tumors displayed heterogeneous expression profiles . they were sorted into two large clusters , which nearly perfectly correlated with the molecular subtype , with all but one of the basal bcs in the left cluster and all but one of the luminal a bcs in the right cluster ( fig1 b ). visual inspection revealed at least four clusters of related genes responsible for much of the subdivision of samples into two main groups . they are zoomed in fig1 c . the first cluster was enriched in genes involved in cell cycle and mitosis . it was overexpressed in basal overall as compared with luminal a tumors , and in cell lines as compared with cancer tissue samples . the second gene cluster included many genes involved in immune reactions . it was expressed at heterogeneous levels in both luminal a and basal tumors , and was overexpressed in lymphocytic cell lines as compared to epithelial cell lines . the third and the fourth clusters were strongly overexpressed in luminal a overall as compared with basal bc samples . the third cluster included genes involved in tgfβ signaling as well as transmembrane tyrosine kinase receptors . gene ontology analysis using ingenuity software ( ingenuity pathway analysis v5 , www . ingenuity . com ) confirmed these data with significant overrepresentation ( right - tailed fisher &# 39 ; s exact test ) of the functions “ cell cycle ” ( p = 4 . 6e - 07 ) and “ dna replication , recombination , and repair ” ( p = 6 . 1e - 05 ) in the first cluster , “ immune response ” ( p = 8 . 1e - 10 ) and “ cellular growth and proliferation ” ( p = 8 . 1e - 10 ) in the second cluster , “ tumor morphology ” ( p = 2 . 2e - 04 ) and “ nervous system development and function ” ( p = 2 . 3e - 04 ) in the third cluster . analysis of canonical pathways showed overrepresentation of “ g2 / m transition of the cell cycle ” ( p = 6 . 8e - 08 ) “ nfkb ( nuclar factor kappa - b ) signaling pathway ” ( p = 1 . 3e - 04 ) and “ tgfβ ( tumor growth factor beta ) signaling ” ( p = 4e - 03 ) in the first , second and third clusters , respectively . no correlation was found between these gene clusters and the nine kinase families ( agc ( cyclic nucleotide regulated protein kinase and close relatives family ), camk ( kinases regulated by ca 2 + / cam and close relatives family ), ck1 ( cyclin kinase ), cmgc ( cyclin - dependent kinases ( cdks ) and close relatives family ), rgc ( receptor guanylate cyclases ), ste ( protein kinases involved in map kinase cascades ), tk ( tyrosine kinase and close relatives family ), tkl ( tyrosine kinase related to ick - lymphocyte - specific protein tyrosine kinase -), and atypical ) or the chromosomal location of genes . these results suggest that kinase gene expression is highly different between basal and luminal a bcs . kinase gene expression identifies two subgroups of luminal a breast cancers as shown in fig1 , basal bcs constituted a rather homogenous cluster whereas luminal a bcs were more heterogenous . basal and luminal bcs were distinguished by the differential expression of clusters of genes . by using qt clustering , we identified a single cluster of significance principally responsible for this discrimination ( fig1 b ), corresponding to the above - described first cluster . it contained 16 kinase genes ( table 1 ), which were overexpressed in all basal bcs and some luminal a samples , and underexpressed in most luminal a samples ( fig1 b ). this subdivision of luminal a tumors led us to define for each of them the kinase score ( ks ) based on expression level of these 16 genes . a cut - off of 0 identified two tumor groups : a group containing the luminal a bcs with negative score ( hereafter designated aa ) and a group containing the luminal a bcs with positive score ( hereafter designated ab ; fig2 a ). luminal aa made up two - thirds of the luminal a cases and luminal ab bcs the remaining one - third . proteins encoded by the 16 genes overexpressed in luminal ab bcs ( table 1 ) are all serine / threonine kinases ( except srpk1 , which is a serine / arginine kinase ) involved in the regulation of the late phases of the cell cycle , suggesting that luminal ab tumors show a transcriptional program associated with mitosis . characteristics and prognosis of the two subgroups of luminal a breast cancers the histoclinical characteristics of the two luminal a subgroups are listed in table 3 . strikingly , they shared most features but were different according to sbr grade with more grade iii in the ab subgroup and more grade i - ii in the aa subgroup . ki67 expression did not distinguish ab from aa cases but three - fourths of luminal ab were ki67 - positive . in conclusion , no factor but grade could distinguish aa from ab bcs . ** to assess differences in clinicopathologic features between the two groups of luminal a patients , fisher &# 39 ; s exact test was used for qualitative variables with discrete categories , the wilcoxon test was used for continuous variables , and the log - rank test was used to compare kaplan - meier rfs . we compared the survival of three groups of patients , i . e . patients with basal , luminal aa and luminal ab bcs . we excluded from analysis the basal medullary breast cancers known to harbor good prognosis . with a median follow - up of 55 months after diagnosis , 5 - year relapse - free survival ( rfs ; fig2 b ) was best for patients with luminal aa tumors ( 53 samples , 83 % rfs ), and worse for patients with luminal ab tumors ( 27 samples , 65 % rfs ) and for patients with basal bc ( 43 samples , 62 % rfs ; p = 0 . 031 , log - rank test ). thus , the expression of 16 kinase genes ( kg set ) identified within luminal a tumors of apparent good prognosis a subgroup that showed a prognosis similar to basal cases . we then compared the prognostic ability of our ks - based classifier with other histoclinical factors ( age , pathological tumor size , sbr grade , and axillary lymph node status , ihc p53 ( 1 %) and ki67 ( 20 %) status , esr1 and pgr mrna levels ) in our 80 luminal a samples ( table 4a ). in univariate and multivariate cox analyses , the only factor that correlated with rfs was the ks - based classifier . the hazard ratio ( hr ) for relapse was 7 . 77 for luminal ab tumors compared to luminal aa tumors ([ 95 % ci 1 . 97 - 30 . 66 ], p = 0 . 003 ). validation of two prognostic subgroups of luminal a breast cancers in published series as a validation step , we analyzed three sets of published gene expression data to identify and compare the two subgroups of luminal a bcs identified by the ks . we first defined as above the molecular subtypes of tumors . before assigning a subtype , each centroid was evaluated by its concordance with those defined by sorlie et al [ 4 ], and none was under 90 % in the three data sets . the distribution of the subtypes is shown in supplementary table 5 . ** to assess differences in clinicopathologic features between the two groups of luminal a patients , fisher &# 39 ; s exact test was used for qualitative variables with discrete categories and the wilcoxon test was used for continuous variables . five years relapse was done using the kaplan - meier method and compared between groups with the log - rank test . a total of 276 samples were identified as luminal a . the number of genes in the kg set represented in each dataset ranged from 7 to 16 ( supplementary table 5 ). we computed the ks for each tumor . the same cut - off as in our series led to the identification of aa ( 190 samples ) and ab ( 86 samples ) subgroups in each set ( fig2 c ), with the same proportions as in our own series . samples form the three studies were pooled before prognostic analyses . histoclinical correlations of the two subgroups were similar to those found in our series ( supplementary table 6 ). ** log - rank p - value . log - rank tests were used to assess the differences in both groups of luminala . we then compared rfs of the two luminal a subgroups in the 276 samples . with a median follow - up of 104 months after diagnosis , luminal ab tumors were associated with a worse prognosis than luminal aa tumors , with respective 5 - year rfs of 90 % and 73 % ( p = 6 . 3e - 6 , log - rank test ; fig2 d ). for comparison , 5 - year rfs was 64 % in basal samples in the three pooled series . we also performed univariate and multivariate survival analyses ( table 4b ). wang et al &# 39 ; s series ( 79 luminal a samples ) was analyzed separately due to the lack of available histoclinical data . in univariate analysis , the hr for relapse was 4 . 84 for luminal ab tumors compared to luminal aa tumors ([ 95 % ci 2 . 13 - 11 . 00 ], p = 1 . 7e - 04 ). the two other series were merged for analyses ( 197 luminal a samples ). three variables , including pathological tumor size , pgr mrna expression level and ks - based subgrouping , were significantly associated to rfs in univariate analysis . in multivariate analysis , only the ks - based classifier retained significant prognostic value , confirming the prominence of the ks over the sbr grade and other variables . the hr for relapse was 2 . 48 for luminal ab tumors compared to luminal aa tumors ([ 95 % ci 1 . 37 - 4 . 50 ], p = 0 . 002 ) we then studied the association of the ks with the intrinsic molecular subtypes . we merged all data sets , including our 227 tumors , the 295 van de vijver et al &# 39 ; s tumors , the 414 loi et al &# 39 ; s tumors , and the 286 wang et al &# 39 ; s tumors , resulting in a total of 1222 tumors . the ks and molecular subtypes were determined for all tumors : 367 tumors were luminal a , 99 luminal b , 172 erbb2 - overexpressing , 214 basal , 161 normal - like and 209 unassigned . we computed and compared the distribution of the ks in each subtype . as shown in fig3 a , most of the luminal a and normal - like tumors had negative ks , while most of the basal and luminal b tumors had positive ks . all pairwise comparisons of ks between the five subtypes were significant ( p & lt ; 0 . 05 ; t - test ; data not shown ). erbb2 - overexpressing and unassigned samples were equally distributed with respect to their ks . the luminal ab tumors displayed a median ks , intermediate between that of luminal b tumors , to which the score was closer , and that of luminal aa tumors . the five molecular subtypes displayed different ks . however , because the range of ks was rather large in each subtype , we studied whether the ks had any prognostic value in other subtypes than luminal a by comparing survival ( log - rank test ) between ks - negative and ks - positive tumors ( fig3 a ). as expected , difference was strong in luminal a cases ( p = 1 . 1e - 07 ). no difference was seen for erbb2 - overexpressing tumors ( p = 0 . 86 ). there was a non significant trend ( p = 0 . 18 ) in luminal b tumors towards better rfs in ks - negative vs ks - positive samples . an opposite trend was observed in basal ( p = 0 . 23 ) with better rfs in ks - positive samples . the difference was strongly significant in normal - like tumors with 5 - year rfs of 89 % in ks - negative tumors and 50 % in ks - positive tumors ( p = 3 . 1e - 05 ). interestingly , the ks could also be applied to the 209 samples not assigned to a molecular subtype by the intrinsic gene set . it classified them in two prognostic subgroups , with difference for 5 - year rfs between tumors with low ks ( 82 %) and tumors with high ks ( 60 %, p = 0 . 001 ). the luminal ab tumors displayed an intermediate ks pattern between luminal aa tumors and luminal b tumors ( fig3 b ). comparison of histoclinical features between luminal aa , luminal ab and luminal b samples in the three public data sets confirmed this finding ( supplementary table 6 ), with a significant increase from luminal aa to luminal ab to luminal b for pathological tumor size and rate of relapse , and a significant decrease for grade , mrna expression level of esr1 and pgr , and 5 - year rfs . these results confirm that luminal aa and ab represent new clinically relevant subgroups of bcs until now unrecognized , and suggest a continuum between these three subgroups . charafe - jauffret e , ginestier c , monville f , et al . how to best classify breast cancer : conventional and novel classifications ( review ). int j oncol 2005 ; 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