line names bolded were identified as having significantly reduced pCHK levels.
pCHK1/CHK1 ratios are listed below each lane.
contains data on ~950 cell lines. We graphed each cell lines copy number variation (CNV) and mRNA level for the key ATR pathway genes. From the graphs, we identified outlier cell lines containing both low CNV and mRNA levels for the specified gene (Figure 4.10A). We obtained seven cell lines and tested ATR pathway function using the readout of pCHK1 levels after replication stress (Figure 4.10B). Three of the acquired lines,HCC2218, BT20, and LN319, had significantly reduced pCHK1 compared to the control U2OS cells.
We then tested the obtained ATR and CHK1 frameshift cell lines and the outlier cell lines with reduced pCHK1 for increased sensitivity to the ATRi. Additional control cell lines, HCT116 and TE5, which robustly phosphorylated Chk1 after HU treatment, were also included in the analysis. We treated the cells with increasing concentrations of the ATRi and measured the cell viability by alamarBlue after three population doublings (Figure 4.11). In comparison to the control cell lines (orange lines), the ATR frameshift (green lines), CHK1 frameshift (blue line) and ATR pathway deficient cell lines (black lines) displayed a wide range of sensitivities to the ATRi. From this data, there is no clear observable relationship between mutations in the ATR pathway and sensitivity to the ATRi.
To analyze the data further, we graphed the IC50 for the ATR pathway defective cell lines in comparison to all other cell lines tested including the ATRIP deletion cell lines (Figure 4.11B). Overall, the IC50 values ranged between >0.1-10µM. Of note, the calculation of the IC50 for the three most resistant ATR defect cell lines is lacking in complete accuracy as the full dose response curve was not captured in the assay (Figure 4.11A). We hypothesized the ATR defect cell lines would have an overall decrease in
Figure 4.11. Identified cell lines with ATR defects have varied sensitivities to the ATRi. A. ATRi dose response curves. Cells were treated with ATRi for three population doublings. Cell viability was calculated using alamarBlue and comparing untreated to treated cells. GraphPad Prism was used to graph the dose response curves. Black lines (LN319, HCC2218, BT20) were identified from the CNV vs mRNA graphs and have reduced pCHK1 after HU. Green lines (HEC-1-a, HEC59, GP2D) contain the ATR frameshift mutation. The blue line (IGROV-1) contains the CHK1 frameshift mutation.
Control cell lines (TE5, HCT116) are in orange. B. Graph comparing calculated ATRi IC50 from ATR defect cell lines to all other cell lines tested. C. Graph shown in B but with lung cancer cell lines removed.
average IC50 in comparison to all other cell lines tested, such as observed when comparing ATRi IC50 in ALT positive and negative cells lines [200]. The lung cancer cell lines tended to have higher IC50 values and as such, we removed them from a second comparison graph (Figure 4.11C). This also did not reveal any significant differences between the two populations. The siRNA, shRNA, and isogenic cell lines strongly supported our hypothesis, including cell lines with demonstrated alterations in ATR kinase activity. However, the cancer cell line models yielded no clear relationships between ATR pathway protein expression levels or ATR signaling defects and sensitivity to the ATRi.
Discussion
The newly developed ATR inhibitors are currently entering phase II clinical trials.
These inhibitors have shown promising pre-clinical results in combination with DNA damaging chemotherapies such as platinums, PARP inhibitors, topoisomerase poisons, and gemcitabine [183,184,195]. In the clinic, the ATRi is also being combined with taxanes and the newly FDA approved anti-PDL1 therapy. However, there is no clear indication of which patient populations would best benefit from treatment with the ATRi. In this study, we conducted a whole genome siRNA screen to identify genetic determinants for sensitivity to the ATR inhibitor. As the ATRi is only used in combination with traditional chemotherapies in the clinic and not as a monotherapy, we also performed the whole genome screen in the presence of ATRi and cisplatin. ATR inhibition alone or in combination with cisplatin is most synthetic lethal with loss of ATR pathway genes and DNA replication genes. ATR inhibition is also synthetic lethal with loss of nucleotide biosynthesis genes.
Reduction in ATR activity increases the dependence on the remaining kinase activity We validated reduction of ATR pathway genes as being synthetic lethal with ATR inhibition by siRNA, shRNA, and isogenic cell lines, both in this study and previous work [183]. We also showed overall ATR kinase activity is reflective of sensitivity to the inhibitor using an isogenic cell line. We initially hypothesized knockdown of ATR sensitizes cells to the ATRi because there was less total protein in the cell. However, this hypothesis does not explain why knockdown of the other ATR pathway genes also sensitizes cells as ATR levels are unaffected. We do know ATR is activated every S-phase to overcome replication stresses and regulates origin firing, facilitates repair of replication forks, and prevents premature onset of mitosis [28]. In the presence of replication stress when ATR is inhibited the replication forks collapse into double strand breaks [96]. We hypothesize cells with reduced ATR pathway function have higher levels of replication stress and thus a higher dependence on the remaining ATR functionality to maintain cell viability. If ATR is inhibited is those cells, a significant reduction in remaining ATR function occurs, and the cells die.
The ATR pathway is not frequently mutated in cancer.
Identifying cancers with reduced ATR pathway function proved challenging. The most prevalent alteration of the ATR pathway is deletion of the ATRIP gene. However, all of the ATRIP deletion cell lines we acquired expressed some level of ATRIP protein and those protein levels did not correlate with ATRi IC50. These cells also had a wide range of growth rates, which could alter sensitivity to the inhibitor. We corrected for this by altering the length of the dose response assay to accommodate for three population
doublings. Additional work on cell lines with ATR or CHK1 frameshift mutations or low expression of a key pathway gene did not reveal an obvious correlation between having ATR pathway defects and sensitivity to the ATRi. The tested cell lines came from a wide variety of cancers containing innumerable genetic differences.
In addition to identifying genetic alterations which sensitize cells to the ATRi, it is also crucial to know genetic alterations which promote resistance. Key future studies need to identify these alterations so patients not to treat can be properly identified. These mechanisms could include ATM upregulation as ATR and ATM share many substrates, increased origin firing to compensate for collapsing replication forks, or upregulation of ATR expression upon exposure to the drug. Additionally, we never tested if the ATRi is effectively inhibiting ATR in each of the tested cell lines. Increased efflux, decreased influx, or increased metabolism of the drug are all pathways the cancer cells could have employed to resist the ATRi treatment.
There is no good biomarker for ATR activity
To test for ATR pathway defects in our acquired cell lines, we used phosphorylated CHK1 levels after HU treatment as a readout of ATR activity. This is a poor biomarker because CHK1 gene expression is cell cycle regulated and each cell line had a different cell cycle distribution. Resources also limited this study. There are only a few good antibodies for phosphorylated ATR substrates. Additionally, ATM phosphorylates many of the same substrates, and the availability of reagents does not correct for the cell cycle and cell doubling time differences. Cell lines with fewer cells actively replicating DNA
would not have as big of an induction of pCHK1 after HU treatment because HU only effects S-phase cells. These limitations proved a challenge in this study.
This is further shown by the data from the S1333 mutant ATR lines. In vitro, S1333A-ATR is hyperactive but in cells expressing S1333A-ATR, there is only slightly increased basal pCHK1. At low doses of replication stress, S1333-ATR maintains higher levels of pCHK1 but at higher doses of HU, all differences in pCHK1 levels disappear.
Conversely, S1333D-ATR is less active in vitro, but in cells there are no alterations in pCHK1 levels. However, these cell lines had very different sensitivities to the ATRi, which is reflective of the ATR mutant’s in vitro kinase activity. Using a pCHK1 readout after HU would not have predicted this. Therefore, the cell lines identified as having ATR pathway defects may have been incorrectly labeled. However, there is no clear way to fix this. In order to effectively identify which cancers are sensitive to the ATRi, which are not, and why, a large cell line panel would need to be tested. Discussed below are some other ways our data and others may help direct the ATRi in the clinic.
ATRi synergizes with the CHKi
Consistent with our work, the Helleday group recently published the ATRi synergizes with the CHKi in cancer cells [192]. However, the CHK inhibitors used in that study did poorly in the clinic and most studies with a CHKi have been terminated due to patient toxicity as well as for business reasons [248]. Many of these early CHK1 inhibitors also equally inhibit CHK2 and have other off-target effects such as inhibition of Src family kinases [216]. Two newly developed CHK1 inhibitors are more selective for CHK1 and
are currently in phase I and phase II clinical trials [249]. It remains to be seen if a CHK1i will gain FDA approval.
DNA polymerase D1 and E are mutated in cancer
Recently, a group published loss of DNA Polymerase D1 as being synthetic lethal with reduced ATR functionality [198]. We previously published this finding prior to their work and the whole genome screen also identified knockdown of POLD1 as being synthetic lethal with the ATRi [183]. While POLD1 is not commonly lost in cancer, a point mutation within the exonuclease domain can occur. A point mutation in the same domain of POLE also occurs. These mutations effect the polymerases proofreading activity leading to an increase in DNA mismatches [250,251]. Loss of polymerase proofreading will increase the mutation rate of the DNA but will not necessarily alter the processivity of the replication fork or increase replication stress levels. Our screen and their work identified loss of the polymerase as synthetic lethal with the ATRi not loss of proofreading. Additional work needs to be done to test if these exonuclease domain mutations will confer sensitivity to the ATRi.
ATRi synergizes with anti-metabolites
Our previous work found RRM1 and RRM2 knockdown as synthetic lethal with the ATRi [183]. In this study, we decided to further examine the synthetic lethal relationship with nucleotide metabolism. During the validation screening, we found the enzymes involved in addition of the phosphates as being synthetic lethal with ATRi (Figure 4.5E). This process is tightly regulated and distortions in the nucleotide pool can greatly
impact the replication fork [206,252]. A commonly used drug in the lab, hydroxyurea, inhibits ribonucleotide reductase. HU and the clinical compound gemcitabine synergize with the ATRi to kill cells (data not shown and [184]). In early stages of cancer development, overexpression of oncogenes or viral proteins induces genomic instability through depletion of the nucleotide pools [169] and the TCGA does identify some nucleotide metabolism genes as being deleted. Deletion of chromosome 3p, commonly occurring in ccRCC, results in the loss of NME6, and is predicted to disturb nucleotide biosynthesis [245]. However, it remains to be tested if ccRCC has depleted or imbalanced nucleotide pools. In the clinical trials, the ATRi is combined with gemcitabine. The CHKi is also commonly combined with gemcitabine.
Conclusions
We conducted a whole genome siRNA screen with ATR inhibition to identify clinically actionable synthetic lethal relationships. The top identified pathways included DNA replication and the ATR pathway. We extensively validated that reduction in ATR pathway genes or signaling sensitizes cells to the ATRi by siRNA, shRNA, and isogenic cell lines. However, identifying cancer cell lines with ATR pathway defects proved challenging, and we were not able to validate our findings in cell culture models. A large cell line panel needs to be tested to identify the genetic determinants of ATRi sensitivity or resistance. Phase II clinical trials are commencing for this drug. These trials present an opportunity for researchers to identify the genetic differences between responders and non- responders directly from patient samples.
CHAPTER V
siRNA SCREENING IDENTIFIES POTENTIAL NEW ATR PATHWAY OR DNA DAMAGE RESPONSE GENES
Introduction
The canonical ATR activation pathway involves ATR localization through ATRIP binding to RPA, loading of the 9-1-1 complex onto dsDNA:ssDNA junctions, and the recruitment of the ATR activator TOPBP1. Once activated, ATR phosphorylates hundreds of downstream proteins, most of which remain uncharacterized [28]. More recent studies of the ATR activation pathway identified additional proteins necessary for full ATR activation, such as the MRN complex and RHINO [67,68,84,85]. Our lab has also recently identified a new ATR activator, ETAA1 (Appendix C). While we understand the basic ATR activation pathway, there is still much to learn.
We conducted three whole genome siRNA screens with the ATRi, CHKi, or hyrdroxyurea (HU), discussed in Chapter IV. Comparison of the top synthetic lethal genes from each of the screens identified the ATR pathway genes, among 180 genes, as synthetic lethal with all three drugs (Figure 4.3A). We hypothesized within those 180 genes, were additional, yet uncharacterized ATR pathway genes. Using the data generated from the whole genome screens as well as other genetic and proteomic screen data, we selected genes to validate in the secondary screens with the goal of identifying a new ATR pathway gene.
In this chapter, I will discuss the secondary validation screens and work on three genes of interest, RNF208, ARID3B, and BRD3. I examined localization of the proteins, γH2AX levels and ATR signaling after knockdown, and co-immunoprecipitating proteins identified by IP-mass spectrometry. From this data, we selected BRD3 for further characterization. Ultimately, we concluded the siRNA to BRD3 had off-target effects and knockdown of BRD3 does not sensitize cells to the ATRi. My collaborator, Kareem Mohni, has continued work on this project characterizing a new gene of interest, HMCES.
Work on HMCES will not be discussed in this chapter but should be published in the coming year.
RESULTS
Secondary screens tested selected genes for synthetic lethality with several inhibitors After completing the primary screen, we selected genes for validation using a wide variety of criteria. Preliminarily, we identified the top synthetic lethal genes with each inhibitor as well as those synthetic lethal with multiple inhibitors. We then used the published literature and other genomic and proteomic datasets to modify our selections. In the primary screen, 71 genes with synthetic lethal relationships with the ATRi are enriched at replication forks by iPOND [103]. Of those, 29 have no known functions. Many of those genes were included in our secondary screen. We did not select genes for the secondary screens with well-characterized functions in the ATR pathway, DNA replication, transcription, or mRNA maturation.
In the secondary screen, we purchased 4 individual siRNAs per gene, with one siRNA plated per well (Dharmacon siGENOME). Additionally, we screened a collection
of siRNAs purchased for a secondary validation screen previously done in the lab, as many of our genes of interest were within this collection. Overall, the secondary screen comprised of 11-384 well plates. The results from our secondary screen utilizing the previously purchased siRNA collection was published in Kavanaugh et al. [253].
We used the same methodology for the secondary screens as the primary screens.
We used U2OS cells, and after transfection, we allowed the cells to grow for 72 hours. On day 3, we split the cells into 4 new 384-well plates and left one plate untreated and treated the remaining three plates with the selected inhibitors. After an additional 72 hours, cell viability was measured using alamarBlue. In addition to the conditions tested in the primary screen, we decided to include a high dose of HU. We treated the cells with high dose HU for only 24 hours and then released them into fresh media for the remaining 48 hours before measuring cell viability. Arm 1 of the screen comprised of CHKi, low dose HU, and high dose HU (Figure 5.1A), and Arm 2 of the screen comprised of the ATRi, cisplatin, and ATRi/cisplatin (Figure 5.1B).
Data analysis differed from the primary screen. We calculated cell viability for each siRNA by comparing the alamarBlue value from the treated plate to the untreated plate. These values were then normalized to correct for plate-to-plate variation. Any siRNA resulting in a viability reduction of 15% or greater after drug treatment was considered to have validated and approximately 36% of siRNAs validated in the ATRi secondary screen. We also included a statistical analysis to correct for false discovery rate [203]. The siRNAs that validated with the ATRi are listed in Appendix B and asterisks denote statistically validated siRNAs. For a gene to validate, 2 of 4 siRNAs must have reached the biological and statistical threshold. Additionally, we utilized the GESS
Figure 5.1. siRNA synthetic lethality secondary screens included six drug conditions.
A-C. Schematic of the siRNA screens. U2OS cells were transfected with siRNAs and left untreated or treated with drug. Cell viability was measured by alamarBlue. n=3 A. Cells were treated with 0.05 µM CHKi (AZD7762), 0.2 mM Low dose HU, and 3.0 mM High dose HU. Cells were treated with CHKi and Low HU for 72 hours. Cells were treated with High dose HU for 24 hours and released into fresh media for the remaining 48 hours.
B. Cells were treated with 0.1 µM ATRi (VX-970), 0.5 µM cisplatin, and 0.05 µM ATRi/
0.1 µM cisplatin for 72 hours.
analysis to identify any significant off-target effects for each siRNA [254,255]. This analysis compares the siRNA sequence to the 3’-UTR region of genes and determines if the siRNA has any off-target miRNA-like effects but no off-target effects were identified.
Characterization of RNF208, ARID3B, and BRD3
We identified three candidate proteins for further study, RNF208, ARID3B, and BRD3. Initial characterization of these proteins utilized several assays. We looked for co- localization with the replication fork by immunofluorescence and IPOND. After knockdown, we looked for induction of γH2AX with and without replication stress to determine if loss of these proteins increases DNA damage or replication stress and we looked for defects in ATR signaling to see if these proteins function in the activation of ATR. Last, we identified protein interactors by IP-mass spectrometry to gain understanding of potential pathways in which these proteins might function.
RNF208 is a ring finger protein with no published function. The RING finger domain can facilitate protein dimerization [256]. In the secondary screens, RNF208 knockdown sensitized cells to low dose HU, the CHKi, and the ATRi. Additionally, RNF208 was identified and validated in a replication stress response screen also done in the lab [253]. In this screen, after siRNA transfection, cells were measured for their ability to recover from replication stress by monitoring γH2AX levels and incorporation of the thymidine analog EdU after release from HU. The identification of RNF208 in this screen suggests RNF208 might function in the replication stress response.
To test if RNF208 is in the ATR activation pathway, we examined phospho-CHK1 (pCHK1) levels after knockdown of RNF208 before and after replication stress induced by