BACKGROUND
xenograft models remain a cornerstone technology in the development of anti-cancer agents  <cit> .
the ability of immunocompromised rodents to support the growth of human tumors provides an invaluable transition between in vitro testing, pre-clinical development and clinical trials.
for decades, data from xenograft models has informed development decisions with respect to dosing schedules, pharmacokinetics/pharmacodynamics  and potential toxicities.
yet several challenges remain, including understanding the extent to which well-characterized xenograft models replicate the biology and growth characteristics of patient disease.
furthermore, with the paradigm shift towards agents with specific molecular targets and personalized medicine, a comprehensive molecular profile for xenograft models may be essential for successful in vivo evaluation.
to this end, considerable resources are being applied to the generation of novel xenograft models combined with molecular profiling of existing models  <cit> .
within the developmental therapeutics program  of the national cancer institute, the primary in vitro assay used to detect potential anti-cancer activity is the nci- <dig> cell line screen.
to date, this panel of human tumor lines has been used to evaluate almost one hundred thousand pure compounds and approximately fifty thousand natural product extracts.
many of these cell lines will grow as subcutaneous xenografts, thus cell lines sensitive to an agent in vitro were often subjected to further analyses in xenografts derived from those cell lines.
the nci- <dig> panel has been extensively molecularly characterized, with data available for gene expression, dna variation , protein expression, dna methylation, microrna expression and metabolomics  .
the compare algorithm  allows investigators to correlate nci- <dig> drug activity profiles with all other open agents in the database and with molecular characteristics of the cells  <cit> .
while the in vitro grown cells have been characterized, the corresponding subcutaneous xenografts had not.
however, other studies have succeeded in molecular profiling of other xenografts  <cit> .
these predominantly cdna and tissue-array based studies lack the potential for retrospective cross-platform analysis that underscores the nci- <dig> cell line set.
the microxeno project was initiated to generate genome-wide cdna microarray data for all subcutaneous xenograft models currently used within the dtp.
comprehensive transcriptomic analysis will help address questions such as: can expression of molecular target help inform model selection for a given agent or target, or to what extent and by what manner do specific cell line tumors adapt during prolonged growth in vivo?
the work presented here provides a reference dataset that can be used to confirm the genetic characteristics and stability of models going forward.
this ongoing project will ultimately encompass over  <dig> models, with data from cell lines and successive xenograft passages.
the panel includes tumor cell lines from diverse histological origins including leukemia/lymphoma, non-small cell lung, colon, cns, melanoma, ovarian, renal, prostate, liver, gastric, head and neck, pancreatic, and breast cancer.
it also includes, but is not limited to, many of the cell lines in the nci- <dig> panel .
here we describe the procedures and quality control criteria used to derive microxeno release  <dig> .
the study utilizes affymetrix hg-u <dig> plus  <dig>  arrays, capable of identifying more that  <dig>  human transcripts from > <dig>  probe sets  <cit> .
the current release encompasses  <dig> experiments with each consisting of data from the originating cell lines and the resulting xenografts at passages  <dig>   <dig> and  <dig> .
in addition, we detail several approaches to utilize the data to predict possible biological outcomes.
we propose that this dataset  will improve selection and execution of subcutaneous xenograft experiments during the evaluation of cancer therapeutics.
as this study is based primarily on lines from the nci- <dig> panel, the potential also exists for integration with other nci- <dig> datasets .
rapid dissemination of this data will also permit the extramural community to perform meta-analyses in support of their own in vivo studies.
RESULTS
this study focused on generating pan-genomic cdna microarray data for diverse xenograft models from the time of initial implantation to the tenth passage using the affymetrix hg-u <dig> plus  <dig>  array.
each experiment comprised the originating in vitro cell lines  along with tumor samples from in vivo passages  <dig>   <dig> and  <dig>  for each in vivo passage, five tumors were harvested.
the  <dig> human xenograft experiments contained within this release led to the generation of  <dig> arrays.
table  <dig> details the specific cell lines along with tumor types, histology, host strain and any special growth requirements or irregularities.table  <dig>
tumor cell lines, host mice, protocol variances
tumor typea
breast
cervical
cns
colon
gastric
leukemia/
lymphoma
liver
lung
melanoma
ovarian
pancreatic
prostate
renal
atumor cells derived from the 4th in vitro passage were innoculated subcutaneously into mice.
tumors were passaged  <dig> consecutive times in mice.
at passages  <dig>   <dig>  and  <dig> ,  <dig> tumors were harvested, cut into small pieces and flash frozen in liquid nitrogen.
samples were then processed as described in methods.
for comparative purposes,  <dig> samples of the in vitro cultivated cells at passage  <dig>  were also prepared for microarray analysis.
b3 mg/kg q7d sc estradiol.
cmatrigel  <dig>  mg/ml p <dig> only.
dher2/erbb <dig> transfectant of mda-mb- <dig>
epc <dig> subline isolated from liver metastasis in mice.
microarray data quality control
multiple layers of quality control criteria were applied to the dataset.
first, the  <dig> cel files  were visually inspected using dchip  to identify arrays with structural defects.
significant physical issues were identified in one mda-mb-231 t p <dig> sample, which was removed.
next, .cel files were uploaded and analyzed en masse using the qc tools contained within genespring gx <dig> .
results demonstrated one replicate from the pc- <dig> p <dig> had control probe errors and it was excluded .
the hybridization was repeated using the original pc- <dig> p <dig> rna sample on a new chip that yielded satisfactory results and was included in further analyses.
lastly, principal component analysis  was used to identify outliers.
for example, results shown in figure 1b identify one population of arrays segregated from the primary component.
closer inspection identified these .cel files as passages  <dig> and  <dig> of sf- <dig> and sf- <dig>  this finding suggested a conserved problem with late passage for these lines.
we then investigated whether displacement of tumor cells by an outgrowth of mouse cells was responsible for the observed effects.
results from endpoint pcr  using mouse and human specific primers directed against ptger <dig> <cit>  showed the first in vivo passage of sf- <dig> and sf- <dig> tumors contained both mouse and human genomic dna as expected, but all tumors harvested from 4th and 10th serial passages were devoid of human genomic dna.
the sf- <dig> and sf- <dig> models differed from others in the study in that they utilized matrigel® to initially establish tumor growth in passage  <dig> and they were implanted into nod.scid/ncr mice since growth in athymic nu/nuncr mice was unsuccessful.
it is recognized that nod.scid/ncr mice have a propensity for spontaneous tumor formation  <cit>  and also it is reasonable to speculate that matrigel®  mouse sarcoma cells) may encourage spontaneous host cell outgrowth.
this emphasizes the need for routine monitoring of mouse outgrowth especially when matrigel®, and possibly a nod.scid background are employed.
although mouse outgrowth was not a problem for the remaining models, this phenomenon should be an important consideration for studies involving serial passage of tumor fragments over extended periods of time.
in light of these results, p <dig> and p <dig> samples for sf- <dig> and sf- <dig> were not included in this data release.figure  <dig>
study design and quality control.
a) control probe signal profiles were generated for  <dig> affymetrix hg-u <dig> plus  <dig>  array .cel files.
the single outlier  is highlighted.
b) 3d principal component analysis  was performed on all .cel files; a population of outliers representing p <dig> and p <dig> passages for sf- <dig> and sf- <dig> glioma lines is shown in red.
control probe profiles and 3d pca were generated using genespring gx <dig> .
c) endpoint pcr of genomic dna from sf- <dig> and sf- <dig> tumors at p <dig>  p <dig> and p <dig> using mouse or human-specific ptger <dig> primers .
genomic dna from b16f <dig>  and lncap  cell lines were included as positive controls, ntc = no template control.
data is representative of all tumors processed from these xenografts.
hierarchical clustering qc
all experiments were subjected to hierarchical clustering to confirm similarity in microarray signatures for cell lines and subsequent xenograft passages.
fold-change data  for each parameter was used to generate the hierarchical cluster shown in additional file  <dig>  this analysis confirmed that for the majority of experiments, the originating cell lines and subsequent in vivo passages clustered together.
however, p <dig> data for caki- <dig>  sn12c and rxf  <dig> renal lines were shown to cluster together, suggesting a high degree of similarity between these samples .
the identity of these tumors was confirmed by repeating the identifiler® str analyses.
thus, the clustering of these p <dig> renal tumors of distinct cell line origins had a biological basis and was not the result of technical errors.
other exceptions involved the co-clustering of mda-mb- <dig> and mda-n  along with a similar trend for a <dig> and a549/asc- <dig> .
these observations were anticipated given that mda-n is derived from mda-mb- <dig> and a549/asc- <dig> is a tumorigenic clone of a <dig>  additionally, two breast cancer cell lines  did not cluster together nor did three ovarian lines  .
closer scrutiny provides a plausible explanation given these lines differ significantly within their categories.
specifically, mcf <dig> is an estrogen-dependent  tumor whereas mda-mb-231 t is triple negative .
similarly, cp <dig> and ovcar- <dig> are ovarian carcinomas whereas ovcar- <dig> is an adenocarcinoma.
ovcar- <dig> is also er + while ovcar- <dig> is er negative and cp <dig> is a cisplatin-resistant subline of a <dig>  following quality control, the final dataset comprised  <dig> complete experiments and  <dig> partial experiments  for a total of  <dig> arrays.
monitoring changes in transcript expression
the central goal of this study was to ascertain expression levels for any given transcript across all in vivo models and with successive passage.
to this end, normalized gene expression data were generated for all  <dig> conditions .
throughout the study, when multiple probe sets were present for the same transcript, the jetset methodology  <cit>  was used to select the most robust candidate.
data for four example probe sets; 205225_at , 206426_at , 201839_s_at , and 201746_at  at p <dig>  p <dig> and p <dig> are plotted in figure  <dig>  results showed that mcf <dig> cells expressed the highest level of esr <dig> across the panel, consistent with their known estrogen receptor positive status and their absolute dependence on exogenous estradiol for growth in mice.
furthermore, esr <dig> expression was shown to increase modestly with passage, suggesting serially passaged tumors remain a valid target for estrogen receptor antagonists.
mlana  is a melanoma-restricted antigen and results show expression to be limited primarily to the melanoma cell lines.
mlana expression was relatively consistent with passage, apart from uacc- <dig> where levels modestly increase at p <dig>  similarly, epcam is highly expressed on many epithelial cells and results show considerable variation in mrna expression levels even between epithelial lines.
while most tumors had stable expression of epcam from p <dig> to p <dig>  there were a few models with notable changes including a <dig>  caki- <dig> and nci-h <dig>  the final example, tp53/p <dig> serves to show the value of integrating relative expression data with pre-existing genetic information.
this tumor suppressor and master regulator of the cell cycle is frequently mutated or deleted in tumors  <cit> .
this analysis confirmed the relative lack of p <dig> expression in p53-null hl <dig> cells.
however, there was considerable variability in levels of expression for models with mutant p <dig>  this information could be useful for studies of agents targeting cells with mutant/deleted p <dig> e.g., the wee <dig> inhibitor mk- <dig> or mutant p <dig> oncolytic adenovirus  <cit> .
overall, this analysis serves to illustrate the potential of these data within therapeutic studies and provide evidence that mrna expression can change markedly with in vivo passage.figure  <dig>
transcript expression relative to other models and with passage.
log <dig> normalized gene expression values at passage  <dig>   <dig> and  <dig> plotted for four probe sets; 205225_at , 206426_at , 201839_s_at , and 201746_at .
the p <dig> status is shown for 201746_at as wild type , mutant  or absent .
another approach to data mining involves plotting the extent of change in expression with passage.
to exemplify, analyses were performed on two groups of therapeutically relevant transcripts, those involved in drug resistance and those coding for select receptor tyrosine kinases .
for resistance genes, expression relative to other models at p <dig> was plotted  along with the change in expression from p <dig> to p <dig> .
several noteworthy trends were evident.
for hct- <dig>  a highly mdr drug-resistant cell line in culture, expression of the multidrug transporter abcb <dig>  was the highest relative to other lines at p <dig>  however by p <dig>  the expression had declined to that comparable to other tumors.
this suggests hct- <dig> tumors may acquire sensitivity to agents such as doxorubicin, paclitaxel and other mdr sensitive agents with serial in vivo passage  <cit> .
this finding is confirmed by in vivo efficacy data for paclitaxel against subcutaneously implanted hct- <dig> xenografts .
as suggested by the array data, differences in the response of p <dig> and p <dig> tumors to paclitaxel treatment were observed.
the p <dig> tumors showed progressive growth in spite of paclitaxel therapy .
in contrast, the p <dig> tumors responded to treatment with total growth inhibition .
comparison of tumor weights between the p <dig> vehicle and p <dig> paclitaxel-treated mice showed statistically significant differences at days  <dig>   <dig> and  <dig> with p values of  <dig> ,  <dig> , and  <dig> , respectively.
in contrast, there was no difference between the p <dig> vehicle-treated and paclitaxel-treated groups at any time point.
these data support the conclusion that hct- <dig> human colon tumor xenografts acquire paclitaxel sensitivity during serial in vivo passage.figure  <dig>
change in expression from p <dig> to p <dig> for a subset of transcripts involved in drug resistance.
a) log <dig> normalized expression values for each transcript in all models at p <dig>  b) change in log <dig> normalized expression for each transcript in all models from p <dig> to p <dig>  for each probe set, entries are formatted where red is the highest value, green is the lowest and the median is black.
expression of microsomal glutathione s-transferase  has been shown to confer resistance to cisplatin  <cit> .
in this analysis, expression of mgst <dig>  increased with passage in several cell lines such as lox imvi and nci-h <dig>  given the general trend toward increased expression from p <dig> to p <dig>  it could be surmised that increased resistance would be observed in serially passaged tumors.
this observation is consistent with our data, where evaluation of cisplatin in subcutaneous lox imvi xenografts showed sensitivity to cisplatin declines with serial in vivo passage.
when cisplatin was administered at the maximum tolerated dose to lox-imv <dig> tumor-bearing mice at p <dig>  p <dig> and p <dig>  the optimal percent test/control values were 19%, 41%, and 64%, respectively.
the %t/c is inversely related to the tumor sensitivity so the greater the tumor response the lower the %t/c.
a %t/c of 40% or lower is indicative of antitumor activity  <cit> .
thus, as predicted by the changes in mgst <dig> relative expression in lox imv <dig> tumors with serial in vivo passage, p <dig> tumors were highly sensitive while the p <dig> tumors were not.
the ranking of relative mgst <dig> expression levels at p <dig> shows a549/asc- <dig> and a <dig> have the greatest and molt- <dig> the lowest mgst <dig> expression.
this suggests cisplatin would be inactive against a <dig> tumors and active against molt- <dig> tumors.
this is borne out by in vivo sensitivity testing where molt- <dig> has a statistically significant reduction in tumor growth in mice receiving  <dig>  mg cisplatin/kg compared to vehicle controls  while a <dig> tumors do not respond even with an increased cisplatin dose  and a smaller initial starting tumor size .
interestingly, the reverse trend in mrna expression was observed in ca <dig> cells, where mgst <dig> was downregulated at p <dig>  here, although no xenograft data exists to confirm this, sensitivity to cisplatin could be predicted to increase with in vivo passage.
lastly increased expression of abcg <dig>  a transporter that enhances resistance to mitoxantrone, daunorubicin and doxorubicin  <cit>  was noted in ekvx cells from p <dig> to p <dig>
results in figure  <dig> show a similar analysis focused on a subset of cancer-related receptor tyrosine kinases.
again, several trends were evident.
for example, pc-3 m cells expressed the highest relative levels of kdr  at p <dig>  however, levels declined by p <dig>  an observation that could have consequences for evaluation of therapeutics targeting this pathway .
the melanoma cell lines m <dig> and malme-3 m expressed significant levels of kit   relative to other models at p <dig>  with serial passage, expression of kit declined slightly in malme-3 m by p <dig> whereas the levels were increased in m <dig> at p <dig>  conversely, a <dig> cells expressed low levels of kit at p <dig>  but expression increased markedly at p <dig>  these observations may have consequences for experiments where a c-kit inhibitor  is being evaluated.figure  <dig>
change in expression from p <dig> to p <dig> for a subset of transcripts coding for receptor tyrosine kinases .
a) log <dig> normalized expression values for each transcript in all models at p <dig>  b) change in log <dig> normalized expression for each transcript in all models from p <dig> to p <dig>  for each probe set, entries are formatted where red is the highest value, green is the lowest and the median is black.
a general metric of model stability
the prior analysis suggested that significant changes in transcript expression occurred in several models from p <dig> to p <dig>  therefore, we sought a general metric of stability for each xenograft model.
to achieve this, the number of transcripts showing >3-fold increase or >3-fold decrease  from p <dig> to p <dig> and p <dig> to p <dig> was determined for each of  <dig> models.
we reasoned the higher the stability of the model, the smaller the number of transcripts with changes in expression that would be observed between passages.
figure  <dig> illustrates the results of this analysis, where models such as hl- <dig>  and molt- <dig>  may be defined as highly stable, whereas nci-h <dig> and ekvx tumors are markedly altered at p <dig>  with approximately 50% of these changes occurring between p <dig> and p <dig>  from this analysis it is evident that protracted in vivo growth profoundly alters the transcriptome for most models.
generation of a simple metric of stability allows models to be ranked according to the degree of change.
whether these changes represent gradual adaptations to growth in a mouse microenvironment or selection-pressure promoting outgrowth of sub-clones remains to be determined.
however, it is interesting to note that a survey of genes  related to the epithelial-mesenchymal transition  identified widespread changes in several models with passage .
given the recognized effects of emt on drug sensitivity, this phenomenon may be worthy of further scrutiny  <cit> .figure  <dig>
ranking model stability.
for each model, genespring gx <dig> was used to generate a list of differentially expressed transcripts for p <dig> to p <dig> and p <dig> to p <dig> .
the number of differentially regulated transcripts at p <dig> to p <dig> and p <dig> to p <dig> was then plotted for each model and results sorted in terms of p <dig> to p <dig>  to generate a measure of model stability.
the cell line to xenograft transition
this dataset can be interrogated to monitor gene expression changes occurring during the immediate transition from in vitro to in vivo growth.
however, this analysis is complicated by potential interference from cross-hybridizing mouse mrna from the xenograft samples.
although cell sorting can remove mouse cell contamination  <cit> , an alternative strategy involves identifying probe sets on the affymetrix hg-u <dig> plus  <dig>  array with the potential to cross-hybridize with mouse mrna and excluding these from analysis or flagging them for additional evaluation.
to this end,  <dig> murine mrna samples , all performed in triplicate, were applied to the human affymetrix hg-u <dig> plus  <dig>  arrays to generate a list of cross-hybridizing probe sets .
mouse rnas of varied origin were used to provide diversity in the detection of cross-hybridizing events.
results demonstrated a total of  <dig> probe sets have the potential to bind mouse mrna.
this includes all possible binding events ranging from just one of the mouse samples cross hybridizing to a probe set to the cross hybridization of all five of the different murine samples.
although relatively large, this list likely includes probe sets that bind non-specifically to any cdna population along with those mrnas showing high homology between mouse and human.
increasing the stringency to  <dig> and  <dig> out of  <dig> murine samples that must bind to a particular probe set before that probe is excluded from the analysis reduces the number of probe sets with the potential to cross-hybridize to murine rna by 3-fold .
to provide flexibility to the investigator the list of transcripts with the total number of mouse rna samples found to cross-hybridize to each probe set is shown in additional file  <dig>
as an example of the in vitro to in vivo transition, table  <dig> shows the results from pairwise analysis of prostate lines  with their respective p <dig> xenografts.
the  <dig> highest up-regulated transcripts before removal of the  <dig> cross hybridizing probe sets are shown in table  <dig>  with transcripts showing potential mouse artifacts identified.
hemoglobin epsilon  <dig>   is a probable cross-hybridization event that is important because pc- <dig> cells are not expected to express this mrna.
other genes of note that were removed as a result of mouse cross-hybridization include serpinb <dig>  cxcl <dig>  col3a <dig> and adm. all with the exception of serpinb <dig> are genes of the stromal compartment .
removal of the mouse cross-hybridizing probes provides greater confidence that observations such as increased expression of il- <dig> , cxcl <dig> , and angptl <dig>  represent genuine adaptations of pc-3/pc3-m cells to in vivo growth.
these upregulated genes point toward activation of pathways involved in invasion and metastasis .
table  <dig> shows david gene ontology  analysis for the top  <dig> up-regulated genes following removal of the mouse cross-hybridizing probes.
consistent with the literature  genes involved in the extracellular matrix , cell adhesion, chemotaxis, cytokine, immune response, tumor-host interaction and growth factor induced signal transduction were up-regulated in xenograft tumors relative to those cells grown in vitro.
a spreadsheet of fold-change data for the p <dig> to p <dig> transition  is shown in additional file  <dig>  similar analyses for the p <dig> to p <dig> transition for the top  <dig> up-regulated genes and respective david go analysis for  <dig> of the  <dig> model classes  can be found in additional file  <dig> table  <dig>
top  <dig> up-regulated probe sets in the prostate tumor type
left table includes all probe sets, the mouse rna binding probe sets are identified by the number of cross hybridizing mouse tissue probes that occurred .
right side of table shows the top  <dig> human up-regulated probe sets following removal of the mouse component.
david gene ontology  functional annotation on the prostate tumor models during their transition from in vitro to in vivo growth
CONCLUSIONS
the evaluation of cancer therapeutics using xenograft models is a resource-intensive and time-consuming endeavor.
currently, molecular profiling with large-scale genetic, proteomic and metabolic screening technologies is emerging as a powerful tool to improve and guide model selection.
in this study, cdna microarray data was generated for  <dig> xenograft models routinely used within the developmental therapeutics program at the nci.
the majority of these tumor cell lines are available to the research community through the dctd tumor repository  thus allowing this data to provide guidance for other research studies.
aside from the obvious utility of ranking models in terms of transcript expression for specific genes of interest, analysis demonstrated that prolonged in vivo passage markedly alters the transcriptome of many models.
this observation emphasizes the importance of maintaining passage consistency to minimize experimental artifacts.
similarly, these findings provide one explanation for the difficulties reported in reproducing experimental data since the methods for generating test tumors can impact the study profoundly  <cit> .
these data are deposited at http://dtp.nci.nih.gov/microxeno/download.html and in the gene expression omnibus  under accessions gse <dig> and gse <dig>  all subsequent data releases will be deposited in the same locations.

 xenograft models remain a cornerstone technology in the development of anti-cancer agents. the ability of immunocompromised rodents to support the growth of human tumors provides an invaluable transition between in vitro testing, pre-clinical development and clinical trials. for decades, data from xenograft models has informed development decisions with respect to dosing schedules, pharmacokinetics/pharmacodynamics and potential toxicities. yet several challenges remain, including understanding the extent to which well-characterized xenograft models replicate the biology and growth characteristics of patient disease. furthermore, with the paradigm shift towards agents with specific molecular targets and personalized medicine, a comprehensive molecular profile for xenograft models may be essential for successful in vivo evaluation. to this end, considerable resources are being applied to the generation of novel xenograft models combined with molecular profiling of existing models. within the developmental therapeutics program of the national cancer institute, the primary in vitro assay used to detect potential anti-cancer activity is the nci- cell line screen. to date, this panel of human tumor lines has been used to evaluate almost one hundred thousand pure compounds and approximately fifty thousand natural product extracts. many of these cell lines will grow as subcutaneous xenografts, thus cell lines sensitive to an agent in vitro were often subjected to further analyses in xenografts derived from those cell lines. the nci- panel has been extensively molecularly characterized, with data available for gene expression, dna variation, protein expression, dna methylation, microrna expression and metabolomics. the compare algorithm allows investigators to correlate nci- drug activity profiles with all other open agents in the database and with molecular characteristics of the cells. while the in vitro grown cells have been characterized, the corresponding subcutaneous xenografts had not. however, other studies have succeeded in molecular profiling of other xenografts. these predominantly cdna and tissue-array based studies lack the potential for retrospective cross-platform analysis that underscores the nci- cell line set. the microxeno project was initiated to generate genome-wide cdna microarray data for all subcutaneous xenograft models currently used within the dtp. comprehensive transcriptomic analysis will help address questions such as: can expression of molecular target help inform model selection for a given agent or target, or to what extent and by what manner do specific cell line tumors adapt during prolonged growth in vivo? the work presented here provides a reference dataset that can be used to confirm the genetic characteristics and stability of models going forward. this ongoing project will ultimately encompass over models, with data from cell lines and successive xenograft passages. the panel includes tumor cell lines from diverse histological origins including leukemia/lymphoma, non-small cell lung, colon, cns, melanoma, ovarian, renal, prostate, liver, gastric, head and neck, pancreatic, and breast cancer. it also includes, but is not limited to, many of the cell lines in the nci- panel. here we describe the procedures and quality control criteria used to derive microxeno release. the study utilizes affymetrix hg-u plus arrays, capable of identifying more that human transcripts from > probe sets. the current release encompasses experiments with each consisting of data from the originating cell lines and the resulting xenografts at passages and. in addition, we detail several approaches to utilize the data to predict possible biological outcomes. we propose that this dataset will improve selection and execution of subcutaneous xenograft experiments during the evaluation of cancer therapeutics. as this study is based primarily on lines from the nci- panel, the potential also exists for integration with other nci- datasets. rapid dissemination of this data will also permit the extramural community to perform meta-analyses in support of their own in vivo studies.  this study focused on generating pan-genomic cdna microarray data for diverse xenograft models from the time of initial implantation to the tenth passage using the affymetrix hg-u plus array. each experiment comprised the originating in vitro cell lines along with tumor samples from in vivo passages and for each in vivo passage, five tumors were harvested. the human xenograft experiments contained within this release led to the generation of arrays. table  details the specific cell lines along with tumor types, histology, host strain and any special growth requirements or irregularities.table tumor cell lines, host mice, protocol variances tumor typea breast cervical cns colon gastric leukemia/ lymphoma liver lung melanoma ovarian pancreatic prostate renal atumor cells derived from the 4th in vitro passage were innoculated subcutaneously into mice. tumors were passaged consecutive times in mice. at passages and, tumors were harvested, cut into small pieces and flash frozen in liquid nitrogen. samples were then processed as described in methods. for comparative purposes, samples of the in vitro cultivated cells at passage were also prepared for microarray analysis. b3 mg/kg q7d sc estradiol. cmatrigel  mg/ml p only. dher2/erbb transfectant of mda-mb- epc subline isolated from liver metastasis in mice. microarray data quality control multiple layers of quality control criteria were applied to the dataset. first, the cel files were visually inspected using dchip to identify arrays with structural defects. significant physical issues were identified in one mda-mb-231 t p sample, which was removed. next,.cel files were uploaded and analyzed en masse using the qc tools contained within genespring gx. results demonstrated one replicate from the pc- p had control probe errors and it was excluded. the hybridization was repeated using the original pc- p rna sample on a new chip that yielded satisfactory results and was included in further analyses. lastly, principal component analysis was used to identify outliers. for example, results shown in figure 1b identify one population of arrays segregated from the primary component. closer inspection identified these.cel files as passages and of sf- and sf- this finding suggested a conserved problem with late passage for these lines. we then investigated whether displacement of tumor cells by an outgrowth of mouse cells was responsible for the observed effects. results from endpoint pcr using mouse and human specific primers directed against ptger showed the first in vivo passage of sf- and sf- tumors contained both mouse and human genomic dna as expected, but all tumors harvested from 4th and 10th serial passages were devoid of human genomic dna. the sf- and sf- models differed from others in the study in that they utilized matrigel® to initially establish tumor growth in passage and they were implanted into nod.scid/ncr mice since growth in athymic nu/nuncr mice was unsuccessful. it is recognized that nod.scid/ncr mice have a propensity for spontaneous tumor formation and also it is reasonable to speculate that matrigel® mouse sarcoma cells) may encourage spontaneous host cell outgrowth. this emphasizes the need for routine monitoring of mouse outgrowth especially when matrigel®, and possibly a nod.scid background are employed. although mouse outgrowth was not a problem for the remaining models, this phenomenon should be an important consideration for studies involving serial passage of tumor fragments over extended periods of time. in light of these results, p and p samples for sf- and sf- were not included in this data release.figure study design and quality control. a) control probe signal profiles were generated for affymetrix hg-u plus array.cel files. the single outlier is highlighted. b) 3d principal component analysis was performed on all.cel files; a population of outliers representing p and p passages for sf- and sf- glioma lines is shown in red. control probe profiles and 3d pca were generated using genespring gx. c) endpoint pcr of genomic dna from sf- and sf- tumors at p p and p using mouse or human-specific ptger primers. genomic dna from b16f and lncap cell lines were included as positive controls, ntc = no template control. data is representative of all tumors processed from these xenografts. hierarchical clustering qc all experiments were subjected to hierarchical clustering to confirm similarity in microarray signatures for cell lines and subsequent xenograft passages. fold-change data for each parameter was used to generate the hierarchical cluster shown in additional file this analysis confirmed that for the majority of experiments, the originating cell lines and subsequent in vivo passages clustered together. however, p data for caki- sn12c and rxf renal lines were shown to cluster together, suggesting a high degree of similarity between these samples. the identity of these tumors was confirmed by repeating the identifiler® str analyses. thus, the clustering of these p renal tumors of distinct cell line origins had a biological basis and was not the result of technical errors. other exceptions involved the co-clustering of mda-mb- and mda-n along with a similar trend for a and a549/asc-. these observations were anticipated given that mda-n is derived from mda-mb- and a549/asc- is a tumorigenic clone of a additionally, two breast cancer cell lines did not cluster together nor did three ovarian lines. closer scrutiny provides a plausible explanation given these lines differ significantly within their categories. specifically, mcf is an estrogen-dependent tumor whereas mda-mb-231 t is triple negative. similarly, cp and ovcar- are ovarian carcinomas whereas ovcar- is an adenocarcinoma. ovcar- is also er + while ovcar- is er negative and cp is a cisplatin-resistant subline of a following quality control, the final dataset comprised complete experiments and partial experiments for a total of arrays. monitoring changes in transcript expression the central goal of this study was to ascertain expression levels for any given transcript across all in vivo models and with successive passage. to this end, normalized gene expression data were generated for all conditions. throughout the study, when multiple probe sets were present for the same transcript, the jetset methodology was used to select the most robust candidate. data for four example probe sets; 205225_at, 206426_at, 201839_s_at, and 201746_at at p p and p are plotted in figure  results showed that mcf cells expressed the highest level of esr across the panel, consistent with their known estrogen receptor positive status and their absolute dependence on exogenous estradiol for growth in mice. furthermore, esr expression was shown to increase modestly with passage, suggesting serially passaged tumors remain a valid target for estrogen receptor antagonists. mlana is a melanoma-restricted antigen and results show expression to be limited primarily to the melanoma cell lines. mlana expression was relatively consistent with passage, apart from uacc- where levels modestly increase at p similarly, epcam is highly expressed on many epithelial cells and results show considerable variation in mrna expression levels even between epithelial lines. while most tumors had stable expression of epcam from p to p there were a few models with notable changes including a caki- and nci-h the final example, tp53/p serves to show the value of integrating relative expression data with pre-existing genetic information. this tumor suppressor and master regulator of the cell cycle is frequently mutated or deleted in tumors. this analysis confirmed the relative lack of p expression in p53-null hl cells. however, there was considerable variability in levels of expression for models with mutant p this information could be useful for studies of agents targeting cells with mutant/deleted p e.g., the wee inhibitor mk- or mutant p oncolytic adenovirus. overall, this analysis serves to illustrate the potential of these data within therapeutic studies and provide evidence that mrna expression can change markedly with in vivo passage.figure transcript expression relative to other models and with passage. log normalized gene expression values at passage and plotted for four probe sets; 205225_at, 206426_at, 201839_s_at, and 201746_at. the p status is shown for 201746_at as wild type, mutant or absent. another approach to data mining involves plotting the extent of change in expression with passage. to exemplify, analyses were performed on two groups of therapeutically relevant transcripts, those involved in drug resistance and those coding for select receptor tyrosine kinases. for resistance genes, expression relative to other models at p was plotted along with the change in expression from p to p. several noteworthy trends were evident. for hct- a highly mdr drug-resistant cell line in culture, expression of the multidrug transporter abcb was the highest relative to other lines at p however by p the expression had declined to that comparable to other tumors. this suggests hct- tumors may acquire sensitivity to agents such as doxorubicin, paclitaxel and other mdr sensitive agents with serial in vivo passage. this finding is confirmed by in vivo efficacy data for paclitaxel against subcutaneously implanted hct- xenografts. as suggested by the array data, differences in the response of p and p tumors to paclitaxel treatment were observed. the p tumors showed progressive growth in spite of paclitaxel therapy. in contrast, the p tumors responded to treatment with total growth inhibition. comparison of tumor weights between the p vehicle and p paclitaxel-treated mice showed statistically significant differences at days and with p values of,, and, respectively. in contrast, there was no difference between the p vehicle-treated and paclitaxel-treated groups at any time point. these data support the conclusion that hct- human colon tumor xenografts acquire paclitaxel sensitivity during serial in vivo passage.figure change in expression from p to p for a subset of transcripts involved in drug resistance. a) log normalized expression values for each transcript in all models at p b) change in log normalized expression for each transcript in all models from p to p for each probe set, entries are formatted where red is the highest value, green is the lowest and the median is black. expression of microsomal glutathione s-transferase has been shown to confer resistance to cisplatin. in this analysis, expression of mgst increased with passage in several cell lines such as lox imvi and nci-h given the general trend toward increased expression from p to p it could be surmised that increased resistance would be observed in serially passaged tumors. this observation is consistent with our data, where evaluation of cisplatin in subcutaneous lox imvi xenografts showed sensitivity to cisplatin declines with serial in vivo passage. when cisplatin was administered at the maximum tolerated dose to lox-imv tumor-bearing mice at p p and p the optimal percent test/control values were 19%, 41%, and 64%, respectively. the %t/c is inversely related to the tumor sensitivity so the greater the tumor response the lower the %t/c. a %t/c of 40% or lower is indicative of antitumor activity. thus, as predicted by the changes in mgst relative expression in lox imv tumors with serial in vivo passage, p tumors were highly sensitive while the p tumors were not. the ranking of relative mgst expression levels at p shows a549/asc- and a have the greatest and molt- the lowest mgst expression. this suggests cisplatin would be inactive against a tumors and active against molt- tumors. this is borne out by in vivo sensitivity testing where molt- has a statistically significant reduction in tumor growth in mice receiving  mg cisplatin/kg compared to vehicle controls while a tumors do not respond even with an increased cisplatin dose and a smaller initial starting tumor size. interestingly, the reverse trend in mrna expression was observed in ca cells, where mgst was downregulated at p here, although no xenograft data exists to confirm this, sensitivity to cisplatin could be predicted to increase with in vivo passage. lastly increased expression of abcg a transporter that enhances resistance to mitoxantrone, daunorubicin and doxorubicin was noted in ekvx cells from p to p results in figure  show a similar analysis focused on a subset of cancer-related receptor tyrosine kinases. again, several trends were evident. for example, pc-3 m cells expressed the highest relative levels of kdr at p however, levels declined by p an observation that could have consequences for evaluation of therapeutics targeting this pathway. the melanoma cell lines m and malme-3 m expressed significant levels of kit relative to other models at p with serial passage, expression of kit declined slightly in malme-3 m by p whereas the levels were increased in m at p conversely, a cells expressed low levels of kit at p but expression increased markedly at p these observations may have consequences for experiments where a c-kit inhibitor is being evaluated.figure change in expression from p to p for a subset of transcripts coding for receptor tyrosine kinases. a) log normalized expression values for each transcript in all models at p b) change in log normalized expression for each transcript in all models from p to p for each probe set, entries are formatted where red is the highest value, green is the lowest and the median is black. a general metric of model stability the prior analysis suggested that significant changes in transcript expression occurred in several models from p to p therefore, we sought a general metric of stability for each xenograft model. to achieve this, the number of transcripts showing >3-fold increase or >3-fold decrease from p to p and p to p was determined for each of models. we reasoned the higher the stability of the model, the smaller the number of transcripts with changes in expression that would be observed between passages. figure  illustrates the results of this analysis, where models such as hl- and molt- may be defined as highly stable, whereas nci-h and ekvx tumors are markedly altered at p with approximately 50% of these changes occurring between p and p from this analysis it is evident that protracted in vivo growth profoundly alters the transcriptome for most models. generation of a simple metric of stability allows models to be ranked according to the degree of change. whether these changes represent gradual adaptations to growth in a mouse microenvironment or selection-pressure promoting outgrowth of sub-clones remains to be determined. however, it is interesting to note that a survey of genes related to the epithelial-mesenchymal transition identified widespread changes in several models with passage. given the recognized effects of emt on drug sensitivity, this phenomenon may be worthy of further scrutiny.figure ranking model stability. for each model, genespring gx was used to generate a list of differentially expressed transcripts for p to p and p to p. the number of differentially regulated transcripts at p to p and p to p was then plotted for each model and results sorted in terms of p to p to generate a measure of model stability. the cell line to xenograft transition this dataset can be interrogated to monitor gene expression changes occurring during the immediate transition from in vitro to in vivo growth. however, this analysis is complicated by potential interference from cross-hybridizing mouse mrna from the xenograft samples. although cell sorting can remove mouse cell contamination, an alternative strategy involves identifying probe sets on the affymetrix hg-u plus array with the potential to cross-hybridize with mouse mrna and excluding these from analysis or flagging them for additional evaluation. to this end, murine mrna samples, all performed in triplicate, were applied to the human affymetrix hg-u plus arrays to generate a list of cross-hybridizing probe sets. mouse rnas of varied origin were used to provide diversity in the detection of cross-hybridizing events. results demonstrated a total of probe sets have the potential to bind mouse mrna. this includes all possible binding events ranging from just one of the mouse samples cross hybridizing to a probe set to the cross hybridization of all five of the different murine samples. although relatively large, this list likely includes probe sets that bind non-specifically to any cdna population along with those mrnas showing high homology between mouse and human. increasing the stringency to and out of murine samples that must bind to a particular probe set before that probe is excluded from the analysis reduces the number of probe sets with the potential to cross-hybridize to murine rna by 3-fold. to provide flexibility to the investigator the list of transcripts with the total number of mouse rna samples found to cross-hybridize to each probe set is shown in additional file as an example of the in vitro to in vivo transition, table  shows the results from pairwise analysis of prostate lines with their respective p xenografts. the highest up-regulated transcripts before removal of the cross hybridizing probe sets are shown in table  with transcripts showing potential mouse artifacts identified. hemoglobin epsilon is a probable cross-hybridization event that is important because pc- cells are not expected to express this mrna. other genes of note that were removed as a result of mouse cross-hybridization include serpinb cxcl col3a and adm. all with the exception of serpinb are genes of the stromal compartment. removal of the mouse cross-hybridizing probes provides greater confidence that observations such as increased expression of il-, cxcl, and angptl represent genuine adaptations of pc-3/pc3-m cells to in vivo growth. these upregulated genes point toward activation of pathways involved in invasion and metastasis. table  shows david gene ontology analysis for the top up-regulated genes following removal of the mouse cross-hybridizing probes. consistent with the literature genes involved in the extracellular matrix, cell adhesion, chemotaxis, cytokine, immune response, tumor-host interaction and growth factor induced signal transduction were up-regulated in xenograft tumors relative to those cells grown in vitro. a spreadsheet of fold-change data for the p to p transition is shown in additional file similar analyses for the p to p transition for the top up-regulated genes and respective david go analysis for of the model classes can be found in additional file table top up-regulated probe sets in the prostate tumor type left table includes all probe sets, the mouse rna binding probe sets are identified by the number of cross hybridizing mouse tissue probes that occurred. right side of table shows the top human up-regulated probe sets following removal of the mouse component. david gene ontology functional annotation on the prostate tumor models during their transition from in vitro to in vivo growth  the evaluation of cancer therapeutics using xenograft models is a resource-intensive and time-consuming endeavor. currently, molecular profiling with large-scale genetic, proteomic and metabolic screening technologies is emerging as a powerful tool to improve and guide model selection. in this study, cdna microarray data was generated for xenograft models routinely used within the developmental therapeutics program at the nci. the majority of these tumor cell lines are available to the research community through the dctd tumor repository thus allowing this data to provide guidance for other research studies. aside from the obvious utility of ranking models in terms of transcript expression for specific genes of interest, analysis demonstrated that prolonged in vivo passage markedly alters the transcriptome of many models. this observation emphasizes the importance of maintaining passage consistency to minimize experimental artifacts. similarly, these findings provide one explanation for the difficulties reported in reproducing experimental data since the methods for generating test tumors can impact the study profoundly. these data are deposited at http://dtp.nci.nih.gov/microxeno/download.html and in the gene expression omnibus under accessions gse and gse all subsequent data releases will be deposited in the same locations. 
given that gene expression results indicated some models undergo profound changes with in vivo passage, a general metric of stability was generated so models could be ranked accordingly. removal of the murine artifacts followed by pairwise analysis of in vitro cells with respective passage xenografts and go analysis illustrates the complex interplay that each model has with the host microenvironment. to illustrate mining strategies supporting therapeutic studies, transcript expression was determined: 1) relative to other models, 2) with successive in vivo passage, and 3) during the in vitro to in vivo transition. xenograft modelsaffymetrix hg-u plus arraycdna microarraynci- cell line screentranscriptomic stabilitytranscriptomic expressionin vitro to in vivo transitionissue-copyright-statement© the author 2014 the utility of monitoring changes in gene expression with extended in vivo tumor passages was illustrated by focused studies of drug resistance mediators and receptor tyrosine kinases. ranking models according to relative transcript expression in vivo has the potential to improve initial model selection. forty-nine human tumor xenografts at in vivo passages and were subjected to cdna microarray analysis yielding a dataset of affymetrix hg-u plus arrays. this study provides strategies to aid selection of xenograft models for therapeutic studies. these data highlight the dynamic nature of xenograft models and emphasize the importance of maintaining passage consistency throughout experiments. development of cancer therapeutics partially depends upon selection of appropriate animal models. therefore, improvements to model selection are beneficial. lastly, changes occurring during transition from in vitro to in vivo growth may have important consequences for therapeutic studies since targets identified in vitro could be over- or under-represented when tumor cells adapt to in vivo growth. noteworthy observations included a significant decline in hct- colon xenograft abcb transporter expression and increased expression of the kinase kit in a with serial passage. for example, combining p tumor expression data with mutational status could guide selection of tumors for therapeutic studies of agents where p status purportedly affects efficacy.
 development of cancer therapeutics partially depends upon selection of appropriate animal models. therefore, improvements to model selection are beneficial.  forty-nine human tumor xenografts at in vivo passages and were subjected to cdna microarray analysis yielding a dataset of affymetrix hg-u plus arrays. to illustrate mining strategies supporting therapeutic studies, transcript expression was determined: 1) relative to other models, 2) with successive in vivo passage, and 3) during the in vitro to in vivo transition. ranking models according to relative transcript expression in vivo has the potential to improve initial model selection. for example, combining p tumor expression data with mutational status could guide selection of tumors for therapeutic studies of agents where p status purportedly affects efficacy. the utility of monitoring changes in gene expression with extended in vivo tumor passages was illustrated by focused studies of drug resistance mediators and receptor tyrosine kinases. noteworthy observations included a significant decline in hct- colon xenograft abcb transporter expression and increased expression of the kinase kit in a with serial passage. these trends predict sensitivity to agents such as paclitaxel and imatinib would be altered with extended passage. given that gene expression results indicated some models undergo profound changes with in vivo passage, a general metric of stability was generated so models could be ranked accordingly. lastly, changes occurring during transition from in vitro to in vivo growth may have important consequences for therapeutic studies since targets identified in vitro could be over- or under-represented when tumor cells adapt to in vivo growth. a comprehensive list of mouse transcripts capable of cross-hybridizing with human probe sets on the hg-u plus array was generated. removal of the murine artifacts followed by pairwise analysis of in vitro cells with respective passage xenografts and go analysis illustrates the complex interplay that each model has with the host microenvironment.  this study provides strategies to aid selection of xenograft models for therapeutic studies. these data highlight the dynamic nature of xenograft models and emphasize the importance of maintaining passage consistency throughout experiments. electronic supplementary material the online version of this article contains supplementary material, which is available to authorized users. keywords xenograft modelsaffymetrix hg-u plus arraycdna microarraynci- cell line screentranscriptomic stabilitytranscriptomic expressionin vitro to in vivo transitionissue-copyright-statement© the author 2014 