BACKGROUND
pancreatic ductal adenocarcinoma  is the fourth leading cause of cancer death in the united states  <cit> .
the five-year survival rate is a dismal 5%, as effective treatment regimens are limited  <cit> .
a better understanding of the underlying disease biology is needed to develop new and successful treatment strategies to manage this deadly disease.
several key molecular genetic alterations in pancreatic cancer have been identified  <cit> .
activating mutations of kras occur in 95% of cases.
the cdkn2a locus, encoding p16ink4a and p14arf, which respectively intersect the rb and p <dig> pathways, is homozygously deleted in 80% of tumors.
tp <dig> is itself inactivated, usually through point mutation, in 55% of cases.
smad <dig>  a central mediator of tgfβ signaling, is deleted in approximately 50% of cases.
furthermore, tgfbr <dig>  its upstream receptor, is deleted in 20% of tumors, underscoring a central importance of this signaling pathway in pancreatic cancer.
myc is amplified in approximately 30% of cases.
recently, deletions and mutations in five different subunits of the swi/snf chromatin remodeling complex have been found to occur in about a third of cases  <cit> .
however, despite what is already known, recent surveys of the pancreatic cancer genome have identified scores of additional candidate cancer genes that merit further investigation  <cit> .
with the advent of dna microarrays and “next-generation” dna sequencing, the field of genomics has transformed our ability to study diseases like cancer on an “omic” scale.
over the past decade, these technologies have spurred structural studies producing a compendium of cancer alterations, including dna mutations, deletions, amplifications, and rearrangements.
yet, because of the sheer volume of data, such studies have far outpaced our ability to functionally evaluate candidate cancer genes  <cit> .
the development of rna interference  techniques has accelerated our capacity to study knockdown phenotypes and infer the function and mechanism of disease genes  <cit> .
while traditionally used to characterize single genes at a time, several groups have adapted the technology to use small interfering rna  or short hairpin rna  libraries for high-throughput screens  <cit> , including in pancreatic cancer  <cit> .
these large-scale, highly parallel efforts provide the potential to functionally annotate genes on an “omic” scale.
here, we describe a high-throughput functional interrogation of the pancreatic cancer genome using an shrna-based screen.
we simultaneously evaluate  <dig> candidate pancreatic cancer genes, nominated from genomic profiles, across  <dig> genetically diverse cell lines.
after integrating the functional and genomic data, we further characterize nine top candidates, both uncovering new pancreatic cancer biology and validating an integrative approach for the functional annotation of cancer genomes.
methods
cell lines
cancer cell lines were obtained directly from the american type culture collection, and grown in rpmi- <dig> high-glucose media  supplemented with 10% fetal bovine serum .
hpde cells  <cit>  were obtained from dr. ming tsao , and grown in keratinocyte serum-free media .
pooled shrna lentiviral library screen
the shrna screen, schematically depicted in figure  <dig> , was adapted from published protocols  <cit> .
potential advantages of a pooled  screen include economies of scale and discernment of subtle fitness effects by competitive growth over many days.
the  <dig> targeted genes were selected based on the identification of recurrent structural abnormalities  in pancreatic cancer genomes  <cit> .
these abnormalities are listed for each gene in additional file  <dig>  gipz lentiviral shrnamir constructs targeting these genes  were obtained from open biosystems/thermo scientific; catalog numbers are listed in additional file  <dig>  the  <dig> pgipz shrnamir plasmid dnas were combined at equimolar concentration into a single pool.
the shrna dna pool was then used to transfect 293t cells, together with a trans lentiviral packaging mix .
pooled shrna lentiviral supernatant was collected 48 hrs later, and frozen in aliquots to improve screen reproducibility.
the lentiviral library was then used to infect target cell lines at low multiplicity of infection , so that most cells contained a single shrna knocking down the expression of a single gene.
additionally, enough cells were infected to provide an average representation of approximately  <dig>  lentiviral integrations  for each of the  <dig> shrnas in the library, mitigating potential artifacts from specific integration sites or from multiple integrations  <cit> .
to infect target cell lines, lentivirus was diluted in serum/antibiotic-free media containing 10 μg/ml polybrene .
cells were spun at 30°c for 1 hr at  <dig>  rpm, allowed to recover for 4 hrs , spun again for an additional 1 hr, and then the media replaced with complete rpmi- <dig> growth media.
all target cell line infections were carried out minimally in triplicate .
two days post infection, a fraction of the infected cells was harvested for an initial time point , and puromycin selection  was then initiated for the remaining cells.
cells were cultured for an additional 4 weeks in the presence of selective media.
care was taken not to allow the cells to become too confluent or to split too thinly.
cells were periodically harvested, including the last time point , which was the standard comparison point for the screen data presented.
genomic dna was isolated from harvested cells, sheared ten times through a  <dig> gauge needle, and subsequently used as template for pcr amplification of library shrna hairpins.
sufficient genomic dna template was included in the pcr reaction to ensure an approximate  <dig> -fold average representation of each library shrna hairpin , thereby maintaining the initial ~ <dig> -fold representation of integrations.
pcr primers common to the shrnamir backbone vector and bounding the half hairpin target sequence were as follows: forward 5′-tagtgaagccacagatgta-3′; reverse 5′-atgtatcaaagagatagcaaggtattcag-3′.
to deconvolute shrna representation in the t = 4 weeks vs. t =  <dig> cell pools, gel-purified pcr products were differentially labeled and co-hybridized  to a custom agilent microarray designed  to include probes complementary to shrna hairpin sequences.
microarrays were imaged and fluorescence intensities extracted.
for each microarray, log <dig> background-subtracted fluorescence ratios were globally normalized .
unless otherwise specified, screen data reported represent the average ratios from replicate cell line infections.
screen data analysis and validation
high-confidence on-target shrnas/phenotypes were identified using a new analytical approach , based on finding two or more different shrnas targeting the same gene and displaying concordant enrichment/depletion profiles across the cell lines .
custom perl scripts were used to calculate the pearson correlation coefficient between shrnas targeting the same genes, and also to permute cell line identities to generate the randomized null distribution of correlations.
to define meaningful correlations, we determined false discovery rates  as the ratio of false positives  to observed positives at or above any given correlation cutoff.
for validation, q-rt-pcr was performed using assay-on-demand taqman probes and reagents .
catalog numbers for probes include: nup <dig>  and klf <dig> .
western blots were done on whole cell lysates, using the following primary antibodies: myc , pan-ras , nup <dig> , gapdh , smurf <dig> .
densitometry calculations were carried out using publicly available imagej software.
for sirna knockdown, on-targetplus smartpool sirnas were obtained from thermo scientific: kras , smurf <dig> , nup <dig> , klf <dig> , non-targeting control .
cell growth/viability assays were done using a modified wst- <dig> protocol as previously described  <cit> .
in each assay, a full time course was performed, though usually only day  <dig> is shown for brevity.
array-based comparative genomic hybridization  data
findings from the screen were interpreted in the context of previously published acgh data  <cit>  .
briefly, that data set comprises agilent 244 k cgh array profiles from  <dig> pancreatic cancers .
tumor/normal fluorescence ratios were normalized and mapped onto the genome  using agilent software.
RESULTS
targeted shrna screen
in pancreatic  cancer genomes, loci that are recurrently amplified or deleted are likely enriched for known or novel cancer genes  <cit> .
typically, each such locus is studied individually to discover the driver gene.
in an effort to accelerate this process, we developed a pooled shrna screening strategy to simultaneously evaluate  <dig> candidate pancreatic cancer genes that together represent  <dig> different loci of recurrent dna amplification or deletion; thus the genes selected included both candidate oncogenes and tumor suppressors .
most of the  <dig> candidates were focally amplified or deleted in a subset of cancers, and some were also reported to carry mutations   <cit> .
a few known cancer genes  were also included in the screen as positive controls.
the pooled shrna screen was carried out as a competitive growth/viability assay.
the general workflow, adapted from schlabach et al.
<cit> , is depicted in figure  <dig> and described in more detail in methods.
in brief, pancreatic cancer cell lines were infected with a pooled shrna lentiviral library comprising  <dig> shrnas targeting the  <dig> genes  .
infections were done at low multiplicity of infection, ensuring that most cells harbored a single shrna knocking down the expression of a single gene.
the pooled, infected cells were then cultured for four weeks, after which depleted or enriched shrnas  were identified by pcr amplification of shrna hairpins and comparative hybridization  to a custom hairpin microarray.
the shrna library screen was carried out on ten different cell lines .
these included seven genetically-diverse pancreatic cancer cell lines that together harbor the vast majority of copy number alterations from which the  <dig> genes were selected.
we also included a single immortalized, non-tumorigenic human pancreatic ductal epithelial  cell line  <cit>  to facilitate discovery of tumor suppressor genes .
lastly, we also screened two breast cancer cell lines to help distinguish genome-specific from generic essential genes .
the raw and cell line-averaged screening data are available in additional files  <dig> and  <dig>
screen analysis and validation
the pooled shrna library screen yielded high quality and reproducible data, as supported by multiple lines of evidence.
first, replicate screens of each cell line showed good correlation; the average pair-wise pearson correlation coefficients  for cell line replicates ranged from  <dig> - <dig>  .
the two cell lines  with the lowest r-values were those with the least shrna library representation; however, this was mitigated by more screen replicates .
notably, in an unsupervised analysis of the shrna depletion/enrichment data, cell line replicates most often clustered together .
second, time course samplings, done for a subset of the cell lines, demonstrated consistently increasing shrna depletion  over time .
third, we noted that distinct shrnas targeting the same gene often exhibited correlated growth phenotypes  across the panel of cell line screened .
we capitalized on this last observation to define “high-confidence” on-target knockdown phenotypes, an approach we termed copote .
when analyzing hundreds of shrnas, it is possible that two different shrnas targeting the same gene have a similar growth phenotype  just by random chance.
therefore, to correct for multiple hypothesis testing, we compared the distribution of observed pearson correlations to that from randomly permuted data .
notably, we observed a significant rightward shift in the observed distribution of correlations, indicating an enrichment of shrnas targeting the same gene  above that expected by chance; false discovery rates  are reported in additional file  <dig>  of the  <dig> genes included in the screen  represented by two or more shrnas and therefore evaluable), we identified  <dig> genes with “high confidence” knockdown phenotypes, defined by having at least two different shrnas exhibited significantly correlated depletion/enrichment profiles  across the ten cell lines.
we note that other approaches have been used to leverage information from multiple shrnas targeting the same gene, including redundant sirna activity  analysis  <cit> , rnai gene enrichment ranking   <cit> , and the gene activity ranking profile  score  <cit> .
all of these methods consider either the top-most depleted shrna or all shrnas for a given gene.
our approach is fundamentally different in that we consider all shrna pairs, therefore focusing primarily on the evidence for correlated  phenotype rather than on the strength of shrna depletion.
focusing primarily on the  <dig> high-confidence genes, we next validated knockdown for a subset of biologically-interesting genes.
we included some known pancreatic cancer genes, but mainly focused on novel genes with biological functions plausibly related to pancreatic cancer, and also demonstrating logical connections to the underlying genomic data, e.g.
shrna depletion for amplified candidate oncogenes.
validation was done by transducing individual  shrnas, or by transfecting independent sirnas , and then verifying target knockdown by rt-pcr and/or western blot .
for known pancreatic cancer oncogenes and tumor suppressor genes, finding the expected growth phenotypes  provided additional screen validation.
observations on known cancer genes
among the high-confidence shrnas/phenotypes, several shrnas targeting known oncogenes showed the anticipated pattern of depletion  .
for example, three different knockdown-validated  <cit>  shrnas targeting the kras oncogene were generally depleted across the panel of cell lines, though with some cell lines  showing substantially more depletion than others  .
on-target knockdown of kras and consequent reduced cell viability were verified using independent kras-targeting sirnas .
in pancreatic cancer, kras frequently harbors activating point mutations and may be amplified and/or overexpressed.
notably, in the cell line panel there was a good correlation of kras-shrna screen depletion levels with both kras mutation status and kras transcript levels .
this pattern of dependency is consistent with classic oncogene addiction  <cit> .
the shrnas targeting the myc oncogene also exhibited variable depletion across the panel of cell lines.
however, unlike with kras, the cell lines with lower myc transcript levels were associated with substantially higher depletion levels .
the basis for this observation is unclear, and we caution that the rnai knockdown and phenotype requires validation.
nonetheless, we speculate that there might exist a threshold below which myc levels are insufficient to support cell growth, and that in cell lines with high myc levels incomplete shrna-mediated knockdown is insufficient to pass that threshold.
we recently reported smurf <dig>  encoding an e <dig> ubiquitin ligase, to be amplified in a subset of pancreatic cancers, where it drives cell invasion but not growth in aspc <dig> cells  <cit> .
here, in the context of the pooled shrna screen, we reproduced that result.
the single shrna targeting smurf <dig> was neither depleted nor enriched in smurf1-amplified aspc <dig> cells , consistent with its role in cell invasion but not growth.
interestingly, in non-amplified cell lines the smurf <dig> shrna was generally depleted, suggesting a possible additional role in cell growth specific to a non-amplified context, a knockdown threshold effect as speculated above for myc , or an off-target effect.
the findings for smurf <dig> also suggest an added benefit of screening additional phenotypes, e.g.
cell invasion.
we also observed the expected pattern of shrna enrichment for shrnas targeting known tumor suppressor genes, best exemplified by cdkn2a.
a single shrna targeting cdkn2a was enriched in a subset of the screened cell lines .
notably, the cell lines that did not show substantial enrichment were in fact those with homozygous deletion of cdkn2a .
these data suggest a utility of the shrna knockdown screen approach in identifying not only oncogenes , but also potentially novel tumor suppressor genes .
while the focus of our screen was pancreatic cancer, the inclusion of a breast cancer out-group also provided an opportunity to identify breast cancer selective dependencies.
among the high-confidence genes/phenotype, most notably shrnas targeting the cell-cycle regulator ccne <dig> showed selective depletion in the two breast cancer cell lines .
ccne <dig> has been reported to be the driver of 19q <dig> amplification in breast cancer  <cit> .
indeed, natajaran et al.
reported mda <dig> breast cancer cells to be sensitive to ccne <dig> knockdown  <cit> , which we replicated here .
our findings underscore a likely selective dependency and possible point of therapeutic attack in breast cancer.
cytoband 19q <dig> amplicon
while kras  and myc  are among the most commonly amplified oncogenes, the 19q <dig> region also shows broad amplification in the majority of pancreatic cancers, and high-amplitude, focal amplifications in approximately 20% of cases .
the recurrence and focality strongly suggest the presence of an important oncogene within this amplicon.
akt <dig>  which functions in the pi <dig> kinase pathway, resides near this chromosomal region, and would be a natural candidate for the primary driver of this amplification.
however, as we previously noted  <cit> , the smallest common region of amplification occurs proximal to akt <dig>  as akt <dig> is excluded from the amplicon in several pancreatic cancers .
these data imply that akt <dig> is not the principal driver of 19q <dig> amplification.
to evaluate this amplicon, our screen included shrnas targeting each of the  <dig> genes residing within the smallest common region of amplification.
from our screen, three shrnas targeting genes residing at 19q <dig> were preferentially depleted in those cell lines harboring 19q <dig> amplification .
among these, two high-confidence  shrnas targeted plekhg <dig>  encoding a plekstrin homology domain protein, and a single shrna  targeted med <dig>  a mediator of rna polymerase ii transcription complex subunit.
these data agree well with findings described by kuuselo et al.
<cit> .
those investigators performed a focused sirna-based analysis of genes within the 19q <dig> amplicon, reporting that knockdown of plekhg <dig> and med <dig> reduced cell viability in panc <dig>  but not miapaca <dig>  cells.
thus, our data corroborate and extend  prior work and highlight a still under-appreciated role of plekhg <dig> and med <dig>  as likely oncogenes driving 19q <dig> amplification in pancreatic cancer.
nup153/fast <dig> tgfβ signaling axis
one novel observation derived from our screen centers on nup <dig>  which encodes a nuclear pore complex protein .
nup <dig> was included in the screen because we identified it to be focally amplified in a single pancreatic cancer cell line, pl <dig> .
the nup <dig> nucleoporin regulates the distribution of specific proteins between the nucleus and the cytoplasm, interestingly including the transducer of tgfβ signaling, smad <dig>  <cit> .
in particular, nup <dig> stoichiometrically competes with fast <dig>  a smad <dig> nuclear retention factor, to shuttle smad <dig> out of the nucleus, thus dampening tgfβ signaling.
further implicating this axis in pancreatic cancer, we also noted recurrent focal deletions of fast <dig> in other pancreatic cancer cases .
in our screen, two different high-confidence shrnas targeting nup <dig> showed varying levels of depletion across the cell line panel.
notably, cell lines with an intact upstream tgfβ signaling pathway  generally exhibited higher levels of nup153-shrna depletion, compared to cell lines with a compromised tgfβ signaling pathway  .
our findings therefore suggest that altered nup153-fast <dig> shuttling of smads may provide an alternate means by which pancreatic cancers disrupt tgfβ signaling.
the role of an altered nup153/fast <dig> tgfβ shuttling axis in pancreatic carcinogenesis warrants further investigation.
klf <dig> dependency
another compelling finding relates to klf <dig>  the intestinal kruppel-like transcription factor.
klf <dig> was included in our screen because we identified it to be focally amplified in a pancreatic cancer cell line, hpac .
interestingly, klf <dig> has been paradoxically reported to function as both a tumor suppressor  <cit>  and an oncogene  <cit>  in different tumor types .
our finding of focal klf <dig> amplification in pancreatic cancer suggests a possible oncogenic role.
in our screen, three different high-confidence shrnas targeting klf <dig> showed depletion in most cell lines .
though interestingly, a single cell line, panc <dig>  with extremely low levels of klf <dig> transcript showed substantial klf5-shrna enrichment .
we verified on-target klf <dig> knockdown and the contrasting knockdown growth-phenotypes  by sirna transfection .
the basis for shrna enrichment in the sole panc <dig> line is unclear.
we speculate that klf <dig> might be epigenetically-silenced in panc <dig>  because in that cell line it plays a growth suppressive role; thus further knockdown would promote cell growth.
in contrast, in every other cell line in the panel, klf <dig> transcript levels are appreciable, and knockdown reduces cell growth .
taken together, our findings support a context-dependency of klf <dig> function, whilst the preponderance of data  supports a predominantly oncogenic role in pancreatic cancer.
of note, a recent exome sequencing study  <cit>  reported a single heterozygous mutation  in the dna-binding domain of klf <dig> in the pancreatic cell line panc <dig> .
the authors interpreted the mutation to be functionally inactivating, suggesting a likely tumor suppressive role.
although panc <dig>  was not included in our screening panel, we sought to further characterize klf <dig> in that line.
by analysis of microarray data  <cit> , klf <dig> showed relatively high transcript levels in panc <dig>  compared to other pancreatic cancer cell lines .
further, from our prior transcriptome sequencing  data  <cit> , 64% of klf <dig> reads in panc <dig>  mapped to the wildtype allele , thus excluding epigenetic silencing of the wildtype allele.
notably, sirna mediated knockdown of klf <dig> in panc <dig>  cells resulted in marked growth inhibition .
this finding suggests that the single klf <dig> mutation in panc <dig>  is most likely a passenger mutation, and provides additional support for klf <dig> being predominantly oncogenic in pancreatic cancer.
future studies should define the transcriptional targets and mechanisms underlying klf <dig> dependency in pancreatic cancer.
CONCLUSIONS
in summary, we have detailed a proof-of-principle approach for the highly-parallel functional evaluation of candidate cancer genes, here for pancreatic cancer.
we have simultaneously evaluated  <dig> candidate pancreatic cancer genes, selected as those recurrently and focally amplified or deleted, by a pooled shrna library screen on  <dig> genetically-diverse cell lines.
we have also described a novel approach, copote, to enrich for on-target shrnas and knockdown phenotypes, based on identifying shrnas targeting the same gene that exhibit correlated phenotype.
our screen has uncovered novel pancreatic cancer genes and pathways, most notably highlighting potential roles of a putative nup153-fast <dig> smad shuttling axis controlling tgfβ signaling and an oncogenic function of the klf <dig> transcription factor, both meriting further study.
future screens might include more shrnas per gene , more cell lines, and additional phenotypic assays.
nonetheless, our study here supports the general feasibility of a highly-parallel functional analysis of candidate cancer genes, addressing a fundamental bottleneck in the annotation of cancer genomes.
note added in proof
during review of our manuscript, shao et al.
<cit>  described an rnai-screen analysis approach  that is conceptually similar to ours .
abbreviations
acgh: array-based comparative genomic hybridization; copote: correlated phenotypes for on-target effects; fdr: false discovery rate; kd: knockdown; pcr: polymerase chain reaction; rnai: rna interference; rt-pcr: reverse transcription pcr; q-rt-pcr: quantitative rt-pcr; shrna: short hairpin rna; sirna: short interfering rna.
competing interests
the authors declare that they have no competing interests.
authors’ contributions
ahs and jrp conceived the study, designed experiments, and wrote the manuscript.
ahs and ks developed and optimized the screen.
ahs performed the screen and all subsequent analysis and follow up experiments.
cpg characterized the genetic context of various cell lines.
all authors read and approved the manuscript.
supplementary material
additional file 1
genes included in the shrna screen.
click here for file
additional file 2
depletion/enrichment  of each shrna for each cell line .
click here for file
additional file 3
depletion/enrichment  of each shrna for each cell line replicate screened.
click here for file
additional file 4
correlation coefficients  and false discovery rates  for all hairpins targeting the same gene.
click here for file
additional file 5
tgfβ pathway status, empirically determined by tgfβ-responsive growth inhibition, in pancreatic cancer cell lines  pl <dig>  and  hpac .
click here for file
acknowledgements
we wish to thank members of the pollack lab for helpful discussions.
this study was funded in part by grants from the nci: r01ca <dig> , and from the stanford digestive disease center .
a.h.s.
was supported by fellowships from the nsf, stanford graduate fellowship program, and cancer biology program.
k.s.
was supported by fellowships from the stanford medical scientist training program and the paul & daisy soros foundation.
c.p.g.
was supported by a fellowship from the stanford genome training program.

 pancreatic ductal adenocarcinoma is the fourth leading cause of cancer death in the united states. the five-year survival rate is a dismal 5%, as effective treatment regimens are limited. a better understanding of the underlying disease biology is needed to develop new and successful treatment strategies to manage this deadly disease. several key molecular genetic alterations in pancreatic cancer have been identified. activating mutations of kras occur in 95% of cases. the cdkn2a locus, encoding p16ink4a and p14arf, which respectively intersect the rb and p pathways, is homozygously deleted in 80% of tumors. tp is itself inactivated, usually through point mutation, in 55% of cases. smad a central mediator of tgfβ signaling, is deleted in approximately 50% of cases. furthermore, tgfbr its upstream receptor, is deleted in 20% of tumors, underscoring a central importance of this signaling pathway in pancreatic cancer. myc is amplified in approximately 30% of cases. recently, deletions and mutations in five different subunits of the swi/snf chromatin remodeling complex have been found to occur in about a third of cases. however, despite what is already known, recent surveys of the pancreatic cancer genome have identified scores of additional candidate cancer genes that merit further investigation. with the advent of dna microarrays and “next-generation” dna sequencing, the field of genomics has transformed our ability to study diseases like cancer on an “omic” scale. over the past decade, these technologies have spurred structural studies producing a compendium of cancer alterations, including dna mutations, deletions, amplifications, and rearrangements. yet, because of the sheer volume of data, such studies have far outpaced our ability to functionally evaluate candidate cancer genes. the development of rna interference techniques has accelerated our capacity to study knockdown phenotypes and infer the function and mechanism of disease genes. while traditionally used to characterize single genes at a time, several groups have adapted the technology to use small interfering rna or short hairpin rna libraries for high-throughput screens, including in pancreatic cancer. these large-scale, highly parallel efforts provide the potential to functionally annotate genes on an “omic” scale. here, we describe a high-throughput functional interrogation of the pancreatic cancer genome using an shrna-based screen. we simultaneously evaluate candidate pancreatic cancer genes, nominated from genomic profiles, across genetically diverse cell lines. after integrating the functional and genomic data, we further characterize nine top candidates, both uncovering new pancreatic cancer biology and validating an integrative approach for the functional annotation of cancer genomes. methods cell lines cancer cell lines were obtained directly from the american type culture collection, and grown in rpmi- high-glucose media supplemented with 10% fetal bovine serum. hpde cells were obtained from dr. ming tsao, and grown in keratinocyte serum-free media. pooled shrna lentiviral library screen the shrna screen, schematically depicted in figure , was adapted from published protocols. potential advantages of a pooled screen include economies of scale and discernment of subtle fitness effects by competitive growth over many days. the targeted genes were selected based on the identification of recurrent structural abnormalities in pancreatic cancer genomes. these abnormalities are listed for each gene in additional file gipz lentiviral shrnamir constructs targeting these genes were obtained from open biosystems/thermo scientific; catalog numbers are listed in additional file the pgipz shrnamir plasmid dnas were combined at equimolar concentration into a single pool. the shrna dna pool was then used to transfect 293t cells, together with a trans lentiviral packaging mix. pooled shrna lentiviral supernatant was collected 48 hrs later, and frozen in aliquots to improve screen reproducibility. the lentiviral library was then used to infect target cell lines at low multiplicity of infection, so that most cells contained a single shrna knocking down the expression of a single gene. additionally, enough cells were infected to provide an average representation of approximately lentiviral integrations for each of the shrnas in the library, mitigating potential artifacts from specific integration sites or from multiple integrations. to infect target cell lines, lentivirus was diluted in serum/antibiotic-free media containing 10 μg/ml polybrene. cells were spun at 30°c for 1 hr at  rpm, allowed to recover for 4 hrs, spun again for an additional 1 hr, and then the media replaced with complete rpmi- growth media. all target cell line infections were carried out minimally in triplicate. two days post infection, a fraction of the infected cells was harvested for an initial time point, and puromycin selection was then initiated for the remaining cells. cells were cultured for an additional 4 weeks in the presence of selective media. care was taken not to allow the cells to become too confluent or to split too thinly. cells were periodically harvested, including the last time point, which was the standard comparison point for the screen data presented. genomic dna was isolated from harvested cells, sheared ten times through a gauge needle, and subsequently used as template for pcr amplification of library shrna hairpins. sufficient genomic dna template was included in the pcr reaction to ensure an approximate -fold average representation of each library shrna hairpin, thereby maintaining the initial ~ -fold representation of integrations. pcr primers common to the shrnamir backbone vector and bounding the half hairpin target sequence were as follows: forward 5′-tagtgaagccacagatgta-3′; reverse 5′-atgtatcaaagagatagcaaggtattcag-3′. to deconvolute shrna representation in the t = 4 weeks vs. t =  cell pools, gel-purified pcr products were differentially labeled and co-hybridized to a custom agilent microarray designed to include probes complementary to shrna hairpin sequences. microarrays were imaged and fluorescence intensities extracted. for each microarray, log background-subtracted fluorescence ratios were globally normalized. unless otherwise specified, screen data reported represent the average ratios from replicate cell line infections. screen data analysis and validation high-confidence on-target shrnas/phenotypes were identified using a new analytical approach, based on finding two or more different shrnas targeting the same gene and displaying concordant enrichment/depletion profiles across the cell lines. custom perl scripts were used to calculate the pearson correlation coefficient between shrnas targeting the same genes, and also to permute cell line identities to generate the randomized null distribution of correlations. to define meaningful correlations, we determined false discovery rates as the ratio of false positives to observed positives at or above any given correlation cutoff. for validation, q-rt-pcr was performed using assay-on-demand taqman probes and reagents. catalog numbers for probes include: nup and klf. western blots were done on whole cell lysates, using the following primary antibodies: myc, pan-ras, nup, gapdh, smurf. densitometry calculations were carried out using publicly available imagej software. for sirna knockdown, on-targetplus smartpool sirnas were obtained from thermo scientific: kras, smurf, nup, klf, non-targeting control. cell growth/viability assays were done using a modified wst- protocol as previously described. in each assay, a full time course was performed, though usually only day is shown for brevity. array-based comparative genomic hybridization data findings from the screen were interpreted in the context of previously published acgh data. briefly, that data set comprises agilent 244 k cgh array profiles from pancreatic cancers. tumor/normal fluorescence ratios were normalized and mapped onto the genome using agilent software.  targeted shrna screen in pancreatic cancer genomes, loci that are recurrently amplified or deleted are likely enriched for known or novel cancer genes. typically, each such locus is studied individually to discover the driver gene. in an effort to accelerate this process, we developed a pooled shrna screening strategy to simultaneously evaluate candidate pancreatic cancer genes that together represent different loci of recurrent dna amplification or deletion; thus the genes selected included both candidate oncogenes and tumor suppressors. most of the candidates were focally amplified or deleted in a subset of cancers, and some were also reported to carry mutations. a few known cancer genes were also included in the screen as positive controls. the pooled shrna screen was carried out as a competitive growth/viability assay. the general workflow, adapted from schlabach et al., is depicted in figure  and described in more detail in methods. in brief, pancreatic cancer cell lines were infected with a pooled shrna lentiviral library comprising shrnas targeting the genes. infections were done at low multiplicity of infection, ensuring that most cells harbored a single shrna knocking down the expression of a single gene. the pooled, infected cells were then cultured for four weeks, after which depleted or enriched shrnas were identified by pcr amplification of shrna hairpins and comparative hybridization to a custom hairpin microarray. the shrna library screen was carried out on ten different cell lines. these included seven genetically-diverse pancreatic cancer cell lines that together harbor the vast majority of copy number alterations from which the genes were selected. we also included a single immortalized, non-tumorigenic human pancreatic ductal epithelial cell line to facilitate discovery of tumor suppressor genes. lastly, we also screened two breast cancer cell lines to help distinguish genome-specific from generic essential genes. the raw and cell line-averaged screening data are available in additional files and screen analysis and validation the pooled shrna library screen yielded high quality and reproducible data, as supported by multiple lines of evidence. first, replicate screens of each cell line showed good correlation; the average pair-wise pearson correlation coefficients for cell line replicates ranged from -. the two cell lines with the lowest r-values were those with the least shrna library representation; however, this was mitigated by more screen replicates. notably, in an unsupervised analysis of the shrna depletion/enrichment data, cell line replicates most often clustered together. second, time course samplings, done for a subset of the cell lines, demonstrated consistently increasing shrna depletion over time. third, we noted that distinct shrnas targeting the same gene often exhibited correlated growth phenotypes across the panel of cell line screened. we capitalized on this last observation to define “high-confidence” on-target knockdown phenotypes, an approach we termed copote. when analyzing hundreds of shrnas, it is possible that two different shrnas targeting the same gene have a similar growth phenotype just by random chance. therefore, to correct for multiple hypothesis testing, we compared the distribution of observed pearson correlations to that from randomly permuted data. notably, we observed a significant rightward shift in the observed distribution of correlations, indicating an enrichment of shrnas targeting the same gene above that expected by chance; false discovery rates are reported in additional file of the genes included in the screen represented by two or more shrnas and therefore evaluable), we identified genes with “high confidence” knockdown phenotypes, defined by having at least two different shrnas exhibited significantly correlated depletion/enrichment profiles across the ten cell lines. we note that other approaches have been used to leverage information from multiple shrnas targeting the same gene, including redundant sirna activity analysis, rnai gene enrichment ranking, and the gene activity ranking profile score. all of these methods consider either the top-most depleted shrna or all shrnas for a given gene. our approach is fundamentally different in that we consider all shrna pairs, therefore focusing primarily on the evidence for correlated phenotype rather than on the strength of shrna depletion. focusing primarily on the high-confidence genes, we next validated knockdown for a subset of biologically-interesting genes. we included some known pancreatic cancer genes, but mainly focused on novel genes with biological functions plausibly related to pancreatic cancer, and also demonstrating logical connections to the underlying genomic data, e.g. shrna depletion for amplified candidate oncogenes. validation was done by transducing individual shrnas, or by transfecting independent sirnas, and then verifying target knockdown by rt-pcr and/or western blot. for known pancreatic cancer oncogenes and tumor suppressor genes, finding the expected growth phenotypes provided additional screen validation. observations on known cancer genes among the high-confidence shrnas/phenotypes, several shrnas targeting known oncogenes showed the anticipated pattern of depletion. for example, three different knockdown-validated shrnas targeting the kras oncogene were generally depleted across the panel of cell lines, though with some cell lines showing substantially more depletion than others. on-target knockdown of kras and consequent reduced cell viability were verified using independent kras-targeting sirnas. in pancreatic cancer, kras frequently harbors activating point mutations and may be amplified and/or overexpressed. notably, in the cell line panel there was a good correlation of kras-shrna screen depletion levels with both kras mutation status and kras transcript levels. this pattern of dependency is consistent with classic oncogene addiction. the shrnas targeting the myc oncogene also exhibited variable depletion across the panel of cell lines. however, unlike with kras, the cell lines with lower myc transcript levels were associated with substantially higher depletion levels. the basis for this observation is unclear, and we caution that the rnai knockdown and phenotype requires validation. nonetheless, we speculate that there might exist a threshold below which myc levels are insufficient to support cell growth, and that in cell lines with high myc levels incomplete shrna-mediated knockdown is insufficient to pass that threshold. we recently reported smurf encoding an e ubiquitin ligase, to be amplified in a subset of pancreatic cancers, where it drives cell invasion but not growth in aspc cells. here, in the context of the pooled shrna screen, we reproduced that result. the single shrna targeting smurf was neither depleted nor enriched in smurf1-amplified aspc cells, consistent with its role in cell invasion but not growth. interestingly, in non-amplified cell lines the smurf shrna was generally depleted, suggesting a possible additional role in cell growth specific to a non-amplified context, a knockdown threshold effect as speculated above for myc, or an off-target effect. the findings for smurf also suggest an added benefit of screening additional phenotypes, e.g. cell invasion. we also observed the expected pattern of shrna enrichment for shrnas targeting known tumor suppressor genes, best exemplified by cdkn2a. a single shrna targeting cdkn2a was enriched in a subset of the screened cell lines. notably, the cell lines that did not show substantial enrichment were in fact those with homozygous deletion of cdkn2a. these data suggest a utility of the shrna knockdown screen approach in identifying not only oncogenes, but also potentially novel tumor suppressor genes. while the focus of our screen was pancreatic cancer, the inclusion of a breast cancer out-group also provided an opportunity to identify breast cancer selective dependencies. among the high-confidence genes/phenotype, most notably shrnas targeting the cell-cycle regulator ccne showed selective depletion in the two breast cancer cell lines. ccne has been reported to be the driver of 19q amplification in breast cancer. indeed, natajaran et al. reported mda breast cancer cells to be sensitive to ccne knockdown, which we replicated here. our findings underscore a likely selective dependency and possible point of therapeutic attack in breast cancer. cytoband 19q amplicon while kras and myc are among the most commonly amplified oncogenes, the 19q region also shows broad amplification in the majority of pancreatic cancers, and high-amplitude, focal amplifications in approximately 20% of cases. the recurrence and focality strongly suggest the presence of an important oncogene within this amplicon. akt which functions in the pi kinase pathway, resides near this chromosomal region, and would be a natural candidate for the primary driver of this amplification. however, as we previously noted, the smallest common region of amplification occurs proximal to akt as akt is excluded from the amplicon in several pancreatic cancers. these data imply that akt is not the principal driver of 19q amplification. to evaluate this amplicon, our screen included shrnas targeting each of the genes residing within the smallest common region of amplification. from our screen, three shrnas targeting genes residing at 19q were preferentially depleted in those cell lines harboring 19q amplification. among these, two high-confidence shrnas targeted plekhg encoding a plekstrin homology domain protein, and a single shrna targeted med a mediator of rna polymerase ii transcription complex subunit. these data agree well with findings described by kuuselo et al.. those investigators performed a focused sirna-based analysis of genes within the 19q amplicon, reporting that knockdown of plekhg and med reduced cell viability in panc but not miapaca cells. thus, our data corroborate and extend prior work and highlight a still under-appreciated role of plekhg and med as likely oncogenes driving 19q amplification in pancreatic cancer. nup153/fast tgfβ signaling axis one novel observation derived from our screen centers on nup which encodes a nuclear pore complex protein. nup was included in the screen because we identified it to be focally amplified in a single pancreatic cancer cell line, pl. the nup nucleoporin regulates the distribution of specific proteins between the nucleus and the cytoplasm, interestingly including the transducer of tgfβ signaling, smad. in particular, nup stoichiometrically competes with fast a smad nuclear retention factor, to shuttle smad out of the nucleus, thus dampening tgfβ signaling. further implicating this axis in pancreatic cancer, we also noted recurrent focal deletions of fast in other pancreatic cancer cases. in our screen, two different high-confidence shrnas targeting nup showed varying levels of depletion across the cell line panel. notably, cell lines with an intact upstream tgfβ signaling pathway generally exhibited higher levels of nup153-shrna depletion, compared to cell lines with a compromised tgfβ signaling pathway. our findings therefore suggest that altered nup153-fast shuttling of smads may provide an alternate means by which pancreatic cancers disrupt tgfβ signaling. the role of an altered nup153/fast tgfβ shuttling axis in pancreatic carcinogenesis warrants further investigation. klf dependency another compelling finding relates to klf the intestinal kruppel-like transcription factor. klf was included in our screen because we identified it to be focally amplified in a pancreatic cancer cell line, hpac. interestingly, klf has been paradoxically reported to function as both a tumor suppressor and an oncogene in different tumor types. our finding of focal klf amplification in pancreatic cancer suggests a possible oncogenic role. in our screen, three different high-confidence shrnas targeting klf showed depletion in most cell lines. though interestingly, a single cell line, panc with extremely low levels of klf transcript showed substantial klf5-shrna enrichment. we verified on-target klf knockdown and the contrasting knockdown growth-phenotypes by sirna transfection. the basis for shrna enrichment in the sole panc line is unclear. we speculate that klf might be epigenetically-silenced in panc because in that cell line it plays a growth suppressive role; thus further knockdown would promote cell growth. in contrast, in every other cell line in the panel, klf transcript levels are appreciable, and knockdown reduces cell growth. taken together, our findings support a context-dependency of klf function, whilst the preponderance of data supports a predominantly oncogenic role in pancreatic cancer. of note, a recent exome sequencing study reported a single heterozygous mutation in the dna-binding domain of klf in the pancreatic cell line panc. the authors interpreted the mutation to be functionally inactivating, suggesting a likely tumor suppressive role. although panc was not included in our screening panel, we sought to further characterize klf in that line. by analysis of microarray data, klf showed relatively high transcript levels in panc compared to other pancreatic cancer cell lines. further, from our prior transcriptome sequencing data, 64% of klf reads in panc mapped to the wildtype allele, thus excluding epigenetic silencing of the wildtype allele. notably, sirna mediated knockdown of klf in panc cells resulted in marked growth inhibition. this finding suggests that the single klf mutation in panc is most likely a passenger mutation, and provides additional support for klf being predominantly oncogenic in pancreatic cancer. future studies should define the transcriptional targets and mechanisms underlying klf dependency in pancreatic cancer.  in summary, we have detailed a proof-of-principle approach for the highly-parallel functional evaluation of candidate cancer genes, here for pancreatic cancer. we have simultaneously evaluated candidate pancreatic cancer genes, selected as those recurrently and focally amplified or deleted, by a pooled shrna library screen on genetically-diverse cell lines. we have also described a novel approach, copote, to enrich for on-target shrnas and knockdown phenotypes, based on identifying shrnas targeting the same gene that exhibit correlated phenotype. our screen has uncovered novel pancreatic cancer genes and pathways, most notably highlighting potential roles of a putative nup153-fast smad shuttling axis controlling tgfβ signaling and an oncogenic function of the klf transcription factor, both meriting further study. future screens might include more shrnas per gene, more cell lines, and additional phenotypic assays. nonetheless, our study here supports the general feasibility of a highly-parallel functional analysis of candidate cancer genes, addressing a fundamental bottleneck in the annotation of cancer genomes. note added in proof during review of our manuscript, shao et al. described an rnai-screen analysis approach that is conceptually similar to ours. abbreviations acgh: array-based comparative genomic hybridization; copote: correlated phenotypes for on-target effects; fdr: false discovery rate; kd: knockdown; pcr: polymerase chain reaction; rnai: rna interference; rt-pcr: reverse transcription pcr; q-rt-pcr: quantitative rt-pcr; shrna: short hairpin rna; sirna: short interfering rna. competing interests the authors declare that they have no competing interests. authors’ contributions ahs and jrp conceived the study, designed experiments, and wrote the manuscript. ahs and ks developed and optimized the screen. ahs performed the screen and all subsequent analysis and follow up experiments. cpg characterized the genetic context of various cell lines. all authors read and approved the manuscript. supplementary material additional file 1 genes included in the shrna screen. click here for file additional file 2 depletion/enrichment of each shrna for each cell line. click here for file additional file 3 depletion/enrichment of each shrna for each cell line replicate screened. click here for file additional file 4 correlation coefficients and false discovery rates for all hairpins targeting the same gene. click here for file additional file 5 tgfβ pathway status, empirically determined by tgfβ-responsive growth inhibition, in pancreatic cancer cell lines pl and hpac. click here for file acknowledgements we wish to thank members of the pollack lab for helpful discussions. this study was funded in part by grants from the nci: r01ca, and from the stanford digestive disease center. a.h.s. was supported by fellowships from the nsf, stanford graduate fellowship program, and cancer biology program. k.s. was supported by fellowships from the stanford medical scientist training program and the paul & daisy soros foundation. c.p.g. was supported by a fellowship from the stanford genome training program.
a novel analytical approach was used to discern probable on-target knockdown, based on identifying different shrnas targeting the same gene and displaying concordant phenotypes across cell lines. recent surveys of the pancreatic cancer genome have uncovered numerous new alterations; yet systematic functional characterization of candidate cancer genes has lagged behind. the pooled shrna library design delivered reproducible data. for candidate pancreatic cancer genes, selected from recurrently altered genomic loci, we performed a pooled shrna library screen of cell growth/viability across different cell lines. knockdown-associated effects on cell growth were assessed by enrichment or depletion of shrna hairpins, by hybridization to barcode microarrays. knockdown of known oncogenes and a tumor suppressor showed the expected contrasting effects on cell growth. knockdown data were integrated with genomic architecture and gene-expression profiles, and selected findings validated using individual shrnas and/or independent sirnas. pancreatic cancer is a deadly disease with a five-year survival of less than 5%. to address this challenge, here we have devised a highly-parallel rna interference-based functional screen to evaluate many genomically-nominated candidate pancreatic cancer genes simultaneously. most notably, the analysis also revealed novel possible oncogenic functions of nucleoporin nup and kruppel-like transcription factor klf in pancreatic cancer. by integrating physical and functional genomic data, we were able to simultaneously evaluate many candidate pancreatic cancer genes. our findings uncover new facets of pancreatic cancer biology, with possible therapeutic implications.
 pancreatic cancer is a deadly disease with a five-year survival of less than 5%. a better understanding of the underlying biology may suggest novel therapeutic targets. recent surveys of the pancreatic cancer genome have uncovered numerous new alterations; yet systematic functional characterization of candidate cancer genes has lagged behind. to address this challenge, here we have devised a highly-parallel rna interference-based functional screen to evaluate many genomically-nominated candidate pancreatic cancer genes simultaneously.  for candidate pancreatic cancer genes, selected from recurrently altered genomic loci, we performed a pooled shrna library screen of cell growth/viability across different cell lines. knockdown-associated effects on cell growth were assessed by enrichment or depletion of shrna hairpins, by hybridization to barcode microarrays. a novel analytical approach was used to discern probable on-target knockdown, based on identifying different shrnas targeting the same gene and displaying concordant phenotypes across cell lines. knockdown data were integrated with genomic architecture and gene-expression profiles, and selected findings validated using individual shrnas and/or independent sirnas. the pooled shrna library design delivered reproducible data. in all, copote analysis identified probable on-target gene-knockdowns. knockdown of known oncogenes and a tumor suppressor showed the expected contrasting effects on cell growth. in addition, the screen corroborated purported roles of plekhg and med as 19q amplicon drivers. most notably, the analysis also revealed novel possible oncogenic functions of nucleoporin nup and kruppel-like transcription factor klf in pancreatic cancer.  by integrating physical and functional genomic data, we were able to simultaneously evaluate many candidate pancreatic cancer genes. our findings uncover new facets of pancreatic cancer biology, with possible therapeutic implications. more broadly, our study provides a general strategy for the efficient characterization of candidate genes emerging from cancer genome studies. pancreatic cancerfunctional genomicsrnai screenshrna screennup153klf5 